MCII - Munich Climate-Insurance Initiative

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MCII - Munich Climate-Insurance Initiative

Global Natural Catastrophe UpdateNatural Catastrophes 2011World mapWildfiresCanada, 14–22 MayDroughtUSA, Oct. 2010–ongoingWildfiresUSA, April/Sept.Floods, landslidesGuatemala, El Salvador11–19 Oct.Winter Storm JoachimFrance, Switzerland,Germany, 15–17 Dec.Severe storms, tornadoesUSA, 20–27 MayHurricane IreneUSA, Caribbean22 Aug.–2 Sept.FloodsUSA, April–MaySevere storms, tornadoesUSA, 22–28 AprilFlash floods, floodsItaly, France, Spain4–9 Nov.EarthquakeTurkey23 Oct.FloodsPakistanAug.–Sept.FloodsThailandAug.–Nov.Earthquake, tsunamiJapan, 11 MarchTropical Storm WashiPhilippines, 16–18 Dec.Cyclone YasiAustralia, 2–7 Feb.Number of events: 820Landslides, flash floodsBrazil, 12/16 Jan.Floods, flash floodsAustralia,Dec. 2010–Jan. 2011DroughtSomaliaOct. 2010–Sept. 2011EarthquakeNew Zealand, 22 Feb.EarthquakeNew Zealand, 13 JuneNatural catastrophesSelection of significantloss events (see table)Geophysical events(earthquake, tsunami, volcanic activity)Meteorological events(storm)Hydrological events(flood, mass movement)Climatological events(extreme temperature, drought, wildfire)Source: MR NatCatSERVICE© 2011 Munich Re 2


NatCatSERVICENatural catastrophes worldwide, 1980 – 2010Number of events by peril with trendNumber500450400350300250200150100501980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010Geophysical events(Earthquake, tsunami,volcanic eruption)Meteorological events(Storm)Hydrological events(Flood, massmovement)© 2011 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2011


NatCatSERVICEIncome Groupsdefined by World Bank 2012Source: World Bank Country Classification (http://data.worldbank.org/about/country-classifications/country-and-lending-groups)No dataIncome Groups 2012 (defined by World Bank, Dezember 2011):High income economiesUpper middle income economiesLower middle income economiesLow income economies(GNI ≥12,276 US$)(GNI 3,976 – 12,275 US$)(GNI 1,006 – 3,975 US$)(GNI ≤1,005 US$)© 2012 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2012


NatCatSERVICENatural catastrophes worldwide 1980 – 2011Income Groups defined by World Bank 201222,200 Loss events** 2,275,000 Fatalities5%18%9%47%48%17%26%30%** Events reported at individual country level: i.e. storm could affected threecountries and is reported as three events.Overall losses* US$ 3,530bn8%3%Insured losses* US$ 870bn5% 1%23%66%94%*in 2011 values *in Werten von 2009*in 2011 valuesIncome Groups 2012 (defined by World Bank, Dezember 2011):High income economiesUpper middle income economiesLower middle income economiesLow income economies(GNI ≥12,276 US$)(GNI 3,976 – 12,275 US$)(GNI 1,006 – 3,975 US$)(GNI ≤1,005 US$)© 2012 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2012


NatCatSERVICENatural catastrophes worldwide 1980 – 2011Income Groups defined by World Bank 201222,200 Loss events** 2,275,000 Fatalities5%27%18%26%9%47%78%48%17%30%** Events reported at individual country level: i.e. storm could affected threecountries and is reported as three events.Overall losses* US$ 3,530bn8%3%Insured losses* US$ 870bn5% 1%23%11% 1%66%94%*in 2011 values *in Werten von 2009*in 2011 valuesIncome Groups 2012 (defined by World Bank, Dezember 2011):High income economiesUpper middle income economiesLower middle income economiesLow income economies(GNI ≥12,276 US$)(GNI 3,976 – 12,275 US$)(GNI 1,006 – 3,975 US$)(GNI ≤1,005 US$)© 2012 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2012


NatCatSERVICEGlobal weather catastrophes 1980 – 2011Income Groups defined by World Bank 2012 – Number of eventsNumber of events6005004003002001001980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010Income Groups 2012 (defined by World Bank, Dezember 2011):High income economies(GNI ≥12,276 US$)Upper middle income economies(GNI 3,976 – 12,275 US$)Lower middle income economies(GNI 1,006 – 3,975 US$)Low income economies(GNI ≤1,005 US$)© 2012 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2012


NatCatSERVICENatural catastrophes worldwide 1980 – 2011Income Group „low“ (GNI ≤1,005 US$) defined by World Bank 2012Number of events140120100806040201980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010Geophysical events(Earthquake, tsunami,volcanic eruption)Meteorological events(Storm)Hydrological events(Flood, massmovement)Climatological events(Extreme temperature,drought, forest fire)© 2012 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at January 2012


Insurance industry provides quantitative data of climate change relatedlosses – important information also for political decision makers.New GDV*-study on future increases of nat cat losses in Germany basedon climate modellingStatistical loss model storm/hail of PIK:Regional distribution of changes in losses in a A1B-scenario relative to the averageof the past 25 yearsApril toSeptember(Summer)Averagechange oflosses in %* German Association of Insurers


New GDV-study on future nat cat losses based on climatemodellingFlood model of PIK:Mean loss in dependence on return period (values in million EUR)• •


Future regional vulnerability of human populationsto climate changeGlobal climate-demography vulnerability index (CDVI)Regions with a high CDVI are expectedto be most negatively impacted byclimate change.The CDVI is based on ecological anddemographic models© McGill UniversitySource: Samson, J. et al. (2011) Geographic disparities andmoral hazards in the predicted impacts of climate change onhuman populations. Global Ecology and Biogeography.© 2011 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research


NatCatSERVICEThe insured and non-insured worldProperty insurance premium per capita – OverviewNo dataInsurance Groups:Highly insured countriesWell insured countriesBasically insured countriesInadequately insured countries(>1,000 US$)(101 - 1,000 US$)(11- 100 US$)(< 10 US$)Source: Munich Re, Property insurance premium (non-life including health), per capita in 2008© 2011 Münchener Rückversicherungs-Gesellschaft, Geo Risks Research, NatCatSERVICE – As at May 2011


Countries with low insurance penetration levels showdecreases in GDP after weather related catastrophesGDP p.c. development in countries with different levels of insurance penetrationx 100% trend deviation after a weather related catastropheHigh insurance market penetrationLow insurance market penetrationSource: Melecky M et Raddatz C.(2011) „How Do Governements Respond after Catastrophes?“ World Bank;22/05/2012 13


Conclusions – the MCII Approach• People in developing countries are most vulnerable toincreasing weather extremes• They have not contributed to the problem, but are sufferingfrom it• It is just fair that industrialized countries support theadaptation of developing countries to the increasing risks• Insurance in contrast to donor money is a reliable promiseinto the future for payouts on a predefined basis• Insurance (especially parametric) can assure quick payoutsand thus help avoid secondary losses


Conclusions – the MCII Approach• Insurance gives risk a price tag and thus can incentivize riskreduction on a national and local level• Insurance cover can be preconditioned on risk reductionmeasures, DRR measures can be rewarded by premiumdiscounts• MCII is writing a new submission elaborating in more detailhow insurance related mechanisms linked with DRR can beutilized in the context of loss and damage – theopinions/contributions of the delegates are essential for us

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