TAX EXEMPT PRE-EVENT CATASTROPHE RESERVES - IN THE WIND?

1. TAX EXEMPT PRE-EVENT CATASTROPHE RESERVES - IN THE WIND? Factor Development David Fennell Casualty Loss Reserve Seminar September 13, 1999

2. Outline • Origins of state specific factors • Factors by line of insurance • Modifying factors based on judgement • Advantages and limitations recognized in the analytical approach

3. Origins of State Specific Factors • New York Dept of Ins factors: • Premium multipliers by state • Based on PCS data from 1950 to 1996 • Trended for Construction Cost Indices and Population Growth • Annual Reserve increment $2 Billion

4. Annual Cat Reserve Increments Based on New York Factors

5. Line Of Insurance Issues • Historical cat data not collected by line of insurance • $2 Billion funds some but not all cats • $3.2 Bil annual average cost since 1950 • $4.2 Bil annual average cost since 1967

6. LINE OF INSURANCE ISSUES South Carolina • Used A.M. Best data by state and line of insurance • Available from 1967 • Use statistical properties to separate catastrophic losses from typical losses • Cat loss is loss in excess of mean plus X * Std dev

7. LINE OF INSURANCE ISSUES South Dakota • For states with less severe catastrophic history, the method could not work as well • Low credibility for some state/line of insurance combinations • Some data cleansing necessary

8. Judgement Modifications • Factors based only on historical averages may be high or low depending on recent history of major cats in a state • South Carolina hurricane • New Madrid earthquake • Probabilistic modeling provided an alternative which could inform judgement • Multiple vendors solicited for modeling indications • Team analyzed six sets of modeling indications to supplement historical losses

9. Issues With Judgement Modifications • Some modeling indications were for commercial versus personal lines risks. • Line of insurance had to be inferred afterward. • Models treat different perils differently • Tornado/hail separate from hurricane • Some modelers did not include indications for all states • Varying composition of model output

10. Scatter • The tool used for comparing methods was the scatter chart.

11. Regression Line • The agreement between methods was measured by the regression line.

12. Residual Plot • Residual plots from the regression detected outliers

13. Weighted Regression • Weights for each method were derived by team consensus based on perceived similarity of the alternative to our reserve approach.

14. Outliers • States more than than two standard deviations from zero were considered candidates for modification.

15. Wind Factors Modified • Homeowners factors modified by judgement for CO, HI, KS, NE, OK • CMP factors modified for FL, HI, NV • Allied Lines factors modified for AL, DE, FL, HI

16. Earthquake Factors Modified • Considerations for modification given to 12 states: • AK, AR, IL, IN, KY, MO, MS, OH, SC, TN, UT, WA • Earthquake history for these 12 states was lacking • Regression approach had to be adapted due to lack of ability to fit a meaningful regression line • Assumed that California had credible history and forced regression line through it

17. Conclusions • Factors were built considering • Exposure: Cost and population indices • Funding: Best allocation of a fixed reserve increment amount • Frequency: Both modeled and historical • Severity: Historical excess losses and model simulations • Credibility: Adjustments made in some premium line of insurance combinations • Data quality: Investigations uncovering data anomalies led to some factor revisions