3rd Meeting of the High Level Expert Panel on Water and Disasters Marseille, June 9-10, 9 Water Disasters The Role of the Insurance Sector Wolfgang Kron Geo Risks Research Munich Reinsurance Company Themes Recent Disasters and Loss Statistics Reasons for Increasing Losses Risk Spreading and Risk Partnership Insurance Aspects 4 Annexes: A: PML assessment and cat modeling B: Obligatory insurance C: Cat bonds D: Micro-insurance
Recent Disasters and Loss Statistics Cyclone Sidr Bangladesh 2007 economic: 3,375 mio US$ insured: 0 deaths: 3,363 Tsunami Indian Ocean 2004 Floods Sudan 2007 economic: 10,000 mio US$ insured: 1,000 mio US$ deaths: 220,000 economic: 300 mio US$ insured: 0 deaths: > 150 Cyclone Nargis Birma economic:?? insured: 0 deaths: > 100,000 Focus: Humanitarian Aspect United Kingdom Oman / Cyclone Gonu 2007 Central Europe 2002 economic: 8,000 mio US$ insured: 6,000 mio US$ deaths: 5 economic: 3,900 mio US$ insured: 650 mio US$ deaths: 7 economic: 18,000 mio US$ insured: 3,400 mio US$ deaths: > 100 USA / Hurricane Katrina 2005 economic: 125,000 mio US$ insured: 61,600 mio US$ deaths: > 1322 Focus: Monetarian Aspect
Principal causes of flooding important for insurance considerations Storm surge River flood Flash flood Cause: high water level due to wind setup (plus astronomical high tide and waves, no effects by rainfall) Cause: long lasting, widespread rainfall with great depth; inundation starts from the river Cause: locally heavy rainfall Exposed: coastal plains (of seas, bays, lakes) Losses: low frequency (dykes), very high potential Exposed: flood plains (always the same areas) Losses: low frequency (dykes), high potential Exposed: any location Losses: high frequency, usually relatively small, high destruction potential The costliest floods in the 21st century (original values in US$ million, not adjusted for inflation) * including windstorm losses) losses in m US$: total insured [% ins] 2000 Japan: Typhoon Saomai 1,400 1,050 75 2002 China (Yangtze) 8,200 <1 2003 China (Yangtze, Huai) 7,890 <1 2004 China (Yangtze, Yellow, Huai) 7,800 <1 2004 India, Bangladesh, Nepal 5,000 <1 2005 China (Pearl) 5,000 <1 2005 India (Mumbai) 5,000 770 15 2006 India (Gujarat, Orissa) 5,300 400 8 2007 Indonesia (Jakarta) 1,700 410 24 2007 Tajikistan 1,000 <1 2007 India 2,600 <1 2007 Oman: Tropical Cyclone Gonu 3,900 650 17 2007 China (Huai) 6,800 <1 2007 Pakistan: Tropical Cyclone Yemyin 990 <1 2007 Bangladesh: Tropical Cyclone Sidr * 3,775 <1 2000 Italy (north), Switzerland (south) 8,500 470 6 2000 United Kingdom 1,500 1,100 73 2002 Central Europe (Elbe, Danube) 21,500 3,400 16 2003 France (Rhone) 1,600 900 56 2005 Romania, Bulgaria 2,440 15 <1 2005 Switzerland, Austria, Germany (Bavaria) 3,300 1,760 53 2007 United Kingdom 8,000 6,000 75 2001 USA: Tropical Storm Allison (Houston,TX) 6,000 3,500 58 2001 Argentina 750 <1 2005 Canada (Alberta) 860 190 22 2005 USA: Hurricane Katrina (Gulf Coast) * 125,000 61,600 49 2007 Mexico (Tabasco) 2,500 350 14 2007 Australia (East Coast) * 1,300 680 52 Australia (Queensland)? 2,000 1,600 >80 2000 Mozambique, Zimbabwe, South Africa 715 50 7 2007 Madagascar * 240 <1 2007 Sudan 300 <1
Number of events: 283 26% 5% Great Natural Disasters 1950 2007 Percentage distribution worldwide 28% Geological events Earthquake, tsunami, volcanic eruption Deaths: 1.8 Million 7% 2% 14% 27% Weather related events Windstorm dry Wet-storm Flood Temperature extremes 34% 2% 13 % tsunami 55% Overall losses: US$ 1,770bn* Insured losses: US$ 370bn* 6% 5% 4% 10% 24% 31% *2007values 26% 15% 24% Munich Re Geo Risks Research, NatCatSERVICE 55% Great Natural Disasters 1950 2007 180 160 140 120 Total losses (in 2007 values) Insured losses (in 2007 values) Trend total losses Trend insured losses US$ bn. 100 80 60 40 20 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Munich Re, Geo Risks Research, NatCatSERVICE
70 60 50 Great Flood Disasters 1950 2007 Total losses (in 2007 values) Insured losses (in 2007 values) Trend total losses Trend insured losses 40 US$ bn. US$ bn. 30 20 10 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Note: Storm surges are not considered Flood disasters, but rather belong to Windstorm disasters. In the same way tsunamis belong to Earthquake disasters Munich Re, Geo Risks Research, NatCatSERVICE Great Natural Disasters The affected region's ability to help itself is distinctly overtaxed. - Interregional or international assistance is necessary - Thousands are killed - Hundreds of thousands are made homeless - Substantial economic losses - Considerable insured losses Why only great natural disasters?... because neglecting the development in worldwide communication activity during the past decades extremely biases the statistics of ALL loss events. It may even lead to wrong trends. Great disasters, however, were known even in the past. Munich Re Geo Risks Research, NatCatSERVICE
Flood losses in Europe 30 Total losses [US$ bn] 25 20 15 10 5 0 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 10-year running mean Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE As at: February Flood losses in Europe 7 6 Insured losses [US$ bn] 5 4 3 2 1 0 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 10-year running mean Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE As at: February
Reasons for increasing losses Increase in the World s Population Value concentration in urban agglomerations/ megacities Urban Population 1950: 30% - 2005: 50% - 2030: 60%) Value concentration along coasts 2/3 of the world s population live within 200 km of the coast 1/3 within 50 km; 1/10 within 5 km Risk awareness and risk perception (false) feeling of safety behind a dyke Climate change 350 Number of loss events 1980 2006 Floods Windstorms Earthquakes 300 250 200 150 100 50 0 2006 2004 2002 2000 1998 1996 1994 1992 1990 1988 1986 1984 1982 1980 2007 Munich Re Geo Risks Research, NatCatSERVICE Probable influence of climate change
Risk spreading and risk partnership What is Risk? Hazard Risk = f ( Values at risk ) f ( Vulnerability Insurance reduces the financial vulnerability of the insureds. Risk reduction requires Public authorities (state, community, NGOs) Partnership People concerned (private persons, companies) Finance industry (insurance and capital market)
Risk partnership Main tasks of the partners Public authorities/organisations basic prevention measures - avoiding frequent losses - mitigation during rare events People concerned/affected actions during rare events Finance/insurance industry securing existence - loss reduction/limitation - prevention of ruinous consequences for personal/ business property Main tasks of the partners Public authorities basic prevention measures - land-use regulations - ensure they are observed - technical flood control - observation networks - forecasting and warning - flood retention - providing information
Main tasks of the partners People affected loss prevention/reduction/limitation - proper construction - spot protection - appropriate behaviour (alarm plan, checklist) - seeking/receiving information - maintaining risk awareness Main tasks of the partners Insurance industry securing existence - assuming part of the risk - proper risk assessment - adequate contracts - providing information - accumulation control - formation of natural perils reserves - capacity through balance of risks Make sure that the commitments towards the insureds can be fulfilled.
The international risk spreading system Insurance clients Primary insurers Re-insurers Retrocession Capital market Example of reinsured losses Hurricane Gilbert (Jamaica 1988) economic loss: insured loss: 2 000 mio US$ 700 mio US$ reinsured loss: 690 mio US$ (99 %) typical percentages of reinsured losses: weak markets: >90% strong markets <50%
Risk partnership in a more holistic way... Insureds Insurers State Reinsurers International donors, Development banks Capital market, Banks Reinsurers are more than just a source of insurance payments. We share our expertise in - hazard identification - risk assessment - PML assessment (Probable Maximum Loss) Annex A - risk reduction and accumulation control - insurance solutions for example: Obligatory insurance Annex B Micro-insurance Annex C Cat bonds Annex D - disseminate information
Topics Geo - Annual review of natural catastrophes Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE First edition in 1994 Available in 5 languages : - German - Englisch - French - Spanish -Italian For many other pulications on natural hazards, natural dissasters and related topics, please go to http://www.munichre.com TOPICS and SOLUTIONS Georisks Flood insurance aspects Costliest inland flood events since 1990 Year Country/Region Fatalities Economic Insured losses losses (mio US$) (mio US$) 1998 China 4,160 30,700 1,000 (3%) 1996 China 3,048 24,000 445 (2%) 1993 United States 48 21,000 1,270 (6%) 2002 Europe 37 21,000 3,400 (16%) 1995 North Korea 68 15,000 (<1%) 1991 China 2,628 13,600 410 (3%) 1993 China 3,300 11,000 (<1%) 1994 Italy 68 9,300 65 (1%) 1993 Asia 2,953 8,500 (<1%) 2000 Italy, Switzerland 38 8,500 470 (6%) 2007 United Kingdom 9 8,000 6,000 (75%)
Shares of insured losses are low because - insurance penetration is low due to lack of risk awareness - in some countries people cannot afford insurance - damage to infrastructure (dykes, bridges, roads etc.) is usually not insured Flood insurance Premium: 1st aspect: PRICING Calculation of the premium for a single risk: Annual premium = Average annual loss expectation = Risk = Hazard x Exposed values x Vulnerability probability values exposed to expected loss of the event the natural event (percent of value)
Approaches to a solution Flood insurance - information about the individual exposure - definition of zones according to exposure level (country-wide for all areas) - exclusion of particularly exposed areas - adequately structured insurance contracts including deductibles and limits - encouragement of measures for individual loss reduction - insurance package including coverage for other natural hazards (geographical spread of risk) Flood insurance Hazard zonation countrywide available (insurance industry) -Germany -Austria -Italy EU flood directive requires members of EU to develop hazard & risk maps Munich Re has developed simplistic flood hazard maps worldwide
Flood insurance Hazard zonation: Flood risk classes in the German system ZÜRS GK1 GK2 GK 4, high hazard: Flooded at least once in 10 years* GK 3, medium hazard: Flooded at least once in 10 to 50 years* GK 2, low hazard Flooded at least once in 50 to 200 years* ( area protected by dykes) GK 1, very low hazard: Flooded less than once in 200 years* GK4 * statistical mean GK3 Principle of the insurance Flood insurance sum of premiums from all clients A B = Only those, who subjectively feel threatened by a flood, have interest in insurance cover; a large portion of them is in fact exposed to a high risk and experiences losses more or less regularly. sum of payments to the affected clients ( + yields) ( + administrative costs + profits ) Adverse selection The others feel safe and do not want to get insured. If the portfolio mainly consists of members of group A, the spatial and temporal risk compensation is not guaranteed anymore.
Flood insurance Deductibles - The insured bears a part of the loss, e.g. - a fixed amount - a percentage of the loss - a percentage of the sum insured Deductibles Flood insurance example: Windstorm Lothar 1999 - Germany Percentage of the total number of losses (buildings) deductible: 500 Reduction of the number of losses by 51%
Deductibles Flood insurance example: Windstorm Lothar 1999 - Germany Percentage of the total losses amount (buildings) deductible: 500 Reduction of the total loss amount by: 35% Flood insurance Effect of deductibles - The insured pays a portion of the loss himself. - The number of minor losses and the administrative costs will be drastically reduced. - The total effort of the insurers will be reduced. - Premiums can be kept at a low level or be reduced. - Insureds are motivated to loss reduction measures in order to keep their own losses low. - The total loss/costs are reduced.
Flood insurance Full natural peril insurance packages: Examples: East Asia: STF (Storm-Tempest-Flood) covers United Kingdom: All-Natural-Peril covers France: Catastrophe pool Flood insurance other natural peril insurance packages typical example: Extended Elementary Peril Insurance in Germany Flood is insured together with: - Earthquake - Subsidence - Landslide - Snow pressure - Avalanche - Volcanic eruption not included peril: - Windstorm not insured perils: - Groundwater - Storm surge
Storm surge Risk = Annual loss expectation = Frequency x Loss Risk = 0 x very uncertain result Calculation of a risk-adequate premium is almost impossible. Premium: 2nd aspect: CAPACITY How much can a natural catastrophe cost us?
For example, a large-scale flood event as in August 2002 in the Elbe and Danube catchments in Germany? return period For example,... or an even bigger one? return period
WANTED: The Probable* Maximum Losses (PML) that a portfolio, i.e. a company may face * Probable depends on the company s risk policy, but also on legal requirements (e.g. Solvency II) return period Reserves must match the Probable Maximum Losses! but they cost money. Why? More details of PML modeling ANNEX A Because they must be made available quickly after big events and cannot be tied up in long-term, high-interest investments. This aspect also constitutes a portion of the premium required. For storm surges, this portion is (much) larger than the portion related to the loss expectation of a single risk.
Conclusions - Losses from floods have increased and reached new dimensions. - Public authorities, affected people and enterprises, and the insurance industry must work together in a risk partnership. - Insurers and reinsurers are capable of providing the financial support needed to recover from disaster while, at the same time, pursuing their business. - The insurance industry can considerably contribute to risk reduction and loss reduction. - They must protect their own business by accumulation control. - New instruments have been developed for insuring the poor and for coping with extremely large single losses. - It is of crucial importance to create and constantly maintain proper risk awareness on all levels of the society. What does an insurance company focus on to evaluate the risk of water-related disasters? Base: Aspects: Pricing Capacity, accumulation control Risk = Hazard x Exposed values x Vulnerability - Types of flooding, frequency, time of occurrence - Existing general preparedness measures: observation, early warning, flood control systems etc. - Land-use policy and its enforcement - Availability of hazard maps - Loss event experience - Distribution of values (spatial, vertical) - Site protection - Individual preparedness level - Construction type (material, number of stories etc.) - Resiliency of exposed values to water - Average loss rate, average loss - Awareness and education level, familiarity with floods Hazard Exposed values Vulnerability
ANNEXES A: PML assessment and cat modeling B: Obligatory insurance C: Cat bonds D: Micro-insurance ANNEX A PML Assessment and Catastrophe Modeling
How much can a natural catastrophe cost? WANTED: The Probable Maximum Losses (PML) that a portfolio, i.e. a company may face return period
Calculation of a PML curve To obtain (estimate) the loss of a single event, we have to combine: liability distribution vulnerability loss ratio (in % of s.i.) event scenario + + water depth 0 50 100 150 200 kilometers Values at risk Vulnerability Hazard PML calculation Example Superposition of flooded areas with built-up areas
Spatial Analysis tool: Geographical Information System (GIS) Flooded area Settlement area Inundated settlement area Result: inundated settlement areas Loss Analysis: per postcode-sector SI = sum insured A s = total settled area A f = flooded part of settled area Loss: L = SI x A f /A s
Damage ratio Situation during a River Flood Damage ratio 1. Ratio of the number of affected policies and the total number of policies in the hazard zone building not affected building affected 2. Average loss ratio
Loss Analysis: per postcode-sector SI = sum insured A s = total settled area A f = flooded part of settled area R D = damage ratio Loss: L = SI x A f /A s x R D Result: probable losses per postcode sector Accumulation analysis Accumulated losses = PML Summing up the losses from each postcode sector (separately for each line of business: individual, commercial, industrial; buildings, contents, business interruption)
from historic events, we have some loss experience loss loss but as we have only a VERY limited number of historic events, we need to generate more events stochastically 1 2 3 4 5 6.. event 0 loss experience from a stochastic event set 0 0 Schaden loss 0 0 0 0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 0 1500 3000 4500 6000 7500 event 9000 10500 12000 13500 15000 EventID
0 06 empirical PML curve 50 Schaden loss 04 30 02 01 How high is 200-year loss? 0 1 10 100 1000 10000 100000 return period WKP (years) 0 06 50 What is the return period of a given historic event? empirical PML curve Schaden loss 04 30 02 01 0 1 10 100 1000 10000 100000 return period WKP (years)
ANNEX B Obligatory flood insurance Possible solution Flood insurance - Obligatory flood insurance required by the state for basic needs, with limited cover (e.g. 100,000) plus - Voluntary flood insurance for the losses exceeding the limit offered by the private insurance market.
Legal problems Obligatory flood insurance - Freedom of contract This kind of insurance is not for protecting a third party. - Right of equality There are different hazard levels. - Scope of cover Who/What must be included? Buildings/Contents? Private/Commercial/Industrial objects? - Enforcement What happens if someone is not willing to buy insurance? Other problems Obligatory flood insurance - Risk perception Great catastrophes happen very seldom; why pay premiums for something that may happen in one s lifetime with a less than 10% chance? - Public acceptance Many do not feel threatened; these people feel they have to pay for the problems of others. - Risk-adequate premiums and deductibles Both need to be high; the consequence is that people pay a lot, but do not get compensated for small and moderate losses. - Moral hazard Insureds tend to (ab)use the insurance, there is no or only a reduced incentive for preparedness and prevention measures.
Incentives/enforcement - Insurance package Include several/all natural perils; including storm would also prevent problems in distinguishing between wind and water losses (e.g. Asia: STF cover). - No compensation by the state without insurance - No state loans without insurance protection - No free loans for recovery without insurance protection - Tax incentives Obligatory flood insurance - Low-cost construction measures for upgrading existing structures (e.g. subsidies) - Creating/raising risk awareness by information and education Flood insurance Solutions in some selected countries - Great Britain all peril cover - Germany multiple peril cover (as extended coverage) - France, Spain obligatory cover - Switzerland mixed system - The Netherlands exclusion
Principles (1) Obligatory flood insurance - (At least) high-frequency events must be subject to risk-adequate insurance conditions. - In a great catastrophe, accumulated losses can exceed the capacity of the insurance market. - Any type of obligatory insurance requires a guarantee by the state, because losses can exceed any limit. - Limiting the state guarantee is against the protection goal and must be ruled out. - The guarantee must cover all loss scenarios (e.g. small- and large-scale). Principles (2) Obligatory flood insurance - The obligatory insurance can be managed - by the state (e.g. USA, France) or - by the insurance industry (e.g. California Earthquake Agency - CEA); - In any case it will be some kind of a pool/fund solution. - The risk of the state s guarantee must be seen in the light of climate change. - A fund must be built up for the catastrophe situation.
Guarantee by the state Building up a fund Obligatory flood insurance Example: The Netherlands with 16,000,000 inhabitants If 1 per capita/month were collected, the fund would consist after ten years of approximately Euro 2bn * ( 1 x 12 x 10 x 16,000,000 = 1.92 bn) The probability that a -100-year event occurs in these ten years is 9.6% -500-year event occurs in these ten years is 2.0% * This assumes that no payments have to be made during this period, i.e. only flood losses occur that can be handled by the insurance industry. Revenues are also neglected. Flood insurance: Summary Society s point of view Interests: Spread of risk among individuals and over time Minimization of disruptive effect of loss events Minimization of loss cost Possible solutions: Private insurance National solidarity Combination of both Claims management Liquidity for quick rebuilding Risk management Claims management Responsible behaviour Legal framework
Flood insurance: Summary Pure solidarity solutions Pros: - Availability of cover can be guaranteed - Affordability of cover through society-wide sharing of risk Cons: - No immediate incentives for responsible behaviour and risk management (but can be introduced) - Consequence: higher overall loss cost - Fairness: What about Right of compensation in the case of avoidable losses? - Liquidity in the case of two-digit billion euro losses? ANNEX C Cat bonds
Cat bonds We have potential of record losses from single natural catastrophes huge amounts of money in the international financial markets Alternative Risk Transfer (ART): Catastrophe bonds (Cat bonds) new financial instruments, which supplement the classical distribution of risk via the reinsurance market. geared to very large potential losses exclusively used in developed countries Cat bonds How does it work? A specified risk (e.g. losses from a hurricane in Florida) is transferred from a risk carrier (sponsor) reinsurers, large companies such as a national railroad company to investors hedge funds, specialised catastrophe-oriented funds, asset managers, life insurers, reinsurers, banks, pension funds The investor buys a share of the cat bond. If the catastrophic event for which the bond is issued does - not occur: the invested capital plus high interest is paid back to the investor at maturity. - occur: the investor loses its principal or a portion of it.
Cat bonds How is occurrence (triggering of the cat bond) defined? - by a certain loss to the sponsor (indemnity trigger) - by a market loss (industry loss index trigger) - if a set of certain defined physical threshold values (e.g. wind speeds at certain points or discharges) are exceeded (parametric trigger). Cat bonds Current situation: - only one cat bond has been triggered so far (by hurricane Katrina), - trigger points still quite high, (Example: Munich Re issued a cat bond in 2007; it covers covers: hurricane losses in 26 US states until 2010. trigger: market loss (total insured losses) > US$ 35bn) - increasing experience will probably reduce prices and enhance the competitiveness of cat bonds, - diversity of cat bonds in terms of expected loss levels, trigger types, and underlying perils will grow.
Cat bonds (1) Today, the availability of huge amounts of money in the international financial markets, the potential of record losses from single natural catastrophes, and the need for special products have led to the dawning of new financial instruments, which supplement the classical distribution of risk via the reinsurance market: these are called catastrophe bonds (cat bonds). Through a cat bond, a specified risk (e.g. losses from a hurricane in Florida) is transferred from a risk carrier (sponsor) to investors. The sponsor is usually a member of the (re-)insurance industry, but may also be a large company (such as a national railroad company). The investor buys a share of the bond and earns interest on the purchased notes. If the catastrophic event for which the bond is issued does not occur during its lifetime, the invested capital is paid back to the investor at maturity. If it does occur, however, the investor loses its principal or a portion of it. The definition of the "occurrence", i.e. the trigger of the cat bond, can be defined in different ways: a) by a certain loss to the sponsor (indemnity trigger), b) by a market loss (industry loss index trigger), or c) if a set of certain defined physical threshold values (e.g. wind speeds at certain points or discharges) are exceeded (parametric trigger). Munich Re issued a bond in 2007 that covers hurricane losses in 26 US states until 2010. The investors of that note will lose their invested capital if the market loss (total insured losses) in any one event exceeds US$ 35bn. Cat bonds (2) Cat bonds are usually high-interest, but also high-risk investments and are practically only purchased by professional investors. Investors choose to invest in catastrophe bonds because their return is largely uncorrelated with the return on other investments, so cat bonds help investors achieve diversification. Investors who participate in this market include hedge funds specialised catastrophe-oriented funds, asset managers, life insurers, reinsurers, banks, and pension funds. Only one cat bond has been triggered so far (by Hurricane Katrina), because the trigger points were set quite high in the past. Over the coming years, increasing experience with cat bonds on the part of both investors and sponsors could reduce prices and thereby enhance the competitiveness of these financial instruments. Furthermore, it is also possible that the diversity of cat bonds in terms of expected loss levels, trigger types, and underlying perils will grow in the future. Cat bonds are geared to very large potential losses and are therefore an instrument exclusively used in developed countries. Another instrument used in a similar way is a swap. Here, an identical portion of risk from two independent (and distant) events is exchanged between two partners who are thus both sponsor and investor. For example, a portion of the "Flood Europe" risk is transferred in exchange for the same portion of the "Hurricane Florida" risk.
ANNEX D Micro-insurance Micro-insurance Flood insurance penetration in developed countries is low. Reasons: - lack of risk awareness - lack of financial means - insurance cover is not available
Micro-insurance For whom is it meant? - for low-income people, - for people ignored by mainstream commercial and social insurance schemes, - for people who do not have access to regular products. For what is it meant? - to provide cover against specific perils in exchange for regular premium payments, - to help people to manage their risk better, - to help people to maintain their standard of living. Micro-insurance How does it work? basically, like any other insurance scheme, but some aspects make a difference: - MI does not cover a single client but rather thousands of clients under one contract. - MI requires an intermediary between the client and the insurance company (e.g. a local non-governmental organisation or a rural bank that can handle the distribution and administration).
Micro-insurance What are the problems? - low premiums and high transaction costs per client, - lack of infrastructure, - lack of insurance knowledge, - insurance illiteracy (clients do not understand the concept of insurance), - low and irregular income, - lack of data. Most important: Raising awareness and educating the people concerned. Micro-insurance Current situation: - Micro-insurance covers for risks related to natural disasters are still hardly available. - As fewer than 100 million people (or 3%) of the world's poor have access to insurance, the MI market has a huge development potential. - Helping people to develop a stable life situation will also allow them to eventually become normal clients of the insurance industry. - A scheme underprivileged residents of Jakarta, Indonesia, who suffer from flooding practically every year, is currently being set up. -In Colombia (and soon in other Latin American countries) a micro-insurance is developed for low-income groups and microentrepreneurs for protection against the impacts of natural disasters.
Example Colombia (and soon in other Latin American countries) Munich Re - cooperates with insurance companies offering insurance to low-income groups and microentrepreneurs. - provides a solution to protect the balance sheet of microfinance institutions in case of natural disasters. Latin American: protect the property of microenterpreneurs and for microfinance institutions Even with low sums insured, hundreds of thousands of clients add up to an important accumulation and produce the need for reinsurance protection. Munich Re cooperates with insurance companies and microfinance institutions in Colombia to sell newly developed life and property products to low-income groups and microentrepreneurs. Additionally Munich Re has developed a solution to protect the balance sheet of microfinance institutions in case of natural disasters. Similar business models are currently being developed in other latinamerican markets. In this context Munich Re developed pricing models for microinsurance products and is willing to grant reinsurance protection bundled with microfinance market expertise and consulting services. It is very important to mention that Munich Re sees microinsurance as a business opportunity and applies the same Return on Investment principles as in our traditional business. We understand, that the desired social effect in the form of a safety net for the uninsured in Latin America can only be attained in a sustainable way if the business is profitable for all participants Example India: 1) Micro-insurance A cooperative of fishermen (NGO) organizes a micro-insurance scheme. If a large-scale disaster (e.g. a tsunami as in 2004) hits the coast, practically all fishermen lose their belongings. They are insured via the MI scheme. The cooperative needs reinsurance to be able to pay out the losses. 2) Microcredit-insurance Banks give credits to fishermen for buying boats and equipment. In a large-scale disaster practically all fishermen may lose their belongings and their source of income. Hence, they cannot pay back the loans. For the bank, this means an accumulation loss that it cannot bear. It will get bancrupt if it has no (re-)insurance cover.