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1 Exposure,hazard,vulnerability – insurance risk management with and without climate change Mr. Andrew Mitchell.

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Presentation on theme: "1 Exposure,hazard,vulnerability – insurance risk management with and without climate change Mr. Andrew Mitchell."— Presentation transcript:

1 1 Exposure,hazard,vulnerability – insurance risk management with and without climate change Mr. Andrew Mitchell

2 exposure, hazard, vulnerability – insurance risk management with and without climate change Andrew Mitchell Willis Analytics Climate Change: Impacts on the Caribbean Caribbean Community Climate Change Centre University of the West Indies 16 June 2007 ©Copyright 2007 Willis Limited all rights reserved.

3 3 insurance risk identification and quantification the cost-benefit of insurance - smoothing, pooling, diversifying experience-based rating - generalised linear models poor identification of extremes - no geography, no science, no engineering reinsurance provides cover for catastrophe event accumulations of loss cat modelling introduced to reinsurance sector in early 1990s discipline this created is as important as the numbers in output cat modelling has become a pre-requisite for new capital, esp Bermuda provided demonstrable stability - far fewer failures in 2000-2005 vs 1990-1995 cat modelling is cross-disciplinary and multi-component stochastic event sets probabilistic treatment of primary and secondary uncertainty

4 4 catastrophe loss models: structure HAZARD event generation local intensity calculation VULNERABILITY mean damage ratios building inventory FINANCIAL applying insurance terms and conditions location detailspolicy conditions EXPOSURE sums insured risk type coverage type

5 5 catastrophe loss models: output Island Jamaica Parish St. James OccupancyTemporary Lodging Construction Unknown Reinforced Concrete Height Unknown 4 stories Yearbuilt Unknown 2006 Return PeriodOccupancy only+ Construction+ Height+ Year Built 1000 61.36%57.41%46.01%44.17% 750 56.49%52.72%41.26%39.53% 500 49.48%46.06%34.65%33.11% 250 37.50%34.82%23.87%22.64% 200 33.74%31.29%20.60%19.47% 100 22.59%20.84%11.40%10.60% 50 12.72%11.58%4.39%3.95% 25 5.00%4.40%0.69%0.57% 10 0.23%0.17%0.00% 5 model sensitivity analysis RMS RiskLink v6.0 hurricane EP curve primary modifier variations

6 6 exposure: US land-falling hurricane losses – actual source: Normalized Hurricane Damages in the United States: 1900-2005 Pielke et al Natural Hazards Review (submitted)

7 7 exposure: US land-falling hurricane losses – revalued source: Normalized Hurricane Damages in the United States: 1900-2005 Pielke et al Natural Hazards Review (submitted)

8 8 exposure: growth and data capture population growth growth in property values growth of urban concentrations settlement and development in exposed regions rise in standard of living increased international trade - marine cargo exposure increased insurance penetration increased correlation means exposure to cat events rises faster than income base insurance exposure data: capture and reporting limited by legacy systems quality and type has not been standardised trans- and multi-national policies mean location identification is confused ? largest source of error in modelling

9 9 hazard: source of losses hurricaneearthquake hurricaneearthquake

10 10 hazard: relative size of losses other types of hazard: fire theft explosion terrorism volcanic eruption other classes of business: liability health aerospace marine credit finex hurricaneearthquake

11 11 hazard: complications secondary hazards not modelled - landslip, fire following earthquake other non-modelled loss contributors - economic loss, vulnerability factors impact of climate change will vary geographically and over time existing hazards change, new hazards emerge impact on frequency and severity unclear data too limited: current trends vs natural variability local uncertainty - confused by feedback systems downscaling and regional modelling not ready climate change - just another source of uncertainty?

12 12 vulnerability: other components of insurance loss mean damage ratios engineering - design and construction components calibrated by loss and claims experience non-linear factors economic demand surge claims inflation - fraud, propensity to claim business interruption loss adjusters expenses claims management strategy approved suppliers, approved repairers regional restrictions saturation point unclear poor repair quality vs retro-fitting natural increase in vulnerability and inter-dependence of systems political interference

13 13 insurance: risk management and climate change growing connection between insurance and academia contextual information vs “plug-in” data the flat earth has returned - data and modelling required for everywhere solvency and regulation - risk-based capital underwriting, reserving, credit, operational, liquidity, investment insurance as economic not social function reduction in insurance relief relative to economic losses risk appetite to meet return-on-capital targets interface between insurance and public policy non-stationarity means limited insurance adaptation is possible insurance cannot provide cover for the predictable


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