FINANCIAL RISK TRANSFER MECHANISMS OVERVIEW

Second Meeting of the Regional Platform for Financial Risk Transfer Mechanisms Mauritius, 26 th September 2012 FINANCIAL RISK TRANSFER MECHANISMS OVERVIEW â Luc Malâtre, Consultant to the COI

FINANCIAL RISK TRANSFER MECHANISMS OVERVIEW : CONTENTS Characteristics of financial risk transfer mechanisms for natural disasters The risks to be covered for the Islands project Review of the perils affecting the region Analysis of past events and their consequences Existing and required data Existing mechanisms in the Islands and other states The French CATNAT scheme The Mauritius Sugar Insurance Fund Board National contingency funds : Madagascar and Seychelles Parametric schemes : Malawi, Central America, the Caribbean The African Risk Capacity project Lessons to be drawn for the Islands project Which risks can be transferred, who buys coverage, what type of coverage Technical requirements Strategic decisions and action plan 2

CHARACTERISTICS OF FINANCIAL RISK TRANSFER MECHANISMS FOR NATURAL DISASTERS What are the risks covered and their characteristics? Perils : cyclones, floods, earthquakes, droughts,... History and data on events : dates, strengths, duration Physical damage and economic losses Who is covered = who purchases coverage and is indemnified? Individuals companies local authorities states Who provides coverage? Insurers Reinsurers Banks and Financial markets States Multilateral institutions How is compensation calculated? Actual damage and losses Parametric / index based calculations Deductibles / attachment points, limits / aggregates The sums insured and premiums will depend heavily on : Is coverage optional or general? What are the capacity for risk retention and risk pooling / mutualisation? What level of reinsurance protection? 3

REVIEW OF THE PERILS AFFECTING THE REGION perils Comoros Madagascar Mauritius La Réunion Tropical Less than More than Less than Less than cyclones yearly y yearly y yearly y yearly y Storm Surges Seychel les Very rare Zanziba r Very rare Unfrequent Frequent Unfrequent Frequent Rare Not reported Floods Unfrequent Less than yearly Less than yearly Frequent Droughts Unfrequent Unfrequent Unfrequent Unfrequent Rare Unknow n Volcanic eruptions Earthqua kes Rare but strong impact Linked to eruptions Not exposed Not exposed Frequent but no impact rare rare Linked to eruptions Rare Not exposed Not exposed Not exposed Rare Tropical cyclones and associated floods or storm surges are the shared risks Drought and severe floods outside cyclonic conditions possible during ENSO oscillations Drought is under represented (or reported) but is increasing in all territories Geophysical phenomenon are less shared, except tsunamis Tsunamis 1 event in 2004 1 event in 2004 1 event in 2004 1 event in 2004 1 event in 2004 1 event in 2004 5

REVIEW OF THE PERILS AFFECTING THE REGION / SOCIO-ECONOMIC DATA 2010 Madagascar Mauritius Comoros Seychelles Zanzibar La Réunion GDP million US $ 9947 11 310 610 1 007 590 17 500 Population 000s 21 320 1 290 754 86 1 000 830 GNI per capita US $ 430 8 240 770 11 130 526 22 500 Surface Km2 592 000 2 040 1 862 453 2 328 2 512 Population living below 5m elevation above sea level 2% 6% 14% 42% 7% Population living within less than 100km from the sea 50% 100% 100% 100% 100% 100% 6

ANALYSIS OF PAST EVENTS AND THEIR CONSEQUENCES (1/2) The most damaging g events by country from 1975 to 2010 (source EM-DAT) Comoros Madagascar Mauritius Disaster Date Damage Damage Damage Disaster Date Disaster Date (K US$) (K US$) (K US$) Storm 10/01/1983 23 000 Storm 01/02/1977 350 000 Storm 06/02/1975 200 000 Storm 03/01/1987 9 000 Storm 20/12/1981 250000 Storm 22/12/1979 175 000 Storm 14/02/1985 5 568 Storm 24/03/1982 250 000 Drought Jan-99 175 000 Storm 24/01/1989 5 236 Storm 09/04/1984 250 000 Storm 09/02/1994 135 400 Storm 07/03/2004 250 000 Storm 29/01/1989 60 000 Storm 15/03/2007 240 000 Storm 22/01/2002 50 000 Storm 15/03/1986 150 000 Storm 16/01/1982 650 Flood 18/01/2003 150 000 Storm Feb-82 323 Storm 17/02/2008 60 000 Storm 24/01/1997 50 000 La Réunion (Météo-France) Seychelles Zanzibar Disaster Date Damage Damage Disaster Date (K US$) (K US$) Disaster Storm 1980 325 000 Earthquake/ tsunami Storm 1989 260 000 Flood 13/08/1997 1 700 Storm 2002 125 000 Date Damage (K US$) 26/12/2004 30 000 Flood 2005? 7

ANALYSIS OF PAST EVENTS AND THEIR CONSEQUENCES (2/2) Total costs of disasters for the last 30 years and 2010 GPD in million US$ 8

EXISTING AND REQUIRED DATA Available data of damage and loss estimates The EM-DAT database permits comparisons between territories but is incomplete, especially for events prior to the 80 s. Other sources are mostly derived from EM-DAT There are numerous national or international reports and documents from international organizations and NGO s, but they need to be centralized and made consistent The Regional Specialized Meteorological Centre is located in La Réunion and operated by METEO FRANCE; it monitors cyclones and records their characteristics. Missing and required Characteristics of droughts and floods Standardized assessment of damage and losses Consistent approach to evaluate economic losses Models including damage functions 9

EXISTING AND REQUIRED DATA : NEXT STEPS Data acquisition Complement the data for territories with a standardized approach (PDNA, DALA or other internationally adopted method for damage estimates) Take examples of practices from IOC members, know-how transfer is possible Use regional resources (RSMC for cyclones) and international databases to create an IOC database on hazards, vulnerabilities, exposures and costs of past events Modelling Existing data and capacities sufficient to model the main risks (cyclones, drought) Flood hazard still to be mapped in details Damage functions can be created from existing data for risk modelling Maximum height of sea level rise due to storm surge simulated with the Meteo-France storm surge model for La Réunion (figures in cm) 10

TRADITIONAL INSURANCE MECHANISMS : The French CATNAT insurance scheme Since 1982, natural disasters have been fully insured under all policies covering property in France, today 40 millions policies (99% of individuals and companies are covered in mainland France) The French State plays a major role in this compensation scheme : Coverage is defined by Law Premium rates and deductibles are set by the State (deductibles increased if repeated losses) For coverage to apply an inter-ministerial commission must declare a natural disaster situation When a natural catastrophe situation is officially declared, insurers organize the usual loss surveys where necessary, and pay compensation for the losses assessed according to policy provisions. The cost of this coverage is a flat 12% additional premium on all Property policies (6% on vehicles). Total CATNAT premiums collected by insurers appr. 1,3 Bn per annum, losses average 900M. In practice, the costliest events have been floods (57%) and subsidence (37%), as well as cyclones in overseas departments - in mainland France, storms are covered outside of the CATNAT scheme. Subsidence losses in 2003, resulting from drought in mainland France, amounted to 1,4 Bn. In La Reunion, where 60% of households and most companies are insured, Dina (2002) cost 95 M. A major flood (in Paris) or earthquake (Southern France) would cost over 10 Bn. The French State gives its guarantee to the Caisse Centrale de Réassurance (CCR, state-owned) which provides insurers with unlimited reinsurance protection : most insurers buy it. 12

TRADITIONAL MECHANISMS : The Mauritius Sugar Insurance Fund Board (SIFB) Sugar cane dominates the economy in terms of cultivated land (90% of arable lands) and foreign currency earnings (25% of export earnings in 2008). Insurance has been compulsory since 1946 for all cane planters and millers, and provided by SIFB, a non-profit Statutory Body. It covers losses arising from cyclones, drought, excessive rainfall and fire. To ensure that losses are not due to cane fields deliberately neglected, abandoned, or to diseases, pest, the Fund undertakes at least 3 annual inspections of cane cultivations. The premium, collected from the proceeds of the harvest, is a percentage of the value of the total insurable sugar (TIS) of each insured farmer or miller : TIS is the weighted average sugar yield per ha of the 3 best years out of the 8 preceding years * number of ha on which canes have been cut down and sent to mill Premium rates, between 5.5% and 8.8%, depend for each insured on past compensation received and premiums paid, and can be upgraded thanks to prevention actions. These rates have been reduced by 50% in 2012. In case of a natural disaster, an Event Year may be declared by the SIFB, no later than 31 st January. This opens the process towards compensation : The sugar accrued to each Insured is calculated : amount of cane supplied * extraction rate The sugar accrued is then compared to TIS to assess loss payable around the end of February 1999 was the worst year with compensation of MUR 2,3 Bn versus premiums of MUR 0,7 Bn ; reinsurers paid MUR 1,3 Bn. From 2005 to 2010 total compensation was MUR 2,6 Bn, premiums MUR 4 Bn, ofwhich 10% was ceded for reinsurance. In 2012 the SIFB having $170M in reserves ceased buying reinsurance. 13

NATIONAL CONTINGENCY FUNDS : Madagascar and Seychelles Madagascar has suffered 46 natural disasters (cyclones, droughts, epidemics, floods ) cumulatively affecting more than 11 million people in the past 35 years, causing $ billions in damage and losses. The Madagascar authorities have therefore decided in 2008 to set up anationalcontingency Fund to cope with the difficulties raised by these major events : The initial amount was 1 Billion Ariary (US$ 620 000), e.g. around 0.1% of 2008 current expenditures (0.01% of GDP) The fund consists in a State Treasury deposit account, to be fed annually by an amount defined in the frame of the Finance Law The government shall decide how to use the amounts available on the contingency fund, in order to answer critical situations caused by a natural disaster Seychelles lies outside the tropical cyclone belt, but its islands are indirectly affected by atmospheric disturbances and are likely to be affected by global warming and associated climate changes. Seychelles State set up 3 financial mechanisms to reduce underlying risk factors of national disasters: Annual budget allocations (Ministries, Agencies, etc.), a Natural Disaster Fund (established in 2012 Sr10M or US$ 0.8M), and a National Contingency Fund : Initial amount is Sr75M (US$ 6M) or 0.6% of GDP This Contingency Fund is designed to cover expenses triggered by any substantial increase in the price of fuel products and food, natural calamities or costs related to piracy The Fund is replenished annually. If money is withdrawn, the Minister of Finance must explain to Parliament what it is spent on 14

PARAMETRIC MECHANISMS : Weather index-based insurance against Drought in Malawi (1/2) Agriculture represents 38% of the country s GDP but its performance has been weak and erratic mainly due to the impact of drought; this has constrained the country s growth. 2 risk transfer mechanisms have been set up: 1) On a micro level Banks in Malawi are unwilling to lend to small farmers, primarily because of the risk of insolvency in case of drought : without access to loans farmers cannot purchase quality seeds that would increase productivity and raise their living standards. The World Bank, in collaboration with Malawi s National Association of Small Farmers, developed a weather index-based crop insurance contract, sold to individual farmers, to increase their access to finance and protect them and their banks from weather risk. The contract is designed to provide compensation when rainfall during a crop growing g cycle is insufficient for farmers to grow and to optimize their yields : A weather insurance index measures changes in rainfall, thanks to 23 local meteorological stations, In case of severe drought, it is assumed that all farmers within a 20-30 kilometre radius will be similarly affected. The insurance contract is bundled with bank loans to farmers : the insurance pays off part or all of the entire loan directly to the bank if the index hits the specified contract threshold. In 2011, the number of farmers covered was 10,500 for an amount insured of US$ 4.5 million: a relatively low take-up because the scheme is not compulsory and consequently expensive. 15

PARAMETRIC MECHANISMS : Weather index-based insurance against Drought in Malawi (2/2) 2) On a macro level In addition to economic losses for the Nation as a whole, Malawi s government finance are highly vulnerable to adverse weather shocks due to the unanticipated need for emergency interventions. A pilot was launched in 2008, in partnership with The World Bank, to provide Malawi with contingency funding in the event of extreme drought during the 2008/2009 agricultural season. The contract was structured as a derivative based on a rainfall index. The index links rainfall and maize production so that, if precipitation falls below a certain level, the index will reflect the projected loss in maize production : The level of rainfall is the only variable in the index The index is based on a model used by government since 1992, thanks to23 weather stations Under the contract, if the maize production in the country, as estimated by the rainfall index, drops below the historical average, Malawi will receive a payout from the World Bank of up to a maximum of $5 million (corresponding to a 10% drop). The World Bank transferred the risk through a mirroring agreement with a reinsurer. 16

PARAMETRIC MECHANISMS : The Caribbean Catastrophe Risk Insurance Facility (CCRIF) Following the huge losses caused by Hurricane Ivan in 2004, the Caribbean Community Heads of Government, with the help of the World Bank, decided to implement a risk transfer program for member countries. Started in 2007, CCRIF insures 16 countries against earthquakes, hurricanes and excess rainfall. Country risk profiles were created based on historical data to determine each country s premium. Annual premiums vary from $ 200,000 to 3,000,000 per country. Once a predefined level of earthquake, wind speed or amount of rain is reached, payout occurs within 14 days. The total coverage is limited to $ 100 million. So far there have been 8 payouts to 7 governments for events in 2007 (1M), 2008 ($6,3M), 2010 ($24,75M). This scheme allows Caribbean governments to be insured at a much lower cost than the usual market price, and to receive fast payments because under a parametric, index-based scheme there is no assessment of actual losses since indemnities are only based on the index. Reinsurers accept to protect this scheme, although they have many other opportunities to reinsure other risks in the region at higher prices. 17

PARAMETRIC MECHANISMS : The Regional Insurance Facility for Central America (RIFCA) Since 1975, disasters in Central America & the Caribbean have on average affected 4,7 million people annually, causing some 5,300 deaths and US$3.3 billion in physical losses per year (source EM-DAT) Inter-American Development Bank partnered with a reinsurer in 2010 to develop an insurance mechanism for countries in Central America and the Dominican Republic. Under the facility each government has established a captive insurance company, itself supported by the international reinsurance and capital markets : Each captive issues to its national government a single parametric natural catastrophe cover, usually for earthquakes and hurricanes The government pays a premium for this coverage, typically $2,5M for a $50M limit The scheme will pay in case of natural disaster affecting > 5% of the population RIFCA is based on parametric modelling of exposed population, as opposed to classical indemnitybased solutions : The use of physical intensity parameters enhances calculation of the effectively exposed population and payouts to the countries This Insurance facility will provide participating governments with quick access to insurance proceeds following a disaster. This approach allows them to plan more effectively and reduces the need for costly post-disaster debt financing. At the moment, the scheme has started in 2011 with the Dominican Republic. 18

A PARAMETRIC PAN-AFRICAN PROJECT : The African Risk Capacity project (ARC) As viewed previously quick-disbursing funding helps protect livelihoods of the vulnerable, lowers the total assistance cost and protects development gains, when coupled with adequate contingency plans : a contingency fund of US$250 M could save African countries and donors nearly US$1 Bn in cash over 20 years (WFP estimate). In 2010, the AU initiated the ARC Project, envisaged as an African-owned financial entity providing governments with quick funds in the event of a severe drought by pooling risk across the continent : Pay-outy would be based on pre-defined rainfall trigger specified by each country, Initial scheme would cover severe drought, but shall later expand to other risks, such as flood. African governments joining the ARC will pool risks across the continent, thereby reducing costs: preliminary findings indicate a 50% reduction in the contingent funds needed if the risk is pooled among nations and managed as a group. The ARC risk evaluation for each country will rely on the Africa RiskView model, thatestimatesboth how many people may be affected by different drought severities and the required response costs. Each country will customize 3 parameters which will determine its premium: the deductible, the ceded percentage and the maximum payout Preliminary analysis shows that with 9 dispersed countries and a max. payout of US$30 M per country, ARC would require an initial capital of ca. US$175 M to remain solvent over several years. 19

LESSONS TO BE DRAWN FOR THE ISLANDS PROJECT : Transferrable risks, who buys coverage, what type of coverage Transferrable risks Cyclones are documented, including related floods, rainfalls and storm surges Tsunamis are the result of seismic activities Droughts can be measured through rainfall levels Who buys coverage is it compulsory or facultative Individuals, Farms, Companies, Local authorities, Governments What type of coverage Indemnity i.e. French CatNat or Mauritius SIFB National contingency funds i.e. Madagascar or Seychelles Parametric i.e. CCRIF, RIFCA, Malawi or ARC 21

LESSONS TO BE DRAWN FOR THE ISLANDS PROJECT : Technical requirements Necessity to build probabilistic models Based on historic data of events, as well as evaluation of vulnerabilities, they enable to link the intensity of the peril (e.g. wind speed or rainfall) to a return period and to financial costs History of events characteristics (wind speeds, sea rises, rainfalls, ) duration and frequencies Vulnerabilties Property at risk, Damage function Costs Direct damage (reconstruction) Consecutive economic losses An opportunity : the CCR initiative in La Réunion In its role as reinsurer, CCR has hired a modelling agency to develop a probabilistic model of cyclone risks (including related floods and storm surges). Using data from METEO-FRANCE on past events, it will relate wind speeds to return periods and expected damage. This will permit to quantify return period losses. We suggest exploring the feasibility of extending this project to the whole COI Region. 22

LESSONS TO BE DRAWN FOR THE ISLANDS PROJECT : Strategic decisions and action plan Decide what risks can be shared / mutualised Decide who will be insured Decide on type of coverage Decide how to measure damage and losses Build probabilistic model(s) with the help of meteorological authorities and modelling agencies Decide structure insurance and reinsurance, location, administration, staffing, Seek international support 23

FINANCIAL RISK TRANSFER MECHANISMS OVERVIEW THANK YOU 24