advanced property ratemaking sean devlin care meeting june 6-7, 2005
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Advanced PropertyRatemaking
Sean DevlinCARe MeetingJune 6-7, 2005
2GE Insurance Solutions
June 6-7, 2005
Agenda Audience Pre-requisites Pro Rata/ELR determination Primary “Price” Experience Rating Exposure Rating Weighting of Methods Conversion of Loss Cost to Pricing Summary and Questions
3GE Insurance Solutions
June 6-7, 2005
What Do I Assume You Know? Basic Property Insurance/Reinsurance Knowledge
TIV and its components Primary ratemaking for property (CAS Exams) Coverage forms Routine reinsurance contract terms
Cat modeling basics The vendor models See my other presentation for further information
Yes, a shameless plug Use multiple models for each account
Basic exposure and experience rating Steve will “deep dive” into exposure rating
4GE Insurance Solutions
June 6-7, 2005
ELR DeterminationFoundation of Exposure Rating
Which ELR to use? Must match your curve in exposure rating Preference: Eliminate cat as much as possible Options for ELR:
• Full LR• No cat whatsoever• Exclude certain cats
Methodology Equivalent to primary ratemaking, except Need for factors to back out certain cats to match exposure curve, if the match isn’t already made
5GE Insurance Solutions
June 6-7, 2005
Pro Rata RatemakingDetermining your ELR
Breakout components Basic LR – very stable small, non-cat events Risk LR – losses subject to a per risk Layer
• Breakout into layers, like per risk rating• Appropriate blend of experience & exposure
Small Cat LR(s) – experience rate vs. model Modeled Cats
Why breakout? Inuring reinsurance or contract features Understand the drivers of the ELR Appropriate targets for quoting business
6GE Insurance Solutions
June 6-7, 2005
Pro Rata RatemakingDetermining your Target Loss Ratio
Loss Ratio Loading Total Example/Comments30.0% 2.5% 32.5% First 100K per risk10.0% 2.0% 12.0% unl xs 100k per risk10.0% 2.0% 12.0% Thunderstorm/Tordano/Hail2.0% 0.5% 2.5% Winterstorm/Wildfire5.0% 5.0% 10.0% Hurricane/EQ
30.0% 0.0% 30.0% Could be negative load for slide87.0% 12.0% 99.0% Total Should be less than 100%
7GE Insurance Solutions
June 6-7, 2005
Pro Rata Ratemaking (Cont’d)
Cat LossesHurricane losses (RMS WS)
Earthquake Fire Following Winterstorm Wildfire Extratropical wind Terrorism Other – what could happen?
Further details – see my other presentationShameless plug #2
8GE Insurance Solutions
June 6-7, 2005
Pro Rata Ratemaking (Cont’d)
Trend Parameters Cost of contracting labor Size of homes increasing Deductible impacts on frequency and severity Data – shifts in and out of E&S market Excess business Non-standard classes Demand surge
9GE Insurance Solutions
June 6-7, 2005
Pro Rata Ratemaking (Cont’d)
Final Rating Determine loss distribution – convolute or simulate
Lognormal – for parts Large loss component - optional Cat should be different distribution
• use vendor output• “curve” for other cat losses
Apply contract terms – READ THE SLIP This is very important for various reasons:
Loss sensitive features Caps on per risk/per occurrence Knowing your upside vs. downside Some ROE/RORAC models depend on this
10GE Insurance Solutions
June 6-7, 2005
Pro Rata Ratemaking (Cont’d)
Special Considerations Pro Rata on XS
Consider effect of leveraged trends Effect estimated by applying loss distribution Distribution can be actual data or approximate Losses develop slower Rate change is difficult to monitor More cyclical than other lines
Parameters applied on subject business, not all Important for surplus – typically not split out Know what business is in the price monitoring
Watch for shifts in segments Split up in homogenous groups to remove bias
11GE Insurance Solutions
June 6-7, 2005
Note on Primary “Price” Price Monitoring Reports
Typically created to measure price lift circa 2000 Know what is (isn’t) captured
Filed rate changes Schedule modification factors Experience modification factors SIR/Limit Terms and conditions New business
Test for bias Trend or shift in adjusted loss ratios Discuss with client changes More important for high capacity eaters
12GE Insurance Solutions
June 6-7, 2005
Note on Primary “Price” Effect of missing uncaptured price
Typically underestimated the magnitude of change Softening Cycle:
Underestimating decreased rates Underestimating reserves Calendar year results lag true results Delays recognition of results Softening prolonged– damage is slowly realized
Hardening Cycle: Underestimating increased rates Overestimating reserves Calendar year results lag true results Delays recognition of results Hardening prolonged– success is slowly realized
13GE Insurance Solutions
June 6-7, 2005
Primary “Price” (cont’d)
Rate Adequacy Over Time
Time
Ind
ex
Regional
Specialty
National
14GE Insurance Solutions
June 6-7, 2005
Primary “Price” (cont’d)
True Price vs Captured Price
Time
Ind
ex
Price Monitor
Actual Price
“Uncaptured Rate” change
15GE Insurance Solutions
June 6-7, 2005
Primary “Price” (cont’d)Price Assumption Effects on Cal Yr Results
Time/Year
Lo
ss R
ati
o
Plan
Actual
Cal Yr
Calendar Year results understated during soft market
Actual peak of soft market
Should be hardening here
16GE Insurance Solutions
June 6-7, 2005
Experience Rating Premium Side
Same as pro rata, mostly Splitting up business into exposed and not exposed In split business, parameters may be different Exiting class? Reflect all premium affected if excl.
Loss Side Capping at policy limits – TIV and loss both trend Losses should be on same basis as exposure rating Reflective of per risk definition – READ the slip Two methods to calculate burning cost
Empirical - weighted Fit distribution
Split quoted layers into sub layers to add credibility
17GE Insurance Solutions
June 6-7, 2005
Exposure Rating (cont’d)
General Considerations ELR must reflect the data underlying loss curve What curve to use
PSOLD – becoming a standard Lloyd’s curve
• Reversals exist• A premium calculator for facultative
Ludwig curves – outdated Other company curves – basis unknown Understanding of the data and assumptions is key
Understand the basis for companies profiles
18GE Insurance Solutions
June 6-7, 2005
Exposure Rating (cont’d)
What is in the companies profile? Limits – don’t assume, ask if unsure
Business interruption and/or contents included? Policy limit Location limit PML MFL Key location Limits or values for layered business ITV issues
Other coverages Excess policies Subscription business
19GE Insurance Solutions
June 6-7, 2005
Exposure Rating (cont’d)
What is in the companies profile (cont’d)? Any perils excluded? Homeowners
Form (HO-2,3,4,5,6) Coverage A only or all coverages
Farmowners Multiple diverse buildings on a farm One TIV
Smell test for reasonability, especially: Order of magnitude of some TIV Premium allocation
20GE Insurance Solutions
June 6-7, 2005
Exposure Rating (cont’d)
PSOLD Data from 1992-2002 Can separate business by
Occupancy – 22 groups, diff. strongest btw.• Manufacturing• Non-manufacturing• HPR• Little differences between groups
State – not a big driver Include/Exclude Cats >$100M industry loss Include/Exclude WTC Include/Exclude Business Interruption
Based on 1.8M occurrences, after scrubbing
21GE Insurance Solutions
June 6-7, 2005
Exposure Rating (cont’d)
Issues With PSOLD Not all segments represented evenly by PSOLD Loss history is thin for some groups Losses above $5M in the database are thin
# of losses > $5M is # of losses > $10M is
Refer to a list of large industry losses for more input Blanket policies small amount of database US business only – applicable abroad?
HO – US homes are built out of “cardboard” Factory in US similar to one in UK? Main street business in US same as France?
22GE Insurance Solutions
June 6-7, 2005
Exposure Rating (cont’d)
Don’t Trust the Black Box Check the output for reasonability Contract Match:
Definition of risk• One Building (possibly less)• Multiple Buildings at one location• Entire Policy• Company has sole determination
Exposure profiles Loss curve Dual trigger contracts – cat and risk combined Scope of coverage
READ THE SLIP
23GE Insurance Solutions
June 6-7, 2005
Weighting of MethodsGeneral Considerations
Actual vs. Expected counts to layer (significant) Actual – Needs to be adjusted for volume Severity differences – may need to subdivide layer Make sure that both methods reflect the same risk No loss = no weight to experience? Not necessarily Deficiencies in exposure data or curves Past experience indicative of future Do not be afraid of splitting quoted layer into parts
24GE Insurance Solutions
June 6-7, 2005
Conversion to PricingGeneral Considerations
Create loss distribution – even if “not needed” Adjust for treaty features – AAD, swing rate, etc. Understand upside and downside of deal “Unpriced” capacity – blown limit, cat on tail of curve Is the rate on line appropriate “Red Zone” catastrophe utilization Treaty correlation to book
Layered/Subscription business Catastrophes
Soft Factors Check yourself for naive capital – cheap cat cover
25GE Insurance Solutions
June 6-7, 2005
Key Takeaways
Understand the data inputs Understand your models and parameters Understand strength and weakness of the models Proper match to treaty terms – READ THE SLIP Reflect true primary price Rate for everything Include the untested exposure Work with your underwriter Question everything – Assume nothing at face value
THINK - Don’t Just Go Through The Motions
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