homeowners reserving it’s not as easy as it looks
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Homeowners Reserving It’s Not As Easy As It Looks. Casualty Loss Reserve Seminar September 13, 2004. 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. - PowerPoint PPT PresentationTRANSCRIPT
Homeowners Reserving
It’s Not As Easy As It Looks
Casualty Loss Reserve Seminar
September 13, 2004
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
Homeowners Reserving
LDF's 1 to 2 2 to 3 3 to 4 4 to 5 5 to 61993 0.9910 0.9996 0.9998 0.9972 0.99921994 0.9917 0.9930 0.9955 0.9972 0.99781995 0.9996 0.9882 0.9932 0.9978 0.99881996 0.9982 0.9929 0.9960 0.9958 0.99981997 0.9788 0.9930 0.9914 0.9985 0.99991998 1.0050 1.0010 0.9993 1.00141999 0.9941 0.9988 1.00002000 1.0489 1.00742001 1.0376
3 year avg 1.0268 1.0024 0.9969 0.9986 0.99954 year avg 1.0214 1.0001 0.9967 0.9984 0.99915 year avg 1.0129 0.9986 0.9960 0.9982 0.99915 ex hi/lo 1.0122 0.9976 0.9961 0.9978 0.9992
2003 Industry Schedule P data
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
Topics of Discussion
Catastrophes Non Catastrophe Seasonality Coverage Expansion/Contraction Mix of Business Reinsurance Environmental Changes
Catastrophes
Seasonality of Occurrence Differences in Development Differences in Frequency Differences in Severity Other Issues Catastrophe Modeling
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
Catastrophe Seasonality
# of CatastropheCatastrophes $
1st Quarter 22.6% 33.0%2nd Quarter 37.8% 35.7%3rd Quarter 21.8% 16.6%4th Quarter 17.8% 14.6%Total 100.0% 100.0%
1991-2003 dataExcluding Hurricane Andrew (3Q1992)
CatastropheTornado Seasonality
050
100150200250300350400
Tornados
Jan March May July Sept Nov
Month
Three Year Average 2001 to 2003
Series1
Source: Storm Prediction Center Historical Data
CatastropheHurricane Seasonality
0
10
20
30
40
50
60
70
Jan March May July Sept Nov
Hurricanes from 1900 to 2000
Series1
Hurricanes by Month
CatastropheWildfire Seasonality
See Attached
Catastrophe Frequency and Severity
Differences in Frequency by quarter
Catastrophe Frequency Relativities(3 year averages)
0.200
0.700
1.200
1.700
2.200
15 mo 18 mo 21 mo
1st Q
2nd Q
3rd Q
4th Q
Catastrophe Frequency and Severity
Differences in Severity by quarter
Catastrophe Severity Relativities(3 year averages)
0.600
0.7000.800
0.900
1.0001.100
1.2001.300
1.400
15 mo 18 mo 21 mo
1st Q
2nd Q
3rd Q
4th Q
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
CatastropheDifferences in Development
Acc Qtr 3 Month LDF2002Q1 1.7992002Q2 1.5162002Q3 1.5132002Q4 1.4822003Q1 1.5492003Q2 1.3262003Q3 5.4312003Q4 1.0552004Q1 1.290
Hurricane Isabel 9/18/03
California Wildfires
October 2003
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
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
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
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
PLIC Actual & Modeled Ex Cat Ex Mold Pure Premium 20 Accident Quarters
0
50
100
150
200
250
300
Actual062004 CWModeled062004 CWModeled122003
Coverage Expansion/Contraction
Mold Sinkhole Sewer Backup Extra Contractual Liability Automatic Increased Limits Guaranteed Replacement Cost Other?
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
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
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
Coverage Expansion/ContractionMold Development
6 Month Development Factors
1.000
1.020
1.040
1.060
1.080
1.100
1.120
Coverage Expansion/ContractionMold Development
9 Month Development Factors
0.990
1.000
1.010
1.020
1.030
1.040
1.050
Coverage Expansion/ContractionMold Development
AQ Incurred LDF's 3 6 9 12
Countrywide1998Q1 - 2000Q4 1.449 1.048 1.024 1.0202001Q1 - 2002Q2 1.475 1.080 1.038 1.029Change 1.8% 3.1% 1.4% 0.9%
Texas1998Q1 - 2000Q4 1.489 1.079 1.043 1.0302001Q1 - 2002Q2 1.781 1.192 1.103 1.059Change 19.6% 10.5% 5.8% 2.8%
Countrywide Excl Texas1998Q1 - 2000Q4 1.445 1.044 1.021 1.0182001Q1 - 2002Q2 1.432 1.060 1.025 1.023Change -0.9% 1.5% 0.4% 0.5%
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
Coverage Expansion/ContractionMold Prediction Model
Claims Incurred
Water Claims Mold Average
Year Damage 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.
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
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
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
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?
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
Mix of Business
Coverage Form State Deductible
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
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)
Mix of BusinessState
Incurred Claim Frequency (x 100)
Source: ISO HO Data cube, Accident Year 2002
Washington 4.447New Jersey 4.526Wisconsin 4.663Massachusetts 4.848Florida 4.991
Missouri 9.196Kentucky 10.781North Carolina 10.862Oklahoma 10.886Louisiana 14.360
All States 6.845
Mix of BusinessState
Developed Claim Severity
Source: ISO HO Data cube, Accident Year 2002
North Carolina 2,732Delaware 3,240Kansas 3,699Iowa 3,868Pennsylvania 3,899
Minnesota 6,136Florida 6,160Washington 6,713New Jersey 6,835California 7,446
All States 4,866
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
Reinsurance
Facultative Catastrophe
– Layers, Aggregates, Reinstatements State Run Pools
– Florida Hurricane Fund– Citizens (Florida)– Wind Storm Pools– Fair Plans
Environmental Changes
Claim behaviors have shown a marked changed in last several years
Claim frequency has been steadily declining over the past five years
Environmental ChangesClaim Behavior
Incurred Claim Frequency (x 100)
Source: ISO HO Data cube
Dwelling All PolicyForms Forms
1998 9.525 8.5571999 8.697 7.7392000 8.195 7.4382001 7.920 7.2052002 6.845 6.232
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 upward
trend
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