1. Homeowners Reserving It’s Not As Easy As It Looks Casualty Loss Reserve Seminar September 13, 2004

2. Presenters Mark Allaben FCAS, MAAA – VP and Chief Actuary – Personal Lines – The Hartford Betsy DePaolo FCAS, MAAA – VP and Actuary – Personal Lines Reserving and CW Pricing – Travelers

3. Homeowners Reserving 2003 Industry Schedule P data

4. Homeowners Reserving Short Tailed – Within 12 months 98% of ultimate claims have been reported 96% of reported claims have been closed 93% of ultimate dollars have been incurred 85% of ultimate dollars have been paid Many considerations in first year of development

5. Topics of Discussion Catastrophes Non Catastrophe Seasonality Coverage Expansion/Contraction Mix of Business Reinsurance Environmental Changes

6. Catastrophes Seasonality of Occurrence Differences in Development Differences in Frequency Differences in Severity Other Issues Catastrophe Modeling

7. Catastrophe Definition ISO definition: Any event with industry insured damage greater than $25 million Not just Hurricanes and Earthquakes Can also include – Hail Storms / Thunderstorms – Snowstorms/Blizzards/Ice storms – Wildfires – Winter Freeze

8. Catastrophe Seasonality

9. Catastrophe Tornado Seasonality

10. Source: Storm Prediction Center Historical Data

11. Catastrophe Hurricane Seasonality

12. Hurricanes by Month

13. Catastrophe Wildfire Seasonality See Attached

16. Catastrophe Frequency and Severity Differences in Frequency by quarter

17. Catastrophe Frequency and Severity Differences in Severity by quarter

18. Catastrophe Seasonality Even the occurrence date within the quarter can have a significant impact on development Examples: – Hurricane Isabel occurred on 9/18/03, near the end of the 3 rd quarter – California Wildfires occurred in October 2003, the beginning of the 4 th quarter

19. Catastrophe Differences in Development Hurricane Isabel 9/18/03 California Wildfires October 2003

20. Catastrophe Reserving Models Use of Catastrophe Models – Post Storm Simulation Storm Track, Wind speed, Tides – Exposure Based Projection Deductibles, construction, location, specialized coverage – Adjust for local conditions Demand Surge, Debris removal One Tool in the Loss Reserving Tool Belt

21. Catastrophe Other Issues Large catastrophes may have extremely different claim patterns depending on circumstances – Difficulty in reaching claimants – Lack of Electricity, Phone service – Use of Additional Living Expense Coverage – Issues with Supply and Demand of building materials

22. Catastrophe Websites Hurricane – National Hurricane Center – www.nhc.noaa.gov www.nhc.noaa.gov Tornado – Storm Prediction Center – www.spc.noaa.gov www.spc.noaa.gov Wildfires – USDA Forest Service – www.fs.fed.us/fire/news

23. Non Catastrophe Seasonality Differences in Frequency and Severity for Catastrophes vs. Non-Catastrophes – Catastrophe frequency is much lower than non- catastrophe frequency – Catastrophe severity is higher than non- catastrophe in 2 nd and 3 rd quarters, lower in 1 st and 4 th quarters

25. Coverage Expansion/Contraction Mold Sinkhole Sewer Backup Extra Contractual Liability Automatic Increased Limits Guaranteed Replacement Cost Other?

26. Coverage Expansion/Contraction Mold Increases in frequency and severity of mold- related claims began to be seen in late 2000 / early 2001. Majority of the claims were seen in the state of Texas. Severity of claims much greater than average HO claim severity

27. Coverage Expansion/Contraction Mold - Industry Reaction Companies began implementing limits on mold coverage or excluding mold from coverage altogether Typical mold limits are $5,000 or $10,000 Limits caused average severity to begin leveling off

28. Coverage Expansion/Contraction Reserving Issues with Mold Mold claims tended to have longer development than normal HO claims As exclusions and limits began to take effect, the development patterns seen during mold time period were no longer accurate predictors for development

29. Coverage Expansion/Contraction Mold Development

32. Coverage Expansion/Contraction Mold - One Reserving Method Separate Mold from Other losses – Track separately Create a Mold Prediction Model – Mold comes from Water Damage – Use Frequency and Severity Method Number of water damage losses turn to mold Average value of mold loss Mold claims times average value equals losses

33. Coverage Expansion/Contraction Mold Prediction Model Claims Incurred Water ClaimsMold Average YearDamage Mold Freq. Losses Severity 2000 3,267 784 24.0% $22,805,776 $29,089 2001 3,223 896 27.8% $30,918,272 $34,507 2002 2,576 801 31.1% $22,339,890 $27,890 2003 3,200 1,024 32.2% $15,360,000 $15,000 Note: 2003 includes a cap of $10,000 per mold claim.

34. Coverage Expansion/Contraction New Mold Threat Multiple events in a short Time Horizon – Damage from Hurricane Charley not repaired before Hurricane Frances hit – Electricity not restored to properly dry out property after a severe weather event – Tornados followed by severe thunderstorms

35. Coverage Expansion/Contraction Extra Contractual Liability (ECL) “Bad Faith” Claim handling practices Payments in excess of coverage amounts – Waiver of deductibles – Extension of additional living expenses – Negotiated losses/ settlements – coverage disputes Increasing frequency Impact is to lengthen the development tail

36. Coverage Expansion/Contraction Guaranteed Replacement Cost Historically, in event of total loss, Guaranteed Replacement Cost (GRC) coverage could be purchased. Insurers paid to completely rebuild home, regardless of Coverage A amount. Problems with underinsurance led insurers to set limit on GRC, typically 120% or 125% of Coverage A Such a change in exposure could result in a change in development patterns in data

37. Coverage Expansion/Contraction Automatic Increased Limits Annual provision to increase Coverage A (or Coverage C for Condo/Tenant) to account for inflation Intended to limit chance of underinsurance Does AIL change development patterns?

38. Coverage Expansion/Contraction Other??? We don’t know what the next “issue” may be Watch for changes in frequency, severity, development patterns. Communicate with claim department regarding any trends they may be seeing Implement detailed claim coding so the next issue can be quickly identified and tracked

39. Mix of Business Coverage Form State Deductible

40. Mix of Business Coverage Form Dwelling vs. Condo vs. Tenant Coverage – Average Developed Severity Dwelling: 4,866 Condo: 3,520 Tenant: 3,286 – Average Incurred Frequency (x100) Dwelling: 6.845 Condo: 3.739 Tenant: 1.807 Source: ISO HO Data cube, Accident Year 2002

41. Mix of Business State Study performed on state-specific loss development patterns Significant differences in 1 st year of development Predominant cause of loss in state appeared to be the primary factor Four states (NC, SC, AL, WA), which has a heavier mix of fire claims, developed faster than other states (smaller LDF’s)

42. Mix of Business State Incurred Claim Frequency (x 100) Source: ISO HO Data cube, Accident Year 2002

43. Mix of Business State Developed Claim Severity Source: ISO HO Data cube, Accident Year 2002

44. Mix of Business Deductible Changes in deductible buying patterns could impact both frequency and severity Historically, deductibles of $100 and $250 were common Consumers are moving to $500, $1000 and even $2,500 deductibles as a means to decrease their Homeowners premium

45. Reinsurance Facultative Catastrophe – Layers, Aggregates, Reinstatements State Run Pools – Florida Hurricane Fund – Citizens (Florida) – Wind Storm Pools – Fair Plans

46. Environmental Changes Claim behaviors have shown a marked changed in last several years Claim frequency has been steadily declining over the past five years

47. Environmental Changes Claim Behavior Incurred Claim Frequency (x 100) Source: ISO HO Data cube

48. Environmental Changes Claim Behavior Pattern has been continuing in 2003 and 2004 Drop in frequency most prominent at smaller claim levels Some of the frequency drop may be explained by changes in deductible selections But drop in frequency is also seen at claim sizes larger than average deductible Consumers concerned about large rate increases following a claim and/or being cancelled/non-renewed Consumers are effectively self-insuring Corresponding severities have exhibited an upward trend

49. Conclusions Homeowners reserving may be easier than most other lines but watch out for the pitfalls Separate Catastrophe and Non-Catastrophe Claims Examine data by Accident Quarter Watch for signs of unexpected coverage expansion or contraction which may impact patterns Watch for changes in mix of business (coverage form, state, deductible) Consider the impact of reinsurance Watch for changes in consumer/claimant behavior that may signal a turn