Using Expert Claims Systems and Reserving Issues

1. Using Expert Claims Systems and Reserving Issues CAS Spring Meeting San Diego, CA May 21, 2002

2. Considerations for The Potential Use of a Model • Potential Uses of a Predictive Model • Reserving Tool • Settlement Tool • Triage Tool

3. Considerations for The Potential Use of a Model • Pros • Greater Consistency • Quicker Responsiveness to Inflation and Claim Characteristic Shifts • Better Ability to Triage Resources & Priorities • Improved Allocation of Loss • Makes Resources Available for Other Tasks • Potential for Better Data Quality

4. Considerations for The Potential Use of a Model • Cons • Impact on Actuarial Methods • Potential Loss of Expertise • Cost to Implement and Maintain • Creates Higher Budget for Settlement ???

5. Considerations WhileBuilding a Model • Build Internally or License From Vendor • Issues: Expertise, Cost, Black Box, Maintenance • Determination of Explanatory Variables • Vendor’s Minimum Requirements • Intuitive and Non-Intuitive Factors • How Many Variables? • Data Quality and Availability Issues

6. Considerations WhileBuilding a Model • Data Quality and Availability Issues • Historical • Was the variable captured? • How completely? • How accurately? • Is the information readily available? • Has the variable changed its meaning over time?

7. Considerations WhileBuilding a Model • Data Quality and Availability Issues • Prospective • Will the variable be populated when needed? • Will the variable be updated in a timely manner when it changes? • Who will be responsible for entry and data quality going forward? • Is the variable dependant on a derivation or is it input directly?

8. Effect on Actuarial Practices • Initial Measurement of Impact • Triangles of Paid-to-Incurred Ratios Can Be Analyzed to Gauge The Impact • For a Relatively Stable Book of Business, The Paid-to-Incurred Ratios Emerge in a Consistent Pattern • Deviation of “Post Model” Pattern From Historical Pattern Provides a Rough Estimate of the Impact

9. Effect on Actuarial Practices • Initial Measurement of Impact • Need to Account for the Pace of Implementation • Useful to Perform Initial Measurement For Different States, Loss Limits and Valuation Dates When Statistically Possible • Results From Initial Measurement Can Indicate Areas of Change That May Impact Actuarial Practices

10. Effect on Actuarial Practices Paid to Incurred Ratio -----------------Valuation------------------ Accident Year 12151821 1997 .435 .489 .600 .647 1998 .426 .491 .597 .642 1999 .466 .520 .611 .662 2000 .499 .556 .623 .644 Difference in Paid to Incurred Ratio Versus Accident Year 2000 -----------------Valuation------------------ Accident Year 12151821 1997 .064 .067 .023 (.003) 1998 .073 .065 .026 .002 1999 .033 .036 .012 (.018)

11. Effect on Actuarial Practices • Issues for Loss Projections • Ultimate Loss Projections • Limitations on Incurred Loss Methods During Transition • Paid Loss Methods • Berquist/Sherman Method • Use Findings from Initial Measurement of Impact • Patterns Eventually Settle Into New Incurred Pattern • Incurred Losses Usually More Volatile Anyway

12. Effect on Actuarial Practices • Issues for Loss Projections • Other Areas Impacted • Internal Evaluations of Market Segments • Potentially Better • Replacing General IBNR With Specific Exposure Related Case Reserve • Critical for Actuaries to Make Sure Pieces Balance • Situations Where Raw Incurred Losses Are Used • Accident Year • Calendar Year

13. Effect on Actuarial Practices • Importance of Monitoring Usage • Identification of Areas Where the Model Has Issues • Identification of Emerging Trends • Effect on Loss Statistics • Identification of Reserve Process Issues • Preparation for the Next Update

14. Evaluating and UpdatingThe Model • Accuracy Testing • Runoff Studies • Compare Performance Versus Control Groups • Posted Results of Segment Using Model Versus Segment Not Using Model • Same Time Frame, Different Populations • Different Time Frame, Same Populations • Model Versus Posted Results • Model Versus Expectations

15. Evaluating and UpdatingThe Model • Accuracy Testing • Runoff Studies (cont.) • Levels to Measure Relative Accuracy • Aggregate • Case Level • Critical to Consider Potential Biases • Mix Issues • Open Claims

16. Evaluating and UpdatingThe Model • Important to Keep The Model Updated • Claim Environment is Dynamic • Best Practices Changes • Societal Changes • Technology Changes • Regulatory/Statute Changes • Data Underlying The Model Can Become Obsolete Quickly • Data Quality is Likely Improving

17. Evaluating and UpdatingThe Model • Important to Keep The Model Updated • Frequent Updates Soften The Magnitude of Version Changes • Frequent Updates Keep The Model Responsive as Possible • Tradeoff of Time and Resources

18. Evaluating and UpdatingThe Model • Considerations in Model Updating • Document Material Changes • Best Practices • Acquisitions • Book of Business Shifts • Gather The Opinions of the Model Users • Review The Inventory of Model Variables • Possible Additions? Possible Removals? • Data Quality Changed? Marginal Explanatory Value?

19. Evaluating and UpdatingThe Model • Considerations in Model Updating • Test Preliminary Model Update • Does It Address Known Issues? • Does Anything Appear Counter-Intuitive? • Any Changes in the Way The Model is Used? • Communication is Important