1. 1998 CASUALTY LOSS RESERVE SEMINAR Intermediate Track III- Techniques SEPTEMBER 28, 1998

2. INTRODUCTION The Ideal Situation Loss reserve data should contain a long stable history of homogeneous claim experience, where no significant operational changes materially affect either the mix of business or the handling of claims, and there should be sufficient number of claims to produce credible loss patterns. Slide 1

3. INTRODUCTION The Reality Virtually All Elements of “The Ideal” are Periodically Violated: 1. The Mix Changes 2. Claim Handling Changes: Payments Accelerate / Decelerate Case Reserves are Strengthened / Weakened 3. The Environment Changes: New Causative Agents Impact Loss Costs Society’s Attitudes Change Court Decisions Change “The Rules” Changes in the Economy Affect Claim Inflation Slide 2

4. INTRODUCTION This Session Will Discuss 1. The potential impact of mix changes. (Slides 4-10) 2. Changes in claim closing patterns. (Slides 11-21) 3. Changes in case reserve adequacy. (Slides 22-31) 4. Tail factor selection. (Slides 32-37) Slide 3

5. CHANGE IN MIX Cumulative Paid Losses (Combined) Accident Months of Development Year 12 24 36+. 1994 $2,000 $4,000 $5,000 1995 $2,000 $4,000 $5,000 1996 $2,000 $4,000 1997 $2,000 Slide 4

6. CHANGE IN MIX Cumulative Paid Losses (by Type of Claim) Each of % of Months of Development 1994-1996 Total 12 24 36+ Category A (75%) $1,500 $1,800 $2,000 Category B (25%) $500 $2,200 $3,000 $2,000 $4,000 $5,000 1997 Category A (25%) $500 Category B (75%) $1,500 $2,000 Slide 5

7. CHANGE IN MIX Cumulative Paid Losses (by Type of Claim) Each of Months of Development 1994-1996 12 24 36+ Category A $1,500 $1,800 $2,000 Category B $500 $2,200 $3,000 $2,000 $4,000 $5,000 1997 If Forecasting By Claim Category Category A $500 $600 $700 Category B $1,500 $6,600 $9,000 $2,000 $7,200 $9,700 1997 If Ignoring Claim Category Combined $2,000 $4,000 $5,000 Slide 6

8. CHANGE IN MIX Key Principle Always Search for Subdivisions of Data Related to Possible Causes of Variable Loss Development Slide 7

9. CHANGE IN MIX Suggested Subdivisions of Data Include Primary: 1. Geographic: Laws Vary, Regional Office May Use Different. Claims Personnel, Degree of Litigiousness Varies 2. New Products Versus Old 3. Subline or Coverage 4. Deductibles or Policy Limits 5. Type of Loss Payment (e.g. Medical vs. Indemnity) Reinsurance: 1. Attachment Point 2. Production Source 3. Line or Subline Slide 8

10. CHANGE IN MIX How Do You Decide? Ask: 1. Underwriters 2. Claims Department 3. Agents 4. Actuaries The Key: Learn as Much as Possible About the Book of Business You are Evaluating. What it has been historically What it is becoming Slide 9

11. CHANGE IN MIX What Should be Done if Mix Change Includes New Business for Which You Have Insufficient Data? 1. Seek Alternative Sources of Data. For example, perhaps a general. liability book formerly comprised solely of “OL&T” exposures, but in. recent years began adding “M&C” risks Possible Solution: Relate ISO development patterns for M&C to OL&T. and modify development factors for your evaluation. 2. Discuss Potential Impacts With Claims, Underwriting, and Other. Actuaries. Discuss how the change might affect: Length of the tail Frequency Severity Loss Ratios Slide 10

12. CLAIM CLOSING PATTERNS How Can Changes In Payment Patterns Be Recognized? Look at Settlement Rates for the Most Recent Accident Years Ask the Claims Department About Changes in: - Opening and Closing Practices - The Claims Handling Environment - Levels of Staffing, Reorganizations - Definition of a Claim (e.g. Multiple Claimants) Slide 11

13. CLAIM CLOSING PATTERNS Data Needed Reported Claims Development Triangle Closed Claims Development Triangle Projected Ultimate Claims Paid Loss Development Triangle Slide 12

14. CLAIM CLOSING PATTERNS Unadjusted Paid Loss Development Method Accident Months of Development Year 12 24 36 Ultimate 1995 $1,000 $4,000 $6,000 $6,000 1996 $1,000 $3,500 $5,250 1997 $750 $4,223 12-24 24-36 36-Ult Age - Age 3.75 1.50 1.00 Age - Ultimate 5.63 1.50 1.00 Slide 13

15. CLAIM CLOSING PATTERNS Accident Reported Claims Year 12 24 36 Ultimate 1995 500 900 1,000 1,000 1996 480 880 980 1997 450 900 Accident Closed Claims Year 12 24 36 1995 250 810 1,000 1996 240 704 1997 180 Slide 14

16. CLAIM CLOSING PATTERNS Accident Closed / Reported Year 12 24 36 1995 50.0% 90.0% 100.0% 1996 50.0% 80.0% 1997 40.0% Accident Closed / Ultimate Year 12 24 36 1995 25.0% 81.0% 100.0% 1996 24.5% 71.8% 1997 20.0% Slide 15

17. CLAIM CLOSING PATTERNS Accident Closing Percent Year 12 24 36 1995 20.0% 71.8% 100.0% 1996 20.0% 71.8% 1997 20.0% Accident Adjusted Closed Claims Year 12 24 36 1995 200 718* 1,000 1996 196 704 1997 180 * 718 = 71.8% x 1,000 Slide 16

18. CLAIM CLOSING PATTERNS - AY 1995 Actual Adjusted Actual Adjusted Closed Closed Paid Paid Age Claims Claims Losses Losses 0 0 0 $0 $0 12 250 200 $1,000 ? 24 810 718 $4,000 ? 36 1,000 1,000 $6,000 ? Slide 17

19. CLAIM CLOSING PATTERNS Linear Interpolation of Adjusted Paid Losses AY = 1995 200 - 0 @ 12 Months 250 - 0 x (1,000 - 0) + 0 = 800 AY = 1995 718 - 250 @ 24 Months 810 - 250 x (4,000 - 1,000) + 1,000 = 3,507 AY = 1996 196 - 0 @ 12 Months 240 - 0 x (1,000 - 0) + 0 = 817 Slide 18

20. CLAIM CLOSING PATTERNS Adjusted Paid Loss Development Method Accident Months of Development Year 12 24 36 Ultimate 1995 $800 $3,507 $6,000 $6,000 1996 817 3,500 5,985 1997 750 5,550 12-24 24-36 36-Ult Age - Age 4.33 1.71 1.00 Age - Ultimate 7.40 1.71 1.00 Slide 19

21. CLAIM CLOSING PATTERNS Impact of Adjustment Accident Revised Original Year Forecast Forecast Difference 1995 $6,000 $6,000 $0 1996 5,985 5,250 735 1997 5,550 4,223 1,327 Total $17,535 $15,473 $2,062 Slide 20

22. CLAIM CLOSING PATTERNS Step 1: Review Closing Rates to Determine Whether There Has Been a Change Step 2: Seek Independent Confirmation That Change Occurred Step 3: Restate Historical Closed Claims Using Current Closing Rates Step 4: Restate Historical Paid Losses Using Restated Closed Claims Step 5: Apply Standard Loss Development Method To Restated Paid Losses Slide 21

23. CASE RESERVE ADEQUACY Claim Data Accident Reported Claims Year 12 24 36 Ultimate 1995 5,000 8,000 10,000 10,000 1996 5,000 8,000 10,000 1997 5,000 10,000 Accident Closed Claims Year 12 24 36 Ultimate 1995 1,000 6,000 10,000 10,000 1996 1,000 6,000 10,000 1997 1,000 10,000 Slide 22

24. CASE RESERVE ADEQUACY Loss Data Accident Incurred Losses ($000) Projected Year 12 24 36 Ultimate 1995 $10,000 $40,000 $50,000 $50,000 1996 $10,000 $45,000 $56,250 1997 $10,417 $55,340 Accident Paid Losses ($000) Projected Year 12 24 36 Ultimate 1995 $2,000 $24,000 $50,000 $50,000 1996 $2,500 $30,000 $62,500 1997 $3,125 $78,125 The Issue: What Is Driving The Divergence? Slide 23

25. CASE RESERVE ADEQUACY STEP 1: Review Paid-To-Incurred Triangles: Accident Months of Development Year 12 24 36. 1995 20% 60% 100% 1996 25% 67% 1997 30% Does the Change in These Ratios Portray a Speed-Up in Payments, a Decrease in Case Reserve Adequacy, or Both? Slide 24

26. CASE RESERVE ADEQUACY STEP 2: Review Settlement Rates (No. Closed/No. Reported) Accident Settlement Rate Year 12 24 36. 1995 20% 75% 100% 1996 20% 75% 1997 20% Observation: The settlement rates appear to be consistent. Slide 25

27. CASE RESERVE ADEQUACY STEP 3: Review Trends in Average Paid Claims Versus Trends in Average Case Reserves Accident Average Paid Average Case Reserves Year 12 24 12 24. 1995 $2,000 $4,000 $2,000 $8,000 1996 $2,500 $5,000 $1,875 $7,500 1997 $3,125 $1,823 Trend 25% 25% -4.5% -6.3% Observations: Case reserve trend is much lower than paid trend. Slide 26

28. CASE RESERVE ADEQUACY STEP 4: Review Potential Reasons For Observed Trends Is the book shifting to a lower severity mix? Have policy limits and/or reinsurance retentions kept pace with claims inflation? Has anything material changed in the handling of claims? - Turnover in claim department staff - Changes in philosophy If you conclude there has been case reserve weakening (or. strengthening), the data should be adjusted. Slides 28-30 give. one approach. Slide 27

29. CASE RESERVE ADEQUACY STEP 5: Adjust Historical Case Reserves to Current Adequacy Levels Accident Adjusted Average Case Reserves Year 12 24 36. 1995 $1,166 $6,000 $0 1996 $1,458 $7,500 1997 $1,823 Examples: $6,000 = $7,500 / 1.25 $1,116 = $1,823 / (1.25 ^ 2) ASSUME: 25% is the Actual Rate of Claim Inflation Slide 28

30. CASE RESERVE ADEQUACY Adjust Paid to Number Adjusted Formula Incurred = Date + of x Average Losses Losses Open Case Reserves AY = 95 @ 12 Months 6,664 = 2,000 + (4,000 x 1.166) AY = 95 @ 24 Months 36,000 = 24,000 + (2,000 x 6.000) AY = 96 @ 12 Months 8,332 = 2,500 + (4,000 x 1.458) Note: All dollar amounts are in thousands. Slide 29

31. CASE RESERVE ADEQUACY STEP 6: Project Ultimate Losses Using Adjusted Incurred Losses and Standard Loss Development Method Accident Adjusted Incurred Losses ($000) Year 12 24 36 Ultimate. 1995 $6,664 $36,000 $50,000 $50,000 1996 $8,332 $45,000 $62,500 1997 $10,417 $78,125 Slide 30

32. CASE RESERVE ADJUSTMENT Comparison of Estimates Original Original Revised Accident Incurred Paid Incurred Year Estimate Estimate Estimate 1995 $50,000 $50,000 $50,000 1996 $56,250 $62,500 $62,500 1997 $55,340 $78,125 $78,125 Slide 31

33. TAIL FACTORS The Need For Tail Factors Accident Reported Claims. Year 96 108 120 132 144 1986 243 247 250 252 253 1987 250 256 261 264. Accident Open Claims. Year 96 108 120 132 144 1986 55 45 35 25 15 1987 60 53 44 31 Accident Incurred Losses. Year 96 108 120 132 144 1986 341,500 413,200 462,800 495,200 515,000 1987 366,200 443,100 496,300 531,000 IT APPEARS LOSS DEVELOPMENT WILL CONTINUE BEYOND THE ENDPOINT OF THE DATA. Slide 32

34. TAIL FACTOR SELECTION METHODS Techniques To Derive Tail Factors 1. Examine broader data sources: e.g. ISO, NCCI, RAA, Best’s (Caution: Learn. the limitations of such data.) 2. Curve Fitting 3. “Generalized Bondy Method” which assumes that the age-to-age factors are. decaying at a constant rate over time. Example: Determine a tail factor based on the following observed age-to-age factors (LDFs). 96-108 108-120 120-132 132-144 LDF LDF LDF LDF 1.210 1.120 1.070 1.040 Slide 33

35. TAIL FACTOR SELECTION Using Generalized Bondy Method To Calculate Tail Factors (1) (2)=Ln(1) (3)=(2)/(2 prior) (4) Months Actual LDFs Ln(Actual) Decay Ratio Predicted LDFs 96-108 1.210 0.191 108-120 1.120 0.113 0.595 120-132 1.070 0.068 0.597 132-144 1.040 0.039 0.580 144-156 1.024=(1.040) 0.600 156-168 1.014=(1.024) 0.600 168-180 1.008=(1.014) 0.600 Selected Decay Ratio 0.600 Tail Factor (144 months to Ultimate) 1.061=(1.040) 1.500 Notes: 1. This method can be misleading when decay rates are unstable. 2. The tail factor is very sensitive to the last selected age-to-age factor. Slide 34

36. TAIL FACTORS When To Use These Different Approaches To Tail Factors Situation Source Reinsurance lines RAA Data Standard Workers Compensation line NCCI Unusual line where industry data is Curve fitting or Bondy difficult to obtain, e.g. aviation Company’s own data is unstable or not Industry Data credible, or a start-up line Slide 35

37. TAIL FACTORS How Much Tail Can There Be In Development In Reinsured Layers? Line of Selected Cumulative Age to Ultimate Factors*. Business 15 Years to Ult. 25 Years to Ult. W.C. Treaty 1.582 1.149 G.L. Treaty 1.234 1.030 A.L. Treaty 1.021 1.000 * Based on RAA Data. Slide 36

38. TAIL FACTORS Some Examples Of When Development Occurs Beyond 10 Years LINE REASONS Products and Issues complex (Who’s liable? How to prove the Pollution/Environmental injury was caused by the product? Date of loss?) Workers Compensation Occupational Disease Life pension cases, with escalation clauses in some states Medical Malpractice Delayed manifestation, with subsequent complex issues Slide 37