EXTREME EVENTS AND (RE)INSURANCE

1. EXTREME EVENTSAND(RE)INSURANCE Richard J. Murnane RPI/BIOS, 16 Jjune 2011 Researcher Colloquium onExtreme Weather Phenomena under Climate Change (Hurricane Fabian over Bermuda. Sept. 5, 2003)

2. Washington Post, June 15, 2011

3. Overview • Introductory comments • (Re)insurer’s view of science • Climate change relative to business change

4. Why Am I Here? • Senior research scientist at BIOS and program manager for the Risk Prediction Initiative, a science-business partnership at BIOS • Chief scientist with OpenRisk LLC, a catastrophe risk business platform

5. What Is Risk? • Risk = f(climate, exposure, vulnerability)

6. Top 40 For Victims (1970-2010) Swiss Re Sigma, 1/2011

7. Top 40 For Victims (1970-2010) Swiss Re Sigma, 1/2011

8. What Is Risk? • Risk = f(climate, exposure, vulnerability) • Focus on risk of losing $$$ • Probability of loss: • Annual Average Loss (AAL) • Return period loss, e.g., 100 year event • Variance around the probability of loss • Correlation of occurrence and intensity • Clustering

9. 2008 Non-life Premium Volume US and Europe premium: ~$1.4 trillionGlobal ~$1.8 trillion Swiss Re, Sigma 3/2009

10. Top 40 Property Cat Losses 1970-2010 In 2010 dollars: Total ~$350 billion2010 losses ~$43billion Swiss Re Sigma, 1/2011

11. How Do (Re)Insurers: • Assess their risk? • Using catastrophe risk models that provide the “technical” price

12. Generic Risk Model

13. Existing Risk Models • Public models (not open source!) • HAZUS-MH • Florida Public Hurricane Model • Proprietary models • AIR, ARA, EQECAT, RMS • “In-house”models

14. How Do (Re)Insurers: • Assess their risk? • Using catastrophe risk models that provide the “technical” price • Price their (re)insurance? • Model results, in part, but also market price, investment expectations, business considerations, …

15. Underwriting Vs. Investment Returns Aggregate of US, Canada, France, Germany, UK, and Japan 15 10 5 0 -5 -10 -15 Percent Change 1998 1999 2000 2001 2002 2003 2004* Underwriting result Current investment income Operating result Capital gain/loss Other income/charges Swiss Re, Sigma 2/2005

16. Guy Carpenter’s Global Property Rate On Line Index 400 300 200 100 0 Great recession? Andrew Katrina 9/11 1990 1995 2000 2005 2010 Year Guy Carpenter, 2011

17. Overview • Introductory comments • (Re)insurer’s view of science • Climate change relative to business change

18. Sea Surface Temperature Power Dissipation Index Year Changes In Hurricane Power? “… future warming may lead to an upward trend in tropical cyclone destructive potential, and – taking into account an increasing coastal population – a substantial increase in hurricane-related losses in the twenty-first century.” K. Emanuel, Nature, 2005.

19. Or, No Change? “Subjective measurements and variable procedures make existing tropical cyclone databases insufficiently reliable to detect trends in the frequency of extreme cyclones.” Landsea et al., Science, 2006.

20. Future Unfavorable Conditions? “… the increase of [vertical wind shear] has been historically associated with diminished hurricane activity and intensity. A suite of state-of-the-art global climate model[s] project… [s]ubstantial increases in tropical Atlantic and East Pacific shear …” Vecchi and Soden, GRL, 2007.

21. Upward Trend In Strongest Storms? “We find significant upward trends for wind speed quantiles above the 70th percentile…” Elsner et al., Nature, 2008

22. State Of Knowledge IPCC, 2007 CCSP, 2008

23. Overview • Introductory comments • (Re)insurer’s view of science • Climate change relative to business change

24. Potential Impacts • All other things being equal, losses will increase with: • Sea level rise • More frequent events • More intense events • Wetter events (i.e., more floods) • Etc….. • But, to what extent, and over what time scale, can we say with certainty that these changes will occur?

25. “Real World” Impacts • Regulatory and ratings agencies • New cat models

26. AMO And Hurricane Landfalls Goldenberg et al., 2001

27. Florida Hurricane Commission On Loss Projection Methodology • FHCLPM created during the 1995 Legislative Session • Models used for rate filing in the state must be certified by FHCLPM • To date only models based on climatology approved • Models not approved by commission used for reinsurance transactions

28. New Models • New RMS hurricane model • Updated construction and roof types • Higher inland wind speeds • Heightened building vulnerability • Increased losses due to storm surge • Change in losses • Increased insured loss results range from 20 to 100 percent • Some loss estimates in Texas have doubled, losses for Middle Atlantic states also increased significantly • Smaller increases in Florida

29. Market Response • Ratings: • S&Pissued a negative watch on 17 cat bonds due to the revised model • A.M. Best expects companies to incorporate model revisions as soon as practical. • Those companies that have started to use the new version apparently are quick to move as they see little or no impact on their rating or capital requirements

30. Closing Comments • (Re)insurers time horizon is very short: quarters and years, not decades and centuries • To my knowledge: • Clustering not incorporated in models • Correlation in frequency and intensity not incorporated in models • Under-appreciated problem is how to combine, in an optimal manner, results from multiple model