Volume 1: Main Report 71453 v1 ASEAN Advancing Disaster Risk Financing and Insurance in ASEAN Member States: Framework and Options for Implementation April 2012 Disclaimer: The team has made every attempt to verify the contents presented, but the information should be interpreted with due consideration to its limitations resulting from the fact that indirect sources have been used where primary sources were not available, and that the collective knowledge in this area is limited. Volume 1: Main Report ASEAN Advancing Disaster Risk Financing and Insurance in ASEAN Member States: Framework and Options for Implementation April 2012 Disaster Risk Financing and Insurance Program, Global Capital Markets and Non Bank Financial Institutions Unit & GFDRR East Asia and Pacific Disaster Risk Management Program East Asia Finance and Private Sector Unit Global Facility for Disaster Reduction and Recovery © 2012 The International Bank for Reconstruction and Development/The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org All rights reserved This publication is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433. Design: miki@ultradesigns.com Volume 1: Table of Contents Volume 2: Technical Appendices.................................................................................................. v Acknowledgements...................................................................................................................... vi Abbreviations and Acronyms....................................................................................................... vii Foreword .................................................................................................................................... ix Executive Summary...................................................................................................................... 1 Chapter 1. Introduction............................................................................................................... 5 Disaster Risk Management in ASEAN Member States ...................................................................... 8 Objectives of the Report................................................................................................................... 10 Chapter 2. Financial Assessment of Natural Disasters.............................................................. 13 Economic Assessment of Natural Disasters ...................................................................................... 14 Fiscal Risk Assessment of Natural Disasters....................................................................................... 22 Chapter 3. Fiscal Management of Natural Disasters................................................................. 29 Introduction .................................................................................................................................... 30 Ex-Post Practices and Arrangements................................................................................................. 31 Ex-Ante Practices and Arrangements................................................................................................ 40 Chapter 4. Private Catastrophe Risk Insurance Markets........................................................... 45 Private Property Catastrophe Insurance............................................................................................ 46 Agricultural Insurance...................................................................................................................... 54 Disaster Microinsurance................................................................................................................... 61 Chapter 5. Recommendations for Regional Disaster Risk Financing and Insurance Strategy for ASEAN Member States........................................................................ 71 Recommendation 1: Develop Risk Information and Modeling Systems to Assess the Economic and Fiscal Impacts of Natural Disasters....................................................................... 73 Recommendation 2: Develop National Disaster Risk Financing and Insurance Strategies at the National and Sub-national Levels .......................................................................................... 75 Recommendation 3: Establish National Disaster Funds...................................................................... 79 Recommendation 4: Promote Private Catastrophe Risk Insurance Markets........................................ 80 Recommendation 5: Strengthen Regional Cooperation on Disaster Risk Financing and Insurance.................................................................................................................................. 82 Glossary .......................................................................................................................................... 84 List of Annexes ............................................................................................................................... 87 Bibliography and References ........................................................................................................... 119 Makati City, Manila. Volume 2: Technical Appendices Available online at www.worldbank.org/fpd/drfi and www.gfdrr.org/gfdrr/drfi. See “Publications” page of either website. Volume 2 of the report includes 10 supporting technical appendices. This volume complements the main report but is published as a separate input document. It compiles background notes and papers drafted for the preparation of the main report. The team has made every attempt to verify the contents presented, but the information should be interpreted with due consideration to its limitations resulting from the fact that indirect sources have been used where primary sources were not available and that the collective knowledge in this area is limited. An overview of the contents of Volume 2 is presented here. Appendix 1. Disaster Risk Exposure Profiles of ASEAN Member States Appendix 2. Disaster Risk Management Profiles of ASEAN Member States Appendix 3. Fiscal Risk Management of Natural Disasters by ASEAN Governments Appendix 4. Property Catastrophe Risk Insurance Markets Appendix 5. Agricultural Insurance in ASEAN Member States Appendix 6. Disaster Microinsurance: Selected Case Studies and Profiles of ASEAN Member States Appendix 7. Catastrophe Microinsurance – The Need and the Challenge, Finding Solutions Appendix 8. Parametric Insurance – Basic Concepts Appendix 9. Comparison of Ex-Ante Disaster Risk Financing and Transfer Instruments < vi > Acknowledgements This report has been prepared by a team led by Olivier Mahul (World Bank) and Abhas Jha (World Bank), and comprising Emily White (World Bank), Laura Boudreau (World Bank), Charlotte Benson (Public finance specialist, Consultant), Daniel Clarke (Actuary, Consultant), Robert Lee Kong Tiong (Catastrophe risk financing specialist, Institute for Catastrophe Risk Management, Nanyang Technological University, Singapore), Charles Stutley (Agricultural insurance specialist, Consultant), Zuzana Svetlosakova (World Bank), Ligia Vado (World Bank), and Eiko Wataya (World Bank). The team worked in close collaboration with Adelina Kamal (ASEAN Secretariat) and Marqueza Reyes (ASEAN Secretariat and UNISDR Technical Cooperation). The report was presented and discussed with ASEAN Member States at the ASEAN Disaster Risk Financing & Insurance Forum, which was held from November 8-10, 2011 at the ASEAN Secretariat in Jakarta, Indonesia. The Forum provided a venue for the dissemination of the first draft of the report; feedback received from ASEAN Member States during the Forum has been incorporated into this final report. The team gratefully acknowledges the inputs provided by the ASEAN Member States and members of the ASEAN Secretariat during and following the Forum. The report greatly benefited from data and information provided by academic, private sector, and other partners from the international community: Aon Benfield, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) Microinsurance Innovations Program for Social Security Philippines, Guy Carpenter, International Finance Corporation, MicroEnsure, Munich Re, Nanyang Technological University, Swiss Re, Willis Research Network, and the United Nations Development Program Myanmar. The team benefited from feedback provided by the members of the consultative committee: Adelina Kamal (ASEAN Secretariat), Marqueza Reyes (ASEAN-UNISDR Technical Cooperation), Neil Britton (Asian Development Bank), Takahiro Ono (Asia Disaster Reduction Center), Grant Morrison (Australian Agency for International Development), Sugeng Triutomo (National Agency for Disaster Risk Management (BNPB), Indonesia), Teddy Sudinda (BNPB, Indonesia), Pedro Oliviera (European Union), Per Byman (Swedish International Development Cooperation Agency), John Harding (UNISDR), Olivier Mahul (World Bank), and Abhas Jha (World Bank). Financial support from the Global Facility for Disaster Reduction and Recovery (GFDRR) is gratefully acknowledged. < vii > Abbreviations and Acronyms AADMER ASEAN Agreement on Disaster Management and Emergency Response ADB Asian Development Bank AEL Annual Expected Loss ASEAN Association of Southeast Asian Nations CBO Community-Based Organization CCRIF Caribbean Catastrophe Risk Insurance Facility CERF UN Central Emergency Response Fund DRM Disaster Risk Management DRR Disaster Risk Reduction FONDEN Natural Disaster Fund (Mexico) GDP Gross Domestic Product GFDRR Global Facility for Disaster Reduction and Recovery HFA Hyogo Framework for Action IFI International Financial Institution MEF Ministry of Economy and Finance (Cambodia) MFI Microfinance Institution MMPP Malaysia Micro Protection Plan (Malaysia) NDMO National Disaster Management Office NGO Non-Governmental Organization OIC Office of the Insurance Commission (Thailand) PCRAFI Pacific Catastrophe Risk Assessment and Financing Initiative PML Probable Maximum Loss PPP Public-Private Partnership RBC Risk Based Capital TCIP Turkish Catastrophe Insurance Pool (Turkey) UN United Nations UNISDR United Nations International Strategy for Disaster Reduction UNOCHA United Nations Office for the Coordination of Humanitarian Affairs Mayon Volcano, Philippines. < ix > Foreword More than 100 million people in ASEAN Member ity in the region. This program, organized around States have been affected by disasters since 2000, the Hyogo Framework for Action (HFA) and the with events ranging from earthquakes to floods, ASEAN Agreement on Disaster Management and volcanic eruptions, and typhoons. The human and Emergency Response (AADMER), was developed fol- economic costs of these catastrophes are huge, with lowing the signing of a Memorandum of Coopera- annual disaster losses in the region estimated at tion signed by the World Bank, ASEAN Secretariat, close to US$5 billion – a figure likely to increase with and the UNISDR in 2009. Disaster risk financing growing population, urbanization, and sustained and insurance has gained increased interest among GDP growth, all factors which will push more people ASEAN policy makers and was identified as a key and assets into zones vulnerable to natural hazards. area for engagement under the work-program for AADMER. The topic was also highlighted as an area The ability of countries to manage this increasing for regional cooperation at the ASEAN+3 Finance impact of disasters will have important implications Ministers’ meetings in 2011. on the growth and development agenda in the region. Disasters can force countries to divert re- This report is the result of collaboration among sources from longer-term development investments the ASEAN Secretariat, the World Bank, the Global to meet immediate response and recovery needs. Facility for Disaster Reduction and Recovery (GFDRR), Ex-ante disaster risk management, including finan- and the UNISDR. It examines the role of DRFI in the cial contingency planning in the form of a disaster financial resilience of ASEAN Member States against risk financing and insurance (DRFI) strategy, can en- natural disasters. The report looks at many facets of sure access to fast and cost-effective liquidity post- DRFI, reviewing domestic private catastrophe insur- disaster. This can in turn speed up recovery and help ance markets, assessing contingent disaster liabili- maintain the country’s long-term development. DRFI ties of ASEAN Member States, and analyzing fiscal instruments range from property catastrophe insur- arrangements for funding of disasters. It highlights ance for homeowners and agricultural insurance for opportunities to reduce financial and fiscal vulner- farmers and herders to sovereign-level contingent ability through the development of disaster risk fi- facilities such as the World Bank’s loan with catas- nancing and insurance strategies and market-based trophe deferred drawdown option (CAT DDO). financial products. The World Bank and the United Nations Interna- We hope that this report will contribute to the dia- tional Strategy for Disaster Reduction (UNISDR) are logue between ASEAN Member States, develop- assisting ASEAN Member States in the area of disas- ment partners, and other stakeholders in this impor- ter risk financing and insurance as part of a broader tant area of resilience. program to strengthen disaster risk reduction capac- Pamela Cox Rachel Kyte Dr. Surin Pitsuwan Vice President Vice President Secretary-General East Asia and Pacific Region Sustainable Development Network ASEAN Secretariat The World Bank The World Bank Rice field, Bali, Indonesia. <1> Executive Summary This report is a first collaborative effort to pres- ber States affected by disasters since 20001. The ent a comprehensive body of knowledge on 2011 floods in Thailand and, to a lesser extent, Cam- the state of disaster risk financing and insur- bodia, Lao PDR, and Viet Nam were the most recent ance in ASEAN Member States and share ex- example of the region’s high exposure to weather- amples of best practice and lessons from inter- related (hydro-meteorological) disasters. national experience. It is part of a project being jointly conducted by the World Bank, the Global Fa- Each year, on average, the region suffers dam- cility for Disaster Reduction and Recovery (GFDRR), age in excess of US$4.4 billion a consequence of the ASEAN Secretariat, and UNISDR to promote the natural hazards. Annual average regional expected development of national and regional disaster risk losses total US$4.4 billion, equivalent to greater than financing and insurance strategies in ASEAN Mem- 0.2 percent of regional GDP. Myanmar, the Philip- ber States within the context of the broader disaster pines, Viet Nam, Lao PDR, and Cambodia face par- risk management agenda. This report aims to con- ticularly high annual average expected losses relative tribute towards a strengthened understanding and to the size of their economies, standing at equivalent collective knowledge within the ASEAN region on to 0.7 percent or more of GDP. See Figure 1. disaster risk financing and insurance, and to encour- age open dialogue between stakeholders on how Figure 1. Estimated Annual Expected Losses (AEL) strategies can best be developed to increase finan- as a percentage of national GDP cial resilience against natural disasters. 1.0 0.9 Disaster risk financing and insurance has gained 0.9 0.8 0.8 0.8 increased attention among policy makers. Fi- 0.7 0.7 0.7 % of GDP 0.6 nance Ministers in the ASEAN region highlighted the 0.5 importance of regional cooperation on disaster risk 0.4 0.3 0.3 financing and insurance at the ASEAN Finance Min- 0.2 0.2 0.1 0.1 0.1 isters’ Meeting in Bali in April 2011. They agreed 0.0 0.0 0.0 that a regional disaster risk financing and insurance ilip r s La m Ca PDR a N Th ia nd a ng m e Ph ma ne or di Da aysi EA s Na a ne la bo al ap pi n AS ai strategy is essential to deal with natural disasters. o al ss do ya et m M ru Vi M In Si They reiterated this statement at the 14th ASEAN+3 ei un Finance Ministers’ Meeting in Viet Nam in May 2011. Br Key findings Every 100 years, on average, the ASEAN re- gion will face disaster losses totaling US$17.9 ASEAN Member States are highly exposed to billion, equivalent to an estimated 1.0 percent a wide range of adverse natural events. Earth- of regional GDP. Indicative numbers suggest that quakes, floods, tropical cyclones (typhoons), and Lao PDR will face the highest losses relative to GDP, drought have all had large footprints in the region, standing at 11.7 percent. Catastrophic disasters oc- with more than 100 million people in ASEAN Mem- EM-DAT: The OFDA/CRED International Disaster Database – 1 www.emdat.be – Université Catholique de Louvain, Brussels. < 2 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States curring once every 200 years could result in contin- lays in reconstruction as it takes time to secure suffi- gent liability in excess of 8 percent in the Philippines, cient resources from limited public budget envelopes, Cambodia, and Lao PDR. See Figure 2. exacerbating the socio-economic consequences of di- sasters at both the national and household level. Post- Figure 2. Estimated 100-year loss and 200-year disaster budget reallocations can also derail progress Probable Maximum Loss (PML), as percentage of toward the achievement of national and sector devel- national GDP. Note the exclusion of Myanmar and opment goals and objectives. Funding gaps may be Brunei Darussalam due to data limitations (see particularly acute at a sub-national level, potentially Chapter 2) contributing to geographical disparities in economic development and levels of poverty. 16.0 14.0 11.7 n PML (100-yr) Private disaster risk insurance markets have 12.0 n PML (200-yr) failed to offset a significant share of govern- % of GDP 10.0 8.0 7.3 ment contingent liability because they are 6.0 4.7 still underdeveloped in most ASEAN Member 4.0 3.6 States. Property catastrophe insurance, agricultural 2.0 1.4 1.0 1.0 0.7 0.0 insurance, and disaster microinsurance are all still 0.0 under-developed in most ASEAN Member States R a s m sia sia N nd e ne or di PD EA and have achieved low rates of penetration. This Na ne ay la bo ap pi AS ai o al do ilip et m ng La Th M Vi reflects a combination of challenges on the supply Ca In Ph Si side (such as product development, limited delivery channels, lack of technical capacity), challenges on Disasters place a significant fiscal burden on the demand side (such as low insurance education, many governments in the region. In particular, low awareness on exposure to disaster risks), and a the governments of Myanmar, the Philippines, Cam- need to strengthen legal and regulatory systems. bodia, Lao PDR, and Viet Nam face average annual disaster response bills in excess of 0.5 percent of to- Disaster losses are expected to rise in the fu- tal public expenditure. Lao PDR, the Philippines, and ture, in turn increasing the fiscal burden of Cambodia could experience bills totaling 18 percent disasters if existing financial management ar- or more of total public expenditure in the event of a rangements are not improved. There are growing 200-year disaster. concerns about increasing exposure and vulnerabil- ity to natural hazards in the ASEAN region. Predict- ASEAN governments typically have insufficient ed rises in the frequency and intensity of weather- funding arrangements in place for major disas- related hazards as a consequence of climate change ter events. ASEAN governments currently retain appear set to fuel this trend. most of their disaster risk. They rely heavily on annual (contingency) budget allocations for potential disas- ter events and post-disaster reallocations to finance Options for Consideration their disaster response efforts. Immediate humanitar- ian needs are largely met. Cambodia, Lao PDR, and There is growing interest in the development Myanmar regularly struggle, however, to secure ad- of national disaster risk financing and insur- equate and timely funding for early recovery. ance plans in the ASEAN region to improve the management of the fiscal burden associated Inadequate disaster financing arrangements with disasters and inter-annual volatility in di- have exacerbated the adverse socio-economic saster spending requirements. These efforts are consequences of disasters. Most countries face de- also seeking to ensure more timely relief and recon- Executive Summary < 3 > struction efforts, to leverage additional resources, States financial tools to assess the economic and fis- and to alleviate the periodic burden of disasters on cal impacts of natural disasters. It would also assist planned development initiatives. The Philippines, for Ministries of Finance in the design of cost-effective instance, signed a US$500 million contingent credit national disaster risk financing and insurance strat- for natural disasters with the World Bank in mid- egies. The platform could offer tools for insurance 2011. This contingent credit was drawn down on regulators to implement risk-based supervision of December 29, 2011, following the devastating im- domestic insurers and reinsurers and to monitor rate pacts of Tropical Storm Sendong (Washi). Indonesia adequacy for catastrophe risk insurance products. and Viet Nam are also actively exploring ex ante di- saster risk financing and insurance strategies. Recommendation 2: Develop disaster risk financing and insurance strategies at the In parallel, private disaster risk insurance mar- national and sub-national levels to manage kets show some prospects of growth which potential budget volatility associated with could be further stimulated by public sector en- natural disasters and provide insurance coverage gagement. Demand for property catastrophe insur- against natural disasters for key public assets. ance is likely to expand in several countries where Disaster risk financing and insurance strategies could access to mortgages is becoming increasingly con- be developed based on a combination of risk reten- ditional on insurance coverage. There is also grow- tion and risk transfer tools for different layers of risk ing interest in agricultural insurance, in particular in and tailored to the circumstances of individual coun- index-based schemes, with some form of agricultural tries. They could include instruments such as con- insurance available in five ASEAN Member States and tingency budgets, reserves, contingent credit, insur- a range of new initiatives recently launched or under ance, and catastrophe bonds. They need to ensure development. Disaster microinsurance has been par- that the funding available matches the post-disaster ticularly undeveloped in the region but public-private needs. Comprehensive tracking systems would need partnerships are driving the early establishment of di- to be established to monitor the scale and timing of saster microinsurance in two ASEAN Member States. flows of resources. Disaster risk financing and insur- This study identifies five key recommendations ance strategies should be carefully coordinated with to support and encourage the further develop- risk reduction strategies at both national and local ment of cost-effective, affordable, and sustain- levels and reinforce sound risk reduction principles. able disaster risk financing and insurance in National and sub-national disaster risk financing and ASEAN Member States. These recommendations insurance strategies could also include a catastrophe aim to offer a framework for a regional agenda on risk insurance program for key public assets. disaster risk financing and insurance. Recommendation 3: Establish national disaster Recommendation 1: Develop risk information funds as a financial mechanism to ensure the and modeling systems for ASEAN governments fast disbursement and execution of funds in to assess the economic and fiscal impact of nat- the aftermath of a disaster. ural disasters and include those risks in overall A dedicated financial vehicle could be established fiscal risk management. in each ASEAN Member State to conduct transpar- ASEAN Member States could develop a joint region- ent and efficient post-disaster damage assessments al risk information platform for this purpose, build- of public assets (and possibly low-income housing), ing on regional data sources currently in existence mobilize immediate funding post disaster, and ex- and including a geo-referenced exposure database ecute the funds in close collaboration with relevant and regional catastrophe risk models for major line ministries and public agencies. The fund could perils. This platform would offer ASEAN Member contain three windows: < 4 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States o An emergency fund for immediate humanitarian should lead to lower reinsurance prices and re- needs; duced transaction costs. o A program to support the reconstruction of public infrastructure and low-income housing; and Recommendation 5: Strengthen regional coop- o A trust fund to manage the resources and act as eration on disaster risk financing and insurance the contracting authority for risk transfer mech- to support its development, including the es- anisms, via which governments could leverage tablishment of a regional catastrophe risk insur- their financial capacity. ance vehicle. The development of disaster risk financing and in- The national disaster funds could build up reserves surance could be strengthened via regional coop- from the unspent portion of their annual budget eration among ASEAN Member States in three key allocations over time to increase their retention ca- areas; a dedicated regional program on Disaster Risk pacities. The creation of local government disaster Financing and Insurance for ASEAN Member States funds and related pool facilities could also be con- could be established to support these activities: sidered at the sub-national level. o Regional risk information, assessment, and mod- Recommendation 4: Promote private catastro- eling systems. These systems would be more phe risk insurance markets through public-pri- cost-effective than individual country equivalents, vate partnerships and the development of en- particularly in the context of trans-boundary haz- abling regulatory and risk market infrastructure. ards, and would promote regional cooperation in Three key areas for development of enabling regu- risk management. The resulting risk assessments latory and risk market infrastructure could be con- could be used to develop country-specific finan- sidered by ASEAN governments to promote the de- cial disaster risk profiles. velopment of property catastrophe risk insurance, o Regional knowledge advisory services and ca- agricultural insurance, and disaster microinsurance: pacity building programs to facilitate knowledge sharing. o Governments could work toward the development o A regional vehicle could leverage international re- of an enabling insurance regulatory and supervi- insurance and capital markets, potentially gener- sory framework that controls insurers’ exposure ac- ating significant economies of scale via both risk cumulations to catastrophe risk using a risk-based pooling benefits and reduced operating costs, capital approach. Regulation could also be used to thereby making risk transfer products more afford- support the growth of emerging insurance prod- able both for governments and private individuals. ucts that have the potential to increase insurance penetration and reach low-income populations. Recommendations 1 to 3 apply equally to municipal, o Governments could develop risk market infra- provincial, and national levels, although a regional ap- structure to assist the development of a cost- proach would be particularly advantageous in develop- effective, affordable, and sustainable insurance ing risk information and modeling systems. It should market. Risk market infrastructure development also be noted that those recommendations pertaining could include: product development, risk assess- to risk pooling would benefit from scale to allow for ment and pricing methodologies, loss adjustment maximum diversification and economies of scale. Rec- procedures, and distribution channels. The need ommendation 4 is targeted at the national level as it to develop risk market infrastructure is particularly pertains to private markets and Recommendation 5 strong for disaster microinsurance. discusses a regional approach. Each ASEAN Member o Governments could facilitate disaster risk pooling, State may want to prioritize and tailor those recom- creating a larger, more diversified portfolio which mendations based on its country-specific needs. Chapter 1 Introduction Introduction <5> U Bein Bridge, Mandalay, Myanmar. < 6 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States From July 2011 to October 2011, a number of ASEAN Member States were affected by severe flooding. Cambodia, Lao PDR, and Viet Nam were impacted, but Thailand was worst hit, with estimated total economic damage and losses of US$45 billion. Flood waters persisted in some areas through mid-January 2012; at maximum flood extent, 64 provinces in Thailand were affected. Bangkok was also inundated. Initial assessments indicated that the majority of losses were concentrated in the private sector, with manufacturing being the worst hit sector. Insured losses for Thailand could range from US$15 billion to as high as US$20 billion, coming principally through commercial and in- dustrial lines where business interruption has been extensive. The event had consequences for the Japa- nese economy, as reports indicated that Japanese-owned companies in Thailand and Japanese compa- nies supplied by Thai enterprises were particularly affected. The international (re)insurance industry will shoulder a large portion of the burden as cession of risk out of the domestic market for commercial and industrial risks is large. International reinsurers Munich Re and Swiss Re both indicate that their net losses from the flooding will exceed US$600 million. ASEAN Member States are highly exposed to Geophysical disasters, although less frequent a wide range of adverse natural events. Earth- in occurrence, have wrought particular devas- quakes, catastrophic flooding, tropical cyclones, tation in the region. The December 2004 Indian and drought have all had large footprints in the re- Ocean tsunami, triggered by seismic activity off the gion, with more than 100 million people in ASEAN west coast of Sumatra, Indonesia, remains one of Member States affected by catastrophic events since the deadliest disasters on record, costing more than 20002. 200,000 lives across fourteen countries and causing damage in excess of US$4.5 billion. In Indonesia, three earthquakes since 2004 have impacted more ASEAN Member States are at risk from hydro- than 6 million people and caused US$10 billion in meteorological disasters. The monsoon and cy- economic losses5 . Malaysia, Myanmar, the Philip- clone seasons impact all ASEAN Member States, pines, and Thailand also count earthquake events in with topography creating vulnerability to flash their costliest ten disasters since 1900. Indonesia has flooding and landslides in addition to significant 70 active volcanoes classified as dangerous, while in river flood risk, specifically from the vast Mekong the Philippines a review of the historic record indi- river basin. Flood is a recurring problem across the cates that central and southern Luzon are likely to region; in the past ten years alone, half of all ASEAN experience a significant eruption about once every Member States have experienced at least one flood three years. event costing over US$100 million3. Figures on re- cent levels of loss are expected to have increased significantly as a consequence of the major floods Exposure to natural disasters in ASEAN Mem- experienced in Thailand, Viet Nam, Cambodia, and ber States is increasing. Increasing urbanization Lao PDR in 2011. The 2008 cyclone Nargis ranks has seen a growth in the concentration of assets, amongst the deadliest cyclones of all time, causing particularly in flood-prone areas due to the preva- an estimated 138,0004 deaths in Myanmar. lence of coastal cities in the region. In the past 20 years, four ASEAN Member States have experienced EM-DAT: The OFDA/CRED International Disaster Database – 2 catastrophic events costing at least 1 percent of na- www.emdat.be – Université Catholique de Louvain, Brussels tional GDP at 2009 value. A large proportion of EM-DAT: The OFDA/CRED International Disaster Database – 3 www.emdat.be – Université Catholique de Louvain – Brussels EM-DAT: The OFDA/CRED International Disaster Database – 5 Swiss Re Sigma 2008 4 www.emdat.be – Université Catholique de Louvain – Brussels Chapter 1: Introduction < 7 > Figure 1.1. Mortality Risk Index for Multi-Hazard Risk Source: ASEAN DRMI 2010 the population within the region is concentrated in third fell on the public sector (Indonesia BNPB et al, coastal lowlands or deltas at risk of flooding. The 2009). Typhoon Ketsana and a second typhoon di- broad extent of seismic activity across the region rectly after resulted in recovery and reconstruction also puts a vast number of people at risk; in the Phil- requirements totaling US$4.4 billion in the Philip- ippines an estimated 74 percent of the population is pines alone, including US$2.4 billion public spend- vulnerable to natural hazards, while in Lao PDR two ing needs (Philippines Government et al, 2009). thirds of the country’s population face an average of 1.5 serious floods or droughts every year. In Viet Disaster risk financing and insurance (DRFI) can Nam, more than 70 percent of the population is es- help ASEAN Member States increase their fi- timated to be exposed to risks from multiple natural nancial resilience against natural disasters, as hazards and in Cambodia 31 percent of the popula- part of their broader disaster risk management tion is estimated to be in an area of risk from two or agenda. DRFI has been identified as an area for ex- more hazards. ploration under the Prevention and Mitigation com- ponent of the ASEAN Agreement on Disaster Man- Disasters have created considerable public and agement and Emergency Response (AADMER) Work private recovery and reconstruction financing Programme, for implementation in Phase 1 (2010- requirements. The recovery and reconstruction 2012). Strategies and mechanisms for financial pro- cost resulting as a consequence of the 2009 West tection against disasters can reduce the impact of Sumatra earthquakes in Indonesia, for instance, disasters on developing countries by taking pressure was estimated at US$2.4 billion, of which almost a off fiscal and individual budgets in the aftermath of < 8 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States a disaster and by reducing the opportunity costs as- Framework for Action (HFA), there is significant sociated with sourcing funding to meet post-disaster diversity in the progress of implementation needs. Strategies that provide rapid, cost-efficient li- both among countries and each HFA priority. Disas- quidity to governments or individuals can ultimately ter risk management (DRM) efforts have gained mo- reduce the cost of disasters by preventing a resort to mentum since the 3rd Asian Ministerial Conference adverse financial coping mechanisms such as high- on Disaster Risk Reduction (AMCDRR) held in Kuala interest borrowing. Lumpur in 2008. Important milestones also include the 2nd Session of the Global Platform for Disaster Risk Reduction in June 2009 and the 3rd Session of Disaster risk financing and insurance (DRFI) has the Global Platform for Disaster Risk Reduction in been highlighted by the ASEAN Finance Minis- May 2011. See Table 1.1. ters as an area for future regional financial co- operation. The Finance Ministers of ASEAN Mem- ber States highlighted the importance of regional Box 1.1: Hyogo Framework for Action cooperation on disaster risk financing and insurance (HFA) at the ASEAN Finance Ministers’ Meeting in Bali in April 2011. They agreed that a regional disaster risk The HFA is a results-based plan of action adopted financing and insurance strategy is essential to deal by governments around the world to reduce disas- ter risks and vulnerabilities to natural hazards and to with natural disasters. They reiterated this statement increase the resilience of nations and communities to at the 14th ASEAN+3 Finance Ministers’ Meeting in disasters over the period 2005 to 2015. Viet Nam in May 2011, where they requested the initiation of feasibility studies on disaster risk financ- HFA Priority #1: Ensure that disaster risk re- ing and insurance. duction is a national and a local priority with a strong institutional basis for implementation Disaster Risk Management in ASEAN HFA Priority #2: Identify, assess, and monitor di- Member States saster risks and enhance early warning ASEAN Member States take regional, national, HFA Priority #3: Use knowledge, innovation, and and sub-national approaches to disaster risk man- education to build a culture of safety and resilience agement. The ASEAN Committee on Disaster Risk at all levels Management (ACDM) was established in 2003 and tasked with the coordination and implementation HFA Priority #4: Reduce the underlying risk factors of regional activities on disaster management. The HFA Priority #5: Strengthen disaster preparedness Committee has cooperated with United Nations for effective response at all levels bodies such as United Nations International Strategy for Disaster Reduction (UNISDR) and United Nations Office for the Coordination of Humanitarian Af- Disaster risk financing and insurance is a key fairs (UNOCHA). The ASEAN Agreement on Disaster component of HFA Priority #4 and is also one Management and Emergency Response (AADMER) of the five pillars in the framework for disaster risk provides a comprehensive regional framework to management (DRM) promoted by the World Bank. strengthen preventive, monitoring, and mitigation The World Bank has been promoting a proactive measures to reduce disaster losses in the region. and strategic framework for DRM. This framework is based on five pillars: (i) risk assessment; (ii) insti- While progress has been made by ASEAN Mem- tutional capacity building; (iii) risk reduction invest- ber States in all priority actions of the Hyogo ments; (iv) emergency preparedness; and (v) disaster Chapter 1: Introduction < 9 > Table 1.1. Progress toward the achievement of the HFA priorities as of 2011, as reported by ASEAN Member States Scale: implementation progress ranges from 1 to 5 where: 1 = achievements are minor and there are few signs of planning or forward action 2 = some progress without systematic policy and/or institutional commitment 3 = institutional commitment attained but achievements are neither comprehensive nor substantial 4 = substantial achieved attained but with recognized limitations in capacities and resources 5 = Comprehensive achievement has been attained, with the commitment and capacities to sustain efforts at all levels Priority #1 Priority #2 Priority #3 Priority #4 Priority #5 Brunei Darussalam 3 3 2 2 3 Cambodia 2 2 3 3 2 Indonesia 4 4 3 4 3 Lao PDR 2 4 3 3 3 Malaysia 4 4 4 4 4 Myanmar 3 2 2 2 2 Philippines 4 4 3 3 4 Singapore 5 5 5 3 5 Thailand 4 3 4 3 4 Viet Nam 4 3 3 3 4 Source: Data for all countries except Cambodia and Singapore are taken from UNISDR (2011) HFA Progress in Asia Pacific – Regional Synthesis report 2009-2011. Data for Cambodia and Singapore are taken from their 2009 National progress reports on the implementation of the Hyogo Framework for Action. risk financing and insurance. Despite prevention sub-national levels is a particular challenge. In ad- and mitigation efforts, no country can fully insulate dition, the development and use of tools and meth- itself against major natural disasters. Disaster risk odologies to support DRR activities remains limited, financing and insurance allows countries to increase making investment in disaster risk reduction (DRR) their financial response capacity in the aftermath of a continuous challenge. Cross-sector and cross- a disaster and to reduce the economic and fiscal bur- jurisdictional coordination, a current area of weak- den of natural disasters by devising financial strate- ness often underlined by low capacity and limited gies combining post-disaster financing (for example, resources, require strengthening. Finally, while there post disaster credit) and ex ante risk financing (for has been progress in raising public awareness, coun- example, reserves, contingent credit, and risk trans- tries find it challenging to sustain awareness of fer instruments like insurance). low frequency disaster risks and to expand public knowledge beyond high risk areas that face recur- rent events. According to the most recent HFA progress report for the Asia Pacific region6, the limited institution- Progress on HFA priority #1. The importance of alization of DRM as a priority at the national and an institutional framework for DRM is widely accepted. Between 2009 and 2011, new DRM Regional Synthesis report 2009-2011 6 policies and legislature were introduced or ad- < 10 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States opted in the Philippines, Viet Nam, and Thai- progress in improving its research methods and tools land. While most countries reported that they have in risk assessment. dedicated funds for response, budget allocation for disaster risk reduction measures is in general still Progress on HFA priority #4. Rapid urbaniza- limited. The Philippines and Malaysia have made tion, growth of informal settlements, weak en- specific allocations for DRM activities. In Malaysia, forcement mechanisms, and low capacity have US$2 billion was spent on DRR related mitigation all acted as constraining factors in reducing un- measures during 2006-2010, and US$1.7 billion has derlying risk factors. Contingency planning and been allocated for mitigation, early warning, pre- vulnerability and risk assessment figure prominently paredness, and awareness for 2010-2015. In the in the efforts in Indonesia and the Philippines. Indo- Philippines, US$111 million has been allocated for nesia, the Philippines, and Viet Nam have also made the National Disaster Risk Management and Recov- efforts in watershed management and crop diversi- ery Fund (NDRMRF), for risk reduction, prepared- fication. Recovery efforts in Myanmar after Cyclone ness, and response purposes. The Strategic Frame- Nargis (2008) and in the Philippines after typhoons work on Climate Change also provides resources for in 2009 have included DRR measures. financing DRR activities. In addition to the NDRMRF, sectoral agencies, such as infrastructure, agricul- Progress on HFA priority #5. Disaster pre- ture, and social welfare, can use a portion of their paredness activities and the preparation of budgets for DRM purposes. Local governments also contingency plans have been undertaken in have their own Local DRM Funds. several countries. The development and use of contingency mechanisms and financial reserves is Progress on HFA priority #2. While hazard risk still at an early stage, as countries still focus mostly assessments have been carried out by most on post-disaster response. In the Philippines, the countries, they are often limited in terms of the government pledged to make 100,000 education scope of hazards and geographical area cov- and health facilities safe from disasters as part of ered. Myanmar launched an Action Plan on Disaster the ‘One Million Safe Schools and Hospitals Pro- Risk Reduction which includes vulnerability and risk gram’. Targeted school and hospital safety pro- assessment and the production of a national hazard grams were also developed in Lao PDR, while leg- and vulnerability atlas. However, information dis- islative provisions were strengthened in Thailand, semination at the community level is challenging. Viet Nam, and Myanmar. The Philippines completed the Hazard Mapping and Assessment for Effective Community-Based DRM (READY project). Early warning systems have re- Objectives of the Report ceived attention from most governments. This report is part of a project being jointly conducted by the World Bank, the GFDRR, the Progress on HFA priority #3. There has been ASEAN Secretariat, and UNISDR. It aims to pro- progress in the development of disaster risk vide capacity building on disaster risk financing and information. However, with often limited internet insurance (DRFI) in ASEAN Member States. DRFI is connectivity, information dissemination remains a a relatively new topic and, therefore, training and challenge. There have been efforts to include DRM capacity building of local stakeholders is essential. into school curricula (Myanmar, the Philippines, and Governments must understand the benefits and the Lao PDR) but these initiatives often do not reach limitations of disaster risk financing and insurance as university and college levels. Lao PDR carried out a part of their comprehensive DRM strategies. pilot on mainstreaming DRM in education that is to be expanded across the country. Thailand has made Chapter 1: Introduction < 11 > This report is a first collaborative effort to pres- This report presents main findings and recom- ent a comprehensive body of knowledge on the mendations on DRFI in the ASEAN region. Fol- state of disaster risk financing and insurance lowing the World Bank disaster risk financing and in ASEAN Member States. It shares examples of insurance framework, it consists of five chapters, best practice and draws lessons from international including this introduction. Chapter 2 presents a experience. It concludes by presenting options for preliminary economic and fiscal risk assessment of consideration for the development of regional and natural disasters in ASEAN Member States. Chap- national integrated disaster risk financing and insur- ter 3 provides an overview of the fiscal manage- ance strategies, to be further discussed by ASEAN ment of natural disasters currently implemented by Member States. It is expected that this report will ASEAN Member States. Chapter 4 reviews the state contribute toward a strengthened understanding of the private catastrophe insurance markets, includ- and collective knowledge within the ASEAN region ing property catastrophe risk insurance, agricultural on DRFI and will encourage open dialogue between insurance, and disaster microinsurance. Chapter 5 stakeholders on how regional and national strate- identifies five main recommendations for strength- gies can best be developed to increase financial re- ening the long-term financial and fiscal resilience of silience against natural disasters. ASEAN Member States against natural disasters, as part of their broader disaster risk management and climate change adaptation agendas. Chapter 2 Financial Assessment of Natural Disasters < 13 > October 22, 2009 - Typhoon Lupit off the Philippines. < 14 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Quantifying risk is a critical first step in the devel- Economic Assessment of Natural opment of any strategy for financial management Disasters of natural disasters. Furthermore, the value of such analyses goes well beyond disaster risk financing, as Floods, storms (cyclones and typhoons), and outputs have applications across all areas of disas- earthquakes have caused major economic ter risk management, from contingency planning to losses for the ASEAN region over the last 15 resilient building. This chapter presents an initial di- years. Importantly, both low-frequency, high-im- saster risk assessment of the ASEAN region. It looks pact events, such as earthquakes and cyclones, and at the past and potential future costs of natural di- high-frequency, typically lower-impact events, such sasters in the region from both a total economic and as floods, droughts, and wildfires, have caused fiscal perspective. The economic and fiscal risk as- significant economic damage in ASEAN Member sessment of natural disasters presented in this chap- States over the last decade. Figure 2.1 shows his- ter complements other analyses utilizing different torical annual average losses over the period 1996- base data sources and modeling methodologies7. 2010. The figure illustrates the range of perils experienced in the ASEAN region, including high- Readers can consult a number of alternative views such as 7 frequency, low-impact hazards, such as droughts, the 2011 UN Global Assessment Report on Disaster Reduc- tion and the ASEAN DRMI 2010 report for alternative views and low-frequency, high-impacts events, such as on economic losses and risk earthquakes and storms. Figure 2.1. Historical Average Economic Losses for ASEAN Member States by peril (1996-2010) 3,000 Wildfire 2,500 Volcano Storm 2,000 Mass movement wet US$ Millions Forest fire 1,500 Flood Earthquake 1,000 Drought 500 0 Indoensia Viet Nam Myanmar Thailand Philippines Malaysia Cambodia Source: Authors from EMDAT CRED Note: EMDAT CRED loss data is recorded in current US$ dollars of the year in which the disaster occurs. To account for possible changes in exposure and price over time, financial losses are multipled by a factor of (GDP2010/GDPyear). Singapore does not report historical losses over the study period, while Brunei Darussalam only reported one major loss (of US$ 2 million loss in 1998). Due to the small size of annual average historical losses, both countries are excluded from the graph. Chapter 2: Fiscal Assessment of Natural Disasters < 15 > Assessment of natural disaster risk requires torical period under consideration. In practice, while analysis of both historical data and catastrophe catastrophic probabilistic models have been devel- probabilistic models. For example, although the oped and are available for certain perils (earthquakes Philippines experienced relatively low annual average and storms), catastrophic flood probabilistic models losses between 1996 and 2010, it is one of the most are seldom available, mainly due to the underlying exposed ASEAN Member States, particularly to the complexity of such disasters. Therefore, the analysis risk of catastrophic cyclones. For this reason, historical of disaster economic losses in ASEAN Member States information needs to be complemented with proba- presented in this report combines scientific probabilis- bilistic catastrophe risk models; the latter capture the tic models for earthquakes and storms with a histori- possibility of infrequent events, such as a one-in-100 cal approach to modeling losses from all other perils, year storm, even if they are not observed in the his- including floods. See Boxes 2.1 and 2.2. Box 2.1. Loss risk assessment methodology Following the World Bank methodology, a preliminary financial risk assessment has been conducted to calcu- late average expected losses (AELs) and probable maximum losses (PMLs) for the purposes of this report. This assessment is based on a combination of reported historical and simulated disaster losses, the latter obtained from earthquake and typhoon probabilistic models. Historical disaster loss data, as reported by EM-DAT CRED, provide information on historical geophysical and hydro-meteorological events that exceed a defined threshold of severity. Historical loss data for high-frequency, low-impact natural disasters such as droughts, floods, and forest fires for 1996-2010 were extracted from the EM-DAT CRED database. These data are expressed in the database in current US dollars in the year of the di- saster event. Losses were therefore multiplied by a factor equivalent of GDP2010/GDPyear to account for changes in exposure through time as well as for price inflation. Simulated catastrophe losses were computed from probabilistic catastrophe risk models for the perils of earth- quake and typhoon, providing information about catastrophic losses caused by simulated major natural disas- ters of varying severity. Willis Re along with members from the Willis Research Network contributed simulated catastrophe losses for this analysis. Statistical analysis and inference based on the historical data were performed and complemented with the results generated by the probabilistic catastrophe models to calculate AELs and PMLs. < 16 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 2.2. Probabilistic catastrophe risk modeling The economic assessment of natural disasters presented herein uses probabilistic catastrophe risk modeling output. This technique was originally developed by the insurance industry to assess the risk of a portfolio of assets and to price insurance contracts. Probabilistic catastrophe risk modeling is increasingly used by govern- ments to assess their exposure to adverse natural events and by insurance regulators to implement risk-based supervision of insurers/reinsurers underwriting catastrophe risk. Access to catastrophe risk models is limited in the ASEAN region. The principle model sources are: ■■ Independent third-party vendor modeling firm ‘off the shelf’ models ■■ Broking house models ■■ Insurer and reinsurer tools developed in-house Independent third-party model vendor coverage: The table below details ‘off-the-shelf’ model availability from the three largest independent third-party catas- trophe model vendors. For the perils of earthquake and typhoon, all models explicitly capture the principal loss agents of wind damage for typhoon and ground motion for earthquake. Treatment of additional loss agents varies as follows: ■■ Tsunami following earthquake is not modeled by any vendor; ■■ Rainfall-induced-flooding from typhoon is modeled by both vendors providing typhoon modeling in the region; ■■ Coastal storm surge from typhoon is modeled by EQECAT but not included in the AIR Philippines typhoon model. Brunei Darussalam Cambodia Indonesia Lao PDR Malaysia Myanmar Philippines Singapore Thailand Viet Nam Earthquake, AIR Worldwide Earthquake Typhoon Earthquake, Earthquake, Earthquake, EQECAT Earthquake Earthquake Typhoon Typhoon Typhoon Risk Manage- Earthquake Earthquake ment Solutions Broking house models: International brokers operating in the region have also developed models, primarily used for technical support to their clients. Aon Benfield Impact Forecasting has an Asia typhoon model covering the Philippines, Thailand, and Viet Nam. Willis has created regional stochastic risk tools and models mostly for those areas or perils for which there are no vendor models. Their models include typhoon models for the Philippines, Viet Nam, Thai- land, Cambodia, and Lao PDR and earthquake models for the Philippines, Indonesia, Singapore, Malaysia, Viet Nam, Thailand, Cambodia, and Lao PDR. Insurer/reinsurer models: International reinsurers often develop their own models in-house to supplement vendor model output for their catastrophe exposure management and pricing processes. It is likely that the large international reinsurers op- erating in ASEAN Member States have their own view of risk for some territories and perils. Some insurers op- erating in the region will also have models developed in-house – for example, specialist Indonesian earthquake insurer PT Maipark has developed a probabilistic earthquake model to support its operations. Chapter 2: Fiscal Assessment of Natural Disasters < 17 > Every year, on average, the ASEAN region experi- of national GDP: high risk countries, comprising ences losses related to natural disasters estimat- Myanmar, the Philippines, Viet Nam, Lao PDR, ed at US$4.4 billion. Annual expected losses (AEL)8 and Cambodia; medium risk countries, compris- are highest for the Philippines, Indonesia, and Viet ing Indonesia, Thailand, and Malaysia, and low Nam, with AELs of US$1.6, US$1.3, and US$0.8 risk countries, comprising Brunei Darussalam billion respectively, according to the analysis under- and Singapore. Myanmar’s AEL represents 0.9 per- taken for the purposes of this report. Singapore and cent of its GDP, while the Philippines and Viet Nam’s Brunei Darussalam present the lowest expected eco- AELs represent 0.8 percent of their national GDPs. nomic losses from natural disasters in the region9. These three countries have the highest AELs as a per- See Figure 2.2. centage of GDP in the ASEAN region. Lao PDR and Figure 2.2. Annual expected economic losses in ASEAN Member States (US$ millions) 1,800 1,600 1,400 1,200 US$ million 1,000 800 600 400 200 0 sia nd m s m ar sia a R e ne or di PD la Na nm ne la ay bo ap pi sa ai o al do ilip ya et m ng us Th La M Vi M Ca In ar Ph Si eiD un Source: Authors, original data EM-DAT CRED and WRN Br The ASEAN region annual expected loss from Cambodia also have significant AELs with respect to natural disaster represents in excess of 0.2 per- their economies. On average, Lao PDR and Cambo- cent of the region’s GDP. ASEAN Member States dia experience annual economic losses equivalent can be classified into three risk groups accord- to about 0.7 percent of GDP. Indonesia, Thailand, ing to their annual expected loss as percentage and Malaysia face moderate AELs relative to GDP, ranging between less than 0.1 percent and 0.2 per- cent. As expected, the two countries with lowest The annual expected loss (AEL) is an expression of the aver- 8 age annual loss over a long period of time. exposure to natural disasters, Singapore and Brunei AEL in Brunei Darussalam is based on historical data since no 9 Darussalam, face marginal AELs relative to GDP. See simulated earthquake or cyclone loss data was obtained, per- Figure 2.3. Note that limited data was available for haps due to the country’s low exposure. Singapore, present- Myanmar and therefore its AEL may not accurately ing no historical economic loss data related to natural disas- ters during the estimation period, is exposed to earthquakes, reflect the long-term average annual losses Myan- and AEL and PMLs are based on earthquake simulated losses. mar would be expected to sustain. < 18 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Figure 2.3. Annual expected economic losses in ASEAN Member States, as percentage of national GDP 1.0 0.9 0.9 0.8 0.8 0.8 0.7 0.7 0.7 0.6 % of GDP 0.5 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.1 0.0 0.0 0.0 ar s m R a N sia nd sia am e ne or di PD EA nm Na ne la ay bo al ap pi AS ai o al ss do ya ilip et m ng La Th M ru Vi M Ca In Ph Si Da ei un Source: Authors, original data EM-DAT CRED and WRN Br The ASEAN region is estimated to face annual Probable maximum losses for the 100-year disaster losses in excess of US$17.9 billion once return period in the ASEAN region represent every 100 years. Indonesia, the Philippines, and 1 percent of the regional GDP. Probable maxi- Viet Nam present the highest 200-year and 100-year mum losses as percentage of national GDPs, probable maximum losses (PMLs)10. The 100-year however, vary considerably across countries, PML for these three countries ranges from US$9.9 being highest for Lao PDR, Cambodia, and the billion for Indonesia to US$3.7 billion for Viet Nam. Philippines. In these three countries, 100-year loss- Malaysia and Thailand face lower 100-year losses of es as percentage of GDP range from 11.7 percent in US$2.3 billion and US$2.2 billion respectively. Lao Lao PDR to 4.7 percent in the Philippines, indicating PDR, Cambodia, and Singapore face 100-year losses that these countries are particularly vulnerable to ex- ranging from US$0.9 billion for Lao PDR to US$3.6 treme hazard events, such as large earthquakes and million for Singapore. Myanmar and Brunei Darus- typhoons, relative to their economic scale. Viet Nam salam did not present a sufficient number of loss and Indonesia present 100-year losses of 3.6 percent years, either historically or simulated, to compute to 1.4 percent of their GDPs, respectively. Malaysia, reliable PMLs. See Figure 2.4 and Box 2.1. Thailand, and Singapore present 100-year losses equal to or lower than 1 percent of their GDPs. Prob- The PML represents the expected loss severity based on likely 10 able maximum losses for Myanmar and Brunei Da- occurrence, such as the 1-in-100 year loss (event of such se- russalam are excluded from the ASEAN pool due to verity that the recurrence is anticipated only every 100 years) or the 1-in-200 year loss. limited data. See Box 2.3. Chapter 2: Fiscal Assessment of Natural Disasters < 19 > Figure 2.4. 100-year and 200-year probable maximum loss in US$ millions 25,000 20,000 15,000 US$ millions 10,000 5,000 0 N sia s m sia nd R a e ne or di PD EA Na ne ay la bo ap pi AS ai o al do ilip et m ng Th La M Vi Ca In Ph Si n PML (100-yr) n PML (200-yr) Source: Authors original data EM-DAT CRED and Willis with members of Willis Research Network Figure 2.5. 100-year and 200-year probable maximum loss, as percentage of national GDP 16.0 14.0 11.7 12.0 10.0 8.0 7.3 % of GDP 6.0 4.7 4.0 3.6 2.0 1.4 1.0 1.0 0.7 0.0 0.0 R a s m ia sia N nd re ne di PD EA s po Na ne ay la bo pi AS ai a o al do ilip et m ng La Th M Vi Ca In Ph Si n PML (100-yr) n PML (200-yr) Source: authors original data EM-DAT CRED and Willis with members of Willis Research Network < 20 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 2.3. Benefits of Risk Pooling The ASEAN region can benefit from regional risk diversification. The figure below illustrates the benefits of risk pooling across countries and perils in the ASEAN region. The sum of 200-year probable maximum losses for the ten ASEAN Member States totals US$42.1 billion without risk pooling. In comparison, the 200-year prob- able maximum loss with risk pooling amounts to US$21.6 billion. This 48.5 percent reduction could translate into significant savings in the cost of risk transfer (e.g., insurance premiums) if a regional pooled risk transfer mechanism, rather than a series of individual country mechanisms, were developed. 45,000 n ASEAN 40,000 n Vietnam 35,000 n Thailand n Singapore 30,000 n Philippines 25,000 n Malaysia n Laos PDR % of GDP 20,000 n Indonesia 15,000 n Cambodia 10,000 5,000 – Sum of 200-year PML Pool’s 200-year PML It is acknowledged that the 2011 flooding in nity: while the analysis presented in this report re- Thailand tragically demonstrated the cata- veals that potential economic losses are subject to strophic potential of floods, implying the anal- the current state of knowledge, it points at the ne- ysis of flood risk in this report is imprecise due cessity of exploring and of developing probabilistic to the limited availability of catastrophic flood flood models for the improvement of future risk as- models for the ASEAN region. See Box 2.4. This sessments. limitation poses both a challenge and an opportu- Chapter 2: Fiscal Assessment of Natural Disasters < 21 > Box 2.4 Implications of the 2011 Thailand floods for financial loss assessment The approach to risk assessment taken in this report suggests that the 100-year and 200-year damage across all ASEAN Member States, excluding damage from earthquake or windstorm, is approximately equal to US$7.8 billion and US$8.9 billion respectively. However, the damage caused by the 2011 floods in Thailand is estimated to be more than 200 percent higher than this, at US$22 billion. Moreover, the damage from this flooding is estimated to be greater than even the 100-year damage across all ASEAN Member States and across all perils. 25,000 20,000 15,000 % of GDP 10,000 5,000 0 Maximum loss 100-year PML, Maximum loss 100-year PML, Estimated damage 1996-2010, excluding 1996-2010 all perils caused by 2011 excluding earthquake and flooding in Thailand earthquake and windstorm windstorm This box discusses whether and how the methodology in this report may have led to the underestimation of catastrophic flood risk and what can be done about it. Risk assessment in this report has been conducted by combining catastrophe probabilistic models for earth- quake and storm risk with statistical analysis of 15 years of historical data for all other perils. This relies upon the crucial assumption that earthquake and storm events drive losses of catastrophic magnitude (50-year, 100-year, or less frequent losses). If ASEAN Member States are exposed to other perils that can cause major damages then this approach is likely to be insufficient for a complete risk assessment. This is because it is typically not possible to accurately extrapolate the expected damage from 100-year (or less frequent) events from 15 years of historical data. The 2011 Thailand floods suggest that at least one ASEAN Member State is exposed to the risk of catastrophic flooding. This risk cannot, therefore, be assessed by statistical analysis of 15 years of data alone; a catastrophic risk model that combines models of climactic events with models of on-the-ground exposure is required. This model would estimate the probability of flood events of varying severity, the localized extent of damage result- ing from such events, and the exposure. It would most likely capture a combination of factors that contribute towards flooding, namely, short periods of heavy rainfall or chronic rainfall events, possible coastal and river surge, and slope of terrain, among other factors, in order to determine loss potential for residential, commer- cial, and industrial facilities. continues < 22 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 2.4 Implications of the 2011 Thailand floods for financial loss assessment (cont.) If catastrophic flooding may be a significant risk faced by some ASEAN Member States, then a full risk assess- ment will only be possible once a set of catastrophe probabilistic models for flooding has been developed for the region, as outlined above. A thorough understanding of disaster risks would not only be useful in designing effective disaster risk financing and insurance strategies, but would also encourage risk mitigation and pre- paredness, including actions to reduce vulnerability and exposure to natural hazards (e.g., territorial planning, building standards,retrofitting). Fiscal Risk Assessment of Natural Defining contingent liability Disasters Contingent liabilities can be explicit or implicit. Governments only assume financial responsibility Governments have an obvious duty as a provider of for part of the total economic losses incurred as a public goods to repair public infrastructure in the af- consequence of natural disasters. As a basis for de- termath of a disaster. They have a moral and social veloping disaster risk financing and insurance strate- imperative to provide rescue services and short-term gies it is necessary to define public responsibilities in humanitarian relief. Further government actions are the event of a disaster and then to assess the related driven by a combination of poverty reduction and cost in fulfilling these responsibilities; this provides economic growth concerns. These can lead govern- estimates of a government’s contingent liability for ments into the role of “insurer of last resort” and disaster events with different rates of return. This stimulator of economic recovery. See Figure 2.6. section addresses this topic. Figure 2.6. Forms of contingent liability Public imperative Policy choice Moral and social duty Poverty reduction - Search and rescue services - ‘Insurer of last resort’ (lives, homes, livelihoods) - Humanitarian relief Contingent liability Provider of public goods Stimulation of economic growth - Repair and reconstruction of public - Support for economic recovery infrastructure Source: Benson (2009a) Chapter 2: Fiscal Assessment of Natural Disasters < 23 > Contingent liability relating to the loss of public Estimation of contingent liability for personal assets and infrastructure can be calculated losses is more difficult in countries where lev- in countries where a detailed inventory of els of public support are not explicitly defined. public assets and a comprehensive disaster Provision of emergency relief, compensation for loss risk assessment of public property have been of life, injury, and loss of homes, and support for the conducted, although with slight complications recovery of livelihoods, particularly farming, is com- where the private sector is heavily involved in basic mon. However, in the absence of mandated forms services provision. The extent of commitment to and levels of post-disaster support, the amount build-back-better principles and the precise nature provided by a particular government in response to of specific actions required to strengthen resilience different events can fluctuate widely. Indeed, it can (e.g., relocation of public assets) will also affect the even vary where obligations are set. See Box 2.5. cost of public infrastructure reconstruction. Levels of compensation in response to differ- In order to establish the total scale of ent disasters may be influenced by a range of contingent liability, however, governments and factors including: stakeholders need to define their exact roles and responsibilities with regard to affected ■■ The scale of the event, with larger events often communities and businesses. These include resulting in additional forms of compensation precise levels of support that will be provided under to offset potentially exponentially larger indirect different disaster scenarios. and secondary economic consequences. ■■ The level of national and international media Contingent liability relating to personal losses coverage, in turn in part correlated with the can already be directly estimated in countries scale of the event. such as Viet Nam and Lao PDR, where statutory levels of personal compensation in the event of a ■■ The availability of funding relative to the disaster have been set, relating to loss of human life scale and nature of response needs, itself in or injury and loss of homes and productive assets. part influenced by prevailing macroeconomic In both Viet Nam and Lao PDR, compensation is conditions as well as disaster risk financing fixed at very low levels, providing a safety net for arrangements. the poor but also ensuring that related costs are not ■■ Political opportunism. prohibitive. Box 2.5. In-country variations in post-disaster support for affected households ■■ In Thailand, substantially higher payments were made to families who lost their principal breadwinner as a consequence of the 2004 Indian Ocean tsunami than to those who lost breadwinners in more recent flood events. ■■ Homeowners in Indonesia received more support following the 2006 Central Java earthquake than the 2009 West Java and West Sumatra earthquakes (World Bank, 2011a). ■■ In Viet Nam, provinces sometimes provide much higher levels of disaster compensation – in some cases perhaps five to six times more – than legally mandated (Benson, 2009b). Ad hoc compensation may also be provided for private losses in addition to those specified under Vietnamese law. < 24 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States The lack of clarity on forms and levels of post- An initial analysis on this basis indicates that disaster government support to affected com- the annual expected fiscal burden of disasters munities and businesses and variations in ac- is equivalent to 0.5 percent or more of total tual practice make it extremely difficult to public expenditure in Myanmar, the Philippines, estimate public contingent liability from an ex Cambodia, Lao PDR, and Viet Nam. See Figure ante perspective, based on expected govern- 2.7. According to the assumptions outlined below, ment behavior. Moreover, it can make it difficult to this spending would be split across two years, with manage expectations and to provide equitable, cost- early recovery costs relating to a particular disaster efficient disaster response packages. A clear delinea- event accounting for 0.2 percent or more of annual tion of public and private roles and responsibilities expenditure in year one and reconstruction for 0.3 is essential in encouraging private commercial and percent or more of annual expenditure in year two domestic uptake of risk transfer products and invest- in these five countries. See Box 2.6. These countries ment in risk reduction. should have comprehensive financing strategies in place to avoid substantial regular diversion of pub- Evidence on contingent liability lic resources from development to disaster response purposes. Ex post estimates of damage and of public sector shares in recovery and reconstruction spending The particularly high levels of contingent pub- requirements for recent disasters in the ASEAN lic liability relative to annual government ex- region may provide the basis for an alternative penditure for 1-in-100 and 1-in-200 year events approach to the estimation of contingent liabil- in Cambodia and Lao PDR and for 1-in-200 year ity. Observed ratios of damage to public sector recov- events in the Philippines are also noteworthy, ery and reconstruction spending requirements can be emphasizing the importance of instruments to man- applied to the average expected economic loss (AEL) age low-frequency, high-cost events in these coun- and probable maximum loss (PML) data presented in tries. See Figure 2.8 and Appendix 3. Note that lim- Section 2 above to generate public contingency li- ited data was available for Myanmar and therefore ability estimates for hazard events with varying rates that its high AEL relative to government expenditure of return for each ASEAN Member State. As already may be a consequence of the limited historical peri- noted, governments meet some part of the recovery od underpinning the analysis rather than a reflection and reconstruction bill but do not fund it in full. See of the long-term AEL Myanmar would be expected Table 2.1. Contingent liabilities can then be placed in to sustain. context relative to socioeconomic indicators such as GDP, government expenditure, and population. Chapter 2: Fiscal Assessment of Natural Disasters < 25 > Table 2.1. Recent damage, loss and needs assessment estimates for ASEAN Member States Note: Estimates of damage are based on the replacement cost of damaged and destroyed infrastructure and assets at their original location and to original specifications. In contrast, reconstruction costs incorporate changes in location and specification to increase disaster resilience and possible changes in service provision as envisaged in the reconstruction plan. The below table also indicates reported losses. These relate to disrupted flows of income resulting as a consequence of the damage and destruction of physical infrastructure. Losses are not included in the estimates of average expected loss and probable maximum loss reported above so are not taken into account in estimating contingent liability as a percentage of AEL or PML in Figures 2.7 and 2.8. However, they are reported in the table below for the sake of completeness. Damage and losses Recovery and reconstruction requirements Public sector Public sector Total Damage (US$ Losses share in total Total Public sector requirement Year Disaster (US$ million) million) (US$ million) (%) (US$ million) share (%) as % of GDP Cambodia 2009 Typhoon 132 58 74 191 Ketsana Indonesia 2004 Aceh and 4,452 2,920 1,531 34 NA ($4.6bn) 1.8 West Sumatra tsunami 2006 Aceh floods 210 198 12 30 NA NA NA 2009 West Sumatra 2,300 2,070 230 12 2,436.50 31 NA earthquakes Lao PDR 2009 Typhoon 58 51 7 45 124a 20b 0.4 Ketsana Myanmar 2008 Cyclone 4,057 1,754 2,303 NA NA ($1.0bn) NA Nargis–2008 2009 Typhoons 4,383 1,452 2,931 10 4,423d 55c NA Ondoy (Ketsana) and Pepeng (Parma) a $4.8 million (4%) for immediate needs, $47.1 million (38%) over 24 months to restore pre-Ketsana standards plus a further $72 million (58%) for longer-term improvements (structural improvements, relocation of human settlements etc.). The assess- ment noted that the cost of some additional longer-term improvements had yet to be calculated and thus that the estimate of $72 million was based on incomplete information. b The estimate includes relief requirements. c The assessment notes that the exact public sector need depends on government decisions on specific programs of support, the timing and pacing of those programs, and the effectiveness with which they are implemented. d US$2.6 million (59%) in short-term recovery and reconstruction needs and US$1.8 million (31%) in medium-term needs. Sources: Cambodia Royal Government, 2010; Lao PDR Government et al, 2009; Indonesia Government, 2005; Indonesia BAPPENAS and the International Donor Community, 2005; Indonesia Government Kecamatan Development Program and the World Bank, 2007; Indonesia BNPB et al, 2009 ; Philippines Government et al, 2009; TCG, 2008. < 26 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 2.6. Assumptions underlying contingency liability estimates Contingent liability is equivalent to: ■■ 30% of average expected loss ■■ 30% of damage for 1-in-20 year events ■■ 35% of damage for 1-in-100 year events ■■ 40% of damage for 1-in-200 year events 40 percent of contingent liability is incurred within 12 months from the date of a disaster, in the form of recov- ery requirements. 60 percent of contingent liability is incurred 12-24 months from the date of a disaster, in the form of reconstruc- tion requirements. Figure 2.7. Annual expected fiscal burden arising as a consequence of natural disasters as a percentage of annual government expenditure 3.0 Annual expected fiscal burden as % of 2.5 government expenditure 2.0 1.5 n Recovery liability n Reconstruction liability 1.0 0.5 0.0 ar s a R m sia nd sia e i N e ne or di PD EA un nm Na ne la ay bo ap pi ai Br AS o al do ya ilip et m ng La Th M Vi M Ca In Ph Si Note: Limited data was available for Myanmar and therefore its AEL may not accurately reflect long-term average annual losses. Source: authors, original data listed in methodology description. Chapter 2: Fiscal Assessment of Natural Disasters < 27 > Figure 2.8. Estimated probable fiscal burden arising as a consequence of a 1-in-200 year probable maximum economic loss event as a percentage of annual government expenditure 25 1-in200 year PML as % of annual 20 government expenditure 15 n Recovery liability n Reconstruction liability 10 5 0 R s a m sia sia nd e N ne or di PD EA Na ne ay la bo ap pi ai AS o al do ilip et m ng La Th M Vi Ca In Ph Si Note: Myanmar and Brunei Darussalam did not present sufficient number of loss years, either historically or simulated, to compute reliable PMLs. Source: authors, original data listed in methodology description. Box 2.7. Limitations of the public contingency liability analysis The public contingency liability analysis has certain limitations relating to difficulties in determining robust underlying assumptions. As the data in Table 2.1 clearly indicate: ■■ The ratio of damage to recovery and reconstruction costs can vary significantly. For instance, the estimated cost of recovery and reconstruction in Lao PDR following Typhoon Ketsana was more than double that of reported damage because the disaster highlighted the extreme vulnerability of existing as- sets and the need for substantial investment to reduce future risk (Lao PDR Government et al, 2009). ■■ The public sector share in total recovery and reconstruction costs can vary widely. It will depend on the nature and scale of damage and the relative balance of public and private sector asset ownership in the affected sectors. ■■ The relative balance of reconstruction and recovery requirements can differ and most likely var- ies both among countries and types of hazard. (See Table 2.1 footnotes (a) and (d)). The overall split between reconstruction and recovery needs was not reported for the other events.) ■■ Emergency relief needs are typically not included in recovery and reconstruction estimates. As such, the latter provide an underestimate of the total cost of disaster response. Furthermore, data on damage and losses also need to be treated with some caution. The assessments in Table 2.1 are comprehensive and fairly reliable. In other cases, however, damage and loss assessments are often incomplete and subject to inaccuracies. This reflects the fact that many countries lack standard, systematic continues < 28 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 2.7. Limitations of the public contingency liability analysis (cont.) damage assessment guidelines and related training courses, resulting in gaps in data collected and variations in methods of loss estimation. The extent to which private damage is covered can also vary widely, implying that public contingent liability may account for a distortedly high share in total damage in some instances. In addi- tion, total damage and losses in monetary terms are often not reported. A review of EM-DAT revealed that such information is absent for around two-thirds of disasters (Loayza and others 2009). In view of these various limitations, rules of thumb on the ratio of the public contingent liability bill to average expected economic losses or probable maximum losses ideally need to be developed on an individual country and hazard basis. These ratios may well need to be graduated too, with contingent liability as a share of total recovery and reconstruction costs rising as the scale of a disaster event increases. Community and familial support structures may be increasingly undermined as the scale of a disaster increases, forcing exponentially higher reliance on the state, while the proportion of public infrastructure that is totally destroyed, rather than damaged, may also rise. Chapter 3 Fiscal Management of Natural Disasters < 29 > < 30 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States This chapter outlines existing disaster risk financ- funding for slightly larger events can be raised via ing and insurance arrangements for post-disaster the post-disaster reallocation of budgetary resources response in the ten ASEAN Member States. It in- and the realignment of national investment priori- cludes a desk-based review of the performance and ties, potentially at a slightly higher opportunity cost. adequacy of these arrangements and the extent of Governments can also introduce temporary, post- reliance on non-formalized instruments in the form disaster tax increases, increase borrowing or expand of post-disaster budget reallocations, longer-term money supply. Related funding instruments include capital investment realignments, and fiscal deficit fi- development partner contingency credit arrange- nancing. It ends by presenting available evidence on ments and post-disaster reconstruction loans. Re- the scale of the public funding gap for post-disaster maining layers of residual risk associated with lower- response in several ASEAN Member States and em- frequency, higher-cost event should be transferred phasizing the need for comprehensive disaster fi- to third parties via a mixture of more expensive re- nancing tracking systems. International experience insurance tools and catastrophe bonds and, for the is drawn upon for comparison. This analysis aims to most extreme events, via reliance on international open a discussion with the ASEAN Member States assistance. This approach is elaborated upon in fur- on the fiscal management of natural disasters to (i) ther detail in Chapter 5. validate and complete the findings and (ii) discuss the efficiency of the current management in terms There is an additional time dimension relating of resource mobilization and execution. A more de- to the decomposition of post-disaster funding tailed discussion is provided in Appendix 3. needs into the various phases of relief, early recovery, and reconstruction. Some financing Introduction instruments can be activated very rapidly. See Figure 3.1. Certain others may take longer to activate Disasters potentially increase public spending but can generate substantial funding. The disaster requirements while simultaneously reducing risk financing strategy needs to reflect both time revenue. Their immediate and longer-term fiscal and cost dimensions, ensuring that the volume of consequences depend on the nature and extent of funding available at different stages in the response impact of individual disasters and the disaster risk efforts matches actual needs in a cost-efficient financing instruments at a government’s disposal. manner. It also needs to incorporate a systematic To reduce disaster risk, levels of public expenditure tracking system to monitor resources. on risk reduction should be sufficient relative to the level and nature of risks faced, the expected net eco- If adequate and timely funding arrangements nomic and social returns to individual risk reduction are not in place, the adverse socioeconomic options, and the reasonable responsibilities and ob- impact of a disaster can be significantly ligations of government (most critically to avert loss exacerbated, both at macroeconomic and of life) (Benson, 2009). household levels. Recent theoretical econometric modeling by Hallegatte et al (2007) suggests that The World Bank framework for disaster risk the economic impacts of disasters, as defined in financing and insurance advocates a three- terms of gross domestic product (GDP) losses, are tiered layered approach to the development of much higher in countries where public (and private) financing arrangements to cover the residual reconstruction resources are limited and thus where disaster risks that cannot be mitigated. Risks as- reconstruction is spread over a number of years. At sociated with high-frequency, lower-cost events oc- the household level, if public assistance is insufficient curring on a near-annual, recurrent basis should be or even simply delayed poorer families may be met via regular annual budget allocations. Further forced to resort to adverse coping mechanisms Chapter 3: Fiscal Management of Natural Disasters < 31 > Figure 3.1. Availability of financial instruments over time Short term (1-3 months) Medium term (3-9 months) Lomg term (over 9 months) Ex-post financing Contingency budget Donor assistance relief In-year budget reallocation Domestic credit External credit Capital budget reallignement Donor assistance (reconstr.) Tax increase Ex-ante financing Reserve fund Contingent debt Parametric insurance Traditional insurance Source: Ghesquiere and Mahul, 2007 such as informal high-interest borrowing, the sale In some ASEAN states, there is a second more of household and productive assets (sometimes at general budget line for a wider range of un- highly reduced prices), and withdrawal of children foreseen circumstances that can be drawn from school. Opportunities presented by disasters upon once the disaster response budget line is to upgrade infrastructure and technology and to exhausted. In certain other ASEAN Member States, strengthen resilience to future hazard events are also post-disaster relief and early recovery spending re- partly lost if there is insufficient funding available for quirements are simply covered under this more gen- reconstruction. eral budget allocation and there is no disaster-spe- cific line of funding. Ex-Post Practices and Arrangements Singapore is a notable exception. The Govern- Annual budgeting for disaster relief and ment of Singapore makes no annual budgetary early recovery allocations for disaster response because the risks of a disaster are low. In the event that one does occur, Most ASEAN governments make some regular the Government’s Operations Civil Emergency Plan national annual budgetary provision for poten- is activated. This plan gives the Singapore Civil tial disaster relief and early recovery purposes. Defense Force the authority to direct all response National disaster management offices (NDMOs) com- forces under a unified command structure and monly have overall responsibility for humanitarian re- for all required resources to be pooled (Singapore lief and often have a related budget to support them MSD, 2009). This practice parallels that in certain in that role. Local governments can typically request other high-income, low-disaster-risk countries support from this central budget once they have ex- which, similarly, do not allocate annual resources hausted local resources. In some countries, line agen- for disasters. Instead, they have budgetary cies can also access this funding. Certain line agen- mechanisms or funding lines that can be activated cies may hold additional emergency financing of their in the event of a disaster and adequate financial own. Most countries in the region stockpile emergen- capacity to ensure that these lines are sufficiently cy relief items as well. See Table 3.1 and Box 3.1 resourced (Benson, 2011). < 32 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 3.1. Enhancing budgetary arrangements for disaster risk management in the Philippines In 2010, the Philippines passed a new Disaster Risk Reduction and Management Law, replacing the existing disaster risk management system with one emphasizing the need for a coherent, comprehensive, integrated, and proactive approach across different levels and sectors of government and among vulnerable communities. The new law revamped the prevailing National and Local Calamity Funds into National and Local Disaster Risk Management and Recovery Funds (NDRMRF/LDRMRF). These Funds continue to receive annual budget ap- propriations from the relevant level of government but 70 percent can now be used for disaster risk reduction purposes. In the case of the NDRMRF, disbursements are endorsed by the newly constituted National Council to the President, which decides on allocations. The Fund is administered by the Department of Budget and Man- agement (DBM), and disbursements are directly made to affected agencies and local governments. A portion of the NDRRMF is automatically allocated to the Quick Response Fund, which supports immediate response and recovery efforts. To encourage spending on ex ante measures, the declaration of a state of calamity is only required to trigger disbursement of the quick response fund. Monthly reporting on the use of the NDRMRF is required for all national and local agencies which receive support from the national fund. At the local level, the new law removed the 5 percent ceiling imposed on the local calamity fund and set it as a new minimum spending requirement on disaster risk management. The law also allows for any unspent LDRMRF resources to be rolled over at the end of the fiscal year and accrue for up to five years (see Box 3.3), for the LDRMRF to be used for the purchase of insurance coverage, and for local governments to transfer their unexpended LDRRMF to other LGUs. The establishment of a local government disaster response pool is also being discussed (see below) Over the last few years there has been a substantial increase in the level of allocations to the national calamity fund/NDRMRF, rising from PhP 2 billion (US$44 million) in FY2010 to PhP 5 billion in FY2011, with a further increase to PhP 7.5 billion (US$176 million) proposed for FY2012. The FY2012 proposal is equivalent to 85 percent of the Government’s total estimated contingent liability for a one-in-five year event, as estimated ac- cording to the World Bank (2010b). Source: World Bank, 2010b The scale of annual budgetary provision for di- its more general emergency budget line in FY2012, saster response varies considerably between in this case in response to a perceived increase in ASEAN Member States both in absolute terms the incidence of climatic hazards. In contrast, very and relative to average expected needs and limited budgetary provision relative to likely need is total government expenditure. Annual alloca- made for potential disasters in Cambodia, Lao PDR tions are apparently near sufficient to cover statu- and Myanmar. tory personal compensation and early recovery costs in, for instance, Viet Nam (World Bank, 2010a) and Speed of disbursement is critical too. In practice, Indonesia (World Bank, 2011a). The Philippines has it can take some time for these and other forms of also increased its budgetary provision for disaster re- disaster response funding to move, potentially signif- sponse substantially over the past few years and the icantly exacerbating the adverse impacts of disasters allocation now stands at an apparently reasonable both for affected populations and the wider macro- amount to meet immediate humanitarian and early economy. The speed of disbursement depends both relief needs. Thailand is similarly considering a rise in on the complexity of procedures in place (including Chapter 3: Fiscal Management of Natural Disasters < 33 > Table 3.1. ASEAN government annual budget allocations for potential disaster response purposesa National government Annual budget for potential disaster needs Annual budget for wider Held by NDMO Held by line agencies range of unforseen events Local government Brunei Darussalam Cambodia Indonesia US$470m (2011) Lao PDR US$11.7m (2010-11) Malaysia US$3.3m (2008) Myanmar Philippines US$112m (FY2011) Not less than 5% of revenue from regular sources Singapore Thailand US$8.3bn (FY2011) Viet Nam 2-5% of national budget 2-5% of provincial budget Source: See Appendix 3 Legend: n Blank shaded boxes denote where authors are aware of the existence of a budget allocation but no information on budget size was available. (a) This table is based on the best information that the World Bank team has been able to collate, but should be interpreted with due consideration to limitations arising from the secondary nature of the underlying sources. approval processes) for the release of funds to lo- Disaster response budgets may be topped up cal government and national implementing agencies from a range of sources. In Viet Nam, surplus rev- and on the timing of disasters relative to the fiscal enue (defined as the difference between planned calendar. See Box 3.2. and actual revenue) can be used to supplement Box 3.2. Delays in disbursement post disaster ■■ Following Typhoon Ketsana in 2009, it took three months for the LAK 110 billion (US$13.9 million) approved from the Government of Lao PDR Special Fund for emergency relief and early recovery purposes to begin disbursing. ■■ The 2004 Indian Ocean tsunami occurred at the end of the Indonesian fiscal year, after the budget allocation for the next fiscal year had already been approved. In accordance with normal practice regarding two allocations to the Rehabilitation and Reconstruction Fund per year, during annual budget preparation and (if necessary) the mid-budget review, major budgetary appropriations for the tsunami response efforts were therefore not made until mid-2005 (World Bank, 2011a). ■■ In October 2009, the Philippines Congress passed a resolution authorizing the use of unprogrammed funds of up to PhP 12 (US$266 million) for disaster response efforts relating to typhoons Ondoy (Ketsana) and Pepeng (Parma). One year later, the Department of Budget and Management had allocated only 2.8 percent of this PhP 12 billion.11 ■■ According to Viet Nam’s Ministry of Finance, it can take two to three years for the government to secure funds from the investment plan for post-disaster reconstruction purposes (Benson, 2009b). 11 http://www.senate.gov.ph/press_release/2010/0927_legarda3.asp < 34 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States the budget and provide additional relief and early case of Lao PDR. On the other hand, if a disaster does recovery funding. In practice, however, surplus rev- not occur over the course of the fiscal year then lo- enue has been very limited in recent years, in large cal governments are left with unspent resources, po- part because crude oil prices have been much lower tentially at some considerable opportunity cost. In than forecast (World Bank, 2010a). Meanwhile, the the Philippines, for instance, it was estimated some Government of the Philippines authorized the use years back that, nationally, perhaps as much as 50% of PhP 12 billion (US$ 266 million) from its PhP 76 of local government budgetary provision for poten- billion Unprogrammed Fund for relief operations, re- tial disasters went unutilized each year (World Bank habilitation and reconstruction works, and the pro- and NDCC, 2005). The Philippine Department of the vision of support to affected households following Interior and Local Government (DILG) and League of Ondoy (Ketsana) and Pepeng (Parma) in 2009. The Cities are exploring the pooling of reserves at the pro- Unprogrammed Fund can only be released when to- vincial level (Philippines OCD- NDRRMC, 2011) to uti- tal revenue collections for the entire year exceed the lize these resources more effectively and to increase original revenue targets. individual local government access to disaster funds at relatively low cost. Local governments across the ASEAN region are also commonly required by law to make an an- Any remaining resources under both disaster- nual budgetary provision for disaster response specific and more general national and local purposes and to fulfill certain related responsibilities. government budget lines for unforeseen cir- They are expected to utilize these resources and any cumstances typically revert to the budget sur- other available funds before requesting post-disaster plus at the end of the fiscal year in most ASEAN support from national government. Data on the ex- states, with the notable exception of the Philippines. tent of these resources are extremely difficult to ob- See Box 3.3. This practice in part reflects concerns in tain without embarking on a detailed, sub-national some countries that disaster resources may have been data collection exercise. However, it is widely observed used for non-disaster related purposes on occasion, that often only richer local authorities are able to ful- a risk associated with any line of unallocated fund- fill these requirements. Moreover, the funding avail- ing, and that the rolling over of funds could exacer- able at a local level is frequently only sufficient to deal bate this problem. International experience suggests, with relatively localized events as, for instance, in the however, that the multi-year accumulation of unused Box 3.3. Building multi-year disaster reserves in the Philippines Following a recent change in legislation in the Philippines (see Box 3.1), unutilized local government disaster response budget allocations now accrue into a special trust fund at the end of the budget year. This fund is solely for use in supporting disaster risk reduction and management activities. After five years, any remaining funding reverts to the general fund for expenditure on other social services (Philippines Senate and House of Representatives, 2010). A number of bills are under consideration in the Philippines which would potentially alter the Local Disaster Risk Reduction and Management Fund and its operation yet again. One proposed amendment, for instance, seeks to remove the provision that allows local governments to set aside their unspent funds into a trust fund, where, as off-budget items, funds cannot be audited. The amendment proposes reclassification of the unspent funds into a continuing appropriation, implying that the budget would remain valid for a prescribed number of years if unspent. At the time of drafting of this report, however, the debate on the various bills was at an early stage and it was too soon to determine whether any of them would be implemented. Chapter 3: Fiscal Management of Natural Disasters < 35 > Box 3.4. The Mexican Fund for Natural Disasters (FONDEN) Following Hurricane Pauline which struck Acapulco in 1997 and severe floods in Chiapas in 1998, the Federal Government of Mexico established a Fund for Natural Disasters (FONDEN) as a mechanism to finance the post- disaster recovery and reconstruction of public assets. FONDEN’s policies, procedures, and financial instruments provide a useful example of a disaster risk management approach taken by a government. FONDEN consists of three primary financial accounts: ■■ The FONDEN Program for Reconstruction. This program is designed to provide financial support to rehabilitate and reconstruct public assets. It focuses on (i) the reconstruction of public infrastructure at each tier of government (federal, state, and municipal); (ii) the reconstruction of low-incoming housing; and (iii) the restoration of forestry, protected natural areas, rivers, and lagoons. ■■ The FONDEN Trust. This trust was established to provide resources for the approved activities of the FONDEN Program. It also acts as the contracting authority for risk transfer mechanisms, including insurance and cat bonds. ■■ The Revolving Fund. This fund is designed to respond to the immediate needs of the affected population in the event of a disaster, as FONDEN’s financial instrument for emergency response and the acquisition of aid supplies. Collectively, these instruments assist the Government of Mexico in its efforts to respond quickly to emergency situations with humanitarian aid and to support post-disaster rehabilitation and reconstruction. Continuous changes are made to enhance the efficiency and effectiveness of FONDEN’s instruments. See Annex 4 for further details. funds can work well, particularly when combined major budget headings. See Box 3.5. with a basket of other mechanisms and instruments (Box 3.4). Strict accountability mechanisms are also Many governments draw on regular line agen- necessary to reduce the risk of misuse of funds. cy recurrent funding, particularly maintenance budgets, on a near-routine basis to finance rela- In-year budget reallocations tively small-scale disaster-related repairs. There may be substantial reallocations in kind as well, Some short-term funding for emergency relief relating to the redeployment of government staff, and early recovery is often secured via post- vehicles, equipment, and supplies in support of hu- disaster in-year budgetary reallocations or, in manitarian relief and early recovery efforts. Recur- some cases, via more general mid-year adjust- rent spending appropriations for salaries and wages ments in the annual budget. Reallocations typi- are rarely, if ever, explicitly drawn upon but govern- cally occur within the investment or recurrent bud- ment employee earnings are sometimes docked to gets, rather than between them, and often within make compulsory donations to disaster funds. the same line agency. Similarly, local governments are often authorized to reallocate local discretionary Although reallocations are very common, how- resources in the aftermath of a disaster, although ever, very little is known about their scale, and the level of funding involved varies between coun- there has been no systematic effort to record reallo- tries. Less frequently, funds are reallocated between cations in the aftermath of a disaster in any ASEAN < 36 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 3.5. Reallocations in action ■■ In response to the 2010 floods, the Government of Thailand approved the diversion of 4 billion baht (US$126 million) from its Strong Thailand budget to the response efforts, in addition to the 20 billion baht central budget already approved for this purpose.12,13 ■■ A number of Cambodian line agencies use part of their routine maintenance budgets to repair minor disaster-related damage on a near-annual basis. ■■ The Philippine Department of Agriculture (DA) has regularly transferred funding from initiatives such as its rice, corn, and high-value crop programs to support post-disaster recovery of the agricultural sector (Benson, 2008). Based on an analysis of these transfers over the previous five years, in 2008 the DA requested – but did not secure – the creation of a disaster standby fund to the tune of PhP 500 million (US$11.3 million) to reduce further reallocations from its development activities (ibid). http://reliefweb.int/node/373541 12 The Strong Thailand program is off-budget and focuses on infrastructure projects and investment in agriculture, educa- 13 tion and health. state or in most other countries in the world. Admit- Meanwhile the net benefit of reallocated funds tedly, this is not a simple task as related approval may be undermined if their release is delayed. In procedures often rest internally, within a particular the aftermath of the September 2009 Western Su- agency, and transfers may not be reported to higher matra earthquake in Indonesia, for instance, it was authorities. Data on local government reallocations reported that lengthy procedures for the realloca- are particularly difficult to obtain. Nevertheless, it is tion of budgets may have prevented local govern- important to have a sense of the scale of funding ments from restructuring their programs in a timely involved. manner in support of the response efforts (Indonesia BNPB et al, 2009). Associated opportunity costs depend on the scale of reallocations, the original intended pur- Longer-term realignment of investment pose of the funding, and the extent to which budgets the original allocation was sufficient to satisfy its purpose. Governments sometimes have funding Reconstruction efforts typically fall under the available at relatively low opportunity cost due to responsibility of planning and investment min- delays in the implementation of new projects and istries, relevant line agencies, and their local programs that were envisaged in the annual budget. government counterparts. They are built into pub- In certain other circumstances, however, opportunity lic investment plans and related budgets over several costs may be extremely high. For instance, mainte- years succeeding a disaster. These budgets are the nance budgets are already considerably underfund- main source of post-disaster reconstruction in most ed in many countries. In consequence, post-disaster ASEAN Member States, except in the case of cata- reallocations can cause significant delays to planned strophic events when substantial international assis- maintenance, potentially imposing an economic cost tance may be received (see below). on society (e.g., via prolonged travel times along poor roads), resulting in much higher subsequent Reconstruction initiatives are often included under repair costs and rendering the unrepaired infrastruc- relevant sector and local government investment ture more vulnerable to future hazard events. plans and budgets but not necessarily labeled as Chapter 3: Fiscal Management of Natural Disasters < 37 > reconstruction. Thus, again, it is extremely difficult of both tax cuts and increases, using fiscal instru- to ascertain total related spending without intimate ments to redistribute some of the economic burden knowledge of these budgets. For instance, recon- of a disaster to non-affected areas. struction of damaged roads may simply fall within the budget allocation for new roads. However, avail- In practice, post-disaster tax increases are politi- able evidence suggests that, as the principal source cally unpopular. As such, there have been relatively of financing for reconstruction in most countries, few such increases anywhere in the world and pos- such funding is insufficient to support the comple- sibly none at all in the ASEAN region. Where they tion of reconstruction efforts within just a few years. have been applied, however, they have sometimes This may have serious adverse implications for the raised substantial resources for the disaster response wider socioeconomic consequences of a disaster. efforts. See Box 3.6. The post-disaster application of tax cuts to stimulate economic recovery is somewhat Associated opportunity costs may also be high, more common, including in the ASEAN region. See particularly where overall public resources are Box 3.7. limited and the government is faced with a rapidly expanding population. There is often no Deficit financing significant adjustment in either the overall capital investment funding envelope or in allocations from Governments can choose to finance part of their this envelope for more severely-affected sectors and disaster response efforts via deficit financing, local governments in the aftermath of a disaster. In- with corresponding increases either in the mon- stead, reconstruction needs have to compete with ey supply or government borrowing (including prior national and local development goals. In con- via concessional loans from international financial sequence, disasters may force a substantial realign- institutions (IFIs)). Disasters can also result in the un- ment in development investment plans if the recon- intentional widening of a government’s fiscal defi- struction efforts receive significant funding from the cit by reducing revenue and/or, where expenditure capital investment budget. controls are lax, by resulting in unapproved spend- ing. In Myanmar, for instance, a slight widening of Taxation the fiscal deficit from 3.4 percent in FY 2008 to 3.7 percent in FY 2009 was partly attributed to disas- Fiscal instruments can be used to generate ex- ter response spending following Cyclone Nargis in tra government revenue in the aftermath of a May 2008 (ADB, 2010). The deficit was financed disaster and, conversely, via targeted tax breaks via a combination of central bank money creation and holidays, to ease pressure on affected com- and the issue of treasury securities. In Cambodia, munities and businesses and to stimulate eco- Typhoon Ketsana was similarly held in part respon- nomic recovery. Post-disaster tax increases can take sible for a widening of the FY 2009 fiscal deficit. It a number of months to approve and even longer was expected that this additional gap would be met for the resulting revenue to be collected, particularly through increased domestic and external borrowing where tax administration capabilities have been dis- and also that further borrowing would be neces- rupted by a disaster. Thus, they are best suited to sary in subsequent years for reconstruction purposes financing the tail end of early recovery efforts and (Cambodia Royal Government, 2010). reconstruction. Meanwhile, tax breaks imply some dip in revenue in the short term but, by encouraging The appropriateness and implicit cost of deficit recovery, may imply a net increase in government financing depends on prevailing macroeconomic revenue over the longer term. In some situations, circumstances and government macroeconomic, the optimal strategy may be to apply a combination fiscal, and monetary policies at the time of a < 38 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 3.6. International experience - financing disaster response through taxation ■■ In the aftermath of severe floods and heavy rainfall in 2010 that caused total damage of up to $5.2 billion, the Colombian Government issued a Presidential Decree reducing the threshold of the wealth tax from 3 billion to 1 billion pesos. This measure was expected to generate an additional 3.3 trillion pesos (US$1.6 billion) in tax receipts for recovery purposes.14 Temporary disaster-related tax increases were also imposed by the Colombian Government in the wake of the 1985 Armero volcanic eruption and the 1999 Eje Catetero earthquake. ■■ Following the January 2011 Queensland floods, the Australian Government introduced a flood levy for 2011-2012 on middle and higher income taxpayers to help finance the reconstruction efforts. The levy was set at 0.5 percent on that part of an individual’s income between $50,001 and $100,000 and at 1 percent on the portion over $100,000. The ensuing revenue was expected to meet just under a third of the total Aus$5.6 billion (US$5.1 billion) public reconstruction bill.15 ■■ Reconstruction costs incurred as a consequence of the 2010 earthquake in Chile are being met in part through temporary tax increases, including on taxes on corporations, tobacco, and real estate.16  The largest mining companies (together accounting for 94% of annual national production) also agreed to a voluntary 4 to 9 percent increase in royalties paid on mineral extraction through 2014, which is projected to generate over US$1 billion in government revenue. The payments are voluntary because a 2005 royalty law bars changes before 2017.17 14 http://colombiareports.com/colombia-news/news/13537-colombia-to-hike-taxes-16-bln-to-finance-flood-recovery.html 15 http://www.pm.gov.au/blog/questions-about-flood-levy-answered 16 http://www.taxand.com/news/newsletters/Devastating_Earthquake_Leads_to_Changes_in_Tax_Measures 17 http://finance.yahoo.com/news/Mining-giants-agree-to-pay-apf-2365065413.html?x=0 Box 3.7. Stimulating recovery via tax reductions ■■ In the aftermath of the 2004 tsunami, the Government of Thailand offered tax relief, together with soft loans, to businesses to support the recovery process. Following the 2010 floods, affected firms were permitted to delay VAT, stamp duty and tax payments for several months and were granted an import duty exemption on machinery until December 2011 (World Bank, 2011b). ■■ In Lao PDR, agricultural land affected by disasters is exempt from annual land tax (IMF, 2007). ■■ Following the 2006 Yogyakarta earthquake in Indonesia, sub-national governments reduced property taxes by 50 percent for lightly damaged properties and by 75 percent for moderately damaged properties. The Yogyakarta municipal government reduced taxes for tourism-related businesses by 25 percent (Indonesia BNPB et al, 2009). Chapter 3: Fiscal Management of Natural Disasters < 39 > disaster. Domestic borrowing can crowd out private Post-disaster external assistance is not neces- sector investment, including in reconstruction, if sarily additional either. Instead, it may partly dis- interest rates are forced up – an approach that may place short- to medium-term flows of development not be considered appropriate if a government is support. For instance, a large portion of the IFIs’ re- trying to stimulate long-term private sector growth. sponse to disasters has been provided via the repro- Meanwhile, monetary expansion may be inflationary gramming of planned projects and the reallocation and thus possibly unsuitable where rates of inflation of undisbursed funds from ongoing projects (Cum- are already high, particularly if there are indications mins and Mahul, 2008). Furthermore, there can be that the disaster itself is forcing up the price of delays in disbursement of international assistance; certain items (e.g., basic food items and construction absorption difficulties limiting the volume of aid that materials). governments are able to receive; and issues around coordination with other response efforts, thereby Existing levels of domestic and external debt undermining the effectiveness of available resources. and a country’s degree of access to international capital markets are also relevant. For instance, More positively, there have been some delib- the Government of Indonesia currently has room to erate efforts to address some of these issues. self-finance both post-disaster reconstruction activi- Initiatives have been undertaken to improve coor- ties and, if debt issuance is fast, short-term recovery dination, including in the context of the 2004 In- activities through borrowing, following a dramatic dian Ocean tsunami response in both Indonesia and reduction in its level of debt over the past decade, Thailand. Various steps have also been undertaken from around 95 percent to under 30 percent of GDP to increase the speed of delivery of international as- (World Bank, 2011a). See Annex 10. sistance, including via the creation of the UN Central Emergency Response Fund (CERF)18 and the Asian International assistance Development Bank’s (ADB’s) Asia Pacific Disaster Response Fund.19 Meanwhile, the World Bank has International disaster assistance accounts for sought to address issues of both timeliness and ad- a very small proportion of disaster response ditionality by recently creating a crisis response win- spending globally. Much of this assistance is dow specifically for IDA countries. Under this facil- received in response to extreme catastrophic ity, a portion of IDA resources has been set aside to events, rather than more frequent ones. Reflect- provide additional funding to IDA countries, beyond ing this general pattern, ASEAN Member States typi- their annual allocation, in the event of a major di- cally only formally request international assistance saster. for major disasters, although existing NGOs and UN bilateral and multilateral agencies already on the ground may get involved in less severe events. Efforts to raise international disaster support for ASEAN Member States through UN appeals The CERF is a stand-by fund established by the United Na- 18 from bilateral, multilateral and UN agencies and tions to enable more timely, reliable, equitable and coordi- private donors have generated mixed results nated humanitarian assistance to victims of natural disasters over the past decade, with the notable exception and other types of emergency. of the 2004 Indian Ocean tsunami and 2009 Lao The Asia Pacific Disaster Response Fund was established in 19 March 2009. It provides up to US$3 million quick-disbursing Typhoon Ketsana appeals. See Table 3.2. Appeals grant resources in the event of a disaster to meet immediate have raised as little as 15 percent of the requested expenses incurred in restoring life-saving services to affected funding. populations and to augment other aid flows in times of na- tional crisis (ADB, 2009). < 40 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Table 3.2. UN disaster appeals for ASEAN Member States, 2000 - 2010a Funding requested Percent received Country Disaster Year appeal launched US$m % Java earthquake 2006 80 53 Indonesia West Sumatra earthquake 2009 38 42 Floods 2008 10 46 Lao PDR Typhoon Ketsana 2009 12 75 Floods 2004 6 23 Philippines Typhoon Durian 2006 48 15 Typhoon Ketsana 2009 143 44 Indian Ocean Earthquake- Regional appealb 2005 1,400 88 Tsunami (a) Status as of 26 August 2011. No appeals were launched in 2000, 2001, 2002, 2003, 2007 or 2010. Appeals launched in response to situations of conflict are not shown. (b) The appeal included specific requests for Indonesia and Thailand and various non-ASEAN states as well as some requests for regional funding. No specific funding was requested for Malaysia or Myanmar. Source: UN OCHA Financial Tracking Services (http://fts.unocha.org) Ex-Ante Practices and Arrangements In September 2011 the Philippines became the first ASEAN Member State to take out a stand- Contingent credit alone disaster contingency financing loan, in the amount of US$500 million, under a relatively new Several international partners have made ex ante World Bank facility specifically designed for this pur- contingent credit available for disaster recovery and pose. See Box 3.8. The Inter-American Development reconstruction purposes in recent years, facilitating Bank has launched a similar facility for Latin America more rapid access to potentially significant lending and the Caribbean. See Box 3.9. in the aftermath of a disaster. Multi-year reserves In some cases, this line of credit has been included as part of a broader loan, including in Lao PDR and No ASEAN Member States have set up dedicated Viet Nam in the ASEAN region. In Lao PDR, a disaster multi-year reserves to finance the cost of natu- contingency fund for post-disaster repairs was in- ral disasters. Such reserves can be efficient in cov- cluded as a component of a World Bank road sector ering losses caused by small but recurrent adverse project (Lao PDR NDMO, 2011). In the case of Viet natural events. They are usually politically difficult Nam, the contingency funding was in the form of to justify, however, particularly where governments a US$20 million component of a larger US$86 mil- run a budget deficit. An interesting example is the lion World Bank disaster risk management loan. The Disaster Assistance Emergency Fund of the Repub- contingency component was intended to address lic of Marshall Islands in the Northern Pacific. Each a regular annual funding gap for the post-disaster year, the government sets aside a dedicated budget reconstruction of small-scale rural public infrastruc- for this fund, which is matched by a grant contribu- ture. See Box 3.11. Additional financing of US$75 tion from the United States. In counterpart of this million was approved in June 2010 for the contin- grant, the Government of the Republic of Marshall gency component alone. Island agrees to only use the funding in the event of a natural disaster. Chapter 3: Fiscal Management of Natural Disasters < 41 > Box 3.8. The World Bank contingent loan facility The World Bank’s Development Policy Loan (DPL) with catastrophe deferred draw down option (Cat DDO) was launched in 2008, offering a source of immediate post-disaster liquidity to serve as bridge financing while other resources (e.g. concessional funding, bilateral aid, or reconstruction loans) are mobilized. Borrowers have access to financing in amounts of up to US$500 million or 0.25 percent of GDP, whichever is less. The Cat DDO has a ‘soft’ trigger, as opposed to a parametric trigger; funds can be drawn down upon the occurrence of a natural disaster resulting in the declaration of a state of emergency. The Cat DDO is only available for IBRD countries to date, but the World Bank is exploring the scope for its extension to IDA countries. Borrower countries are required to have an adequate integrated disaster risk management program in place, which is periodically re- viewed by the World Bank. See Annex 3 for further details. Box 3.9. International Experience - IADB’s Contingent Credit Facility In February 2009, the Inter-American Development Bank (IADB) launched a US$600 million Contingent Credit Facility for Natural Disaster Emergencies in Latin America and the Caribbean. This product provides IADB bor- rower countries contingent credit of up to US$100 million or 1 percent of GDP, whichever is less, to cover ur- gent post-disaster financing needs until other sources of funding can be accessed. All IADB member countries are eligible to access this facility. Borrower countries are required to have an adequate integrated disaster risk management program in place, including measures relating to risk analysis, prevention, mitigation, emergency preparedness, and disaster response and provision for the adequate and sustainable financing of remaining risks.20 Drawdown of funding is conditional on verification that the country has experienced an event of a certain type, location, and intensity as specifically described in the loan document (IADB, 2009). The trigger is linked to the percentage of population affected as estimated by a model developed by the reinsurer Swiss Re called the Affected Population Trigger. 20 See http://www.iadb.org/news/detail.cfm?Language=English&id=5125 and http://www2.reliefweb.int/rw/rwb.nsf/db- 900sid/LSGZ-7XQE9Y?OpenDocument for further information. Risk transfer the Philippines, for instance, there is some partial all-peril property cover for public assets provided by Risk transfer instruments transfer disaster risk to the Government Service Insurance System General third parties, replacing the fiscal burden of periodi- Insurance Group (GSIS), a state-owned entity. See cally substantial disaster response needs with a rela- Chapter 4. Local government units are required by tively more predictable flow of expenditure in the law to purchase insurance from GSIS–GI, securing form of annual premium payments. cover against all property in which the government has an interest (e.g., government offices, hospitals, In practice, there has been relatively little pub- schools, public markets). In practice, GSIS–GI esti- lic use of risk transfer instruments in the ASEAN mated several years ago that around 30 percent of region. In a few countries, some local governments local government properties were actually insured, have insured their public buildings against natural with highest coverage in Metro Manila, other cities, hazards using traditional indemnity insurance. In and richer municipalities (Benson, 2008). Moreover, < 42 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States even those properties that are covered are consider- frequency and intensity of climatological hazards as ably underinsured according to a recent brief survey a consequence of climate change. No country in the of several local government units in the Philippines, region currently has adequate financing arrange- in part because of budgetary constraints (World ments in place to manage a major disaster event. Bank-GFDRR, 2010). However, these resource issues may be addressed to some degree by recent legisla- Funding gaps may be felt particularly acutely at tive changes in the country that permit the use of lo- the local level. Local governments typically have cal government disaster contingency funds to meet very limited revenue-raising capabilities of their insurance premiums. own. Instead, they are dependent on the transfer of public resources from central government, both In Indonesia, at least two local governments are for reconstruction and other purposes. Local gov- also known to have secured disaster insurance. Sev- ernments that receive most of their resources from eral governments have supported agricultural risk central government in the form of non-earmarked transfer schemes as well, involving both traditional block allocations can be particularly hard hit in the indemnity insurance and, more recently, paramet- event of a disaster, as such allocations often fail to ric insurance products, thereby potentially reducing take disaster-related needs into account. public contingent liability. See Chapter 4. Mean- while, there is some informal discussion underway Precise estimation of funding gaps is by no concerning the possible establishment of a joint ca- means simple. It requires comprehensive data on tastrophe bond for ASEAN Member States plus Chi- public contingency liability for a range of hazards na.21 To date, however, no country in the region has with varying return periods, on all existing disaster made use of this newest generation of sovereign risk risk financing mechanisms (both formal and infor- transfer products (e.g., catastrophe bonds). mal), and, in the case of ex post analysis, on actual flows of funding. See Box 3.10. Moreover, even where all identified disaster response, early recovery, Funding gap analysis and reconstruction needs are met, this does not nec- essarily mean that those needs have been met via ASEAN Member States currently retain most of the most cost-effective financing arrangement. Nev- their sovereign disaster risk, as indicated above. ertheless, even simplified analysis, focusing solely on They rely heavily on annual budget appropriations ex ante tools, is useful in providing some first ap- and de facto post-disaster budget reallocations, the proximation of funding gaps as a basis for reviewing latter both for immediate relief and early recovery and strengthening disaster financing arrangements. and for longer-term reconstruction. See Table 3.3. See Box 3.11. As noted above, it is also important to Available evidence suggests that humanitarian relief develop a clear picture of the likely relative spread of needs are currently largely met through these ar- funding needs and resources over time, distinguish- rangements. Lower income countries in the region, ing between humanitarian relief, early recovery, and however, regularly struggle to secure adequate and reconstruction phases of the response efforts and timely funding for early recovery and, in particular, also between different hazard types. The timing of reconstruction. Moreover, there is increasing concern a disaster relative to the fiscal year should be taken about the rising fiscal burden of disaster response in into account in undertaking this temporal analysis. many countries in the region due to increases in ex- Should a disaster occur towards the beginning of a posure and vulnerability. Any such trends are likely fiscal year, there may be a lapse of a year or more to be further fuelled by predicted increases in the before significant funding can be disbursed for re- construction in some countries. http://www.thejakartapost.com/news/2011/04/08/asean- 21 launch-infrastructure-fund-year.html Chapter 3: Fiscal Management of Natural Disasters < 43 > Box 3.10. Tracking budgetary resources for disaster response Disaster resources need to be systematically tracked in order to effectively manage response efforts, to monitor potential gaps in financing for specific purposes, to support analysis of the costs and benefits of incremental disaster response spending relative to other national priorities, to draw lessons learned on possible improve- ments to existing disaster risk financing arrangements, and to support accountability. Ideally, expenditure on disaster risk reduction should also be tracked to inform structured, evidence-based decision-making around the appropriate balance and composition of risk reduction and post-disaster expenditure. In practice, public spending on emergency relief, early recovery, and reconstruction is not systematically tracked on a regular, routine basis, either in the ASEAN region or in most other countries. The availability of data on local government expenditure is particularly limited and detailed information can often only be obtained di- rectly from individual local government authorities. Notable exceptions include the ground-breaking tracking system established for Aceh and Nias by the Indonesian Government and the World Bank in the aftermath of the 2004 tsunami and the Philippine Government’s tracking initiative relating to the response efforts following tropical storm Ondoy (Ketsana) and Typhoon Pepeng (Parma) in 2009. Both initiatives sought to track assistance from international partners, local civil society organizations, and the private sector as well as from government. These initiatives represent a major step forward. The next step is to institutionalize them into more permanent systems, as already planned in the Philippines. Box 3.11. Assessing funding gaps – results for Viet Nam and the Philippines Preliminary retrospective analysis of the funding gap in Viet Nam for the period 2000 to 2008 indicated that short-term recovery funding requirements were met in full through the annual government contingency budget (World Bank, 2010a).22 The analysis revealed, however, significant funding gaps for reconstruction in 2006, 2007, and 2008 based on the assumption that up to 1 percent of planned capital expenditure in the relevant budget years were reallocated for reconstruction. Most of these gaps were expected to be met through further significant allocations from the capital budget in subsequent years, placing a huge additional burden on these resources as well as delaying reconstruction. Looking forward, it was projected that there would be a future recovery funding gap in Viet Nam for disasters with a return period higher than 10 years and an annual average reconstruction funding gap. The 1-in-10 year government reconstruction funding gap was estimated at about VND 8,500 billion (US$516 million), rising to around VND14,500 billion (US$880 million) once every 50 years. A simplified ex post funding gap analysis for the Philippines based on flows of government and private resourc- es relative to losses following the 2009 typhoons Ondoy (Ketsana) and Pepeng (Parma) indicated that available funding covered only 1.5 percent of total economic damage and around 3 percent of total public sector disas- ter recovery and reconstruction spending requirements (World Bank, 2010b). Had local calamity funds been pooled, then total disaster risk financing available for disaster recovery and reconstruction work would have increased from under PhP 0.2 billion to PhP 14.3 billion, improving government response capacity considerably. The analysis assumed that, on average, about 40% of the central contingency budget and 20% of the local contingency 22 budget are available to finance post-disaster recovery activities. The state contingent liability due to natural disasters was estimated at 55% of the total reported damage estimates, using Central Committee Flood and Storm Control (CCFSC) data. It was further assumed that the government recovery and reconstruction expenditure requirements represent 25 and 30% respectively of total CCFSC damage estimates. For further details see Appendix 3. < 44 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Table 3.3. Preliminary summary of fiscal risk management arrangements in ASEAN Member Statesa Ex post Ex ante Risk transfer International assistance budget realignement Medium-term capital In-year reallocations sovereign insurance Insurance of public Catastrophe bonds Contingnet credit holder insurance Deficit financing of private policy Annual budget Public support Tax increases allocations Parametric assests Brunei Darusallam Cambodia Indonesia Lao PDR Malaysia Myanmar Philippines Singapore Thailand Vietnam (a) This table is based on the best information that the research team has been able to collate, but should be interpreted with due consideration to limitations arising from the secondary nature of the underlying sources. Note also that although many governments are purchasing some insurance for their assets, the number of buildings covered as a share of the total public asset portfolio is thought to be very limited. Chapter 4 Chapter 4: Private Catastrophe Risk Insurance Markets < 45 > Private Catastrophe Risk Insurance Markets < 45 > < 46 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States This chapter describes the current state of private rope (3.07 percent).23 However, the rate of growth of insurance markets in ASEAN Member States for ASEAN non-life insurance markets is promising at an property catastrophe risk insurance, agricultural in- estimated 6 percent24 for 2009. See Figure 4.1 and surance, and disaster microinsurance. Private insur- Figure 4.2. ance markets for residential and business property risks, agricultural risks, and the low-income seg- Catastrophe coverage is typically provided ments of the population can contribute significantly through either an extension for a fire policy to regional resilience against disaster shocks. Where for small risks or through an ‘all-risks’ policy these markets are developed and covering a signifi- covering larger commercial and industrial as- cant component of post-disaster losses, they con- sets. Cover is widely available for catastrophe risk. tribute in three key areas: (i) reducing the contingent In most ASEAN Member States, however, standard liability of the state by reducing the need for post- homeowners insurance does not cover catastrophic disaster assistance; (ii) reducing the contingent liabil- perils. Policies can be extended to cover these perils, ity of the state by transferring some of the cost of usually subject to additional premium. Penetration rebuilding of government assets (where those assets for catastrophe risk insurance tends to be higher for are insured); and (iii) disseminating risk information commercial and industrial facilities through all-risks and providing financial incentives to invest in risk re- policies. duction activities. The private insurance sector can also contribute to the development and enforce- The percentage of standard property damage ment of safer building codes. This chapter looks at ‘fire’ policies extended to cover catastrophic per- some of the challenges these markets are facing ils varies significantly by peril and country, but is and their potential for development. International generally low. Estimates indicate that, typically, less experience is drawn upon for comparison. A more than 10 percent of property damage policies include detailed discussion is provided in Appendices 4 to 7. cover for catastrophic perils25 in the ASEAN region. The lowest incidence of catastrophe risk coverage is Private Property Catastrophe for flood, where underwriters tend to be geographi- Insurance cally selective in granting cover – deeming particu- Market overview lar zones to be uninsurable. It is noted that data on the level of uptake of catastrophe risk insurance in Property catastrophe risk insurance markets ASEAN Member States are very limited and spread in ASEAN Member States are characterized by across a wide range of different types of sources. low penetration. In general, wealth and insur- ance penetration correlate such that the lower Insurance penetration figures from Swiss Re Sigma, 2009 23 data the gross national income per capita, the lower Non-life premium growth from Swiss Re Sigma, 2009 data, 24 the non-life insurance penetration. Insurance (inflation adjusted) for Singapore, Malaysia, Thailand, Indo- penetration for catastrophic perils is limited by the nesia, Philippines, Viet Nam. Data for remaining countries relatively limited development of markets for non-life unavailable. insurance more generally. All but two of the ASEAN Three of ten ASEAN Member States are known to have a 25 higher percentage of policies extended. Singapore is an ex- Member States sit below the Asia regional average ception, where more than 90 percent of policies are extend- for non-life insurance penetration of 1.55 percent of ed to cover catastrophe risk, in part due to insurers’ low per- GDP, and all ASEAN Member States are significantly ception of the risk. Figures for the Philippines vary between 20 and 80 percent. Brunei also sits above 10 percent, with an below non-life insurance penetration levels for devel- estimated 30 to 50 percent (sources AXCO, Guy Carpenter, oped markets in North America (4.51 percent) and Eu- AM Best). Chapter 4: Private Catastrophe Risk Insurance Markets < 47 > Figure 4.1. Non-life insurance penetration 5.0 North America non-life insurance penetration (premium % GDP) 4.5 n Non-life insurance penetration 4.0 (premium % GDP) n Property insurance penetration 3.5 (premium % GDP) European non-life insurance penetration (premium % GDP) 3.0 % of GDP 2.5 2.0 Asia non-life insurance penetration (premium % GDP) 1.5 1.0 0.5 0.0 e sia nd m sia s R am a ar ne or di PD Na nm ay la ne bo al ap pi ai o al ss do ilip ya et m ng Th La M ru Vi M Ca In Ph Si Da ei un Br Source: Authors from multiple sources, principally World Bank, Swiss Re, AXCO Figure 4.2. Non-life insurance penetration vs. gross national income per capita 1.8 1.6 • Malaysia • Singapore 1.4 Non-life premium, as % of GDP 1.2 • Thailand 1.0 0.8 • Viet Nam 0.6 • Indonesia 0.4 • Philippines • Lao PDR • Brunei Darussalam 0.2 • Cambodia 0.0 • Myanmar 500 5,000 50,000 GNI/capita (US$) Source: Authors from multiple sources, principally World Bank, Swiss Re, AXCO < 48 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States The market share of state-owned insurance ternational partners (principally insurers) for injections companies has decreased significantly in recent of capital. years and is expected to decline further in the near-term. However, the state share of the insurance The market for Shariah-compliant insurance market remains strong in Indonesia, Myanmar, and (takaful) is growing significantly in the region. Lao PDR. In Myanmar, state-owned Myanma Insur- Takaful markets in Malaysia and Indonesia – includ- ance holds a monopoly over the market, while state- ing non-life takaful through which catastrophe risk owned enterprises in Indonesia are ranked in the top is covered – are growing rapidly. These products are two by market share for both insurance and reinsur- also a feature of insurance markets in Brunei Darus- ance (PT Asuransi Jasa Indonesia26 and Reasuransi In- salam, Thailand, and Singapore. See Figure 4.3. ternasional Indonesia). In Lao PDR, the state increased its share in insurer Assurances Generales du Lao PDR Areas of challenges and potential for (AGL) to 49 percent in 2000. AGL holds an estimated growth 80 percent of the market for non-life insurance. Aside from Lao PDR, privatization has been the general The purchase of property catastrophe risk insur- trend in the region, with aggressive programs recently ance is not mandated by law, but low voluntary carried out in Viet Nam and Cambodia to significantly demand is bolstered by insurance requirements reduce state control of the market. from lending institutions. Banks in a number of countries make the purchase of an insurance policy a International insurers (and reinsurers) have an condition of lending28 (such as Malaysia, Singapore, increasing presence in the region, largely unin- and Viet Nam), and in some cases the mandatory hibited by government restrictions on foreign insurance policy must include cover for catastrophic ownership of domestic operators. International perils. Mortgages are likely to be a source of sig- insurers are present in almost all ASEAN Member nificant growth for catastrophe risk insurance in the States through domestic branches or as joint ven- Philippines, where damage from the 2009 typhoons tures with, or major shares in, domestic insurers. A has resulted in a move by lending institutions to number of countries have no restrictions on foreign make catastrophe risk insurance compulsory with ownership. Thailand, Malaysia, and Singapore have home loans. Previously, only a standard fire policy all relaxed their limits on foreign ownership of non- was required. Growth is also predicted in Indone- life insurers in recent years. Singapore removed the sia, where property earthquake insurance linked to 49 percent restriction on foreign ownership of insur- mortgages is anticipated to be a key driver of a rise ers in 2000, and Malaysia increased the permitted in catastrophe risk insurance penetration29. threshold for foreign equity for insurers/takaful27 op- erators to 70 percent in 2009. Thailand also increased The only mechanism for pooling property ca- permitted foreign equity for non-life insurers from 25 tastrophe risk in the region is through special- to 49 percent in 2008, but, at the current permitted ist earthquake reinsurer PT Maipark in Indo- 49 percent, is one of the most restricted ASEAN mar- nesia, although pools are being considered in kets for foreign companies. With capital requirements tightening in a number of countries, it is anticipated There are two models for catastrophe insurance linked to 28 that more domestic companies will be looking to in- mortgages. In one model, the policy covers the loan amount and is typically paid directly to the lender in the event of a Note that plans to privatize PT Asuransi Jasa Indonesia have 26 catastrophe destroying/damaging the asset. In the second, been made public by the government, but no confirmed the insurance covers the full value of the property and is typi- timeline was available at the time of publication of this re- cally paid directly to the mortgagor. Proof of this insurance is port. required in order to borrow. 27 Takaful is Shariah-compliant insurance. Fitch Ratings. 29 Chapter 4: Private Catastrophe Risk Insurance Markets < 49 > Figure 4.3. Selected ASEAN Takaful markets Malaysia Indonesia Brunei Darussalam Takaful Market Takaful Market Takaful Market 0.60% GDP 0.05% GDP 0.23% GDP Malaysia is one of the largest Although takaful penetration lags Overall takaful (life and non-life) takaful markets globally, despite significantly behind Malaysia at penetration was 0.23% of GDP in non-life takaful premiums only ac- 0.05% of GDP in 2009 (for life 2009 with slow growth. counting for 7% of the non-life and non-life), growth has been market in 2009. This share is set strong, with a growth rate of 70% Takaful holds a larger portion of to increase; Malaysian takaful is reported for 2009. With the cur- the non-life insurance market in growing significantly faster than rent low level of penetration and Brunei than any other ASEAN the rest of the insurance market the largest muslim population in Member State, with premiums with a rate of 30% in 2009. the world, the market is likely to broadly on a par with convention- increase significantly in the near al non-life insurance in 2009. The number of takaful operators term. in Malaysia is also growing, and in- Takaful penetration is, however, ternational (re)insurers are looking The takaful market is fragmented, largely due to growth in motor for entry opportunities, with recent with few dedicated operators (3 insurance, with conventional in- entrants including HSBC and Tokio in 2008) but more than 30 con- surance dominating for all other Marine. 12 takaful and retakaful ventional insurers offering taka- lines, including property cover. operators are registered with the ful products through takaful win- Malaysian Takaful Association. dows. Source: Authors, with penetration and growth figures from Ernst and Young Global Takaful Report (2011) other ASEAN Member States.30 Specialist reinsurer ports indicate that a pool is also under consideration Maipark was established by the Government of In- for typhoon and flood risk in Viet Nam30. donesia as a joint undertaking of all general insur- ance and reinsurance companies to improve market The development of property catastrophe insur- capacity for underwriting earthquake risk. All domes- ance pools in the region could contribute to sus- tic companies writing earthquake risk must cede a tainable growth in catastrophe risk insurance portion, ranging between 5 and 25 percent depend- penetration. The Turkish Catastrophe Insurance ing on risk location, to Maipark. In the Philippines, a Pool (TCIP) provides an example of how a pooling proposal for a catastrophe risk insurance pool is being facility combined with mechanisms for enforcing considered by the National Disaster Risk Reduction compulsory insurance purchase can contribute to a and Management Council and the Department of Fi- significant increase in take-up rates for catastrophe nance and has gained support from industry players, risk insurance. This pool was designed to deal with including the National Reinsurance Corporation. Re- a lack of local insurance market capacity for under- writing earthquake risk and low voluntary demand Pools exist for agricultural and specialized engineering and 30 for earthquake policies. The TCIP has produced a six- energy risks in ASEAN Member States but general property catastrophe risk is only pooled through the Maipark mecha- 31 AM Best Southeast Asia Life and Non-Life Market Review nism. 2010 < 50 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States fold increase in earthquake insurance penetration a challenge. Malaysia, the Philippines, Indonesia, since its inception in 2000. See Annex 7. The World Viet Nam, Thailand, and Cambodia have mandatory Bank provided technical and financial assistance in or advisory minimum tariffs in place for catastrophic the establishment of this facility. perils. In Indonesia, however, only earthquake pre- miums are controlled and there are no mandatory Excessive fragmentation in ASEAN non-life in- tariffs for flood, which is also a large contributor to surance markets has pushed pricing down in a losses. Reports indicate that regulators in Malaysia number of countries. Many ASEAN non-life insur- and Indonesia have had the most success in ensur- ance markets are characterized by fragmentation, ing observance of mandatory tariffs. In contrast, reg- with the Philippines, Indonesia, Thailand, and Singa- ulators in the remaining countries have struggled to pore all counting more than 50 non-life (or compos- enforce tariffs, even where mandatory, due to pres- ite) insurers operating within their markets. The high sures of competition between insurers. levels of competition generated by the large num- ber of operators has pushed pricing down, in some The catastrophe risk insurance of public assets cases below mandatory or advisory tariffs. Declining has been limited in the region. Where insurance is pricing has been seen across the region and price purchased, state-owned (or part-owned) insurance adequacy, particularly for catastrophe risk, is known companies are often used. This is known to be the to be a concern in the majority of ASEAN Member case for at least four ASEAN Member States: Audley States. Market consolidation is, however, anticipat- Insurance in Brunei Darussalam; GSIS in the Philip- ed as a result of regulators rolling out staggered pro- pines; Dhipaya in Thailand; and monopoly insurer grams of increasing minimum capital requirements. Myanma Insurance in Myanmar. Governments may The implementation of risk-based capital regimes want to consider developing programs of insurance planned or underway in a number of countries will for public assets in collaboration with the private also push under-capitalised insurers into changes of sector to reduce the public share of contingent li- ownership. See Figure 4.4. ability with respect to natural disasters and to de- velop the technical capacity of the domestic market Figure 4.4. Non-life insurance market participants to underwrite catastrophe risk. Non-life insurers Less than More With the exception of Singapore and Malaysia, Monopoly 10 10 to 50 than 50 there is very little domestic reinsurance capac- Philippines ity within the region and premium outflows are Indonesia large. Insurers rely heavily on international reinsur- Thailand ance capacity. Mandatory cessions are being used Singapore by governments to promote retention of risk within Malaysia domestic markets and to build domestic reinsur- Vietnam ance capacity. Regulators must balance the need to develop local market financial and technical rein- Lao PDR surance capacity with the benefits that result from Brunei Darussalam strong connections to international reinsurers. The Cambodia international reinsurance community can (and has Myannmar been seen to) inject and promote technical capac- Source: Authors ity by, for example, providing access to catastrophe Mandatory or advisory tariffs for catastrophe models and mandating that insurers track and re- risk are in place in six of the ten ASEAN Member port on catastrophe accumulations by zone. See States. Enforcement of these tariffs has proved Figure 4.5. Chapter 4: Private Catastrophe Risk Insurance Markets < 51 > Figure 4.5. Reinsurance Cession Agreements Reinsurance cession agreements Cambodia 20% to Cambodia Re by Law Indonesia 2.5% mandatory cession to Reasuransi Internasional Indonesia (see also Maipark) Malaysia 2.5% to 5% voluntary cession to Malaysian Re Philippines 10% mandatory first option to National Reinsurance Corporation Thailand multiple agreements, including 5% voluntary cession (most classes of risk) to Thai Re Viet Nam 20% mandatory cession to Vinare resently abolished Source: Authors from multiple sources including national insurance regulators and AXCO insurance market reports New channels for distribution are emerging in also hold promise as distribution networks for prop- the more developed markets but intermediar- erty catastrophe risk insurance to lower-income seg- ies still dominate distribution of catastrophe ments of the population. risk insurance, with agents dealing principally with smaller risks (such as personal lines insurance) and Regulation of catastrophe risk insurance brokers placing larger risks (principally commercial and industrial). Distribution of insurance through Prudent regulation of insurers is of particular im- retail banks – notably homeowners insurance – is portance for catastrophe risk. This is because insur- growing and is already significant in Thailand and ers underwriting catastrophe risk can be exposed to Singapore. Direct sales channels account for a sig- large correlated losses across a portfolio and higher nificantly smaller portion of premiums in the region. volatility in claims. Regulators therefore face a particu- Branch networks and telemarketing account for the lar challenge with respect to these insurers: defining majority of these direct sales, with internet sales only an adequate capital buffer such that obligations to a feature of the Singaporean market. policyholders are met in the event of a high volume of claims without adversely impacting the competi- The promotion of cost efficient distribution tiveness of the industry. The World Bank is currently channels is one mechanism through which gov- providing technical assistance to the Moroccan Insur- ernments can increase insurance penetration. ance Regulator to build the risk-carrying capacity of The Malaysian insurance regulator – Bank Negara the domestic insurance market. See Box 4.1. Malaysia – is encouraging direct sales through a pro- gram of premium rebates for consumers who pur- Regulatory monitoring and control of exposure chase personal lines insurance (such as homeowners accumulations to catastrophe risk is not wide- cover) through direct means such as walk-ins, the ly adopted in the ASEAN region. Tracking and internet, direct mailing, or telemarketing. Informal reporting of catastrophe accumulations by zone, financial networks – such as Indonesian arisans33 – however, is standard practice for business-as-usual by insurers in a number of countries, as reinsurers require this information. Monitoring of such expo- sures forms part of the regulatory system in the Phil- 32 Multiple sources. Note that these arrangements change peri- ippines, where the Insurance Commission mandates odically, hence this information may have changed since time reporting of catastrophe accumulations and also of drafting and is principally drawn from secondary sources. maintenance of a minimum amount of catastrophe 33 Arisans are informal systems similar to cooperatives used by small numbers of people to pool and manage financial re- sources. They are principally used as savings and health and population that are excluded from the formal financial ser- life insurance mechanisms for low-income segments of the vices sector. < 52 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 4.1. Establishing compulsory catastrophe insurance in Morocco The Government of Morocco is in the process of finalizing a catastrophe insurance law to shift the country from an ex post to an ex ante financing model. The law will introduce a nationwide compulsory insurance scheme through automatic extension of all property (and personal liability) policies to cover catastrophe risk. The World Bank is providing technical assistance to the Moroccan Insurance Regulator in the implementation of this law. The project focuses on design and pricing for the compulsory insurance and the development of tools and methodologies to assess domestic insurance market capacity to absorb risk from the new scheme. The development of probabilistic catastrophe and actuarial models is a key component of the project, and supports the implementation of the law in a number of ways: ■■ It allows creation of a risk-based pricing scheme for the com- pulsory insurance to ensure commercial viability and sustain- ability and to discourage construction in risk-prone areas; ■■ It allows risk-based supervision of the domestic insurance mar- ket with respect to catastrophe risks through use of PML model outputs; and ■■ Additionally, it will be used in the medium-term development of a catastrophe insurance scheme for public assets. excess-of-loss protection by insurers and reinsurers Limited access to probabilistic catastrophe mod- (equal to 5 percent of their aggregate net exposure els for earthquake, typhoon, and flood for ASE- to earthquake/flood/typhoon). There is a need for AN territories is a factor limiting effective moni- more regulators to introduce reporting requirements toring and control of exposure accumulations to for catastrophe accumulations, particularly where catastrophe risk. The development of independent catastrophe scenarios/modeling do not play a role in third-party models is required to overcome this prob- the determination of solvency capital requirements. lem. See Box 4.2. Box 4.2. Monitoring catastrophe risk in Kazakhstan In 2010, the World Bank launched a project with the insurance supervisor in Kazakhstan to develop a system of partial risk-based supervision for domestic insurers (which are highly exposed to earthquakes), in response to concerns around solvency of the domestic market. The project seeks to apply international best practice in the monitoring and control of catastrophe risk – such as the European Solvency II directive. See Appendix 4. In addition to technical assistance in designing the regulation, the World Bank funded the development of a probabilistic catastrophe model for use by the regulator. The model outputs city-level loss coefficients represent- ing a 200-year catastrophe event that can be applied to insurers’ city-specific exposures. A key project output was a methodology to assess aggregate catastrophe net risk retentions of insurers on the basis of a 200-year catastrophe event. Based on the results obtained in applying this methodology, the insur- ance supervisor will impose a regulation on the maximum aggregate net retention level of catastrophe risk ac- cumulation, effectively monitoring and controlling the risk of extreme losses. Chapter 4: Private Catastrophe Risk Insurance Markets < 53 > Regulation in the ASEAN region has been evolv- Singapore and Malaysia have the longest imple- ing over recent years, with more countries mented RBC frameworks, while implementation of working toward frameworks of supervision these regimes is still a work in progress in Indonesia that determine capital requirements based on and the Philippines. In Thailand, the Office of the In- some measure of the level of risk assumed by surance Commission (OIC) has been drafting a RBC the insurer. Setting solvency capital requirements framework using lessons learned from the European with reference to individual companies’ portfolios of Solvency II framework and other established RBC re- risk is prudent and creates a more enabling environ- gimes. The OIC’s effort to implement the new RBC ment under which insurers have the space to grow regime is ongoing. While a RBC regime recognizes in a sustainable fashion. It should be noted that the the need to consider risk assumed in solvency super- definition of a ‘risk-based’ capital regime will vary vision, and is therefore an improvement on earlier from country to country. While there may be gen- systems, without explicit treatment of catastrophe eral agreement that some measure of ‘insurance risk (such as through probabilistic or scenario model- risk’ should be captured within a model of solvency ing) the risk of extreme events is not accounted for supervision, there is less uniformity in exactly how and international best practice not represented. that insurance/underwriting risk should be captured. Regulators in those countries with large Muslim Five countries among the ASEAN Member States populations (principally Malaysia, Indonesia, and class their regulatory systems for insurance as Brunei Darussalam) face the additional challenge risk-based capital (RBC) regimes34. See Figure 4.6. of regulating the takaful market. See Box 4.3. Figure 4.6. ASEAN RBC frameworks as reported by Insurance Regulators35 Brunei Cambodia Indonesia Lao PDR Malaysia Myanmar Philippines Singapore Thailand Vietnam Darussalam Insurance Autoriti Department Otoritas Ministry of Bank Supervisory Insurance Insurance Office of the Ministry of Supervisor Moetari of Financial Jasa Economy, Negara Board, Commission Supervision Insurance Finance Brunei Industry of Keuangan Planning Malaysia Ministry of Department Commission Darussalam the Ministry and Finance Finance and of the of Economy Revenue Monetary and Finance Authority of Singapore RBC No No Yes No Yes No Yes Yes Drafted No Framework Source: Authors, based on sources originating from national insurance regulators RBC as defined by the regulator in each respective country. 34 Note that the Indonesian Parliament approved a bill creating the new regulator OJK Otoritas Jasa Keuangan in October 2011 35 < 54 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 4.3. Regulating Takaful As liabilities under Takaful systems are defined differently than those under traditional insurance, and permitted assets for investment are also different, regulators need to develop principles of supervision for Takaful opera- tors in parallel to those for the traditional insurance market. The risk sharing nature of Takaful insurance poses a particular challenge, where policyholders potentially share in any insufficiency of funds to cover claims payments. For example, to protect consumers in both Malaysia and Indonesia, regulators have formally introduced a requirement for Takaful operators to extend loans from the shareholders fund in the event of any deficit in funds to cover claims payments. Malaysia is moving forward with the most advanced regulatory framework for Takaful in the region, in 2011 it developed a concept paper for Takaful-specific RBC guidelines. The country has further promoted development of the Takaful sector through specific tax exemptions for operators and the establishment of a Shariah Advisory Council within the financial regulator, Bank Negara Malaysia. Agricultural Insurance of the small-scale mixed farming systems of many ASEAN Member States. Fresh water and brackish- water aquaculture (fish farming), mainly for shrimp, Importance of agriculture and natural tilapia, and carp, are also very important. hazard exposure in ASEAN Member States Agriculture is an important socioeconomic sec- In most ASEAN Member States the agricultural tor in ASEAN Member States. In Cambodia, Lao sector faces moderate to severe exposure to PDR, Myanmar, and Viet Nam, more than two thirds tropical cyclones (typhoons) and/or tornados. of the populations are classified as rural and agri- Other natural hazards affecting ASEAN agriculture in- culture is the main source of employment. As of clude seasonal flooding, accentuated by La Niña, and 2009, the agricultural sector contributed between drought associated with El Niño dry patterns, during 21 and 48 percent of national GDP in Viet Nam and which risks of wildfire are also higher. To a certain ex- Myanmar, respectively. Although contributing 15 tent, extreme low-frequency, high-impact events such percent or less of GDP, agriculture is also a very im- as earthquakes and tsunamis also impact agriculture. portant source of rural livelihoods in Indonesia, the Agriculture in the Philippines, Viet Nam, Myanmar, Philippines,Thailand, and Malaysia. Conversely, Sin- and Thailand is very exposed to tropical cyclone dam- gapore and Brunei Darussalam are very small geo- age in certain periods of the year. The Philippines, Viet graphic territories with predominantly urban popu- Nam, Lao PDR, Myanmar, and Cambodia periodically lations. Agriculture is a very insignificant economic experience severe flood damage to agricultural crops activity in these two countries. and livestock. Excess rainfall, which is often associ- ated with typhoons, also leads to problems of flash Paddy rice is the main staple crop grown in the flooding, landslides, and mudslides, most notably in ASEAN region, harvested on two-thirds of the the Philippines and Viet Nam. During the El Niño or total arable area in the region. Other significant dry phase, much of the region is highly exposed to food crops include maize and coffee. Industrial plan- drought, particularly in the Philippines, Indonesia, tation crops such as oil palm, rubber, and coconut Malaysia, Viet Nam, and Thailand, leading to major are also very important, particularly in Indonesia, losses in rain-fed crops. During El Niño dry phases, Malaysia, and Thailand. Livestock, especially poul- wild fires are a severe hazard to the industrial planta- try, pigs, cattle, and buffalo, form a key component tion crops and natural and commercial forestry, espe- Chapter 4: Private Catastrophe Risk Insurance Markets < 55 > cially in Indonesia and Malaysia. jor underwriting losses and most were discontinued by 2000, with the exception of programs in India, ASEAN Member States with significant agri- the Philippines, and Sri Lanka (Hazell, Pomarada and cultural sectors will be strongly affected by the Valdes 1986; Hazell 1992; Mahul and Stutley 2010). impacts of climate change. A recent study shows that changing precipitation patterns, more frequent In 2011, agricultural insurance is available in five extreme droughts and floods, and consequent wa- ASEAN Member States: the Philippines, Thailand, ter stress will negatively impact agriculture36. Climate Viet Nam, Malaysia, and Indonesia, either com- change tends to bring greater uncertainty over crop mercially or on a pilot scale. There is, to the best of production and yields. For traditional agricultural the authors’ knowledge, no agricultural crop or live- indemnity-based insurance and weather index insur- stock insurance in the important agricultural produc- ance, the challenge will be to build climate change ing countries of Cambodia, Lao PDR, or Myanmar. Nor impacts into the design and rating of these products. is it available in Brunei Darussalam or Singapore. The Philippines is the only country in the ASEAN Availability of agricultural insurance and region where public sector agricultural insur- institutional features in ASEAN Member ance continues to operate in 2011. The Philippines States Crop Insurance Corporation (PCIC) is the only public The history of agricultural insurance in the ASE- sector crop and livestock insurer operating in the re- AN region dates back to the late 1970s and early gion. The Philippines is also the only ASEAN Member 1980s when governments in several countries in- State with a long, uninterrupted history of crop insur- troduced public sector crop insurance programs. ance; named-peril insurance and multiple-peril crop Governments in three ASEAN Member States – the insurance (MPCI) have been underwritten by the na- Philippines, Thailand, and Viet Nam – implemented tional insurer, PCIC, for over 30 years. See Table 4.1. public-sector, fully-intervened agricultural insurance systems in the 1970s and 1980s. Other Asia-Pacific Other ASEAN Member States have very small pri- countries introducing public sector agricultural insur- vate sector crop and/or livestock insurance mar- ance during the same period included China, India, kets, and the current trend is for governments Bangladesh, Sri Lanka, and the Democratic People’s to promote subsidized public-private partner- Republic of Korea. ships (PPPs). In 2011, private sector agricultural in- surance is available in four ASEAN Member States, Globally, public sector agricultural insurance pro- namely the Philippines, Thailand, Viet Nam, and Ma- grams have shown poor financial performance. laysia, but has not achieved significant penetration. Programs in the Asia-Pacific region and in South East In parallel, governments in three ASEAN Member Asia have typically performed very poorly financially. States are promoting subsidized PPPs which are un- In general, these programs were designed and im- derwritten by the private insurance sector. In Indo- plemented to meet social as opposed to commercial nesia, the 2009 pilot crop and livestock insurance objectives: premium rates were often capped at be- scheme is being conducted by the Ministry of Agri- low the technically required levels; where programs culture (MoA); in Thailand, a new Rice Disaster Re- were voluntary they often suffered from major prob- lief Top-up scheme was introduced in 2011; and in lems of moral hazard and adverse selection; and the Viet Nam, the government has expressed intentions programs were usually very expensive to implement in 2011 to launch a subsidized privately delivered and administer. Many of these schemes incurred ma- crop, livestock, poultry, and aquaculture insurance under a PPP institutional framework. See Table 4.1 AIT-UNEP RRC.AP, 2011. 36 and Boxes 4.4. and 4.5. < 56 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Table 4.1. Institutional framework for agricultural insurance in ASEAN Member States Philippines Thailand Viet Nam Malaysia Indonesia Public X Private X X X X PPP X X X Source: Authors Agricultural insurance penetration in the have strong public support for agricultural insur- ASEAN region ance, or operate compulsory crop-credit insurance schemes. Agricultural insurance has achieved very little penetration in ASEAN Member States to date. Reflecting limited penetration, the size of the The Philippines had the highest penetration rate agricultural insurance sector, in terms of total in 2009 (ratio of premium subsidies to agricultur- premium volume, in the five ASEAN Member al GDP), standing at 0.012 percent. Other ASEAN States that offer such insurance is currently very Member States had penetration rates of less than small relative to other Asia-Pacific countries. In 0.01 percent. The highest agricultural insurance 2009 (the latest available figures), ASEAN Member penetration rates for the Asia-Pacific region were in States accounted for less than 0.1 percent of the countries such as Australia (0.57 percent of agricul- total agricultural insurance premium volume in the tural GDP), New Zealand (0.39 percent), Japan (1.75 Asia-Pacific region. China had the largest agricul- percent), China (0.4 percent), South Korea (0.5 per- tural insurance market, accounting for 50 percent of cent), and India (0.22 percent) instead. These coun- total premiums, followed by Japan (31 percent) and tries either have well developed insurance markets, India (11.5 percent). See Table 4.2 and Figure 4.7. Table 4.2. Agricultural insurance premiums 2009 by ASEAN Member State (US$ million) Crop 2009 Premium (US$ million) % of 2009 total premium ASEAN Member States Indonesia* 1 0.00% Malaysia* 1 0.00% Philippines** 3 0.10% Thailand** 0.04 0.00% Vietnam* 0.1 0.00% SUB-TOTAL ASEAN 5.14 0.10% China* 1,958.68 49.90% Japan** 1,200.00 30.60% South Korea** 115.81 3.00% Australia* 144 3.70% Other Asia-Pacific (7)** 48.59 1.30 TOTAL ASIA-PACIFIC 3,923.22 100.00% Source: * Solloway 2010; ** Authors Chapter 4: Private Catastrophe Risk Insurance Markets < 57 > Figure 4.7. 2009 Agricultural insurance premium cial AYII pilot, also for rice, which is linked to bank (% of Total) seaonal credit to rice farmers. See Box 4.5. Weather index insurance (WII) is now in its fifth year of imple- Australia 4%% Other Asia-Pacific (7) 1% mentation in Thailand, including under a maize rain- South Korea 3% ASEAN Member States (5) 0% fall deficit scheme and a separate rice rainfall defict program. Both of these programs show potential for India 11% scaling up. Further pilot WII programs have been de- signed and are awaiting implementation on a pilot scale in the Philippines, Indonesia, and Viet Nam. Commercial forestry and plantation crop insurance products (e.g., for oil palm, rubber) are available, but only on a very restricted scale, in Indonesia, Malay- sia, the Philippines, and Viet Nam. See Table 4.3. Livestock insurance is relatively under-devel- Japan 31% China 50% oped in the ASEAN region and currently is only implemented on a commercial scale in the Phil- Source: Authors ippines. Livestock accident and mortality insurance has been underwritten for nearly 30 years in the Philippines, both through PCIC and a private pool Classes and products of agricultural of livestock insurers. In Viet Nam, private sector live- insurance available in ASEAN Member stock insurance has been available for a number of States years through Boa Viet and Groupama insurance companies, but is only underwritten on a very small Traditional indemnity-based crop insurance scale. A livestock mortality and theft insurance pro- products are available in the Philippines and gram was introduced on a pilot basis in Indonesia in Indonesia. PCIC offers named-peril insurance and 2009/10, though the status of the program in 2011 multiple-peril crop insurance (MPCI), as already not- is unknown. Malaysia designed a livestock insur- ed, while Indonesia recently introduced a pilot MPCI ance product in 2008 which has been been put on program. hold37. Livestock epidemic disease insurance is cur- rently underwritten in the Philippines, and Viet Nam There is currently a high level of interest in index has ambitious plans to launch a subsidised epidemic insurance in ASEAN Member States. In 2011, disease insurance program in selected regions for Thailand launched a hybrid area-based crop insur- cattle, pigs, poultry, and aquaculture. See Table 4.4 ance program for rice under the Rice Disaster Re- and Box 4.5. lief Top-up scheme. See Box 4.4. In the Philippines, PCIC has also recently launched a new rice area-yield index insurance (AYII) pilot program for rice produc- ers located in Leyte Province. In Viet Nam, there are 37 In Malaysia, the Tani Malaysia Livestock Pool has designed two AYII programs for rice which are currently await- both livestock and poultry insurance covers but the program is on hold pending agreement between insurers and their re- ing implementation: a government-subsidised PPP insurers on the basis of cover and other terms and conditions. AYII scheme for rice and a separate private commer- See the Malaysia country profile in Appendix 5 for further details. < 58 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 4.4. Thailand Rice Disaster Relief Top-up Crop Insurance Scheme 2011 In 2011, the Government of Thailand elected to estab- lish an insurance scheme linked to its existing disaster relief program. In the event of a disaster, the govern- ment pays disaster relief of THB 606 per rai (0.4 acre). This relief will be topped up by an additional payment ranging from THB 500 to THB 1400 per rai depending on the number of days between planting and the loss occurrence. Claims are only payable on areas where a total loss has been declared. Premiums will be subsi- dized by the government to the extent of 50 percent of the total payable. The government has set the maxi- mum subsidy that the Bank of Agriculture and Agricul- tural Cooperatives (BAAC) can award to participating farmers at a total of THB 3.99 billion (US$132 million). This assumes that every farmer buys cover. For 2011, the government expected 15 percent of the country’s rice farmers to join the scheme. Perils Covered Flood or excessive rainfall, drought, frost, windstorm/ typhoon, fire, and hail. Locations Covered All farmers in Thailand are eligible to be included in the scheme, although the insured areas are likely to reflect BAAC’s current loan portfolio. For 2011, 1.1 million rai, of the total area under rice production of 57 million rai, were expected to be insured, resulting in a 2 percent insurance penetration rate This implied a total sum insured of THB 1.54 billion (US$51 million) and a premium income of THB 13.1 million (US$437,000). Distribution The cover is being distributed to farmers through BAAC. Insurers A pool of eight local insurance companies and nine reinsurance companies will each cover a portion of the risk on a quota share basis. Claims Claims are paid out to any farmers whose land is within an area that has been declared a disaster area. Once the Governor of the Province has declared a disaster, individual farmers may then apply for disaster compensation. The farmer completes a claim form. The farmer must also have title to the land and is usually requested to provide a photograph of the damage. Source: Aon Benfield 2011 Chapter 4: Private Catastrophe Risk Insurance Markets < 59 > Table 4.3. Types of crop insurance products available in ASEAN Member States in 2011 Traditional indemnity based Index based Crop Country  Named Peril MPCI Greenhouse Forestry Area Yield Weather Remote Sensing Indonesia 3* 3 3* Malaysia 3 Philippines 3 3 3 3 3* 3* 3* Thailand 3 3 Viet Nam 3 3 3* Total 1 2 1 4 3 4 1 Notes: 3 Insurance product available on a commercial basis 3* Insurance product is either being implemented on a pilot basis or is still awaiting launch Source: Authors Table 4.4. Types of livestock insurance products available in ASEAN Member States in 2011 Traditional indemnity insurance Country  Livestock Accident & Mortality Livestock Epidemic Disease Poultry Aquaculture Indonesia 3* Malaysia 3* 3* Philippines 3 3 Thailand Viet Nam 3 3* 3* 3* Total 4 2 2 1 Notes: 3 Insurance product available on a commercial basis 3* Insurance product is either being implemented on a pilot basis or is still awaiting launch Source: Authors Public sector support to agricultural insurance premium subsidy). The Government of Viet Nam is in ASEAN Member States also intending to provide very high levels of premi- um subsidies on its planned 2011 PPP insurance pro- Governments in ASEAN Member States provide grams for crops, livestock, poultry, and aquaculture. very high levels of agricultural insurance premi- um subsidies on their public sector and PPP pro- Agricultural insurance in Thailand receives ma- grams, including for the Philippines’s PCIC rice and jor support from government and is currently maize scheme (premium subsidies of 65 to 80 per- one of the most dynamic agricultural insurance cent), the Indonesian pilot crop and livestock insur- markets in the ASEAN region. Between 1978 and ance program in West and Central Java (100 percent 1990, Thailand operated public sector MPCI and premium subsidies in year 1), and the 2011 Thai- livestock insurance programs, both of which were land Rice Disaster Relief Top-up scheme (50 percent terminated. < 60 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 4.5. Government of Viet Nam subsidized pilot agricultural insurance program 2011–13 The Ministry of Agriculture and Rural Development (MoARD) and the Ministry of Finance (MoF) plan to launch a pilot agricultural insurance program in con- junction with the insurance sector in Viet Nam be- tween 2011 and 2013. The objectives of this program are to protect rural livelihoods, to improve the efficien- cy of the insurance market, and to enable farmers to recover more rapidly following natural disasters and/or epidemic disease outbreaks. Insured classes: The pilot program will include the following classes: ■■ Crop insurance: rice ■■ Livestock insurance: cattle and pigs ■■ Poultry insurance ■■ Aquaculture insurance: fin fish, prawns, and shrimp. Pilot provinces: The pilot crop insurance program for rice will be imple- mented in Nam Dinh, Thai Binh, Nghe An, Ha Tinh, Binh Tuan, An Giang, and Dong Thap provinces. The pilot livestock and poultry insurance programs will be implemented in Bac Ninh, Nghe An, Dong Nai, Vinh Phuc, Hai Phong, Thanh Hoa, Binh Dinh, Binh Duong, and Hanoi provinces. Insured perils: Crop insurance will cover catastrophe perils such as typhoon (wind storm) and flood, drought and frost, and specific pests and rice diseases (e.g. brown plant hopper disease). Livestock insurance will cover epidemic diseases in cattle and pigs such as blue-ear disease and foot and mouth disease (FMD). Poultry insurance will cover epidemic diseases including avian flu. Aquaculture insurance will cover natural perils such as storm and flood and fish and prawn diseases. Premium subsidies: The following premium subsidy levels will apply: ■■ Poor rural farming households: premium subsidies of 90-100 percent ■■ Other farmers: premium subsidies of 60 percent ■■ Agricultural production organizations: premium subsidies of 20 percent Source: The Prime Minister No. 315/QD-TTg DECISION On Implementing Pilot Agricultural Insurance Scheme in 2011-13. Hanoi March 1st,2011 Chapter 4: Private Catastrophe Risk Insurance Markets < 61 > ■■ In 2006, a pool of local insurance and rein- Appendix 5, along with detailed profiles on the agri- surance companies introduced the country’s cultural insurance markets in each of the ten ASEAN first pilot WII program for rainfall deficit in Member States. maize production with technical assistance from the World Bank. This purely voluntary WII program, which carries no premium Disaster Microinsurance subsidy, has been implemented for four full Microinsurance is an insurance product de- years through the Bank of Agriculture and signed specifically for low-income populations. Agricultural Cooperatives. The program has Microinsurance products include life and non-life achieved sound underwriting results and is covers as well as blend covers. For the purpose of starting to achieve scale-up. this report, disaster microinsurance refers to a non- ■■ In addition, since 2009, Sompo Japan Insur- life cover for property, financial assets, or livelihoods ance Company (SJIT) has been underwriting that is specifically designed to pay out upon occur- a pilot drought WII program for rice growers rence of a natural disaster. A growing range of di- in selected northern districts of Thailand; this saster microinsurance covers are being developed, program is also showing encouraging results. including property and contents, livelihood, loan, and microenterprise, among others.38 ■■ The Government of Thailand is highly com- mitted to promoting agricultural insurance Microinsurance provides low-income popula- and in 2011 has introduced a new subsidized tions with an efficient, reliable risk manage- Thailand Rice Disaster Relief Top-up crop in- ment tool. The objective of microinsurance is to surance scheme, as already noted, which is prevent vulnerable low-income populations from linked to the existing national disaster relief falling into poverty upon occurrence of an external scheme for rice. This program is being imple- shock, for example, the death of the family bread- mented through a pool of eight local insur- winner or a personal accident. Thus, microinsurance ance companies and nine reinsurance com- acts as a backstop against cyclical poverty resulting panies and is being promoted by government from recurrent external shocks. Disaster microinsur- though the provision of 50 percent premium ance can be particularly useful because it provides subsidies. This natural disaster-linked crop in- cover against systemic risks that make traditional surance scheme may have wider applicability risk-coping strategies, such as borrowing from rela- in the ASEAN region. tives or local moneylenders, impossible or very cost- ly. See Box 4.6. In 2011, Viet Nam drew up proposals for a new subsidized PPP agricultural crop, livestock, poul- Microinsurance can also increase low-income try, and aquaculture insurance program which populations’ willingness to engage in riskier will be insured by the private commercial insur- but more profitable activities. For example, loan ance sector with backing from leading interna- repayment microinsurance can enable microentre- tional reinsurers. The government has committed preneurs to take on credit to grow their enterprises; itself to the provision of very high levels of premium these products often cover the principal and interest subsidies in order to promote this scheme between 2011 and 2013. See Box 4.5. 38 A range of agricultural insurance products targeted at mar- ginal and subsistence farmers have been developed. While these products provide cover against extreme weather and Further details of the experience with and perfor- natural disasters, they are considered agricultural insurance mance of public, private, and PPP agricultural in- products. Discussion of these activities in ASEAN is found in surance in the Asia-Pacific Region are contained in the agricultural insurance section. < 62 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 4.6. Microinsurance protects coastal populations in India In November 2008 Cyclone Nisha struck India and Sri Lanka, causing losses for thousands of families. In the coastal Tamil Nadu state of India, which was impacted by the cyclone, partners Bajaj Allianz, an insurance company, and CARE India, a NGO, had been offering a general insurance policy covering a range of risks since March 2008. The policy provided a defined payout in case of total or partial disability, hospitalization, loss or damage to household or other assets, and death. Within days of the cyclone, the partners received more than 16,000 claims dispersed across 44 villages. The cyclone resulted in claims settlements totaling over US$1.16 million. These were settled by the end of January 2009. The payouts increased the interest of the community in insurance. According to R. Devaprakash, Director of the Tsunami Response Program at CARE India in Chennai, “Many poor people didn’t understand why they should pay money for insurance. Now they realize the value of their investments. And it’s psychological as well: they are not depending on aid from some agency; they are the ones who have taken control. This will really help spread the idea of microinsurance here.” While the payouts highlighted the potential benefits of microinsurance as financial protection against natural disasters, they also exposed the difficulty of pricing microinsurance products without adequate risk data and the challenges of claims adjustment. See Appendix 6. Source: Allianz 2010. of the loan and also sometimes provide the micro- in early stages of microinsurance development, of- entrepreneur with a payout in the case that the cov- ten bundled with access to credit. In time, product ered event occurs. The Microinsurance Catastrophe diversification occurs and products tailored to the Risk Organization (MiCRO), for example, provides contextual needs of specific low-income populations disaster mandatory group catastrophe insurance to become available. See Box 4.7. 50,000 microentrepreneur borrowers in Haiti. See Appendix 6. It is important to note that data on and as- sessments of (disaster) microinsurance markets Microinsurance and disaster microinsur- contained in this report should be interpreted ance in the ASEAN region as suggestive and not absolute. Very limited data are available on the current outreach of (disaster) Disaster microinsurance is as of yet undevel- microinsurance products in ASEAN Member States; oped in ASEAN Member States, with the excep- what data do exist are from diverse sources and dif- tion of the Philippines and Indonesia, where it ferent years. is at early stages of development. Thus, this re- port discusses disaster microinsurance development Market Overview in the context of the development of the broader microinsurance sector. International experience sug- The landscape of microinsurance markets across gests that the development of financial services for ASEAN Member States is highly variable. The two low-income populations tends to begin with micro- largest microinsurance markets in the ASEAN region finance sector development (e.g., credit and sav- are the Philippines and Indonesia and they are likely ings), followed by microinsurance market develop- to remain so in the near term due to a variety of fac- ment. Typically, credit-life and life products appear tors.39 Microinsurance is also present at some level Chapter 4: Private Catastrophe Risk Insurance Markets < 63 > Box 4.7. Development of Microinsurance Microinsurance markets, although not termed as such, have existed in some countries since the late 19th and early 20th centuries. It was not until the 1990s, however, that the international community took significant in- terest in the development of microinsurance schemes as social protection strategies. In the 2000s more private sector interest emerged. The first microinsurance product to achieve significant scale was credit life insurance, which is understandable both because low-income households consistently identify health and life risks as their greatest concerns (Churchill 2006), and because credit life is one of the simplest microinsurance products to develop. Microinsurance market development 1980 1990 2000 2010 2020 Mostly Credit life gains Focused approach Informal schemes and donor-driven popularity, by insurers, large- mutual agreements or subsidized emergence of scale need-based # low-income programs diverse products programs people accessing microinsurance 135 million 1 billion Source: Timeline adapted from Swiss Re 2010; insured population Lloyd’s estimates (2010). Today, innumerable microinsurance schemes exist around the world, providing a rapidly evolving set of microin- surance products to an estimated 135 million people (Lloyd’s 2010). However, this number represents less than 5 percent of the world’s low-income population – evidently, access to microinsurance remains limited. Further- more, although diverse product lines have been developed, they have limited outreach. The vast majority of microinsurance coverage remains life insurance and accidental death and disability. Microinsurance Product Supply Complexity Spectrum Low High Complexity Complexity Life – Accident – Disability – Property – Health – Livestock – Crop – Disaster Source: Authors. A 2007 Microinsurance Centre study estimated that around eight million low-income people outside China were accessing property microinsurance. With the inclusion of the All-China Federation of Trade Unions (ACF- TU) workers, this number rose to 36.2 million people. This estimate included crop, home, livestock, and ‘other possessions’ insurance. of development, ranging from nascent policy and surance is available or under development in Brunei pilot work to blossoming market growth, in Cam- Darussalam or Singapore. Although limited data on bodia, Lao PDR, Malaysia, Myanmar40, Thailand, poverty are available for Brunei Darussalam and Sin- and Viet Nam. There is no evidence that microin- gapore, their 2009 GDP per capita of US$27,3903 Factors include but are not limited to: the degree of develop- 39 has introduced a variant of an insurance product under the ment of micro-financial services sectors, population size, and UNDP-supported Beneficiary Welfare Program. No further supportive regulatory system in the Philippines. information on this program was available at the time of 40 According to UNDP Myanmar, the NGO PACT Myanmar drafting. < 64 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States and US$36,758 (World Bank 2011), respectively, Microinsurance supply chain and small populations suggest that microinsurance is less relevant in these economies and that govern- Informal and formal microfinance institutions ment safety nets may be able to protect vulnerable (MFIs) and community-based organizations41 low-income populations. See Table 4.5 (CBOs) offered the first microinsurance products to appear in ASEAN markets. Different types of Table 4.5. Microinsurance experience MFIs or CBOs dominate depending on the market, in ASEAN Member States but often the appearance of microinsurance has arisen as financial service providers have recognized Experience with Experience with demand for microinsurance services and/or a need Country microinsurance disaster microinsurance Brunei to protect their microlending portfolio. In Cambo- Darussalam n/a n/a dia, MFIs are one of the leading providers of formal Cambodia X – financial services to the poor and are taking the first Indonesia XXX X steps to provide microinsurance, many in conjunc- Lao PDR X – tion with partner NGOs (Alip et al 2009). In Viet Malaysia X – Nam, informal microfinance providers and commu- Myanmar X – nity groups began by delivering life, credit-life, and Philippines XXXX XX health microinsurance with a self-insurance model Singapore n/a n/a (Banking with the Poor 2008). In many cases, es- Thailand XX – pecially in early microinsurance development, the Viet Nam XX – MFI or CBO directly provides microinsurance, act- Key: ing as the risk carrier. It is also common for MFIs No experience: – Very limited: X and CBOs to distribute microinsurance products to Limited: XX their members while passing the risk to an insurance Moderate: XXX partner; this model is appearing more frequently in Strong: XXXX Very Strong: XXXXX the ASEAN region as private insurers become more interested in microinsurance. Source: Authors The Philippines and Indonesia are the only Formal insurers and reinsurers play an increas- ASEAN Member States where disaster microin- ingly important role in the development of mi- surance initiatives have been identified in pre- croinsurance in the ASEAN region, especially di- paring this report. In both countries, disaster mi- saster microinsurance. In the majority of ASEAN croinsurance is in the early stages of development, Member States, private insurers have demonstrated with insurance providers beginning to test market their interest in developing the microinsurance mar- potential through public-private partnerships (PPPs) ket, both for commercial and social reasons (includ- in the past three to four years. The Philippines’ ex- ing at least Cambodia, Indonesia, Malaysia, the Phil- perience is more advanced and, given its support- ippines, Thailand, and Viet Nam). In many of these ive microinsurance regulations and highly exposed countries, insurance industry associations are coop- population to multiple hazards, its disaster micro- erating with the government to develop appropriate insurance market is likely to develop earlier than microinsurance products and regulations. that of Indonesia. In Indonesia, however, multiple efforts are advancing to develop earthquake micro- Community-based organizations, as described by the Interna- 41 insurance, which could provide an opportunity for tional Association of Insurance Supervisors, include mutuals, increased outreach of disaster microinsurance. See mutual benefit organizations, friendly societies, cooperatives, burial societies, fraternal societies, risk pooling organizations, Appendix 6. and self-insurance schemes. Chapter 4: Private Catastrophe Risk Insurance Markets < 65 > International (re)insurers and brokers are also ing property catastrophe microinsurance for Holcim beginning to participate in the more developed Ltd. that will be available for purchasers of Holcim ASEAN microinsurance markets.42 In Indonesia, construction materials or fertilizers43. These inter- for example, Allianz underwrites two group microin- national players bring extensive expertise and risk- surance products that are distributed through MFIs carrying capacity to the market that can facilitate and CBOs. In the Philippines, Munich Re reinsures a increased supply of more complex products such as parametric credit portfolio protection underwritten disaster microinsurance. by the umbrella cooperative and licensed compos- ite insurer Cooperative Life Insurance and Mutual Disaster Microinsurance market potential Benefit Services (CLIMBS). See Box 4.8. International and demand (re)insurers are also testing alternative distribution channels. For example, Zurich Financial is underwrit- Over 222 million people live on less than $2 per day in ASEAN Member States, the income There are some examples of international insurers providing 42 segment often considered the target market microinsurance in ASEAN Member States for many years. Assurances Générales du Laos (ALG), for example, was estab- lished as a joint-venture between the Ministry of Finance of 43 The policies will cover damages from earthquakes, tsunamis, Lao PDR and Allianz in 1990. From 1991 to 1994, AGL tested fires, windstorms and riots. The policies are free to homebuy- microinsurance products in ten villages in Lao PDR with NGO ers for the first year and annual premiums cost less than $10 partners (Allianz AG, GTZ, and UNDP 2006). in subsequent years. Box 4.8. Meso-level parametric catastrophe insurance in the Philippines A public-private partnership in the Philippines involving Munich Re, German aid organization Gesellschaft für Internationale Zusammenarbeit (GIZ), and the Cooperative Life Insurance and Mutual Benefit Services (CLIMBS), an umbrella cooperative and licensed composite insurer, aims to mitigate the effects of extreme weather events on the financial stability of cooperatives and other microfinance providers and to protect their credit portfolios. The ultimate goal of the partnership is to pass on insurance benefits to cooperative and MFI members. Under this partnership, Munich Re reinsures parametric credit portfolio protection underwritten by CLIMBS for its member cooperatives. The product utilizes separate indices for each Philippine municipality and its develop- ment therefore entailed extensive data collection, analysis, and evaluation. Each municipality has a wind speed and a rainfall index that categorize both parameters’ intensity into a 10-, 15- or 20-year reoccurrence event. If a cooperative operating in a given municipality experiences extreme weather conditions that exceed the index set for that municipality, then the weather event triggers a payout for the cooperative. The level of payout is determined as a percentage of the insured portion of the cooperative’s loan portfolio, the actual percentage depending on the event intensity and its corresponding category class. The payout also provides a small pay- ment to cooperative members, with individual allocations determined by the relevant cooperative. GIZ and Munich Re invited CLIMBS to join the strategic alliance in part because of its strong outreach in the country. Composed of over 1,600 primary cooperative members, CLIMBS can act as the crucial link to overcome the significant challenge of distribution. In turn, the catastrophe protection policy reduces cooperatives’ expo- sure to systemic default risk, enhancing their lending capacity and liquidity in critical times and making loans affordable to their members. Secondly, for cooperative members, the policy protects their equity and invest- ments in the cooperatives by enabling them to rebuild their livelihoods after an extreme weather event. It thus prevents low-income households from slipping into poverty. Source: Munich Re 2011. < 66 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States for commercial and social microinsurance. See This estimate is only suggestive of the ASEAN Table 4.6. This estimate does not include Brunei Da- population that could benefit from increased russalam, Myanmar, or Singapore and is based on availability of microinsurance, and must be in- data for 2009 and earlier. Of this segment of the terpreted as such. Where microinsurance is avail- population, at least 133 million live above the inter- able, take-up rates for voluntary products are often national poverty line of $1.2544 and below $245 per low due to a variety of constraints, both on the day, which the private sector often considers the tar- demand side (e.g., lack of financial literacy among get market segment for commercial microinsurance low-income populations) and the supply side (e.g., products. The poorest income segment, living on products whose designs do not address the needs of less than $1.25 a day and totaling some 89 million the low-income market). The challenges for disaster people, is considered better suited to government microinsurance are even more acute due to issues and/or donor-financed social safety nets, including such as risk prioritization by low-income populations social insurance.46 and the complexity of disaster microinsurance provi- sion, among others47. Thus, extrapolating the popu- Denoted in 2005 international dollars (incorporating pur- 44 lation that would purchase (disaster) microinsurance chasing power parity). from these estimates is very difficult. The identified target income group for microinsurance varies 45 between organizations. Note that thresholds both above and Natural disasters are reported as a priority risk below $2 per day have been set by organizations operating in one of four ASEAN Member States for which in this field. risk prioritization surveys are available. The most The segmentation of the microinsurance market into com- 46 mercial and social segments is not intended to suggest that common priority risks reported in these surveys are those lying in the commercial range of US$1.25-2 per day health and death (Churchill 2006). See Table 4.7. do not or should not benefit from publically-supported mi- Although some variation in risk prioritization across croinsurance. Instead, this segmentation is made because it is unlikely that the private sector will be able to address the disaster insurance needs of the lowest income segment. In- 47 It should be noted that even in industrial countries with well- stead, if it does benefit from insurance, this lowest income developed non-life insurance sectors, voluntary purchase group will depend entirely on government/donor support. rates for residential disaster insurance covers tend to be low. Table 4.6. Microinsurance Target Markets in ASEAN Member States (2009 or latest year available) Country Population under $2/day Population under $1.25/day Population in commercial range* Brunei Darussalam n/a n/a n/a Cambodia 8,365,027 4,189,916 4,175,111 Indonesia 116,362,150 43,003,403 73,358,747 Lao PDR 4,171,483 2,142,625 2,028,858 Malaysia 623,520 0 623,520 Myanmar n/a n/a n/a Philippines 41,392,396 20,788,181 20,604,215 Singapore n/a n/a n/a Thailand 17,957,469 7,318,516 10,638,953 Viet Nam 33,602,705 11,433,648 22,169,058 Total 222,474,750 88,876,289 133,598,461 * The commercial range considered in this report is US$1.25 to US$2.00 per day. Note: Values presented for 2009 or latest available value for the period 2006-2009. Note: n/a = not available Source: World Bank Data 2011. Chapter 4: Private Catastrophe Risk Insurance Markets < 67 > ASEAN Member States is likely, it is probable that ers and takaful operators and is distributed these rankings are fairly consistent across countries through branches of selected banks and de- given similar results internationally. While natural velopment financial institutions. disasters are not the most prioritized risk by low- income populations in the ASEAN region, there has ■■ Viet Nam: A 2010 Memorandum of Under- been increasing emphasis by the international com- standing between the Office of Insurance munity on the need to protect low-income popula- Commission and the Ministry of Interior set tions against financial losses from natural disasters out an agreement to cooperate to improve (Swiss Re 2010). the availability of microinsurance products around the country. Table 4.7. Priority risks of low-income households PPPs are driving the development of disaster in selected ASEAN Member States microinsurance in the Philippines and Indone- Country Priority risk sia. This experience is consistent with that in other Indonesia Illness, unforeseen/prohibitive educational countries where disaster microinsurance is being de- expenses, poor harvest veloped. See Appendices 6 and 7. In the Philippines, Lao PDR Illness, livestock disease, death PPPs involving a range of partners have progressed Philippines Death, old age, illness in three important areas: (i) development of a micro- Viet Nam Illness, natural disaster, accidents, illness/death insurance regulatory framework and national strate- of livestock gy; (ii) product development and innovation; and (iii) Source: Various sources summarized in Churchill, 2006 national financial literacy campaign. In Indonesia, PT Asuransi Maipark, owned by all of the country’s gen- The role of the government eral insurance and reinsurance companies, is leading Many governments in the ASEAN region are an initiative to develop an earthquake microinsur- taking action to facilitate the development of ance product, Kartu Gempa. microinsurance markets, especially through public-private partnerships (PPPs). The interest of The Philippines is the first ASEAN Member State ASEAN governments in promoting microinsurance to approve and implement a comprehensive market development has contributed to its growth microinsurance regulation48, although planning and encouraged increased interest from the private and drafting of microinsurance regulations are sector. Some examples include: underway in some other ASEAN Member States. See Box 4.9 and Table 4.8. Well-designed regulato- ■■ Cambodia: In 2010, the Ministry of Economy ry frameworks for microinsurance are important in and Finance (MEF) began granting permis- creating a conducive and enabling environment for sion for the piloting of microinsurance prod- microinsurance market development. Recent case ucts, and in 2011, the MEF began a dialogue studies on insurers in India, South Africa, and the on its draft microinsurance regulation with Philippines, for example, found that government the General Insurance Association of Cam- regulations requiring or encouraging commercial in- bodia. surers to serve low-income and rural communities influenced insurers’ decisions to expand into this ■■ Malaysia: The government has initiated the market (Angove and Tande 2011). The International country’s first microinsurance/microtaka- ful scheme, 1Malaysia Micro-Protection Plan 48 The Philippine insurance code is currently being reviewed, (1MMPP), which it launched in 2010. The and it is expected that microinsurance provision will be re- product is offered by participating insur- vised. < 68 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Association of Insurance Supervisors (IAIS) has re- Given the complexity of disaster microinsur- leased two papers providing regulators in emerging ance provision, appropriate regulations are par- markets with guidance on microinsurance regula- ticularly important for its development. Regula- tion: Issues in regulation and supervision of micro- tions need to address both distributors of disaster insurance, which outlines principles, standards and microinsurance and disaster microinsurance provid- guidance on developing microinsurance markets ers; often, either or both of these are informal (i.e., and Issues paper on the regulation and supervision unregulated). Supportive regulation that promotes of mutuals, cooperatives, and other community- a risk-based approach, for example, with minimum based organizations in increasing access to insur- capital requirements for microinsurers, can help to ance markets, which assists regulators in addressing formalize providers. Disaster microinsurance regu- insurance administrators, distributors, and providers lation can also ensure, for example, recognition of that may fall outside of commonly regulated institu- appropriate products and efficient claims handling tions in insurance. following a disaster. Table 4.8. Microinsurance regulation in ASEAN Member States Country Insurance Regulator Microinsurance Regulation Brunei Darussalam Autoriti Monetari Brunei Darussalam n/a Cambodia Department of Financial Industry of Ministry of Economy Regulation approved, not yet implemented and Finance Indonesia Otoritas Jasa Keuangan - OJK49 No; in October 2011, Government announced microinsur- ance regulation would be developed during 2012 Lao PDR Ministry of Economy, Planning, and Finance No Malaysia Bank Negara Malaysia No Myanmar Supervisory Board, Ministry of Finance and Economy No Philippines Insurance Commission Yes Singapore Insurance Supervision Department of the Monetary Author- n/a ity of Singapore Thailand Office of the Insurance Commission Regulated as an activity line; products considered on a case-by-case basis Viet Nam Ministry of Finance Partial framework in place, not complete Source: Authors In October 2011, Indonesia’s Parliament approved a bill creating a new regulator OJK Otoritas Jasa Keuangan to supervise financial 49 institutions including insurers and reinsurers Chapter 4: Private Catastrophe Risk Insurance Markets < 69 > Box 4.9. Key Features of the Philippine Microinsurance Regulatory Framework ■■ Links premium/contribution and the maximum sum of guaranteed benefits to the daily minimum wage for non-agricultural workers in Metro Manila, the manner and frequency of payments coinciding with their cash flow. ■■ Allows only regulated entities to provide microinsurance, with a special regulatory space specifying a guar- antee fund, capitalization and appropriate risk-based capital for microinsurance, when necessary. Mutual benefit associations (MBAs) wholly engaged in microinsurance are required to have a lower guarantee fund, and cooperative insurance societies lower capitalization. ■■ Mandates market conduct, reducing the period of claims settlement to a maximum of ten days and of suicide exclusion to one year, and requiring a refund of the premium if a suicide claim is not compensable. ■■ Qualifies three delivery channels: – Licensed insurance providers; – Licensed agents and brokers of commercial insurance companies; – Microinsurance agents. ■■ Agents selling only microinsurance are not required to take the regular insurance agents’ license examina- tion but must attend and pass a microinsurance training program. MFIs and cooperatives may be licensed as agents provided they sell microinsurance products to their clients only. ■■ Undertakes initiatives to formulate performance standards and promote financial literacy, with a special focus on the rights and responsibilities of the insured and providers. Source: Report of the 6th International Microinsurance Conference 2010. Recommendations for Chapter 5 Regional Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 71 > < 72 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Five main recommendations are presented, building being addressed (localized versus regional). However, on the review of the state of disaster risk financing and international experience shows that institutional ar- insurance in ASEAN Member States and international rangements that combine both central and decentral- experience. These recommendations aim to contribute ized financial responsibility for disaster risk have had to an open dialogue between ASEAN governments, particular success as they create incentives for risk international financial institutions such as the World reduction at the local levels and give provinces/mu- Bank and Asian Development Bank, and donor part- nicipalities access to powers of central government, ners on efficient and cost-effective financial strategies such as strong coordinating and financial capacity for increased economic and fiscal resilience of ASEAN and easier access to financial markets. See Annex 4. Member States against natural disasters, as part of The need to consider strategies and instruments at their broader disaster risk management and climate the sub-national level is made more urgent by the change adaptation agendas. The five recommenda- high concentrations of population and exposure re- tions aim to offer a framework for a regional agenda sulting from the prevalence of “Mega Cities” in the on disaster risk financing and insurance. Each ASEAN ASEAN region. See Box 5.1. Strategies at the sub-na- Member State may want to prioritize and tailor those tional level can be designed to make allowances for recommendations based on its own needs. the uneven distribution of exposure throughout each ASEAN Member State. Levels of Engagement Recommendations 1 to 3 apply equally to mu- Strategies and instruments for financial protec- nicipal, provincial, and national levels, although tion against natural disasters can be applied at a regional approach would offer particular ad- multiple levels within and beyond a country, vantages in the development of risk informa- including regional, national, provincial, and mu- tion and modeling systems (Recommendation nicipal levels. The most appropriate level (or levels) 1). Note also that those recommendations pertain- for engagement will depend on country-specific con- ing to risk pooling (such as the development of an ditions such as the level of fiscal autonomy of provin- insurance scheme for public assets) would benefit cial and municipal governments and the specific perils from scale to allow for maximum diversification ben- Box 5.1. The Asian Development Bank’s (ADB) DRM efforts in Asia ADB is developing an Integrated Disaster Risk Management (IDRM) framework that incorporates ele- ments of disaster risk reduction (DRR), climate change adaptation (CCA), and disaster risk financing (DRF). The purpose of the IDRM framework is to recognize linkages and synergies across many areas of DRM and to leverage these synergies to craft risk management solutions for member countries. ADB is paying particular attention to the disaster management needs of urban areas. A combination of fac- tors, including urban migration, concentrated economic development, expanded infrastructure, and cli- mate change, has given rise to the need to develop urban-specific IDRM strategies and instruments. With the support of the Japan Fund for Poverty Reduction (JFPR), ADB has begun work with the governments of the Philippines, Indonesia, and Viet Nam to launch disaster finance programs for two cities in each country. The programs will start with urban risk profiling, which will support the development of city selection criteria through a collaborative process involving key government agencies and development partners. Following city selection, DRF options will be developed and tested through consultations and workshops to assess feasibility and market acceptance. DRF options may include disaster liquidity mechanisms, critical asset and infrastructure insurance, and social protection programs directed at households and small business involving microinsurance or microfinance. The three projects are scheduled for completion in 2014. Chapter 5: Recommendations for Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 73 > efits and economies of scale. Recommendation 4 is tential hazards and losses that could arise from these targeted at the national level as it pertains to private hazards are critical for the assessment and manage- markets and Recommendation 5 discusses a region- ment of the potential economic and fiscal burden al approach. arising as a consequence of natural disasters. ASEAN Member States could develop a regional risk Recommendation 1: Develop Risk information platform, including a geo-referenced ex- Information and Modeling Systems posure database and regional catastrophe risk models to Assess the Economic and Fiscal for major perils. This platform could build on ongo- Impacts of Natural Disasters ing national initiatives, such as the development of an earthquake model in Indonesia, and regional and inter- The recent flagship report Natural Hazards, Unnatu- national initiatives such as the Global Earthquake Mod- ral Disasters: The Economics of Effective Prevention el, the Pacific Risk Information System, and the Open highlights the importance of open data in the pro- Data for Resilience Initiative. See Box 5.2 and Box 5.3. cess of effective disaster risk management. Few coun- Existing national datasets and the ASEAN Economic tries collect critical risk data and even fewer have the Ministers (AEM) initiative to identify regional initiatives means to readily share that information. Data on po- that furnish risk data could also be leveraged. Box 5.2. Pacific Risk Information System: The largest collection of geospatial information for the Pacific Island Countries The Pacific Risk Information System (PRIS) has been developed under the Pacific Catastrophe Risk Assessment and Financing Initiative (PCRAFI). The initiative aims to provide Pacific Island Countries (PICs) with disaster risk modeling and assessment tools for enhanced disaster risk management and to engage in a dialogue with PICs on integrated financial solutions to increase their financial resilience to natural disasters and climate change. PCRAFI is a joint initiative between the Secretariat of the Pacific Community (SPC/SOPAC), the World Bank, and the Asian Development Bank, with financial support from the Government of Japan and the Global Facility for Disaster Reduction and Recovery (GFDRR) and technical support from Air Worldwide and New Zealand GNS Science. The PRIS is the result of a three-year effort to collect detailed information on assets, population, hazards, and risks. Physical inspections of more than 80,000 buildings and digitization and inference from satellite imagery of more than 3 million buildings and assets have been undertaken to create an exposure dataset of buildings, major infrastructure, major crops, and population. The PRIS also includes the most comprehensive regional historical hazard catalogue (115,000 earthquake and 2,500 tropical cyclone events) and regional historical loss database ever developed for major disasters. As part of the project, country-specific catastrophe risk models have been developed for earthquakes (including tsunamis) and tropical cyclones (including storm surge), providing the PICs with a financial tool to assess their economic and fiscal exposure to natural disaster and develop cost-effective disaster risk financing and insurance strategies. The Pacific Geonode, an open-source web-based platform, has been developed to provide visualization of risk through maps showing the geographic distribution of potential losses as well as other risk assessment products. Source: PCRAFI (2011) See Annex 8. < 74 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 5.3. Open Data for Resilience Initiative (Open-DRI) OpenDRI is an initiative of the Global Facility for Disaster Reduction and Recovery (GFDRR) of the World Bank aimed at reducing the impact of disasters by empowering decision-makers with better information and the tools to support their decisions. Tools are currently being offered to 25 countries around the world to improve disaster and climate change resilience. Examples of OpenDRIs include: Haitidata: A free, open-source software tool for risk assessment in Haiti that allows organizations and individu- als to share disaster-related data and information. Risk-in-a-Box: A suite of open source tools that close the loop between sharing data and actionable infor- mation to support resilient decision-making. Currently being developed for Indonesia earthquake risk in col- laboration with government stakeholders, GFDRR, Australia-Indonesia Facility for Disaster Reduction and local partners including PT Maipark. Source: GFDRR The regional risk assessment and modeling plat- tingent liability with respect to natural disasters and form would offer ASEAN Member States, among to design its national disaster risk financing strategy other DRM applications, financial tools to assess implemented by the National Disaster Fund, FON- the economic and fiscal impact of natural disasters. DEN. See Box 5.4. The platform could build on re- It would also assist the Ministries of Finance in the gional data sources currently in existence. design of cost-effective national disaster risk financ- ing and insurance strategies, including appropri- The regional risk assessment and modeling platform ate annual budget allocations for potential disaster could also offer tools for regulators to implement events and disaster risk transfer components (such risk-based supervision of domestic insurers and rein- as insurance). The Government of Mexico, for ex- surers and to monitor rate adequacy for catastrophe ample, developed the disaster risk assessment tool, risk insurance products. R-FONDEN, to assess the Federal Government’s con- Box 5.4. R-FONDEN: The financial catastrophe risk model of the Ministry of Finance in Mexico The Government of Mexico developed a catastrophe risk model called R-FONDEN for its national disaster fund, FONDEN. This probabilistic risk model offers catastrophe risk analysis for four major perils (earthquake, floods, tropical cyclones, and storm surge) for infrastructure in key sectors (education, health, roads, and low-income housing) at national, state, and sub-state level. The analysis can be performed on a scenario-basis or on a probabilistic basis. R-FONDEN takes as input a detailed exposure database (including details of buildings, roads, and other public assets) and produces as outputs risk metrics including AEL and PML. This model is currently used by the Ministry of Finance, in combination with actuarial analysis of historic loss data, to monitor the disaster risk exposure of FONDEN’s portfolio and to design disaster risk transfer strategies, such as the placement of indemnity-based reinsurance and the issuance of catastrophe bonds. Chapter 5: Recommendations for Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 75 > Recommendation 2: Develop ■■ Medium risk layer: Contingent credit could Disaster Risk Financing and Insurance finance more severe, but less frequent, di- Strategies at the National and sasters. This budget instrument would allow Sub-national Levels governments to draw down funds quickly after a natural disaster. The World Bank of- A comprehensive national disaster risk financing and fers a contingent credit line, the Develop- insurance strategy should be part of the overall fiscal ment Policy Loan with Catastrophe Deferred risk management strategy of the state. It should aim Drawdown Option (DPL with Cat DDO), to to (i) manage the budget volatility potentially associ- IBRD countries. See Box 5.5 and Annex 3. ated with natural disasters and (ii) provide insurance Governments could also adjust their medi- coverage against natural disasters for key public as- um-term investment plans to release some sets. Particular effort should also be taken to ensure resources for post-disaster response. that the poorest and most vulnerable segments of society receive sufficient disaster-related support and ■■ High risk layer: Low frequency, high sever- that the disaster risk financing and insurance strategy ity risks could be transferred to the interna- reinforces risk reduction principles. tional capital/reinsurance markets through catastrophe reinsurance, cat bonds and/or Financial management of the national cat derivatives. Disaster risk transfer instru- budget against natural disasters ments, such as disaster insurance, would fi- nance major disasters. Governments could ASEAN Member States could develop national purchase parametric insurance against ma- disaster risk financing and insurance strate- jor disasters like earthquakes or tropical cy- gies, building on a risk-layering approach in clones. Payouts would be disbursed based conjunction with a risk reduction strategy. This on parametric triggers, such as the magni- risk-layering approach is based on an optimal mix of tude of an earthquake or the intensity of a risk retention (through reserves/contingency budgets tropical cyclone. This type of insurance is and contingent credit) and risk transfer (such as insur- transparent and allows for fast claims settle- ance). Local, as well as national, governments need ment (usually within two to four weeks). to ensure that they have sound disaster risk financ- ing and insurance strategies in place. See Annex 1 A “bottom-up” disaster risk financing approach for further details and Appendix 9 for a comparative should be considered. Governments should first analysis of risk financing and risk transfer products. secure financing for recurrent events (bottom risk layer) through risk retention (reserves and/or contin- Immediate post-disaster needs could be fi- gent credit) and then move up to increase their lev- nanced through an optimal combination of els of financial resilience through disaster risk trans- financial instruments. Figure 5.1 depicts a three- fer instruments. tiered financial strategy described below. Additional financial capacity could be secured ■■ Low risk layer: An annual budget alloca- through parametric insurance. ASEAN govern- tion/contingency budget could finance re- ments could complement their reserves and/or current disaster losses. An annual budget contingent credit with parametric insurance. Para- appropriation, combined with some minor metric insurance products are insurance contracts post-disaster budget reallocations, could fi- that make payments based on the intensity of an nance recurrent losses such as those occur- event (for example, wind speed, earthquake inten- ring as a consequence of localized floods or sity) rather than the actual loss. Parametric insurance landslides. contracts tend to disperse funds faster than tradi- < 76 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Figure 5.1. Three-tier financial strategy against natural disasters Disaster Risks Disaster Risk Financing Instruments Low Major High Risk Layer Disaster Risk Insurance (e.g., major earthquake, major (e.g., parametric insurance, tropical cyclone) cat bonds) Frequency of event Severity of impact Medium Risk Layer Contingent credit (e.g., floods, small earthquake) Low Risk Layer Contingency budget, reserves, (e.g., localized floods, annual budget allocation) landslides) High Minor Source: World Bank Disaster Risk Financing and Insurance Program, 2010. Box 5.5. World Bank Catastrophe Deferred Drawdown Option The World Bank’s Development Policy Loan (DPL) with catastrophe draw down options (Cat DDO) offers a source of immediate liquidity that can serve as bridge financing while other resources (e.g. concessional fund- ing, bilateral aid, or reconstruction loans) are being mobilized after a natural disaster. Borrowers have access to financing in amounts up to US$500 million or 0.25 percent of GDP (whichever is less). The Cat DDO has a “soft” trigger, as opposed to a “parametric” trigger; funds can be drawn down upon the occurrence of a natu- ral disaster resulting in the declaration of a state of emergency. See Annex 3 for additional details. tional insurance and allow risk to be transferred in In very specific cases, ASEAN governments the absence of traditional insurance market infra- could complement their disaster risk transfer structure (such as claims verification). Importantly, it strategies by issuing catastrophe bonds against is therefore possible to transfer risk where there are extreme losses caused by specific perils. Catas- no independent means of assessing actual incurred trophe bonds are index-linked securities that secure losses to the insured party (in this case the govern- financial resources on the capital markets to be dis- ment). See Box 5.6 and Appendix 8. bursed in the event of the occurrence of pre-defined Box 5.6. Parametric insurance Unlike traditional insurance settlements, which require an assessment of individual losses on the ground, para- metric insurance relies on an assessment of losses using a predefined formula based on variables that are ex- ogenous to both the individual policyholder and the insurer, but which have a strong correlation to individual losses. Parametric instruments allow for fast claims settlement (usually within two to four weeks) and are less exposed to moral hazard and adverse selection. However, parametric products are exposed to basis risk – that is, the possibility that claims payments may not perfectly match individual losses. Careful design of index insur- ance parameters is important to help reduce basis risk. Chapter 5: Recommendations for Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 77 > natural disasters. Cat bonds generally cover the National insurance programs of public highest level of risk and are mainly issued for specific assets perils with an annual probability of occurrence of 2 percent or less (that is, a return period of 50 years National disaster risk financing and insurance or more). Mexico issued cat bonds in 2006 and in strategies should include insurance programs 2009. See Box 5.7 and Annex 5. for public assets. Public assets, such as schools, hospitals, roads, and bridges, can be severely af- Strategies should incorporate comprehensive fected by natural disasters and are currently largely tracking systems to monitor the flow of all pub- uninsured for catastrophe risk in ASEAN Member lic spending in response to disasters, including States. Insurance programs for these assets would the source of related funding. Systematic tracking allow governments to reduce their fiscal exposure to systems are essential in order to effectively manage natural disasters by transferring these risks to private disaster response efforts, identify gaps in funding, insurance markets. support accountability, and draw lessons learned for potential improvements in disaster risk financing ar- In some middle-income countries where fiscal rangements. resources and access to post-disaster capital are limited, governments require by law that public National disaster risk financing and insurance assets have property insurance coverage against strategies should be tailored to the specific cir- natural disasters. This is the case in Latin American cumstances of individual countries. These include countries such as Costa Rica, Mexico, and Colombia. a country’s level of income, the disaster risks faced, In practice, however, most public assets remain unin- the scale and nature of public contingent liability, sured or under-insured, in part because public manag- government fiscal capacity, and the level of access ers are reluctant to spend part of their limited budget to international capital markets. See Box 5.8. In de- on insurance premiums and often lack basic informa- veloping disaster risk financing and insurance strate- tion to select cost-effective insurance coverage. gies, public responsibilities in the event of a disaster will also need to be clearly defined. A disaster risk insurance program for public as- sets could be established in each ASEAN Mem- Individual disaster risk financing and insurance ber State in collaboration with the private insur- strategies also need to take account of the speed ance industry to promote disaster insurance of with which each instrument can be activated. public assets. This program would offer technical The selected basket of instruments needs to reflect assistance to public entities in the design of their ca- the likely temporal distribution of relief, early recov- tastrophe insurance coverage of public assets. Stan- ery, and reconstruction needs for different types of dardized terms and conditions for the property insur- hazards. ance policies would be developed in collaboration Box 5.7. Mexican Catastrophe Bond MultiCat In 2009, the Government of Mexico issued a four-tranche cat bond (totaling US$290 million) with a three-year maturity under the World Bank’s MultiCat Program. The issuer is a Special Purpose Vehicle (SPV) that indirectly provides parametric insurance to the government’s Natural Disaster Fund (FONDEN) against earthquake risk in three regions around Mexico City and against hurricanes on the Atlantic and Pacific coasts. The cat bond will repay the principal to investors unless an earthquake or hurricane triggers a transfer of the funds to the Mexican government. See Annex 5 for additional details. < 78 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Box 5.8. Regional Insurance Facility for Central America (RIFCA) of the Inter-American Development Bank, in cooperation with Swiss Re The Inter-American Development Bank (IADB), in cooperation with Swiss Re, has developed the Regional Insur- ance Facility for Central America (RIFCA) to mitigate the economic impacts of natural disasters in the countries of Central America and the Caribbean. RIFCA has a decentralized structure in which each participating country will be sole owner of a captive but will share administration services with other RIFCA participants. Countries will individually transfer risk to the international reinsurance and capital markets, although countries will be able to enter into collective arrangements that would enable them to jointly place reinsurance in the international market. The coverage provided will be parametric, five-year, reinstatable catastrophe cover for one or more perils. Cover will be provided in two layers, both using the Swiss Re Affected Population Trigger. This trigger is a modeled estimate of the size of the population affected by a natural disaster, based on population data and data on the event’s intensity parameters and location. IADB’s Contingent Credit Facility (discussed in Box 3.9), which can provide up to US$100 million of contingent financing, will comprise the lower layer of coverage. The insurance coverage will sit directly above this layer. Because this insurance will use the same parametric coverage as the contingent credit, the overall coverage provided is “seamless.” The first country to participate in RIFCA is the Dominican Republic, where IADB has provided a US$100 mil- lion contingent loan, US$50 million for earthquake and US$50 million for hurricane, including rainfall. The insurance cover is currently being finalized, with issuance targeted for spring 2012. IADB and Swiss Re plan to expand the Facility to other countries in Central America in the near future. with the private insurance industry. This would assist be then placed on the private (re)insurance market. public managers in identifying their risk exposure and See Box 5.9. A national approach to insuring public their insurance needs. The program could also struc- assets would allow for economies of scale and diver- ture a national insurance portfolio of public assets to sification benefits, thus lowering premiums. Box 5.9. Insurance of public assets in Costa Rica As part of the comprehensive disaster risk financing strategy of the Government of Costa Rica (GoCR), Law 7232 requires public managers to identify the risk exposure of public assets and take action to reduce related financial impacts, including via the purchase of insurance. In practice, however, only a few public assets are properly insured against natural disasters. The GoCR is therefore in the process of establishing a dedicated vehicle, the Catastrophe Risk Transfer Vehicle (CRTV), to offer disaster risk insurance for public assets. The CRTV is expected to be managed by the public insurance company, INS. The CRTV builds on the developing private property insurance market; it allows domestic insurance companies to compete for the underwriting of public assets and provides domestic insurers with incentives to pass the disaster risks to the CRTV through highly competitive reinsurance rates. The CRTV will then aggregate those disaster risks, retain the first losses through its reserves, and pass the excess losses to the international reinsur- ance markets. Chapter 5: Recommendations for Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 79 > Recommendation 3: Establish ■■ An NDF Trust, providing resources for post- National Disaster Funds disaster recovery and reconstruction activities approved by the Program (e.g., for economic The existing process for securing and disbursing pub- recovery). It could also act as the contract- lic funding in the event of a disaster is slow in most ing authority for risk transfer mechanisms, ASEAN Member States. Recent experience in ASEAN including insurance. Member States shows that it can take several months to begin drawing down funds for early recovery pur- The NDF could build up multi-year reserves. The poses and often well over a year before reconstruc- NDF could build up reserves from the unspent por- tion funds begin flowing on a significant scale. This tions of its annual budget allocations over time in can result in delays in recovery and reconstruction, order to increase its retention capacity. The NDF with adverse implications both for affected communi- could potentially be further supplemented by rev- ties and the wider macro-economy. enue generated from temporary post-disaster tax increases, particularly in middle- and higher-income A National Disaster Fund (NDF) could be estab- countries, targeted on geographical areas and sec- lished in ASEAN Member States as a mechanism for the rapid financing of post-disaster opera- tors of an economy that have been relatively unaf- tions.50 A dedicated financial vehicle could be es- fected by the disaster event. tablished in each ASEAN Member State to finance The NDRF could purchase disaster risk transfer post-disaster recovery and reconstruction programs. instruments in order to leverage its financial Building on the experience of the Mexican disaster capacity in case of a disaster. Government regu- fund FONDEN, the National Disaster Fund (NDF) lation would be required to allow the NDF to pay would (i) conduct transparent and efficient damage disaster insurance premiums out of its annual bud- assessments of public assets; (ii) mobilize immediate get allocation. With this approval, the NDF would funding post disaster; and (iii) execute the funds in be responsible for designing and implementing a close collaboration with relevant line ministries and comprehensive disaster risk financing and insurance public agencies. The NDF would be established un- strategy that could include contingent debt agree- der both the Ministry of Finance and the National Di- ments, the purchase of indemnity and parametric saster Management Office (NDMO). The NDF would insurance, and the issuance of catastrophe bonds or include the following windows: alternative risk transfer mechanisms. ■■ An Emergency Fund designed to respond Such funds could also be considered at sub- to the immediate needs of a population af- national levels, such as provincial or municipal fected by a natural disaster, hence support- levels, to assist local governments in the finan- ing the NDMO; cial management of natural disasters. These sub- ■■ A Program for Reconstruction, providing national funds could then be pooled into a larger financial support to rehabilitate and recon- fund managed by the local governments. Disaster struct physical assets. The Program would risk transfer instruments could be accessed collec- focus on the reconstruction of public infra- tively by the pool. structure and low-incoming housing. It is acknowledged that such a fund may be more relevant 50 for middle-income countries like the Philippines, Indonesia, or Viet Nam. Further investigation should be conducted for low-income countries like Cambodia, Lao PDR, and Myanmar. < 80 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Recommendation 4: Promote Private potential to increase insurance penetration and Catastrophe Risk Insurance Markets reach low-income populations. Such products include index-based insurance (increasingly used in The promotion of catastrophe risk insurance of pri- agricultural insurance to protect farmers and herd- vate assets would allow ASEAN governments to re- ers against major disasters), disaster microinsurance, duce their (usually implicit) contingent liability for and takaful (Shariah-compliant insurance) which uti- natural disaster losses. Three key areas for develop- lize novel delivery channels and novel mechanisms ment could be considered by ASEAN governments: (i) for risk transfer. Explicit inclusion of these products the development of an enabling insurance regulatory under regulatory frameworks is required to promote and supervisory framework; (ii) the development of their larger-scale use and to ensure that sustain- risk market infrastructure; and (iii) the facilitation of able growth is coupled with consumer protection. disaster risk pooling. All three areas are relevant, at Governments may also want to consider setting various levels, for property catastrophe risk insurance, “softer,” more enabling regulation for certain prod- agricultural insurance, and disaster microinsurance. ucts. This could include tax-breaks, lower minimum capital requirements, and an expansion of the list Enabling regulation for catastrophe risk of permitted distributors (for example, inclusion of insurance microfinance institutions). Regulators could work toward developing regu- Regulators may also want to consider how they can latory regimes that control exposure to catas- support insurers in maintaining rate adequacy with trophe risk using a full risk-based approach, for respect to catastrophe risk insurance products. example, taking into account probable maximum losses (PMLs) to insurers’ portfolios. While regulatory systems in the region are evolving and, as they de- Developing risk market infrastructure velop, largely recognizing the need to consider the Risk market infrastructure refers mainly to goods level of risk assumed by an insurer when determin- and services that will aid the development of a cost- ing capital requirements, there is a specific need to effective, affordable, and sustainable insurance mar- strengthen monitoring and control of insurers’ expo- ket. It includes product development, risk assess- sure accumulations to catastrophe risk. The evolu- ment and pricing methodologies, loss adjustment tion from non-risk based supervision to an approach procedures, and distribution channels. that considers PMLs would be a medium-term goal involving a number of steps, including working with The need to develop risk market infrastructure is the domestic insurance market to help insurers and particularly strong for disaster microinsurance. reinsurers create internal exposure data collection Distribution and claims-handling challenges that and management systems that would ultimately al- plague many microinsurance schemes are present in low for identification, quantification, and control of the ASEAN region. Although some countries have a catastrophe risk exposure. The regional risk informa- strong MFI/CBO presence to support distribution of tion platform described above would help the in- microinsurance, there is still a need for innovation surance regulator supervise and monitor this line of in distribution channels to reach a larger segment business. See Box 5.2. Some ASEAN Member States of the target population. For example, alternative (such as Thailand) have already begun this process of channels such as the use of mobile phones to dis- regulatory improvement. tribute products should be considered. Regulation could be used to support the growth Governments may want to consider how they of emerging insurance products that have the can partner with the international donor com- Chapter 5: Recommendations for Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 81 > Box 5.10. The Southeastern Europe and the Caucasus Catastrophe Risk Insurance Facility (SEEC CRIF) The Southeastern Europe and the Caucasus Catastrophe Risk Insurance Facility (SEEC CRIF) project is facilitating the development of national catastrophe and weather risk markets in SEEC through the design and introduction of innovative, low-cost insurance products, insurance business production technologies, regulatory reform, con- sumer education, and provision of reinsurance services. The project is a supported by the World Bank, UNISDR, the European Commission, the Swiss State Secretariat for Economic Affairs, and the Global Environment Facility. SEEC CRIF is being implemented through the creation of a specialty government-owned catastrophe risk re- insurer, Europa Reinsurance Facility Ltd. (Europa Re), with the view to improving access to weather risk and catastrophe risk insurance for millions of households, small businesses, and governments in the Facility’s mem- ber states. Established in 2009 in Switzerland, Europa Re employs an independent Board of Directors and is managed by a professional management team. SEEC member governments are Europa Re’s shareholders; cur- rently, Albania, the Former Yugoslav Republic of Macedonia, and Serbia have joined the Facility, with others in discussions to join. Europa Re is currently completing probabilistic high resolution regional earthquake and flood risk models for the SEEC member countries. The models will be used for the purposes of underwriting and pricing flood and earthquake risk in these countries. It is also developing a web-based underwriting and risk pricing platform that will provide insurers with automated real-time underwriting, pricing, and reinsurance decisions for all risks as- sumed through the sales of approved catastrophe insurance products in member countries. This platform will allow participating insurers to keep track of all policies issued through the portal and will enable them to report, and Europa Re to settle, insurance claims. Finally, Europa Re will utilize the platform to track its risk accumula- tions by location and type of risk. munity and private insurance sector to develop Risk pooling provides a point of entry for finan- public goods and services that will contribute cial and technical support to the market. . By ag- to sustainable market growth. The Southeastern gregating risks through a vehicle or facility, a single Europe and the Caucasus Catastrophe Risk Insurance point of entry is created through which the inter- Facility (SEEC CRIF) provides an interesting example of national donor community and/or the government how governments and international donors can col- can inject financial and technical capacity to support laborate to create public or shared market goods for the risk. This point of entry can be used to develop insurance. For the SEEC CRIF facility, catastrophe mod- capacity of the domestic market to underwrite ca- els and an underwriting platform have been devel- tastrophe risks while simultaneously protecting the oped to facilitate market development. See Box 5.10. domestic insurance market from the threat of insol- vency due to large correlated losses. Facilitating disaster risk pooling Turkey provides an interesting example of a Risk pooling can allow domestic insurers to ac- pooled homeowner’s catastrophe insurance pro- cess international reinsurance and capital mar- gram. The Turkish Catastrophe Insurance Pool (TCIP) kets on better terms. By aggregating risks into one was established in 2000 to overcome problems of single insurance portfolio, insurers can approach the market failure in Turkey, namely a lack of local mar- international reinsurance market with a larger, more ket earthquake capacity and low voluntary demand diversified portfolio, which should lead to lower re- for earthquake insurance. The Government of Turkey insurance prices and reduced transaction costs. worked in collaboration with a number of partners < 82 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States including the World Bank to establish a compulsory risk of insolvency from an extreme event. Domestic earthquake insurance scheme to increase uptake and insurers underwrite catastrophe risk but pass the risk to create a pool for earthquake risk that would build onto the pool which is supported by risk capital from the capacity of the domestic insurance market to un- the international reinsurance community, the govern- derwrite earthquake risk while isolating it from the ment, and donors. See Box 5.11. Box 5.11. Turkish Catastrophe Insurance Pool The Turkish Catastrophe Insurance Pool (TCIP) is a public sector insurance company that is managed on techni- cal and commercial insurance principles. The TCIP purchases commercial reinsurance and the Government of Turkey acts as a catastrophe reinsurer of last resort for claims arising out of an earthquake with a return period of greater than 300 years. The TCIP policy is a stand-alone property earthquake policy with a maximum sum insured per policy of US$65,000, an average premium rate of US$46 per annum, and a 2 percent of sum insured deductible. Pre- mium rates are based on construction type (two types) and property location (differentiating between five earthquake risk zones) and vary from less that 0.05 percent for a concrete reinforced house in a low risk zone to 0.60 percent for a house located in the highest risk zone. Since inception, TCIP has averaged a penetration rate of about 20 percent, or 3 million domestic dwellings. See Annex 7 for further details. Recommendation 5: Strengthen disasters while protecting their long-term fiscal ba- Regional Cooperation on Disaster lances. Instead of working on a country-by-country Risk Financing and Insurance basis, this would allow a programmatic approach to disaster risk financing and insurance. This program Regional cooperation on disaster risk financing and could even be extended to other Asian countries. insurance is critical to ensure cost-effective financial management of natural disasters. Donor partners, International Financial Institutions such as the World Regional disaster risk information, assess- Bank and Asian Development Bank, and private ment, and modeling systems stakeholders such as international reinsurers and bro- kers should assist ASEAN Member States in building a Regional investment in disaster risk information, as- regional framework and infrastructure for the financ- sessment, and modeling systems would be more ing of natural disasters. Regional cooperation is es- cost-effective than an individual country approach sential in three areas: (i) risk information, assessment, and would promote regional cooperation in the and modeling; (ii) knowledge exchange and capacity management of risk. A regional approach to the de- building; and (iii) regional vehicles to leverage interna- velopment of catastrophe models makes particular tional reinsurance and capital markets. sense. Disasters cross borders. Hence, typhoon risk A dedicated regional program on Disaster Risk should be modeled using a basin-wide approach Financing and Insurance could be established to and seismic risk according to fault lines that may support the implementation of these activities. span multiple countries. Considerable cost savings The development objective of this program would could be achieved through this approach. This ap- be to reduce the financial vulnerability of ASEAN proach is aligned with the ongoing effort of ASEAN Member States to natural disasters by improving Economic Ministers (AEM) to identify and leverage their financial response capacity in the aftermath of regional initiatives that furnish risk data. Chapter 5: Recommendations for Disaster Risk Financing and Insurance Strategy for ASEAN Member States < 83 > The resulting risk assessments could be used to de- boundary disasters should therefore be regional as velop country-specific financial disaster risk profiles well. Regional risk financing vehicles could assist that, in turn, could be used as the basis for dialogue ASEAN Member States in designing and implement- with and between Ministries of Finance in ASEAN ing their national disaster risk financing and insur- Member States on the necessity to include natural ance strategies. Significant economies of scale may disaster risks in their fiscal risk analyses. be created when risk financing solutions are devel- oped at the regional level. These include both po- tential risk pooling benefits and reduced operating Regional knowledge advisory services and costs. These vehicles can also efficiently leverage the capacity building programs international reinsurance and capital markets. There may be political benefits related to increased region- Capacity building and knowledge advisory services al cooperation as well. are essential to assist ASEAN Member States in the development of disaster risk financing and insurance Such financing vehicles can assist governments in services. A regional platform should facilitate knowl- managing potential fiscal volatility linked to major di- edge sharing among ASEAN Member States and also saster risks in a cost-effective manner. See Box 5.12. with other countries beyond the ASEAN region. They can also help domestic insurance companies to develop and to implement cost-effective and afford- Regional vehicles to leverage international able property catastrophe risk insurance products. reinsurance and capital markets Major natural disasters are not necessarily limited to a single country and the financial response to trans- Box 5.12. Caribbean Catastrophe Risk Insurance Facility The Caribbean Catastrophe Risk Insurance Facility (CCRIF) offers a successful example of a regional catastrophe pool. The CCRIF is the result of two years of collaborative work between CARICOM governments, key donor partners, and the World Bank Group. The Facility became operational on June 1, 2007. Since then, the Facility has disbursed more than US$30 million to the participating Caribbean countries affected by natural disasters to help them finance their immediate post-disaster expenditures. The CCRIF functions as a mutual insurance company controlled by participating governments. The Facility was initially capitalized by participating countries, with support from donor partners. CCRIF helps Caribbean countries lower the cost of insurance by pooling risks. Insured countries pay an annual premium commensurate with their own specific risk exposure and receive compensation based on the level of coverage agreed upon in the insurance contract upon the occurrence of a major disaster. A portion of the pooled risk is retained through reserves, which helps to reduce the cost of insurance premiums. The CCRIF transfers the risks it cannot retain by purchasing reinsurance and catastrophe swaps. Coverage provided by the Facility is parametric in nature. Unlike traditional insurance settlements that require an assessment of individual losses on the ground, parametric insurance relies on a payout disbursement contin- gent on the intensity of an event (e.g., wind speed, ground acceleration). These instruments pay out faster than traditional triggers but have associated basis risk – that is, risk that the payout does not match losses sustained on the ground. See Annex 6. < 84 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Glossary Adverse Selection Adverse selection occurs when potential insurance purchasers know more about their risks than the insurer does, leading to participation by high risk individuals and nonparticipation by low-risk individuals. Insurers react by either charging higher premiums or not insuring at all. Average Expected Loss Expected loss per year when averaged over a very long period (for example, 1,000 years). Computationally, AEL is the summation of products of event losses and event occurrence probabilities for all stochastic events in a loss model. Alternative Risk Transfer Refers to any non-traditional form of insurance risk transfer. Catastrophe bonds are a form of ART. Basis Risk The risk associated with index insurance that the index measurements will not match individual losses. Some households that experience loss will not be covered, for example, and some households that experience no loss will receive indemnity payments. As the geographical area covered by the index increases, basis risk will increase as well. Capacity The maximum amount of insurance or reinsurance that the insurer, reinsurer, or insurance market will accept. Captive Insurance The arrangement whereby a subsidiary company provides insurance or reinsurance for its parent. Catastrophe A severe, usually sudden, disaster that results in heavy losses. Catastrophe Bond A high-yielding, insurance-linked security providing for payment of interest and/or principal to be suspended or cancelled in the event of a specified catastrophe, such as an earthquake of a certain magnitude or above within a predefined geographical area. Catastrophe Model A computerized model generating a set of simulated events to calculate losses arising from a catastrophe. Catastrophe Swap A contract used by investors to exchange (swap) a fixed payment for a certain portion of the difference between insurance premiums and claims. Claim An insurer’s application for indemnity payment after a covered loss has occurred. Combined Ratio The sum of acquisition and administrative expenses and claims and insurance benefits incurred divided by premiums earned. Direct Loss Recovery cost of the damaged assets. Diversification Development of a portfolio with a variety of assets in terms of geographical or sectoral spread, or credit quality. In general, risk is reduced as portfolio diversification increases. Exposure The amount (sum insured) exposed to the insured peril(s) at any one time. Facultative Reinsurance The reinsurance of individual risk at the option of the reinsurer and the ceding company, whether under a treaty or by negotiation. Hard Reinsurance Market A market situation where the supply of reinsurance coverage is restricted and prices rise. Hazard A physical or moral feature that increases the potential for a loss arising from an insured peril or that may influ- ence the degree of damage. Indemnity The amount payable by the insurer to the insured, in the form of cash, repair, replacement, or reinstatement, in the event of an insured loss. This amount is measured by the extent of the insured’s pecuniary loss. It is set at a figure equal to but not more than the actual value of the objects insured just before the loss, subject to the adequacy of the sum insured. Indirect Losses Economic consequences of the damaged assets (e.g., foregone revenue). Insurance A financial mechanism that aims to reduce the uncertainty of loss by pooling a large number of uncertainties so that the burden of loss is distributed. Generally, each policyholder pays a contribution to a fund, in the form of a premium, commensurate with the risk he introduces. The insurer uses these funds to pay the losses (indemnities) suffered by any of the insured. Insurance Captive An insurance company that is owned and controlled by its insureds. Insurance Policy A formal document (including all clauses, riders, and endorsements) that expresses the terms, exceptions, and conditions of the contract of insurance between the insurer and the insured. It is not the contract itself but evidence of the contract. Glossary < 85 > Layer A range of potential loss that is covered by insurance. For example, an insurance contract may pay indemnities only for losses within a specified range of magnitude. Limit Maximum indemnity payout specified in the insurance policy. Loss on Line Annual expected loss as a percentage of the policy limit. Moral Hazard In insurance, moral hazard refers to the problems generated when the insured’s behavior can influence the extent of damage that qualifies for insurance payouts. Examples of moral hazard are carelessness, fraudulent claims, and irresponsibility. Parametric Insurance A form of insurance that makes indemnity payments based not on an assessment of the policyholder’s individual loss, but rather on measures of a parametric index that is assumed to proxy actual losses. Premium The monetary sum payable by the insured to the insurers for the period (or term) of insurance granted by the policy. Premium = premium rate x amount of insurance Also, the cost of an option contract paid by the buyer to the seller. Premium Rate The price per unit of insurance, normally expressed as a percentage of the sum insured. Price Multiple Ratio of the rate on line to the loss on line. Probable Maximum Loss (PML) The largest loss believed to be possible for a certain type of event in a defined return period, such as 1 in 100 years or 1 in 250 years. Rate on Line Insurance premium as a percentage of the policy limit Reinsurance Insurance purchased by an insurer. When the total exposure of a risk or group of risks presents the potential for losses beyond the limit that is prudent for an insurance company to carry, the insurance company may purchase reinsurance. Reinsurance has many advantages, including 1) leveling the results of the insurance company over a period of time; 2) limiting the exposure of individual risks and restricting losses paid out by the insurance company; 3)possibly increasing an insurance company’s solvency margin (percent of capital and reserves to net premium income), hence the company’s financial strength; and 4) enabling the reinsurer to participate in the profits of the insurance company, but also to contribute to the losses, the net result being a more stable loss ratio over the period of insurance. Risk Financing The process of managing risk and the consequences of residual risk through products such as insurance con- tracts, cat bonds, reinsurance, or options. Risk Layering The process of separating risk into tiers that allow for more efficient financing and management of risks. Risk Pooling The aggregation of individual risks to manage the consequences of independent risks. Risk pooling is based on the law of large numbers. In insurance terms, the law of large numbers demonstrates that pooling large numbers of roughly homogenous, independent exposure units can yield a mean average consistent with actual outcomes. Thus, pooling risks allows an accurate prediction of future losses and helps determine premium rates. Risk Retention The process whereby a party retains the financial responsibility for loss in the event of a shock. Risk Transfer The process of shifting the burden of financial loss or responsibility for risk financing to another party, through insurance, reinsurance, legislation, or other means. Soft Reinsurance Market A market situation where the reinsurance coverage supply is plentiful and prices decline. Systemic Risk Risk that impacts the entire financial system, rather than individual sectors. Exposure to systemic risk cannot be avoided through diversification. Total Economic Losses Sum of direct and indirect losses. Annexes < 87 > List of Annexes Annex 1. Disaster Risk Financing and Insurance Framework ............................................................. 88 Annex 2. Financial Risk Assessment of ASEAN Member States ......................................................... 91 Annex 3. World Bank Development Policy Loan with Catastrophe Deferred Drawdown Option ....... 100 Annex 4. Mexican Natural Disaster Fund FONDEN ........................................................................... 102 Annex 5. Catastrophe Bonds in Mexico ........................................................................................... 108 Annex 6. Caribbean Catastrophe Risk Insurance Facility ................................................................... 110 Annex 7. Turkish Catastrophe Insurance Pool .................................................................................. 112 Annex 8. Pacific Catastrophe Risk Assessment and Financing Initiative ............................................. 113 Annex 9. Probabilistic Catastrophe Modeling .................................................................................. 115 Annex 10. Borrowing Capacity of ASEAN Member States .................................................................. 117 Volume 2: Technical Appendices Available online at www.worldbank.org/fpd/drfi and www.gfdrr.org/gfdrr/drfi. See “Publications” page of either website. Volume 2 of the report includes 10 supporting technical appendices. This volume complements the main report but is published as a separate input document. It compiles background notes and papers drafted for the preparation of the main report. The team has made every attempt to verify the contents presented, but the information should be interpreted with due consideration to its limitations resulting from the fact that indirect sources have been used where primary sources were not available and that the collective knowledge in this area is limited. An overview of the contents of Volume 2 is presented here. Appendix 1. Disaster Risk Exposure Profiles of ASEAN Member States Appendix 2. Disaster Risk Management Profiles of ASEAN Member States Appendix 3. Fiscal Risk Management of Natural Disasters by ASEAN Governments Appendix 4. Property Catastrophe Risk Insurance Markets Appendix 5. Agricultural Insurance in ASEAN Member States Appendix 6. Disaster Microinsurance: Selected Case Studies and Profiles of ASEAN Member States Appendix 7. Catastrophe Microinsurance – The Need and the Challenge, Finding Solutions Appendix 8. Parametric Insurance – Basic Concepts Appendix 9. Comparison of Ex-Ante Disaster Risk Financing and Transfer Instruments < 88 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Annex 1. Disaster Risk Financing rapid response once a disaster occurs. The World and Insurance Framework Bank country catastrophe risk financing framework is based on three pillars: To help countries reduce their (over-)reliance on post disaster external assistance, the World Bank has pro- ■■ Assessment of the government’s contingent lia- moted a disaster risk financing and insurance frame- bility. The first step in understanding the govern- work, which is partly based on corporate risk man- ment’s contingent liability is to develop precise agement principles but also considers economic and risk models that accurately reflect the country’s social factors such as the government’s fiscal profile risk exposure to natural hazards and the losses and the living conditions of the poor (Gurenko and associated with various events. Second, a dia- Lester 2003, Cummins and Mahul 2009). logue must take place regarding the roles and re- sponsibilities of the government and individuals This risk management approach relies on the identi- in the aftermath of a catastrophic event. The con- fication and assessment of the (implicit and explicit) tingent liability of the government due to natural contingent liability of a government in the event of disasters is often implicit, as the law usually does natural disasters and on the financing of this contin- not clearly define the financial responsibility of gent liability, possibly using market-based financial the government when a disaster hits the country. instruments. By ensuring that sufficient liquidity ex- The government thus acts as a (re)insurer of last ists immediately following a disaster, modern fund- resort, without knowing precisely its catastrophe ing approaches can help speed recovery, ensure that risk exposure. By understanding the full exposure scarce government funds are well used, and reduce and the extent of public intervention in recovery the risk-enhancing effects of moral hazard. efforts, it is possible to ascertain the contingent liability carried by the government. With sufficient liquidity following a disaster, the gov- ■■ Promotion of commercial property catastrophe ernment can immediately focus on early recovery insurance. The government can reduce its con- and not be distracted by having to close short-term tingent liability by encouraging private competi- funding gaps. At the same time, authorities can tive insurance solutions for the transfer of pri- jumpstart reconstruction, particularly of key pub- vately-owned risks, including property insurance lic infrastructure (including bridges, hospitals, and and agricultural insurance. This can be done by schools). Finally, catastrophe risk management can creating an enabling environment that allows pri- assist countries in the optimal allocation of risk in vate insurers and reinsurers to offer competitive the economy, which may result in higher economic products and, possibly, through the establish- growth, better risk reduction, and more effective ment of catastrophe insurance programs based poverty alleviation. on public-private partnerships, including catas- trophe insurance pools. This allows the govern- The sovereign catastrophe risk financing framework ment to reduce its contingent liability in the case is part of a broader disaster risk management frame- of a natural disaster. The government can thus work promoted by the World Bank, which also in- concentrate its disaster-related financial support cludes: i) risk assessment; ii) emergency prepared- on the poor and disadvantaged. ness; iii) risk reduction; and, iv) institutional capacity building. Catastrophe risk financing complements ■■ Sovereign financial protection against natural other disaster risk management activities and pro- disasters. The government can manage its re- tects against extreme events that cannot be effi- maining contingent liability arising from natural ciently mitigated. It can also provide incentives for disasters by promoting the insurance of public prevention and preparedness activities and allow Annex 1. Disaster Risk Financing and Insurance Framework < 89 > assets and by protecting its budget against exter- and include reserves or calamity funds, budget nal shocks through sovereign risk financing solu- contingencies, contingent debt facilities and risk tions, including reserves, contingent credit and transfer mechanisms. Risk transfer instruments are insurance. instruments through which risk is ceded to a third party, such as traditional insurance and reinsurance, parametric insurance (where insurance payouts are Source of Financing Post-Disaster triggered by pre-defined parameters such as wind speed of a hurricane) and Alternative Risk Transfer Governments have access to various sources of fi- (ART) instruments, such as catastrophe (cat) bonds. nancing following a disaster. These sources can be categorized as ex-post and ex-ante financing instru- These various financial instruments are available ments. Ex-post instruments are sources that do not at different periods of time after a disaster (Figure require advance planning. They include budget re- A1.1). A time-sensitive analysis is therefore required allocations, domestic credit, external credit, tax in- to support the design of a cost-effective disaster risk creases, and donor assistance. Ex-ante risk financ- financing strategy. ing instruments require pro-active advance planning Figure A1.1. Availability of Financial Instruments Over Time Short term (1-3 months) Medium term (3-9 months) Lomg term (over 9 months) Ex-post financing Contingency budget Donor assistance relief In-year budget reallocation Domestic credit External credit Capital budget reallignement Donor assistance (reconstr.) Tax increase Ex-ante financing Reserve fund Contingent debt Parametric insurance Traditional insurance Source: Ghesquiere and Mahul, 2007 < 90 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Figure A1.2. Catastrophe risk layering High severity International Donor Assistance Insurance Linked Securities Risk Transfer Insurance/Reinsurance Contingent credit Risk Retention Reserves Low severity Low frequency High frequency Source: Authors. Among the ex post (post-disaster) financing tools, only once reserves and budget contingencies are ex- contingency budget is the first to be immediately hausted or cannot be accessed fast enough. Finally, available in the aftermath of a disaster. Other ex- international post-disaster donor assistance plays a post financing tools usually take more time to mo- role after the occurrence of an extreme natural di- bilize and are mainly available for the reconstruction saster. phase. These include emergency recovery loans and post-disaster reconstruction loans from international A “bottom-up” approach is recommended: the financial institutions, such as the World Bank. government should first secure funds for recurrent disaster events and then increase its post-disaster fi- Ex ante financing instruments can provide immedi- nancial capacity to finance less frequent but more ate liquidity after a natural disaster. These instru- severe events. The level of fiscal resilience to natural ments are designed and implemented before a di- disasters, which drives the optimal financial strat- saster occurs. They include national disaster reserve egies against natural disasters, is a decision to be funds, contingent credit and insurance. Small but re- taken by the government based on economic and current losses can be retained through reserves and/ social considerations. or contingent credit. More severe but less frequent events, occurring for example once every 7 years or A comparative analysis of ex ante risk financing and more, can be transferred to the insurance or capital risk transfer instruments is provided in Appendix 9. markets. Catastrophe risk layering can be used to design a risk financing strategy (see Figure A1.2). Budget contingencies together with reserves are the cheap- est source of ex-ante risk financing and will gener- ally be used to cover recurrent losses. Other sources of financing such as contingent credit, emergency loans and possibly insurance should enter into play Annex 2. Financial Risk Assessment of ASEAN Member States < 91 > Annex 2: Financial Risk Assessment tor, through mainly agricultural economies, such as of ASEAN Member States Myanmar, Lao PDR, and Cambodia, where agricul- ture accounts from 35 to 49 percent of GDP. In terms of economic development, ASEAN Member States Socioeconomic Setting vary from high income countries, namely Brunei and Singapore, through lower middle income countries, ASEAN covers a total area of 4.47 million square ki- specifically Indonesia, the Philippines, and Thailand, lometers and has a total population of 593 million. to low-income countries, namely Cambodia, Lao Ten countries comprise ASEAN, namely, Brunei Da- PDR, Myanmar, and Viet Nam. russalam, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and A large part of the ASEAN population lives in river- Viet Nam, extending from south of China, east of In- ine plains, deltas, and coastal plains, and is highly dia, and north of Australia. Indonesia is the largest vulnerable to periodic and extensive hazards such as country in the region in terms of land extension, com- flooding, drought, and low-frequency, high-impact prising 42 percent of total area, followed by Myan- hazards such as tsunami and cyclones. Furthermore, mar, which accounts for 15 percent of the ASEAN ASEAN is one of the most exposed regions in the area (Table A2.1). Brunei Darussalam and Singapore world to multiple natural hazards such as typhoons are the smallest countries in the region and together (tropical cyclones), floods, droughts, earthquakes, account for less than 0.12 percent of total ASEAN tsunami, volcanic eruptions, landslides, and forest land area. Indonesia, the Philippines, and Viet Nam fires; ASEAN also faces agricultural and resource have the largest populations in the region, account- risks as well as risks associated with rapid urbaniza- ing for 72 percent of the total ASEAN population. The tion, migration, and socioeconomic change. (See geographically small Singapore stands as the most ASEAN Disaster Risk Profile section and country di- densely populated country, and Lao PDR is the most saster risk profiles.) sparsely populated country in the region. Methodology ASEAN nations span a geographically and economi- cally diverse region. Extending through high hills and A preliminary financial risk assessment has been rugged mountains, elevated plateaus, highlands, conducted for the purposes of this report following floodplains, coastal plains, and deltas, the ASEAN the World Bank methodology, based on a combi- region is also home to large river systems such as the nation of historical and simulated disaster losses. Mekong and the Ayeyarwady, and major water bod- Historical disaster loss data, as reported by EM-DAT ies such as Tonle Sap and Lake Toba (ASEAN DRM, CRED, provide information on past geophysical and 2010). hydro-meteorological events that exceeded a de- fined threshold of severity. Simulated catastrophe On average, the service sector is the main contribu- losses are computed from probabilistic catastrophe tor to the ASEAN regional economy, with an aver- risk models for the perils of earthquake and ty- age GDP contribution of 44 percent, followed by the phoon, providing information about catastrophic industrial sector, which accounts for an average 38 losses caused by simulated major natural disasters percent of national GDP, and the agricultural sec- of varying severity. Willis along with members from tor, accounting for 19 percent. ASEAN Member the Willis Research Network contributed simulated States range, however, from relatively diversified catastrophe losses for this analysis. economies such as Brunei Darussalam, Indonesia, and Malaysia, with 71 percent, 50 percent, and 44 Historical loss data for high-frequency, low-impact percent of their GDP provided by the industrial sec- natural disasters such as drought, floods, and for- < 92 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Table A2.1. ASEAN regional and country socioeconomic characteristics Industry GDP (%) Agricultural GDP Service GDP (%) Density (per sw. GDP (2010 US$) Urban Popula- tion % (2008) % of ASEAN % of ASEAN Population Population Land Area (sq. Km) Country region region km) (%) Brunei Darussalam* 5,270 0.1 388,190 0.1 67 75 10,732 0.7 71 28 Cambodia* 176,520 4 14,494,293 2 80 22 11,343 35 24 41 Indonesia 1,811,570 42 240,271,522 41 126 53 706,558 16 50 35 Lao PDR 230,800 5 6,834,345 1 29 32 7,491 35 27 39 Malaysia 328,550 8 25,715,819 4 78 71 237,804 10 44 46 Myanmar** 653,520 15 48,137,741 8 71 33 20,089 43 20 37 Philippines 298,170 7 97,976,603 17 327 66 199,589 14 32 55 Singapore 700 0.02 4,657,542 1 6,682 100 222,699 0 28 72 Thailand 510,890 12 65,998,436 11 129 34 318,847 12 43 45 Viet Nam 310,070 7 88,576,758 15 267 28 103,572 21 40 39 ASEAN** 4,326,060 100 593,051,249 100 786 51 1,838,725 19 38 44 Note: * Myanmar Agricultural GDP is for 2004, Industry and Service GDP for Brunei Darussalam and Cambodia is for 2007 and 2008 respectively. ** Population density, urban population, and GDP value added by sector for ASEAN is the average of individual country figures. Source: World Bank, IMF, and ASEAN DRMI. est fires for 1996-2010 were extracted from the EM- 2010, with each country’s exposure and prices corre- DAT CRED data. Loss data collected by EM-DAT are sponding to that year. For Myanmar, the absence of expressed in current US dollars in the year of the catastrophic models for earthquake and hurricane disaster event. Losses were therefore multiplied by necessitated a slightly different approach, described a factor equivalent of GDP2010/GDPyear to account below together with the results for other countries. for changes in exposure through time, as well as for price inflation1. Statistical analysis and infer- Country Risk Profiles ence based on historical data was performed and complemented with probabilistic catastrophe mod- Brunei Darussalam Financial Risk Assessment el-generated results to calculate average expected losses (AELs) and probable maximum losses (PMLs). The country has annual expected losses of US$0.35 These risks metrics were calculated as if a disaster of million. However, it is important to emphasize that a given magnitude or return period were to occur in this AEL is associated with one single historical event reported during the estimation period, a forest fire Previous disaster risk assessments of the ASEAN regions have 1 that occurred in 1998, and might not reflect actual followed a historical approach in computing AEL and PML expected economic losses faced by the country as a metrics. This study complements the historical analyses with probabilistic models for a more accurate analysis of country result of natural catastrophes. risk profiles. Further differences between risk metrics report- ed in this and previous analyses might stem from the adjust- Brunei is rarely exposed to large disaster events such ment made to historical loss data to account for changes in as typhoons, earthquakes, or severe flooding, but economic exposure and price inflation through time, which was not taken into account in previous analyses. risks of landslides in flood-prone or hilly areas are Annex 2. Financial Risk Assessment of ASEAN Member States < 93 > serious. Previous studies indicate that the coun- riod. Cambodia faces estimated maximum losses of try has suffered multiple natural disasters in recent US$825 million in a 100-year period, equivalent to years, including floods, landslides, fire outbreaks, 7.3 percent of GDP. More extreme losses, such as and haze, as well as strong winds (ASEAN DRMI, a large earthquake or storm, occurring once every 2010). However, the country lacks a systematic data 200 years would cause losses of US$1 billion, or 8.9 management system, including the recording of percent of GDP. (See Figure A2.2.) historical events. Thus, it is possible that economic losses resulting from natural disasters are under-re- Figure A2.2. Estimated Economic Losses ported, and that risk metrics computed with histori- for Cambodia cal incomplete data might be underestimated. Given 1,200 10 that neither complete historical data nor simulated 9 1,000 8 catastrophic loss data are available for Brunei Darus- 7 US$ Millions 800 % of GDP salam, PMLs are not reported in this study. 6 600 5 4 400 3 Cambodia Financial Risk Assessment 2 200 1 Cambodia experiences annual expected econom- 0 0 ic losses (AEL) of US$74.2 million stemming from AEL 20-year 100-year 200-year natural disasters. Floods are the predominant risk in Cambodia 74.2 405.5 825.0 1,011.7 Cambodia, with annual expected losses of US$41.6 %of GDP 0.7 3.6 7.3 8.9 million or 55 percent of total AEL (Figure A2.1). Source: Authors, original data EM-DAT CRED and WRN Droughts are the second most important risk in the country with annual expected economic losses of US$28.5m, accounting 28 percent of total AEL. Indonesia Financial Risk Assessment Storm and earthquakes represent 4 percent and 3 As one of the most disaster-prone countries in the percent of total AEL, respectively. On average, each world, Indonesia faces annual expected economic year Cambodia experiences estimated losses equiva- losses of US$1.3 billion as a consequence of natural lent to 0.7 percent of its GDP as a consequence of hazards. Multiple natural disasters impact the coun- natural disasters. try periodically, of which earthquake or seismic ac- tivity pose the highest risk, causing annual average Figure A2.1. Annual Expected Loss for Cambodia losses of US$474.8 million or 37 percent of total AEL by Peril (US$ Millions) (See Figure A2.3). Wildfires and floods also pose sig- 2.0 nificant risks for Indonesia, causing average losses of US$410.9 and US$372.7 million and accounting for 32 percent and 29 percent of total AEL, respectively. n Drought On average, the country experiences economic loss- n Earthquake 41.6 28.5 es equivalent to 0.2 percent of its GDP as a result of n Flood natural disasters (See Figure A2.4). n Storm 3.0 It is estimated that Indonesia experiences losses of US$4.7 billion (equivalent to 0.7 percent of GDP) Source: Authors, original data EM-DAT CRED and WRN once every 20 years. Average annual losses and high- It is estimated that Cambodia will experience a maxi- er frequency losses (20-years) are usually triggered mum economic loss of US$405 million, equivalent by high frequency events, such as small earthquakes to 3.6 percent of its GDP, once over a 20-year pe- or seismic activity, floods, and wildfire. On the oth- < 94 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States er hand, high-impact extreme events such as large cause up to US$0.9 billion economic losses, or 11.7 earthquakes occurring once in 100 years can bring percent of the country’s GDP, while a 200-year storm about economic losses of US$ 9.9 billion, equivalent or flood would result in maximum losses of US$1 bil- to 1.4 percent of the country’s GDP (See Figure A2.4). lion, equivalent to a substantial 13.6 percent of GDP. Figure A2.3. Annual Expected Loss for Indonesia Figure A2.5. Estimated Economic Losses for by Peril (US$ Millions) Lao PDR 19.4 1,200 16.0 14.0 1,000 n Drought 12.0 US$ Millions 800 % of GDP 410.9 n Earthquake 10.0 474.8 600 8.0 n Flood 6.0 n Mass movement wet 400 4.0 25.7 327.7 n Wildfire 200 2.0 0 0.0 AEL 20-year 100-year 200-year Source: Authors, original data EM-DAT CRED and WRN Laos 52.3 342.6 875.3 1,020,6 %of GDP 0.7 4.6 11.7 13.6 Figure A2.4. Estimated Economic Losses for Source: Authors, original data EM-DAT CRED and WRN Indonesia 14,000 2.0 1.8 12,000 1.6 Malaysia Financial Risk Assessment 10,000 1.4 US$ Millions On average, Malaysia faces annual economic losses % of GDP 8,000 1.2 1.0 of US$174.6 million caused by natural catastrophes, 6,000 0.8 0.6 equivalent to less than 0.1 percent of the country’s 4,000 2,000 0.4 GDP (Figure A2.7). Floods are the most important 0.2 0 0.0 hazard affecting Malaysia, with annual economic AEL 20-year 100-year 200-year losses of US$91.4 million (52 percent of total AEL), Indonesia 1,303.5 4,722.7 9,865.9 13,267.9 followed by earthquakes and wildfires, which to- %of GDP 0.2 0.7 1.4 1.9 gether account for 48 percent of total AEL (See Fig- Source: Authors, original data EM-DAT CRED and WRN ure A2.6). Figure A2.6. Annual Expected Losses for Malaysia Lao PDR Financial Risk Assessment by peril (US$ Millions) Annual expected losses total US$52.3 million, equiv- alent to 0.7 percent of GDP. Cyclones or tropical 32.1 storms are by far the most important natural hazard 51.7 n Earthquake affecting Lao PDR, alone accounting for US$52 mil- n Flood lion of the total AEL. Floods account for the remain- n Wildfire ing US$0.3 million (See Figure A2.5). 91.4 It is estimated that Lao PDR will experience losses of Source: Authors, original data EM-DAT CRED and WRN up to US$342.6 million as a consequence of natu- ral hazards once every 20 years, equivalent 4.6 per- Malaysia faces a 20-year PML of US$0.9 billion, cent of GDP. A more extreme 100-year event would equivalent to 0.4 percent of GDP. More extreme Annex 2. Financial Risk Assessment of ASEAN Member States < 95 > losses brought about by low-frequency, high-impact longer EM-DAT time series for the number of people events, such as large floods or earthquakes, can affected suggests that the 2008 Cyclone Nargis was generate losses of up to US$2.3 billion once in a a relatively severe event that seems unlikely to reoc- 100-year period and of up to US$3.2 billion once cur once every fifteen years. Due to data limitations every 200 years, equivalent to 1 percent and 1.4 per- the probable losses the country might experience as cent of GDP respectively. result of catastrophes are not reported in the analysis. Figure A2.7. Estimated Economic Losses for Figure A2.8. Annual Expected Losses for Myanmar Malaysia by peril (US$ Millions) 3,500 1.6 3,000 1.4 21.8 2,500 1.2 US$ Millions % of GDP 1.0 n Earthquake 2,000 0.8 1,500 n Storm 0.6 1,000 163.0 0.4 500 0.2 0 0.0 AEL 20-year 100-year 200-year Source: Authors, original data EM-DAT CRED and WRN Malaysia 174.6 953.8 2,332.7 3,242.1 %of GDP 0.1 0.4 1.0 1.4 Philippines Financial Risk Assessment Source: Authors, original data EM-DAT CRED and WRN As one of the top global disaster hot spots, the Phil- ippines faces US$1.6 billion annual expected losses Myanmar Financial Risk Assessment triggered by multiple natural hazards (See Figure A2.10). The most damaging peril affecting the Phil- Due to limited historical economic loss time series ippines is tropical storms or typhoons, which cause data and limited availability of simulated losses from annual expected losses of US$1.1 billion or 71 per- catastrophic probabilistic models, estimated AELs and cent of the country’s total AEL. Earthquakes or PMLs for Myanmar are unlikely to reflect the true risk seismic activity pose the second highest risk, with faced. However, an analysis of available historical annual expected losses of US$464.5 million or 29 data for Myanmar suggests that the annual expected percent of the total AEL. Other hazards impacting loss is approximately US$184.8 million, equivalent the country include floods, landslides, volcanic erup- to 0.9 percent of the country’s GDP. This figure has tions, and droughts. been calculated by multiplying the historical annual average loss incurred between 1996 and 2010, after Figure A2.9. Annual Expected Loss for the adjusting for price and exposure changes, of US$368 Philippines by peril (U.S. Millions) million, by an adjustment factor equal to the aver- 0.8 age number of people affected by natural hazards in Myanmar over the period 1963-2010 divided by n Earthquake 464.5 n Flood the average number of people affected by natural hazards in Myanmar between 1996-2010.This ad- 17.1 n Mass movement wet justment was made using EM-DAT data on people n Storm 1,119 affected adjusted to allow for changes in popula- 1.30 n Volcano tion over the period. The annual expected loss of US$184.8 million is lower than the historical average Source: Authors, original data EM-DAT CRED and WRN loss of US$368 million for 1996 to 2010 because the < 96 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States It is estimated that the Philippines experiences as 100-year earthquake event and as much as US$15 much as US$4.6 billion economic losses once every million as a consequence of a 200-year earthquake 20 years as a result of natural hazards. This 20-year event. Even a very extreme earthquake event occur- probable maximum loss represents a significant 2.3 ring once every 200 years would have relatively min- percent of the country’s GDP. More extreme events, imal economic consequences for Singapore, causing such as 100-year and 200-year disasters can have losses equivalent to less than 0.1 percent of GDP. devastating consequences for the Philippines, with This reflects both the country’s relatively low expo- estimated losses of up to 4.7 percent and 8.3 per- sure and its strong economic position. cent of the country’s GDP, respectively. A2.11. Estimated Economic Loss for Singapore Figure A2.10. Estimated Economic Losses for the 16 1.0 Philippines 14 0.9 0.8 12 0.7 US$ Millions 18,000 9 % of GDP 10 0.6 16,000 8 14,000 7 8 0.5 0.4 US$ Millions 12,000 6 6 % of GDP 0.3 10,000 5 4 0.2 8,000 4 2 0.1 6,000 3 0 0.0 4,000 2 AEL 20-year 100-year 200-year 2,000 1 Singapore 2.2 0.0 3.6 15.0 0 0 AEL 20-year 100-year 200-year %of GDP 0.0 0.0 0.0 0.0 Philippines 1,602.9 4,570.9 9,407.4 16,543.6 Source: Authors, original data EM-DAT CRED and WRN %of GDP 0.8 2.3 4.7 8.3 Source: Authors, original data EM-DAT CRED and WRN Thailand Financial Risk Assessment Thailand faces expected economic losses of Singapore Financial Risk Assessment US$255.6 million every year. These losses represent Singapore is one of the ASEAN Member States least less than 0.1 percent of the country’s GDP, and are exposed to natural hazards. No economic loss from mainly driven by floods and storms, which account natural hazards is reported by EM-DAT during the for 44 percent and 20 percent of total AEL respec- estimation period. Nevertheless, simulation losses tively. Earthquakes or seismic activity and droughts resulting from earthquake catastrophic models indi- are also highly damaging perils for Thailand, jointly cate that the country could potentially experience accounting for 36 percent of the country’s total AEL annual expected losses of US$2.2 million as a result (Figure A2.12). of seismic activity or earthquakes. However, this AEL is minimal in proportion to the country’s economy, Figure A2.12. Annual Expected Loss for Thailand and represents less than 0.1 percent of the country’s by Peril (U.S. Millions) GDP2. (Figure A2.11.) 50.3 50.9 n Drought It is estimated that Singapore will experience US$3.6 million in economic losses as a consequence of a n Earthquake 40.6 n Flood 113.7 n Storm 2 Figures in percentage terms are capped at 0.1 percent. When annual expected economic losses or probable maximum loss- es represent less than 0.1 percent of a country’s GDP, a “less than 0.1 percent” value is reported. Source: Authors, original data EM-DAT CRED and WRN Annex 2. Financial Risk Assessment of ASEAN Member States < 97 > It is estimated that Thailand will suffer US$1 billion counting for 29 percent and 19 percent of the AEL losses, equivalent to 0.3 percent of GDP, once in a (Figure A2.14). 20-year period. An extreme catastrophic event such as a 1-in-200 year storm will cause economic losses Figure A2.14. Annual Expected Losses for Viet of up to US$2.7 billion, equivalent to 0.8 percent of Nam by peril (U.S. Millions) the country’s GDP. 7.9 230.7 148.1 Figure A2.13. Estimated Economic Losses for n Drought Thailand n Earthquake 3,000 0.9 n Flood 399.9 n Storm 0.8 2,500 0.7 US$ Millions 2,000 0.6 % of GDP 0.5 1,500 Source: Authors, original data EM-DAT CRED and WRN 0.4 1,000 0.3 0.2 500 0.1 Viet Nam is estimated to incur economic losses of as 0 0.0 much as US$2.4 billion, equivalent to 2.4 percent of AEL 20-year 100-year 200-year GDP, as a result of natural disasters occurring once Thailand 255.6 1,000.0 2,222.6 2,696.8 every 20 years. For more extreme 1-in-100 events, %of GDP 0.1 0.3 0.7 0.8 such as a major storm or flood, the country is esti- Source: Authors, original data EM-DAT CRED and WRN mated to suffer losses of up to US$3.7 billion, equiv- alent to 3.6 percent of GDP. For even more severe There is an important caveat to Thailand´s financial catastrophic events occurring 1-in-200 years, the risk assessment relating to the scarcity of scientific estimated losses climb to US$4.2 billion, equivalent flood probabilistic models. The 2011 flooding in to 4.1 percent of the country’s GDP (Figure A2.15). Thailand tragically demonstrated the catastrophic potential of floods, with economic damages esti- Figure A2.15. Estimated Economic Losses for mated at US$22 billion, more than eight times the Viet Nam 200-year loss estimated for the country using the 4,500 4.5 current methodology. This finding points out the im- 4,000 4.0 3,500 3.5 precise assessment of flood risk in this report and US$ Millions 3,000 3.0 % of GDP highlights the need for the development of cata- 2,500 2.5 strophic flood models for the ASEAN region (See Box 2,000 2.0 1,500 1.5 2.3 for details). 1,000 1.0 500 0.5 0 0.0 Viet Nam Financial Risk Assessment AEL 20-year 100-year 200-year Viet Nam 786.4 2,488.5 3,718.2 4,249.0 As one of the most disaster-prone countries in the %of GDP 0.8 2.4 3.6 4.1 Asian-Pacific region, Viet Nam faces annual expect- ed economic losses of US$0.8 billion resulting from Source: Authors, original data EM-DAT CRED and WRN multiple natural hazards, including storms, floods, droughts, and earthquakes. Floods present the high- Regional Financial Risk Assessment est risk in the country, with an annual expected loss of US$399.7 million, or 51 percent of the total AEL, Every year, on average, the ASEAN region has ex- followed by storms and droughts, respectively ac- pected economic losses from natural disasters esti- < 98 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States mated at US$4.4 billion, equivalent to 0.2 percent Nam, Indonesia, Thailand, and Malaysia, face me- of regional GDP. Storms are the most serious haz- dium risk of natural disaster losses relative to GDP, ard impacting the region, with an annual expected with Indonesia facing highest relative risks for all re- loss of US$1.5 billion or 33 percent of the total AEL. turn periods, and Thailand following in rank for 400- Earthquakes or seismic activity are the second most year or less frequent relative losses. Lastly, Singapore costly events, with an AEL of US$1.2 billion or 27 faces a low risk of natural disaster losses as percent- percent of the regional AEL. Floods are in third place, age of its GDP for all return periods. presenting an AEL of US$1 billion, or 22 percent of the total AEL. Other important hazards causing eco- Figure A2.17. ASEAN Member States Disaster Risk nomic losses in the ASEAN region include droughts Profile and wildfires. 18 16 ASEAN Member States can be classified into three 14 risk groups according to their annual expected loss 12 as a percentage of national GDP: high risk countries % of GDP 10 comprising Myanmar, the Philippines, Viet Nam, Lao 8 PDR, and Cambodia; medium risk countries com- 6 prising Indonesia, Thailand, and Malaysia; and low 4 risk countries, namely Brunei Darussalam and Sin- 2 gapore. 0 0 50 100 150 200 250 300 350 400 450 500 Figure A2.16. Annual expected loss for ASEAN by Return Period (Years) peril (US$ million) Cambodia Indonesia Lao PDR Malaysia 246.9 Philippines Singapore Thailand Vietnam n Drought n Flood Source: Authors, original data EM-DAT CRED and WRN 1,036.2 n Forest Fire 0.4 Note: Loss exceedance probability as a percentage of national GDP. LEC n Mass movement dry are not computed for Brunei Darussalam and Myanmar due to limited 461.9 27.0 n Mass movement wet loss data. 1,210.0 0.8 n Volcano n Wildfire n Earthquake The ASEAN region can benefit from regional risk Source: Authors, original data EM-DAT CRED and WRN diversification. Figure A2.18 illustrates the ben- efits of risk pooling across countries and perils in the ASEAN region. The sum of 200-year probable ASEAN Member States can be further classified into maximum losses for ASEAN Member States totals three groups according to their risk across different US$42.1 billion without risk pooling. In comparison, probable maximum losses, thereby taking into con- the 200-year probable maximum loss with risk pool- sideration the risk of severe events (Figure A2.17). ing amounts to US$21.6 billion. This 48.5 percent High-risk countries as measured in terms of PML as reduction could translate into significant savings in a percentage of GDP include Lao PDR, Cambodia, the cost of risk transfer (e.g., insurance premiums) and the Philippines. These three countries have the if a regional pooled risk transfer mechanism, rather highest estimated economic losses as a percentage than a series of individual country mechanisms, is of GDP for 20-year return period or less frequent developed. losses. A second group of countries, comprising Viet Annex 2. Financial Risk Assessment of ASEAN Member States < 99 > Figure A2.18. Benefits of Regional Risk Pooling Figure A2.19. Estimated Economic Losses for the 45,000 ASEAN region n ASEAN n Malaysia 25,000.0 1.4 40,000 n Vietnam n Laos 1.2 20,000.0 n Thailand n Indonesia 1.0 US$ Millions 35,000 % of GDP 15,000.0 0.8 n Singapore n Cambodia 30,000 0.6 n Philippines 10,000.0 0.4 US$ Millions 25,000 5,000.0 0.2 20,000 0.0 0.0 AEL 20-year 100-year 200-year ASEAN 4,436.9 9,570.8 17,898.3 21,637.2 15,000 %of GDP 0.3 0.6 1.0 1.2 10,000 Source: Authors, original data EM-DAT CRED and WRN 5,000 0 Sum of 200-year PML Pool’s 200-year PML Source: Authors, original data EM-DAT CRED and WRN Taking the benefits of risk pooling, it is estimated that the ASEAN region will experience economic losses of up to US$9.6 billion, equivalent to 0.5 percent of regional GDP, as a result of natural disasters once ev- ery 20 years. More extreme natural events, such as catastrophes occurring once in 100 years or once in 200 years are estimated to incur regional economic losses of up to US$17.9 billion and US$21.6 billion, respectively, equivalent to 1 percent and 1.2 percent of regional GDP (See Figure A2.19). < 100 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Annex 3. World Bank Development Borrowers have access to financing in amounts Policy Loan with Catastrophe up to US$500 million or 0.25 percent of GDP Deferred Drawdown Option (whichever is less). The Cat DDO has a “soft”, as opposed to a “parametric” trigger, which means The World Bank’s Development Policy Loan with that funds become available for disbursement upon Catastrophe Deferred Drawdown Option (Cat DDO) the occurrence of a natural disaster resulting in the is a contingent credit line that provides immediate declaration of a state of emergency. liquidity to IBRD member countries in the aftermath of a natural disaster. It is part of a broad spectrum of The Cat DDO has a revolving feature; amounts World Bank Group disaster risk financing instruments repaid during the drawdown period are available for available to assist borrowers in planning efficient subsequent withdrawal. The three-year drawdown responses to catastrophic events. period may be renewed up to four times, for a total maximum period of 15 years. The Cat DDO helps develop a country’s capacity to manage the risk of natural disasters and should Pricing Considerations be part of a broader preventive disaster risk management strategy. The Cat DDO complements The Cat DDO carries a LIBOR-based interest rate that existing market-based disaster risk financing is charged on disbursed and outstanding amounts. instruments such as insurance, catastrophe bonds, The interest rate is the prevailing rate for IBRD loans reserve funds, etc. at time of drawdown. A front-end fee of 0.50 percent on the approved loan amount and a renewal In order to gain access to financing, the borrower fee of 0.25 percent also apply. must implement a disaster risk management program which the Bank will monitor on a periodic The Cat DDO provides an affordable source of basis. contingent credit for governments to finance recurrent losses caused by natural disasters. The expected net present value of the cost of the Cat Key Features DDO is estimated to be at least 30 percent lower The Cat DDO offers a source of immediate liquidity than the cost of insurance for medium risk layers that can serve as bridge financing while other (that is, a disaster occurring once every three years). resources (e.g. concessional funding, bilateral aid This cost saving can be even higher when the or reconstruction loans) are being mobilized after country’s opportunity cost of capital is greater. a natural disaster. The Cat DDO ensures that the government will have immediate access to financing following a disaster, which is when a government’s post-disaster liquidity constraints are at their highest. Annex 3. World Bank Development Policy Loan with Catastrophe Deferred Drawdown Option < 101 > Major Terms and Conditions of the Catastrophe Risk Deferred Drawdown Option To enhance/develop the capacity of borrowers to manage catastrophe risk. Purpose To provide immediate liquidity to fill the budget gap after a natural disaster. To safeguard on-going development programs. Eligibility All IBRD-eligible borrowers (upon meeting pre-approval criteria) Appropriate macroeconomic policy framework Pre-approval criteria The presentation of existence of a disaster risk management program. Loan Currency EUR, JPY and USD Up to the full loan amount is available for disbursement at any time within three years from loan signing. Drawdown Drawdown period may be renewed up to a maximum of four extensions. Must be determined upon commitment and may be modified upon drawdown while prevailing maturity policy Prepayment Terms limits. Like regular IBRD loans, the lending rate consists of a variable rate plus a spread. The lending rate is reset semi- annually, on each interest payment date, and applies to interest periods beginning on those dates. The base rate is Lending Rate the value of the 6-Month LIBOR at the start of an interest period for most currencies, or a recognized commercial bank floating rate reference for others. The prevailing spread, either fixed or variable, for regular IBRD loans at the time of each drawdown. 1. Fixed for the life of the loan: Consists of IBRD’s projected funding cost margin relative to LIBOR, plus IBRD’s contractual spread of 0.50%, a risk premium, a maturity premium for loans with average maturities greater than 12 years, and a basis swap adjustment for non-USD loans. Lending Rate Spread 2. Variable resets semi-annually: Consists of IBRD’s average cost margin on related funding relative to LIBOR plus IBRD’s contractual spread of 0.50% and a maturity premium for loans with average maturities greater than 12 years. The variable spread is recalculated on January 1 and July 1 of each year. The calculation of the average maturity of DDOs begins at loan effectiveness for the determination of the applicable maturity premiums, but at withdrawal for the remaining components of the spread. Front-End Fee 0.50% of the loan amount is due within 60 days of effectiveness date; may be financed out of the loan proceeds. Renewal Fee 0.25% of the undisbursed balance. Currency, Conversions, Same as regular IBRD loans. Interest rate, Conversions Caps, Collars, Payment Dates, Conversion Fees, Prepayments Country Limit: Maximum size of 0.25% of GDP or the equivalent of US$500 million, whichever is smaller. Limits for small states are considered on a case-by-case basis. Other Features Revolving Features: Amounts repaid by the borrower are available for a drawdown, provided that the closing date has not expired < 102 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Annex 4. Mexican Natural Disaster The Fund for Natural Disasters Fund FONDEN (FONDEN) Mexico is highly exposed to multiple natural hazards Despite developing an institutional approach to di- and has a long history of disaster events. Located sasters, all levels of government in Mexico were still along the world’s “ring of fire,” where 80 percent of initially required to reallocate funding intended for the world’s seismic and volcanic activity takes place, planned capital investments to post-disaster recon- Mexico is a seismically active country. It is also located struction on a relatively regular basis, as and when in one of the few regions of the world that can be disasters occurred. These reallocations resulted in affected simultaneously by two independent cyclone delays and a scaling back of development initia- regions, the North Atlantic and the North Pacific re- tives and provided a relatively slow means of fund gions. Around 40 percent of Mexico’s territory and disbursement for recovery. In response, legislation a total of 31.3 million people are exposed to storms, was therefore passed in 1994 requiring federal, hurricanes, and floods. Climate change is expected state, and municipal assets to be privately insured. to contribute to an increase in both the frequency In 1996, the government went a stage further and and severity of hydrometeorological hazards. created the Fund for Natural Disasters (FONDEN) in the Ministry of Finance. To address its vulnerability to adverse natural events, Mexico has developed a comprehensive institutional FONDEN is a disaster risk financing and insurance approach to natural disasters. Following two dev- vehicle. Its main purpose is to provide immediate fi- astating earthquakes in 1985, resulting in 6,000 nancial support to federal agencies and local govern- deaths and direct losses in excess of US$4 billion, ments recovering from a disaster for: (i) emergency the Federal Government of Mexico established a Na- assistance; (ii) reconstruction of public infrastructure tional System of Civil Protection (Sistema Nacional (including restoration of forestry and other natural de Protección Civil - SINAPROC) in 1986 as the main resources); and (iii) reconstruction of low income mechanism for inter-agency coordination of disas- homes. FONDEN is also responsible for carrying out ter efforts. SINAPROC provides an organized group studies on risk management and contributing to the of civil protection structures, functional relations, design of risk transfer instruments. methods, and procedures involving all levels of gov- ernment and engaging with the private sector and Main Features of FONDEN non-governmental and civil society organizations. Responsibility for SINAPROC rests with the Ministry FONDEN was originally established as a budgetary of the Interior. tool through which federal funds were annually al- located for expected expenditure on post-disaster A National Center for Disaster Prevention (Centro response. In 1999, a catastrophe reserve fund, Nacional de Prevención de Desastres - CENAPRED) known as the FONDEN Trust Fund, was also estab- was established as well as the technical arm of civil lished through which any unspent portion of this protection and, again, located within the Ministry annual budgetary appropriation could be accumu- of the Interior. CENAPRED’s primary objective is to lated. Disaster losses occurring as a consequence promote the application of technologies for the pre- of geophysical perils including earthquake, volcanic vention and mitigation of disasters, provide techni- eruption, tsunami, landslide and hydrological perils cal training, and disseminate and promote prepared- including drought, hurricane, excess rainfall, hail ness and self-protection measures amongst at-risk storm, flood, tornado, wildfire are eligible for FON- populations. It also provides technical confirmation DEN support. of the occurrence of hazard events. Annex 4. Mexican Natural Disaster Fund FONDEN < 103 > Since 2006 the Federal Government has been re- State governments finance the remaining 50 quired by law to allocate no less than a total 0.4 percent of these reconstruction costs. percent of the annual federal budget to FONDEN together with a disaster prevention fund and an ag- ■■ FONDEN Trust: This Trust Fund manages ricultural fund for natural disasters (net of the un- FONDEN’s financial resources for approved committed funds remaining in the FONDEN Trust activities. It also acts as the contracting au- at the end of the previous fiscal year). Should this thority for risk transfer mechanisms, includ- appropriation be insufficient, the law stipulates that ing insurance and catastrophe bonds. additional resources must be transferred from other These instruments are governed by clear rules of government programs and funds, such as the oil operation and continuous changes are made to revenue surplus. enhance their efficiency and effectiveness. In 2009 a new financing mechanism known as ‘Immediate FONDEN is based on three complementary instru- Partial Support’ (Apoyos Parciales Inmediatos - APIN) ments: the Revolving Fund, the FONDEN Program was introduced under FONDEN’s Program for Recon- and the FONDEN Trust Fund. The first provides mon- struction. This mechanism provides partial financial ies for disaster relief efforts, the second supports re- support immediately following a disaster to meet construction of infrastructure and the third manages urgent needs while the full damage assessment Mexico’s catastrophe risk financing strategy. and fund approval process is undertaken. Following devastating floods in 2010, a new Reconstruction ■■ Revolving Fund: This fund finances emergen- Fund for Local Entities (Fondo de Reconstrucion de cy supplies to be provided in the immediate Entidades Federativas) was also created to provide aftermath of a natural disaster, for instance additional support to local entities. This Fund of- relating to shelter, food and primary health fers zero-coupon lines of credit to local entities to care. In the event that there is high probabil- help cover reconstruction costs. At the end of the ity of a disaster occurring, or imminent dan- 20-year credit period, eligible states pay the interest ger, local governments can declare a situa- on the loan principal and the Fund repays the prin- tion of emergency and obtain resources from cipal. FONDEN’s role within Mexico’s wider national FONDEN immediately. Doing so allows local system of civil protection is indicated in Figure A4.1. governments to prepare for immediate relief needs. FONDEN’s Institutional Structure ■■ FONDEN Program: This program finances the reconstruction and restoration of public in- FONDEN is a trust located within the Civil Protection frastructure (owned by municipalities, state Unit of the Ministry of the Interior, as indicated in governments, and the Federal Government), Figure A4.2. A federal FONDEN Trust Technical Com- natural areas, and private dwellings of low- mittee approves the allocation of FONDEN resources income households following a natural disas- for specific activities and monitors their implemen- ter. It supports the full cost of reconstruction tation. The committee is chaired by the Ministry of of eligible federal infrastructure and manag- Finance and is composed of members from the Min- es the reconstruction efforts through the rel- istry of the Interior, Ministry of Civil Service and the evant federal agencies. It also provides up to FONDEN Trust. Mexico’s national development bank 50 percent of the total cost of reconstruction for public works and services, Banobras, acts as a of eligible state infrastructure, with related fiduciary agent and trustee of the FONDEN Trust. activities executed by the federal entities re- sponsible for each of the affected sectors. < 104 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Figure A4.1. Role of FONDEN’s Instruments in Mexico’s National System of Civil Protection Occurrence of Natural Disaster Emergency and Disaster Disaster Prevention Response and Reconstruction (Ex ante) (Ex post) Years to Days Hours, Weeks, Days Days, Weeks, Months Timeframes Before Disaster After Disaster After Disaster Instruments IMMEDIATE FUND/ FONDEN PROGRAM FOR NEW RECONSTRUCTION FOPREDEN REVOLVING FUND RECONSTRUCTION FUND FOR LOCAL ENTITIES FONDEN TRUST Activities Support to the Resources for Affected Population Reconstruction All federal plans and programs are activated for disaster reponse FONDEN Source: FONDEN (2011). Figure A4.2. Flow Chart of the Civil Protection System in Mexico President of Mexico National Council for Civil Protection Ministry of the Interior (SEGOP) General Coordination of Civil Protection General Directorate of the General Directorate National Center for Natural Disaster Fund (FONDEN) of Civil Protection Disaster Protection State Civil Municipal Civil Protection System Protection System State Council Municipal Council of Civil Protection of Civil Protection Internal Civil Protection Units in Various State Civil Municipal Civil Departments and Agencies Protection Unit Protection Unit (including public/private sectors and society) Mexican Population Source: Authors, from Mexican Civil Protection (2010). Annex 4. Mexican Natural Disaster Fund FONDEN < 105 > FONDEN Program of effort among the federal and state entities; (ii) verify that the requested resources only cover The FONDEN Program is intended to support federal the damage caused by the disaster (and not pre- and local government entities whose financial ca- existing damage); (iii) verify that any items of un- pacity has been overwhelmed by disaster relief and insured damaged infrastructure have not previ- reconstruction needs. Local and federal authorities ously received any reconstruction financing from must follow a set procedure in order to access FON- FONDEN and, if they have, apply lower levels of DEN resources. This procedure entails six main steps financial support in accordance with FONDEN’s and should be completed within 23 days of the oc- predetermined procedure for such eventualities; currence of a disaster: and (iv) develop and submit to the Ministry of 1. Within three days, a specialized federal agency Finance a consolidated request for resources for (the National Water Commission in the event of all damaged sectors, including the Ministry of hydrometeorological phenomena; the National the Interior’s opinion on whether the applica- Forestry Commission in the event of forest fires; tions comply with FONDEN’s requirements for and the National Center for Disaster Prevention resource authorization. in the event of geological phenomena) certifies 6. Within a further five days, a meeting of the the occurrence of a natural disaster and informs FONDEN Technical Committee is convened to the relevant state government. authorize the resources for post-disaster recon- 2. Within four days of the occurrence of the disas- struction and its authorization submitted to the ter, the government sets up a technical commit- Ministry of Finance. The FONDEN Trust Techni- tee comprised of federal and state government cal Committee reviews and transfers approved representatives to identify and assess the dam- funds from the FONDEN Program for Recon- age. Once the Damage Assessment Committee struction federal budget line to the FONDEN is installed, sector sub-committees and agencies Trust. Banobras, FONDEN’s fiduciary agent, may request Immediate Partial Support (APIN) to makes payments from the FONDEN Trust directly finance urgent needs relating to the restoration to the accounts of the relevant public works of communications and lifeline infrastructure. contractors and/or suppliers and providers of Approved resources should be authorized by the goods and services for and on behalf of the ex- Ministry of Finance within 24 hours of the re- ecuting agencies, based on directions received ceipt of requests. from the FONDEN Trust Technical Committee, as indicated in Figure A4.3. 3. Within 10 days following technical confirma- tion that a disaster has occurred, the damage assessment committee presents its findings to FONDEN risk transfer instruments the Directorate General of FONDEN, including In recognition of its considerable contingent fiscal itemized reconstruction and ‘build back better’ liability for disaster losses, the Federal Government needs and related costs. has empowered FONDEN to develop a catastrophe 4. Within 15 days from the occurrence of the di- risk financing strategy to leverage its resources, rely- saster, the Ministry of the Interior issues a dec- ing on a layered combination of risk retention and laration of state of natural disaster. The Ministry risk transfer instruments. FONDEN’s operational of Finance can thereafter approve FONDEN re- manual was modified to allow the FONDEN Trust to sources. transfer risk to the reinsurance and capital markets in 2005, with the insurance premium being defined 5. Within a further two days, the Ministry of Inte- as a service in the government budget law. A va- rior should: (i) verify that there is no duplication < 106 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Figure A4.3. FONDEN’s Resource Allocation Process for Post-Disaster Reconstruction Mexico’s Federal Budget (approved as line 23 of annual budget for fiscal year January 1 – December 31) Additional sub-accounts FONDEN Program Sub-accounts created created for each for Reconstruction for each disaster FONDEN TRUST affected sector (Managed by Banobras*) $$ Other Federal Agencies $$ Requesting $$ Federal Agencies n CONAGUA n CONAFOR n CENAPRED REVOLVING FUND n SCT, SSA, SEP (For emergency support n SEDESOL to the affected population) Requesting State Service Munipalities FOPREDEN Governments providers (For prevention) implementing works Unused Funds Returned to FONDEN Trust Source: Authors, from Mexican Civil Protection (2010). riety of instruments have been developed and ap- Trust places its excess risk with the public insurer plied to transfer disaster risk, involving the strategic Agroasamex, which in turn passes it on to the inter- use of insurance and catastrophe bond options. In national reinsurance and capital markets. 2006, FONDEN issued the world’s first government catastrophe bond, Cat MEX, providing cover against The FONDEN Disaster Risk Financing earthquakes in three specific zones of the country. Strategy for 2011 The Mexican Government has been able to develop sophisticated private financial instruments in part FONDEN’s disaster risk financing strategy as of 2011 because of its strong institutional capacity and its is illustrated in Figure A4.5. The bottom layer of risk, high level of access to global capital markets. The up to US$1 billion, is retained by FONDEN though Federal Government also promotes the private in- its annual budget appropriation and, if necessary, by surance of specific federal and state government an exceptional additional federal budget allocation. assets, thereby reducing financial dependence on The US$400 million layer in excess of this US$1 bil- FONDEN in the event of a disaster. lion is covered through an indemnity-based reinsur- ance policy on the whole FONDEN portfolio. Should The financial structure of the FONDEN Trust is de- total reconstruction costs exceed US$1.4 billion, picted in Figure A4.4. Banobras acts as the Trust’s these excess losses are financed through a further account manager, as already noted. The FONDEN exceptional budget allocation. FONDEN also has a Annex 4. Mexican Natural Disaster Fund FONDEN < 107 > Figure A4.4. Financial Structure of FONDEN Placement of insurance and Management risk transfer products of the trsut fund (e.g., cat bonds) Agroasemex FONDEN Banobras Reinsurance/capital markets Source: FONDEN 2010. catastrophe bond, MultiCat Mexico, in place to pro- ket. Reinsurance payouts are based on the losses vide immediate liquidity should a major earthquake borne by the Federal Government as reported to and/or hurricane occur in pre-defined areas of the FONDEN (that is 100 percent of the damage to fed- country. eral assets and 50 percent of the damage to state/ municipal assets and low-income housing). Only the This is the first time that the Mexican Government replacement costs, which on average represent 75 has placed an indemnity-based excess-of-loss rein- percent of total reconstruction costs, are covered by surance treaty on the international reinsurance mar- the reinsurance treaty. Figure A4.6. FONDEN Disaster Risk Financing The multi-peril cat bond, MultiCat Mexico, was is- Strategy of the Federal Government in 2011 sued in 2009 using the World Bank’s newly es- Low frequency tablished MultiCat Program after the earlier 2006 Mexico MultiCat high severity FONDEN Retention event CatMex matured. This new US$290 million, four- Bond US$ 290 (Exceptional budget allocation) million tranche cat bond with a three-year maturity further diversifies the coverage provided by the 2006 Cat- Mex by pooling multiple risks in multiple regions. Indemnity-based Reinsurance US$ 400 million It provides binary parametric insurance to FONDEN against earthquake risk in three regions around FONDEN Retention Mexico City and against hurricanes on the Atlantic Exceptional budget allocation US$ 200 million and Pacific coasts. For the continued earthquake cover, trigger levels were reduced to include more events and the zones covered extended in order to protect a larger population. In the event of a disas- FONDEN Retention (Annual budget allocation ter, an insurance claim will be triggered if an official US$ 800 million) High declaration of a state of emergency is issued by the frequency Ministry of the Interior and certain other criteria are low severity event also met. The principal will be repaid to investors if no claims are triggered over the life of the bond. Note: The Mexico MultiCat bond covers only earthquakes in three zones The cost of the bond tranches are between 2.5 and and hurricanes in three zones. 4.3 times the expected loss. See Annex 5. Source: Disaster Risk Financing and Insurance Program, GFDRR and FCMNB, 2011 < 108 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Annex 5. Catastrophe Bonds in budgets by transferring extreme natural disaster Mexico risks to capital markets, obviating the need to build up excessive budget reserves. FONDEN uses various instruments to support fed- eral and local governments and entities in respond- Operating structure ing to natural disasters, including reserve funds and risk transfer solutions. In 2006, FONDEN issued a Mexico issued a four-tranche cat bond (totaling US$160 million catastrophe bond (CatMex) to trans- US$290 million) with a three-year maturity under fer Mexico’s earthquake risk to the international the MultiCat Program. The issuer is a Special Pur- capital markets. It was the first parametric cat bond pose Vehicle (SPV) that indirectly provides paramet- issued by a sovereign entity. ric insurance to FONDEN against earthquake risk in three regions around Mexico City and hurricanes on After the CatMex matured in 2009, Mexico decided the Atlantic and Pacific coasts. The cat bond will re- to further diversify its coverage by pooling multiple pay the principal to investors unless an earthquake risks in multiple regions. In October 2009, it issued or hurricane triggers a transfer of the funds to the a multi-peril cat bond using the World Bank’s newly Mexican government. established MultiCat Program, which helps sover- eign and sub-sovereign entities pool multiple perils The SPV structure is displayed in Figure A5.1 and the in multiple regions and reduce insurance costs. institutional arrangements are described below: 1. FONDEN enters into an insurance contract with Objective local insurance company Agroasemex. The purpose of a MultiCat Program is to transfer di- 2. Agroasemex enters into a reinsurance contract saster-related risks, covering multiple hazards, to the with Swiss Re to transfer all of the catastrophe capital markets in order to reduce pressure on public risk. budgets. Doing so ensures that adequate funds are in place for relief activities. 3. Swiss Re enters into a derivative counterparty contract with a Cayman Islands-based special purpose vehicle (MultiCat Mexico 2009 Ltd.) to Outcome transfer the catastrophe risk. The bond was oversubscribed, with broad distri- 4. The SPV issues floating rate notes (cat bonds) to bution among investors. With this bond, Mexico capital market investors to hedge its obligations transferred a pool of disaster risk to the market for to Swiss Re under the counterparty contract. The the first time; secured multi-year protection for the proceeds received from investors are invested in covered risks at a fixed price; and reduced poten- US Treasury money market funds and deposited tial pressure on public budgets. Mexico effectively in a collateral account. locked in funding for disaster relief prior to the oc- 5. A separate event payment account is established currence of an event, rather than relying only on with a third party bank to allow FONDEN to re- public budgets after an event. ceive parametric loss payments directly from the SPV, subject to the insurance contract. The demonstration effect of this transaction for oth- er emerging market countries is significant. It has paved the way for other highly exposed countries to manage fiscal volatility and stabilize government Annex 5. Catastrophe Bonds in Mexico < 109 > Figure A5.1. Financial Structure of MultiCat Mexico 5 Loss Payment Event Loss Payment Collateral Amounts Payment Amounts Solution Account Investment Investments Earnings Reference Rate + Interest Swiss SPV 1 2 3 Spread Reinsurance FONDEN Agroasemex Company 4 Investors Insurance Reinsurance Counterparty Collateral Contract Contract Ltd. Contract Account (Zurich) Note Proceeds Lessons Learned 3. The availability of data and statistics concern- ing the probability and severity of a catastrophic 1. Countries need to have a strong legal and in- event is critical. New countries and regions at- stitutional framework in place for disaster risk tempting to tap the catastrophe bond market financing to facilitate the implementation of risk will need a supporting cat risk model. Donor transfer mechanisms, which should be part of a countries with a specific interest in the develop- disaster risk management framework. ment of disaster risk management capacity in 2. There is potential to replicate this type of trans- developing countries can play an important part action for other middle-income countries. The by financing risk modeling and transaction costs. Mexico bond was significantly oversubscribed, 4. The World Bank’s role as arranger significantly proving that investors continue to exhibit strong increased investor comfort. Future transactions appetite for non-peak risks. will benefit from the standardized fees and de- sign structure offered by the MultiCat Program. Table A5.1. Summary of Terms: Mexico MultiCat 2009 Class A Class B Class C Class D Peril Earthquake Pacific Hurricane Pacific Hurricane Atlantic Hurricane Notional (US$ million) 140 50 50 50 S&P rating B B B BB- Maturity October 2012 October 2012 October 2012 October 2012 Interest Spread 11.50% 10.25% 10.25% 10.25% (over US Treasury Money Market Fund) Expected loss 4.65% 4.07% 4.22% 2.39% Multiple 2.47 2.52 2.43 4.29 Source: FONDEN. < 110 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Annex 6. Caribbean Catastrophe Risk their own reserves or if they were to independently Insurance Facility purchase insurance in the open market. On average, one to three Caribbean countries are Structure and Description affected by a hurricane or an earthquake each year, although during severe hurricane seasons this num- CCRIF functions as a mutual insurance company con- ber can climb much higher. In 2004, the region suf- trolled by participating governments. It was initially fered a disastrous hurricane season, with 15 named capitalized by the participating countries, with sup- storms. Hurricane Ivan, the strongest storm of the port from donor partners. A portion of the pooled season, wrought devastation on the Cayman Is- risks is retained through reserves, which reduces the lands, Grenada, and Jamaica. In Grenada, 89 per- cost of insurance premiums. CCRIF transfers the cent of the country’s housing stock and more than risks it cannot retain by purchasing reinsurance and 80 percent of its public and commercial building catastrophe swaps. structures sustained damage. The damage was esti- mated at over US$800 million, equivalent to approx- The coverage provided by the Facility is parametric imately 200 percent of Grenada’s GDP. The Heads of in nature. Unlike traditional insurance settlements Government of the Caribbean Common Market and that require an assessment of individual losses on Community (CARICOM) were compelled by their ex- the ground, parametric insurance relies on a pay- periences during this catastrophic season to ask for out disbursement contingent on the intensity of an World Bank assistance in improving access to catas- event (e.g., wind speed, ground acceleration). In the trophe risk insurance. case of CCRIF, payouts are proportional to the esti- mated impact of an event on each country’s budget. The estimated impact is derived from a probabilistic Objectives catastrophe risk model developed specifically for the The main objective of the Caribbean Catastrophe Facility. Risk Insurance Facility (CCRIF) is to provide its mem- bers with access to affordable and effective coverage Insured countries pay an annual premium commen- against natural disasters. For a number of reasons, surate with their own specific risk exposure and re- small island states have difficulty absorbing the fi- ceive compensation based on the level of coverage nancial impacts of disasters, including that: i) limited agreed upon in the insurance contract upon the oc- budgetary capacity prevents them from establishing currence of a triggering event. sufficient financial reserves; ii) cross-regional subsidi- zation of recovery efforts is generally impossible due Outcome to their limited size and economic diversification; iii) high debt levels limit their access to credit after di- CCRIF is the first-ever multi-country risk pool. Six- sasters; and, iv) access to catastrophe insurance is teen Caribbean countries joined in 2007 and have limited due to the high transaction costs resulting renewed their policies each year since. Seven pay- from the relatively small level of business brought outs have been made to date (see below for CCRIF into these markets. members and payouts). CCRIF has been well re- ceived by the reinsurance market, which has pro- CCRIF enables countries to pool their individual risks vided capacity at a low rate to the Facility. A US$20 into a single, better diversified, joint reserve mecha- million cat swap between IBRD and CCRIF was the nism. Through risk pooling, CCRIF provides coverage first derivative transaction to enable emerging coun- to countries at a significantly lower cost than individ- tries to access the capital market to insure against ual governments would incur if they had to maintain natural disasters. Annex 6. Caribbean Catastrophe Risk Insurance Facility < 111 > Lessons Learned ticipate in the Facility. Furthermore, CCRIF carries administrative costs that are shared by partici- 1. CCRIF addresses one disaster risk financing need pants; a significant number of participants are of small island states: access to immediate li- required to maintain an affordable average ad- quidity in the aftermath of a disaster. CCRIF does ministrative cost per country. not cover all losses that a country may incur; in- 3. Dialogue on risk financing can enhance discus- stead it covers estimated liquidity needs for the sions with decision makers on more compre- first three to six months after a major catastro- hensive disaster risk management. Risk model- phe. When designing a disaster risk financing ing developed for risk financing products can strategy, it is important to understand that each provide useful information on the risk exposure country requires a tailored combination of disas- of the analyzed economy. This information and ter risk financing tools. There is neither a “one related dialogue on financial protection can help size fits all” strategy nor a “silver bullet” disaster sensitize decision makers to the need for more risk financing tool. comprehensive strategies to deal with losses 2. A critical mass of country participation in CCRIF is from adverse natural events, including actions required for the Facility to benefit from risk pool- to try to avoid the creation of new risks (e.g., ing and diversification. In order for Caribbean territorial planning, building standards) and to countries to benefit from diversification through reduce existing risks (e.g., protective measures, risk pooling (e.g., joint reserves and improved strengthening of infrastructure). reinsurance rates), enough countries must par- CCRIF Member Countries Payout to Date (USD in millions) Anguilla Grenada 8.5 to Barbados (2010) Antigua & Barbuda Haiti 3.2 to St. Lucia (2010) Bahamas Jamaica 1.1 to St. Vincent & the Grenadines Barbados St. Kitts and Nevis 4.2 to Anguilla (2010) Belize St. Lucia 7.8 to Haiti (2010) Bermuda St. Vincent and the Grenadines 6.3 to Turks & Caicos Islands (2010) Cayman Islands Trinidad & Tobago 1 to Dominica (2007) Dominica Turks & Caicos Islands 1 to St. Lucia (2007) < 112 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Annex 7. Turkish Catastrophe functions outsourced to the private sector. TCIP pur- Insurance Pool chases commercial reinsurance and the Government of Turkey acts as a catastrophe reinsurer of last resort Bridging the contents of Europe and Asia, Turkey is for claims arising out of an earthquake with a return highly exposed to severe earthquakes. Despite their period of greater than 300 years. The full capital risk common occurrence, Turkey’s private insurance mar- requirements for TCIP are funded by commercial re- ket was previously unable to provide adequate capac- insurance (currently in excess of US$1 billion) and its ity for catastrophe property insurance against earth- own surplus capital (about US$0.5 billion). quake risk. Without adequate commercial protection of residential buildings, the Government of Turkey The TCIP policy is a stand-alone property earthquake faced a significant contingent financial exposure in policy with a maximum sum insured per policy of post-disaster reconstruction of private property. US$65,000, an annual average premium rate of US$46 and a 2 percent of sum insured deductible. In the aftermath of the Marmara earthquake in Premium rates are based on the construction type 2000, the government worked to limit its financial (2 types) and property location (differentiating be- exposure to earthquake risk in the residential hous- tween 5 earthquake risk zones) and vary from less ing market through the establishment of the Turkish that 0.05 percent for a concrete reinforced house in Catastrophe Insurance Pool (TCIP). This pool enables a low risk zone to 0.60 percent for a house located the Government of Turkey to ensure that owners in the highest risk zone. who pay property taxes on domestic dwellings can purchase affordable and cost-effective earthquake TCIP sold over 3 million policies at market-based pre- coverage. In doing so, the government’s contingent mium rates (i.e., 23 percent penetration) in 2009, a fiscal exposure to earthquakes is decreased by trans- considerable advance on the 600,000 covered house- ferring risk to the international reinsurance markets, holds when the pool was established. To achieve this thereby reducing pressure to provide post disaster level of penetration, the government invested heavily housing subsidies. in insurance awareness campaigns and made earth- quake insurance compulsory for home-owners on TCIP is a public sector insurance company which is registered land in urban centers. The legal framework managed on sound technical and commercial insur- for the program envisages compulsion enforcement ance principles. The Pool operates as a genuine pub- mechanisms in urban settings, while coverage is vol- lic-private partnership with most, if not all, operational untary for homeowners in rural areas. Figure A7.1 Operational Structure of the TPIC Board Governance and key operating decisions GDI TCIP Pool Manager Treasury policy, oversight, Risk assumption and Information systems and and implementation receive accumulation reinsurance claims Insurers Distribution Annex 8. Pacific Catastrophe Risk Assessment and Financing Initiative < 113 > Annex 8. Pacific Catastrophe Risk The PCRAFI has developed a Pacific Risk Information Assessment and Financing Initiative System (PRIS) (including a regional geospatial data- base and country-specific catastrophe risk models), The Pacific Catastrophe Risk Assessment and which offers technical tools for the development of Financing Initiative (PCRAFI) is a joint initiative sustainable and affordable disaster risk financing between the Secretariat of the Pacific Community and insurance solutions for the PICs. SPC/SOPAC, the World Bank, and the Asian Devel- opment Bank, with financial support from the Gov- The PCRAFI initiative has established the larg- ernment of Japan and the Global Facility for Disaster est collection of geospatial information for the Reduction and Recovery (GFDRR). The initiative aims PICs; the Pacific Risk Information System. PRIS to increase the resilience of Pacific Island Countries contains detailed, country-specific information on to natural disasters through the application of tools assets, population, hazards, and risks. The exposure and strategies for disaster risk management. database leverages remote sensing analyses, field visits, and country specific datasets to character- The average annual direct loss caused by natu- ize buildings (residential, commercial, and indus- ral disasters in the South Pacific region is esti- trial), major infrastructure (such as roads, bridges, mated at US$284 million. State of the art catastro- airports, and electricity), major crops, and popula- phe risk models have been developed as part of the tion. More than 500,000 buildings were digitized PCRAFI to assess the economic and fiscal impact of from very-high-resolution satellite images, repre- natural disasters (including earthquakes, tsunamis, senting 15 percent (or 36 percent without PNG) of and tropical cyclones) in the fifteen Pacific Islands the estimated total number of buildings in the PICs. Countries (PICs).51 In particular, these models esti- About 80,000 buildings and major infrastructure mate the economic losses caused by natural disas- were physically inspected. In addition, about 3 mil- ters with different return periods (e.g., frequency of lion buildings and other assets, mostly in rural ar- occurrence). See Figure A8.1. eas, were inferred from satellite imagery. PRIS also includes the most comprehensive regional historical Figure A8.1. Pacific Island Country Disaster Risk hazard catalogue (115,000 earthquake and 2,500 Profile tropical cyclone events) and historical loss database 120% for major disasters, as well as country-specific haz- COO ard models that simulate earthquakes (both ground FIJ 100% shaking and tsunamis) and tropical cyclones (wind, FSM 80% KIR storm surge, and excess rainfall). In peer-reviewing MAR NAU the models, Geoscience Australia described them as 60% NIU “high standard, thorough and representative of best PAL 40% PNG practice.” PRIS contains risk maps showing the geo- SAM graphic distribution of potential losses for each PIC SOL 20% TIM as well as other visualization products of the risk as- 0% TON sessments. These can be accessed, with appropriate TUV 0 50 100 150 200 250 authorization, through an open-source web-based VAN Return period (years) platform. The Pacific Island Countries covered under PCRAFI are: Cook 51 Building on PRIS, applications will be developed with Islands, Federate States of Micronesia, Fiji, Kiribati, Marshall the PICs under the PCRAFI. Some applications are Islands, Nauru, Niue, Palau, Papua New Guinea (PNG), illustrated on Figure A8.2 and described below. Samoa, Solomon Islands, Timor Leste, Tonga, Tuvalu, and Vanuatu. < 114 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Figure A8.2. PRIS Application 2. Mainstreaming risk information into urban and infrastructure planning. PRIS en- Benefits to Pacific Island Countries sures that disaster risk and climate change informa- tion and considerations form an integral part of the urban and infrastructure planning process. Application 1 Application 2 Application 3 Application 3. Rapid post-disaster damage es- timation. In the immediate aftermath of a disaster, Macro economic planning and Rapid post-disaster damage PRIS provides disaster managers and first responders Urban and infrastructure Disaster Risk Financing with the tools and information to quickly gain an overview of areas and population affected and the estimation planning likely severity of the event in terms of potential fa- talities, injuries and building, infrastructure and crop damage. The development objective of the Pacific Disas- ter Risk Financing and Insurance Program is to System System System increase the financial resilience of the Pacific update update update island countries (PICs) against natural disasters and to improve their capacity to meet post-disaster Pacific Risk Information System funding needs without compromising their fiscal Hazard and Exposure Databases and Risk Modelling balances and development objectives. It aims to as- in 15 Countries sist the PICs in the improvement of their macroeco- nomic planning against natural disasters, and the design and implementation of a national disaster risk financing strategy, as part of their national disas- Application 1. Macro-economic planning and ter risk management and climate change adaptation disaster risk financing. PRIS assists the PICs in agenda. The program supports the following activi- the improvement of their macro-economic planning ties: (i) capacity building on integrated disaster risk against natural disasters. It also helps the PICs to de- financing and insurance; (ii) development of private velop an integrated disaster risk financing strategy, disaster risk insurance markets; and (iii) piloting of relying on an optimal combination of reserves, con- the Pacific disaster risk insurance program for gov- tingent credit, insurance, and donor grants. ernments. Annex 9. Probabilistic Catastrophe Modeling < 115 > Annex 9. Probabilistic Catastrophe Independent third party vendor Modeling models: Probabilistic catastrophe risk modeling was originally The table below details ‘off-the-shelf’ model avail- developed by the insurance industry to assess the ability from the three largest independent third-party risk of a portfolio of assets and to price insurance catastrophe model vendors. For the perils of earth- contracts. The technique is increasingly used by gov- quake and typhoon, all models explicitly capture the ernments to assess their exposure to adverse natural principal loss agents of wind damage for typhoon events and by regulators to implement risk-based and ground motion for earthquake. Treatment of supervision of insurers and reinsurers underwriting additional loss agents varies as follows52: catastrophe risk. ■■ Tsunami following earthquake is not mod- Access to catastrophe risk models is limited in the eled by any vendor. ASEAN region. The principal model sources are: ■■ Rainfall-induced-flooding from typhoon is modeled by both vendors providing typhoon ■■ Independent third-party vendor modeling modeling in the region. firm ‘off the shelf’ models ■■ Coastal storm surge from typhoon is mod- ■■ Broking house models eled by EQECAT but not included in the AIR ■■ Insurer and reinsurer tools developed Philippines typhoon model. in-house Table A9.1. Independent third party model vendor coverage Brunei Darussalam Cambodia Indonesia Lao PDR Malaysia Myanmar Philippines Singapore Thailand Vietnam Earthquake, AIR Worldwide Earthquake Typhoon Earthquake, Earthquake, Earthquake, EQECAT Earthquake Earthquake, Typhoon Typhoon Typhoon Risk Management Earthquake Earthquake Solutions Broking house models: pines, Viet Nam, Thailand, Cambodia and Lao PDR and earthquake models for the Philippines, Indone- International brokers operating in the region have sia, Singapore, Malaysia, Viet Nam, Thailand, Cam- also developed models, primarily for technical sup- bodia and Lao PDR. port to their clients. Aon Benfield Impact Forecasting has an Asia typhoon model covering the Philippines, Inclusion of the effects of a loss agent may be through explicit 52 Thailand and Viet Nam. Willis has created regional separate modeling of the loss agent or through inclusion of the direct effects of an additional loss agent when calibrating stochastic risk tools and models mostly for those ar- hazard and vulnerability curves for the principal loss agent. eas or perils for which there are no vendor models. For more information, see http://www.air-worldwide.com, Their models include typhoon models for the Philip- www.eqecat.com and www.rms.com. < 116 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States Insurer/reinsurer models: their own view of risk for some territories and perils. Some insurers operating in the region will also have International reinsurers often develop their own models developed in-house – for example, specialist models in-house to supplement vendor model out- Indonesian earthquake insurer PT Maipark has de- put for their catastrophe exposure management and veloped a probabilistic earthquake model to support pricing processes. It is likely that the large interna- its operations. tional reinsurers operating in the ASEAN region have Box A9.1. Probabilistic catastrophe modeling methodology A typical catastrophe risk model is comprised of the following modules: Hazard module: This module defines the frequency and severity of potential perils (e.g. earthquake, tropical cyclone) at specific locations within the region of interest. This is done by analyzing historical frequencies, and reviewing scientific studies performed on severity and frequencies in the region of interest. The potential of a system (such as a fault or a tropical cyclone basin) to produce events beyond the severity of events observed in the available historical record is considered. This module later generates thousands of stochastic events based on historical data and expert opinion. Exposure module: This is a geo-referenced database of assets at risk, assigning a list of attributes (e.g. exact location, construction type, number of stories) for each asset. This information is used to determine the area’s vulnerability, captured through vulnerability functions typically specific to a construction or occupancy type and an area. Loss Module: This module combines the hazard module and the exposure module to calculate different risk metrics, such as annual expected loss (AEL) and probable maximum losses (PMLs) for various return periods. The AEL is an expression of the long term average annual loss. The PML represents the expected loss severity based on likely occurrence, such as the 1-in-100 year loss or the 1-in-200 year loss. Risk metrics generated by probabilistic risk models are used to compliment historical analysis and are particularly useful for policy makers in assessing the probability of losses and the maximum loss that could be generated by major events in the future (e.g. a large earthquake or cyclone affecting a major city or port). Annex 10. Borrowing Capacity of ASEAN Member States < 117 > Annex 10. Borrowing capacity of ASEAN Member States can be classified into three ASEAN Member States groups according to their debt-to-GDP ratios in 2010. Indonesia, Cambodia, and Brunei Darus- Government gross debt has considerably decreased salam53 have debt-to-GDP ratios lower than 30 per- in many ASEAN Member States over the last de- cent, and are the least indebted countries in the cade. Myanmar and Lao PDR significantly reduced ASEAN region. Five countries show relatively mod- their debts and went from having over 100 percent erate debt levels in 2010. Myanmar, Thailand, the debt-to-GDP ratios in 2001 to presenting reasonable Philippines have debt-to-GDP ratios between 40 debts equivalent to 43 percent and 62 percent of percent and 50 percent, while the debt-to-GDP ra- their GDPs in 2010. Indonesia’s government debt tio for Viet Nam and Malaysia ranges between 50 decreased substantially from a debt-to-GDP ratio of percent and 55 percent. According to this indicator 80 percent in 2001 to a 27 percent ratio in 2010. of debt position, most ASEAN Member States seem The Philippines’s government also reduced its debt to have room for self-finance through debt, and to considerably from 63 percent of its GDP in 2001 varying degrees to self-finance not only post disaster to 43 percent in 2010. Cambodia, Malaysia, Thai- reconstruction activities, but also short-term recov- land, and Viet Nam present rather constant trends ery activities. On the other hand, the self-finance ca- in their government’s debt-to-GDP ratios, with rela- pacity of the most indebted countries in the region, tively moderate debts as a percentage of GDPs of Lao PDR and Singapore, whose debt-to-GDP ratios 30 percent, 54 percent, 44 percent, and 52 percent, were 62 percent and 96 percent in 2010, might be respectively. Singapore’s government stands as the more compromised (Figure A10.2). It is important to most indebted in the ASEAN region, presenting a note that debt-to-GDP ratio is only one indicator of relatively constant trend of debt as a percentage of the financial soundness of governments, and a more GDP between 85 percent and 105 percent. In 2010, in depth analysis is required for an accurate char- Singapore’s government presents a debt equivalent acterization of ASEAN Member States’ debt burden to 96 percent its GDP (See Figure A10.1). sustainability and self-finance capacity54. Figure A10.1. General gross debt of governments The major natural disasters that recently occurred in as percentage of GDP the ASEAN region did not seem to significantly af- fect the cost of borrowing, nor the governments’ 160 ability to access capital markets for Indonesia, Ma- 140 laysia, and the Philippines. Government bonds is- 120 sued by Indonesia had a spread of around 200 basis 100 points over US Treasury bonds as of April 2011 (Fig- % of GDP 80 ure A10.3). Bonds issued by Malaysia had a lower 60 spread of 194 basis points, while those issued by the Philippines had a slightly higher spread of 245 as of 40 April 2011. Viet Nam’s EMBIG seems to be slightly 20 higher than the rest of the countries in the region, 0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 with an EMBIG of 555 basis points over US Treasury Year Singapore Lao PDR Malaysia Vietnam Philippines Thailand Myanmar Cambodia Indonesia 54 Although Lao PDR and Singapore are the most indebted countries in the region in terms of debt-to-GDP ratios, the debt sustainability of both countries can be entirely different 53 Brunei Darussalam’s government does not hold outstanding when taking other measures into account, such as the NPV debt as of 2010. The country’s debt-to-GDP ratio as per IMF of government debt, and the liquidity of the debt, among statistics is zero. others. < 118 > ASEAN: Advancing Disaster Risk Financing and Insurance in ASEAN Member States bonds. Note that peaks observed in 1998 and 2008 were caused by the Asian financial crisis in 1998 and the 2008 global financial crisis. Figure A10.3. Emerging market Bond Global index for ASEAN Member States, spread over US Treasury bonds (basis points) 1400 1200 1000 800 600 400 200 0 3/12/2001 12/7/2003 9/2/2006 5/29/2009 2/23/2012 11/19/2014 Malaysia Philippines Vietnam Indonesia Source: WEO Note: EMBIG is available for four of the 10 ASEAN Member States: Indonesia, Malaysia, Philippines, and Viet Nam. Bibliography and References < 119 > Bibliography and References Macroeconomic Management Beyond the Crisis. Manila: Asian Development Bank, April. Chapter 1. Introduction ADB, 2011. Key Indicators for Asia and the Pacific 201. ADB. 2009. The Economics of climate change in SEA: A Manila: Asian Development Bank. regional review. Asian Development Bank. Arnold, Margaret, 2008. The role of risk transfer and ASEAN Disaster Risk Management Initiative, 2010. insurance in disaster risk reduction and climate change Synthesis Report on Ten ASEAN Countries Disaster Risks adaptation. Stockholm: Commission on Climate Change Assessment. 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Retrieved from http://data.worldbank.org/topic/poverty Global Facility for Disaster Reduction and Recovery 1818 H Street, NW Washington, DC 20433, USA Telephone: 202-458-0268 E-mail: GFDRR@worldbank.org Facsimile: 202-522-3227 Australia Austria Bangladesh Belgium Brazil Canada China Colombia Denmark Egypt Finland France Germany Haiti India Indonesia Ireland Italy Japan Korea, Republic of Luxembourg Malawi Malaysia Mexico The Netherlands New Zealand Nigeria Norway Portugal Saudi Arabia Senegal Solomon Islands South Africa Spain Sweden Switzerland Togo United Kingdom United States Vietnam Yemen Special thanks and appreciation are extended to the partners who support GFDRR’s work to protect livelihood and improve lives: ACP Secretariat, Arab Academy for Science, Technology and Maritime Transport, Australia, Austria, Bangladesh, Belgium, Brazil, Canada, China, Colombia, Denmark, Egypt, European Commission, Finland, France, Germany, Haiti, India, Indonesia, International Federation of Red Cross and Red Crescent Societies, Ireland, Islamic Development Bank, Italy, Japan, Korea, Republic of, Luxembourg, Malawi, Malaysia, Mexico, the Netherlands, New Zealand, Nigeria, Norway, Portugal, Saudi Arabia, Senegal, Solomon Islands, South Africa, Spain, Sweden, Switzerland, Togo, United Kingdom, United Nations Development Programme, United States, UN International Strategy for Disaster Reduction, Vietnam, the World Bank, and Yemen.