Homeowners Reserving It’s Not As Easy As It Looks

1. Homeowners ReservingIt’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. CatastropheDefinition • 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. CatastropheTornado Seasonality

10. Source: Storm Prediction Center Historical Data

11. CatastropheHurricane Seasonality

12. Hurricanes by Month

13. CatastropheWildfire Seasonality • See Attached

16. Catastrophe Frequency and Severity • Differences in Frequency by quarter

17. Catastrophe Frequency and Severity • Differences in Severity by quarter

18. CatastropheSeasonality • 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 3rd quarter • California Wildfires occurred in October 2003, the beginning of the 4th quarter

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

20. CatastropheReserving 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. CatastropheOther 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. CatastropheWebsites • Hurricane – National Hurricane Center • www.nhc.noaa.gov • Tornado – Storm Prediction Center • 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 2nd and 3rd quarters, lower in 1st and 4th quarters

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

26. Coverage Expansion/ContractionMold • 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/ContractionMold - 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/ContractionReserving 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/ContractionMold Development

30. Coverage Expansion/ContractionMold Development

31. Coverage Expansion/ContractionMold Development

32. Coverage Expansion/ContractionMold - 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/ContractionMold Prediction Model Claims Incurred Water Claims Mold Average YearDamageMoldFreq. 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 3,2001,024 32.2% $15,360,000 $15,000 Note: 2003 includes a cap of $10,000 per mold claim.

34. Coverage Expansion/ContractionNew 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/ContractionExtra 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/ContractionGuaranteed 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/ContractionAutomatic 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/ContractionOther??? • 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 BusinessState • Study performed on state-specific loss development patterns • Significant differences in 1st 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 BusinessState • Incurred Claim Frequency (x 100) Source: ISO HO Data cube, Accident Year 2002

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

44. Mix of BusinessDeductible • 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 ChangesClaim Behavior • Incurred Claim Frequency (x 100) Source: ISO HO Data cube

48. Environmental ChangesClaim 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 upwardtrend

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