UN Disaster Reduction Conference, 3 October 2005 Thomas Loster, Munich ReInsurance Foundation

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1 UN Reduction Conference, 3 Thomas, Munich ReInsurance Foundation The last micrometer Thomas Chairman Contents Recent mega disasters trends Reasons Optimizing disaster preparedness DISASTER PREVENTION TODAY, LIVES SAVED TOMORROW King s College London Monday 3 Münchener Rück Stiftung 2 Tsunami Statistics Deadliest Natural s (excl. Droughts) Country Fatalities Missing Refugees Share in Population (%) US$ bn Losses Share of GDP (%) Date Country/Region Event Death Economic Insured Losses (US$m) Bangladesh Tropical Cyclone, Storm Surge 300, India Indonesia 10, ,732 5,792 93, , , China China Earthquake Earthquake Landslide 242, ,000 5, Maldives Sri Lanka Thailand 82 31,147 5, ,115 2,932 21, ,509 58, Japan Earthquake, 142,807 July/Aug China Floodings 140,000 2, Total 174, ,735 1,808, / South Asia Bangladesh Earthquake, Tsunami Tropical Cyclone >170, ,000 >10,000 3,000 > Source: World Bank (05) - Update on the World Bank Response to the Tsunami, Exception: Thailand, governmental source Vietnam Vietnam Floodings Floodings 100, ,000 05, NatCatSERVICE GeoRisikoForschung, Münchner Rück Great Natural s 04 About Memory Date Country/Region Event Fatalities Economic Insured losses (US$ m) May Haiti. Dominican Republic 2,000 June-August Bangladesh. India. Nepal 2,0 5,000 August Hurricane Charley 32 21,300 7,900 Hurricane Frances 39 10,000 5,400 Hurricane Ivan 125,000 11,300 Hurricane Jeanne 2,000 10,000 5,0 October Japan: Niigata prefecture Earthquake 29 28, December South Asia. East Africa Earthquake, Tsunami >100,000 ca. 10,000 ca. 1,000 As at: 24. January 05 05, NatCatSERVICE Geo Risks Research, Munich Re Münchener Rück Stiftung 6 Page 1 of 5

2 UN Reduction Conference, 3 Thomas, Munich ReInsurance Foundation Almost forgotten 4 Hurricanes over Florida in 04 Trends Loss balance, total of all 4: Total economic loss: US$ 62bn Insured market loss: US$ 31bn Wind speed in gusts (km/h) 7 Münchener Rück Stiftung 8 Data Entry NatCatSERVICE Great Natural s Percentage Distribution worldwide 268 Loss events 1,650,000 Deaths 6% 7% 1% 25% 29% 40% Economic losses 1,400 US$ bn 7% Earthquake/Tsunami, Volcanic eruption Windstorm Other 38% 54% Insured losses 230 US$ bn 14% 6% 6% 35% 27% 31% 05 GeoRisikoForschung, Münchener Rück 74% Great Natural s Decade comparison Great Natural s Economic and insured losses 1 >178 bn. US$ Decade Decade Decade Decade Decade Last Factor last 10: 1960s Economic losses (04 values) Insured losses (04 values) Trend of economic losses Trend of insured losses Number Economic losses 44, , , , , ,8 The comparison of the last ten years with the 1960s shows a dramatic increase 2,3 6,9 bn. US$ Insured losses - 6,5 Losses in US$bn. 04 values 13,7 28,8 132,2 96,0 14,6? , NatCatSERVICE Geo Risks Research, Munich Re 05 NatCatSERVICE, Geo Risks Research, Munich Re Page 2 of 5

3 UN Reduction Conference, 3 Thomas, Munich ReInsurance Foundation Global Mean Temperature ( ) Recent Scientific Evidence British scientists estimate, that it is very likely (confidence level >90%) that human influence has already at least doubled the risk of a heat wave exceeding the threshold magnitude of the European heat wave 03 (Stott et al., 04). 04: C A recent model simulation for the North Atlantic suggests that climate change will intensify the maximum wind speed by 0.5 on the Saffir Simpson scale and precipitation by 18% in hurricanes until 50 (Knutson et al., 04). A 05 Nature publication by Emanuel, MIT, (Emanuel, 05) shows for the first time that major tropical storms both in the Atlantic and the Pacific region have already increased since the 1970s in duration and intensity by about 50 percent. The projections are that this trend induced by global warming will continue in the future. Global Warming - Changing Risks Increase in greenhouse gases more extreme weather events Coping Techniques Example Insurance Industry Increase in temperature air + sea Increase in humidity e.g. windstorms, hail storms, rain storms and drought important for insurer: Increase in sea level - stronger events - frequent events Münchener Rück Stiftung 16 Insured and Uninsured World Average Property Premium per Capita per Year Focus Early Warning The key? Inadequately insured Basically insured Well insured Average premium levels, property (non-life) per capita and per year in US$ Münchener Rück Stiftung 18 Page 3 of 5

4 UN Reduction Conference, 3 Thomas, Munich ReInsurance Foundation Forecast success! Awareness issues Source: Münchener Rück Stiftung Why people did not escape Some examples Airplane Safety Card Underestimation (destructive power of the storm) Hope or set of beliefs Age Disability Fear of pilferage Inability to organize (e. g. large families) Lack of transportation Lack of willpower Poverty Hotel Fire Escape November 05: Munich Re Foundation Symposium Worldwide Awareness is the Key Page 4 of 5

5 UN Reduction Conference, 3 Thomas, Munich ReInsurance Foundation Today Lives saved tomorrow Improving warning systems is important More important Investigating unknown, complex issues in individual perception of and response to risks Evaluate bottom-up versus top-down approaches in terms of efficacy and other criteria Improved awareness is a key element with today huge gaps and enormous potentials Thank you for your attention! Come to our Symposium and support our work in this important field Page 5 of 5

Hitting the Poor Impact of Natural Catastrophes in Economies at Various Stages of Development

Hitting the Poor Impact of Natural Catastrophes in Economies at Various Stages of Development Angelika Wirtz, Head of NatCatSERVICE Geo Risks Research, Munich Reinsurance IDRC 2008 Davos Contents Munich