1. CARE Presentation – Ceding Company Considerations David Flitman, FCAS, MAAA, ASA Chief Actuary June 1, 2006

2. 2 Reinsurer Risk Management Use and Appropriateness of PMLS –Three methods of tracking exposure Limits Per occurrence PML – variants (Scenario Based vs. probabilistic) Realistic Disaster Scenarios (Lloyds) Aggregate Loss Modeling (Simulation, Closed Form, distribution dependent (Poisson vs Negative Binomial) –Implication of using each Limits appear overly conservative and tend to shift capacity toward higher rate on line business Per Occurrence PMLs – tend to create bridging problems in between quantifying order of events (first event vs. second event pmls) –How to translate to overall risk metrics for example AM Best’s company weathering two events vs. S&P aggregate 250 return period. Aggregate appears most attractive yet additional assumptions about frequency variability need to be better incorporated. –Serial dependency. SSTs and other basin wide effects

3. 3 Reinsurer Risk Management Model Changes –The modeling companies have instituted massive changes in the last release –RMS 75% Personal Lines and 120% commercial Lines where 45% is frequency –AIR has similar frequency increases also increasing Demand Surge caps to 40% from 30% Correct Model Usage –Are the dials all correctly selected. Demand Surge Storm Surge Secondary Uncertainty Fire Following ALAE Loads Miscellaneous loads – Exposure, Vulnerability, etc… Quantifying Unmodeled Risk –Models work on binary correlation - need to translate risk into event set schemes –Completeness of Portfolio –Adding proxy portfolios for unmodeled business. –Other correlated business – WC Cat, A&H Cat, Crop/Hail

4. 4 Retrocession Capacity Market Changes: –Changes in the Traditional Market M&A and rating downgrades Product Changes –Less Comprehensive e.g. exclusion of Marine/Energy –More Zonal Focused – Primary Companies towers of coverage Price Advantages –With the significant shifts in the market can reinsurerers arbitrage their risks? –Recent losses illustrate that we don’t model credit properly. Capital Markets

5. 5 Markets Changes –Capital Markets Cat Bonds Side car facilities ILWs Greater volume/More trading opportunities More Basis Risk –Shifting away from UNL covers to: –ILW triggers –Parametric triggers –Model Losses

6. 6 Credit Default Modeling Reinsurance (Retrocession) Traditionally modeled via a credit default ratio associated with their rating: –Fails to identify significant correlation. –PML analysis tends to show complete recoveries at all high return periods. –Estimate Correlation via Proxy Portfolios like ILWs or even replicats/sub portfolios of the cedant. –Pattern could be a lot steeper except for counter trend toward more securitization. (Presently Modeled) Return PeriodGrossNetCeded 100051043080 50048040080 25044036080 10040032080 5025021040 25100955 (With Contemplating Correlation) Return PeriodGrossNetCeded 100051045555 50048041565 25044036575 10040032080 5025021040 25100955

7. 7

8. 8