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Climate Change Quantification of business impacts by means of catastrophe modeling leading to tailormade risk transfer solutions Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Or: Nat Cat Reinsurance – how it works and what it needs (Nat Cat) Risk Management generic Identification/Awareness – perception is based on a shared mental model that can be conceptualized Quantification – From conceptual to quantitative model Mitigation – Explore/quantify options through quantification – costing of options: need for integrated models: loss costs (expected loss), cost of capital (or ‘for capacity’) specific Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Transfer – portfolio management diversification Market: price the option and trade etc. Reality and Model Reality Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] To be more precise: Perceived reality Reality and Model Reality Model Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Reality and Model: Proportions Reality Model Economy Society Legal Framework Environment Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Reality and Model: What can be described Reality Model Unrealistic? Modeled Not modeled Reality Model: Abstraction Described in Model Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Model Reality : Interpretation (Verification/Falsification/Calibration) Reality and Model: Development Reality Model conceptional Unrealistic? incremental Modeled Not modeled Reality Model: Abstraction Described in Model Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Model Reality : Interpretation Reality and Model: Development Reality Model conceptional Unrealistic? incremental Modeled Not modeled Reality Model: Abstraction Described in Model Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Model Reality : Interpretation Be reminded: Perceived reality Nat Cat loss model 4 elements Hazard Vulnerability How strong? How frequent? How well built and protected? Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Value distribution Cover conditions What exactly is covered ... where... and how? - Sums insured - Cover limits - Deductibles - Exclusions - etc. Example: Detailed Single Event Simulation Literally hundred thousands of such simulations are run in e.g. the catXos Nat Cat model to assess a portfolio Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] TC North Atlantic – probabilistic (zoom) North Atlantic tropical cyclone event set historic ~1000 events ~100 years probabilistic ~100‘000 events ~10‘000 years Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] The largest loss potentials 110 Peak risks: Earthquake or storm In industrialised countries With high insurance density Hurricane US+Carib. (100y) Quake California 50 75 35 45 19 Northridge 1994 Quake Japan Storm Europe 7.2 FHCF 2007 Typhoon Japan 20 8.4 Daria 1990 Mireille 1991 Katrina 2005 Insurance loss potentials in USD billions: Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Nat cat events (indexed to 2006, source: sigma 2007) Loss potentials from events with a return period of 200 years (100 years for Hurricane North Atlantic) FHCF: Florida Hurricane Catastrophe Fund JER: Japan Earthquake Reinsurance Scheme state-run schemes JER How will climate change impact the re/insurance industry? Possible change in mean AND variance Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] summer heatwave The next 100 years: Increasing variability Model results What has been exceptional in 2003 might become usual by 2070 Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Source: Schär et al., Nature 2004 summer heatwave The next 100 years: Increasing variability Model results What has been exceptional in 2003 might become usual by 2070 Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Source: Schär et al., Nature 2004 The effects of climate change: Storm damage in Europe on the rise Climate change is affecting winter storms in Europe. Based on the findings of a scientific study, Swiss Re forecasts a significant rise in damage from storm events in the long term, creating additional risk for society and insurers to manage CORNELIA SCHWIERZ1, PAMELA HECK2, EVELYN ZENKLUSEN1, DAVID N. BRESCH2, CHRISTOPH SCHÄR1, PIER-LUIGI VIDALE1 and MARTIN WILD1 Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] 1) Institute for Atmospheric and Climate Science, ETH Zürich, Schweiz 2) Swiss Reinsurance Company, Zürich, Schweiz Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Future, A2 Current, Control IPCC Scenarios Source: IPCC 2007, Summary for Policy Makers European Winter Storms Goal and Methodology Compare wind storm losses on a Europe-wide property insurance portfolio in current and future climate conditions: Use 3-dimensional global climate models (Int. community, ETH) Drive regional climate models over Europe with initial and boundary conditions from global models (ETH) Couple windfields (climate model output) with Swiss Re’s state-of-the-art loss model (probabilistic storm hazard set for current and future climate conditions) Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] European Winter Storms Climate Change Impact Increase in annual expected loss for the period 2071–2100 compared to a 1961–1990 reference period: Climate model 1 Swiss Re loss model Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] 68% Climate model 2 48% Climate model 3 16% Climate models show an increase in both storm severity and frequency. Source: Schwierz et al, Modelling European winter windstorm losses in current and future climate, submitted to climatic change Climate Impact Studies On-going Joint Projects Winterstorm Europe – MeteoSwiss, Zürich (NCCR climate), see P. Della Marta Tropical Cyclones North Atlantic – University of Bern, (NCCR climate) Flood Europe – EC Joint Research Center, Ispra, Italy Drought and Subsidence Europe – ETH, Zürich (NCCR climate) Sea Level Rise, Coastal Risks – University of Bern, GKSS Hamburg Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] Tropical Cyclones West Pacific – City University of Hong Kong (more general study, done) Conclusions Past and Present Climate – solid base period longer re-analysis period, better representation of extremes (‘tail events’) – comprehensive probabilistic set (multimodel) ensemble based reanalysis – variables to best represent the cause of loss gust better than mean wind, flood water level better than run-off ( e.g. coupled hydrological and hydraulic models) – reasonable resolution to capture local risk and consistent spatial signals footprint (dependency) Future climate – Avoid surprises, abrupt change (prevention, mitigation, adaptation) Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] – Near future (decade) of more immediate concern (from time-slice to continuum) Ceterum censeo: Easy data access (at adequate costs, simple legal terms) Further reading www.swissre.com Research & Publications Swiss Re publishing Dr. David N. Bresch Swiss Re 23 June 2008 [email protected] [email protected]