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Loss Rating Models:
Challenges and Opportunities
Brian Ingle, FCAS, MAAA
WC-3 Perspectives on Pricing Large
Accounts
2007 CAS Ratemaking Seminar
Large Account Pricing: Current Practice
• Loss Rating Models Play Dominant Role
• Sole Pricing Engine for Some
• Dramatic Differences in Model Sophistication Among
Insurers
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Loss Account Pricing Perspective
Workers Compensation Pricing Continuum:
Manual Rating
Small
2
Experience Rating
Account Size
Loss Rating
Large
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Loss Rating Defined
Pricing Model With:
• Full Credibility Assigned to Account Experience within
“Primary” Occurrence Layer
• Excess Losses Often Derived from “Primary” via industry
ELFs
• Often Totally Divorced from Bureau Loss Costs
• Final Output: Loss Cost per Unit of Exposure by Layer
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Loss Rating Challenges
Mission Creep and Credibility
• Every Account is “Special”
• The Client Wants to be Rated on its Own Experience
• Except for that One Year
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Loss Rating Challenges
Excessive Subjectivity
• Selecting “Primary” Loss Limit (100% Credibility)
• Weighting Loss Rates
• Difficult to Preserve Value as Benchmark
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Loss Rating Challenges
Poster Child for Credibility and Subjectivity Issues
DEVELOPMENT OF $75,000 LOSS PICKS
ACME Corporation
IncurredLosses
Estimated Ultimate Losses Selected
Total Excess of Loss Dev.
B -F
Ultimate
6
Cov. Policy PeriodPremium
ELR
WC
Limits
$75,000
M ethod
M ethod
Losses
05/22/02
92,076
0.80
11,339
0
23,588
49,591
36,589
05/22/01
71,183
0.80
11,636
0
13,415
19,186
16,300
05/22/00
85,065
0.80
191,547
19,779
181,626
175,462
175,462
05/22/99
66,277
0.80
25,947
0
26,572
27,193
26,883
05/22/98
72,345
386,946
0.80
95,958
336,427
0
19,779
97,835
343,035
97,068
368,500
97,452
352,685
Avg Annual Prem. $80K!
Trended
Loss
Cost
Wghts
0.59
0.27
2.41
0.8
1
0.5 *
0.44
1.72
0.91
1
0.8 *
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Loss Rating Challenges
Significant Resource Commitment
• Programming/Testing of Model
• Maintenance/Updating of Factors
• Data Verification, Input and Calculation
• Education and Control
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Addressing the Challenges: Thoughts
Mission Creep
• Define Minimum Size Client Based on Industry
Standard - E.g. minimum 60% credibility under
NCCI X-Mod Rating
• Use Loss Rating Only When Credible Client Specific
Development Triangles Available
• Manage Internal Expectations
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Addressing the Challenges: Thoughts
Subjectivity
• Cap Loss Limitation at 10% State Reference Point
• Capture Average Loss Indication as Well as Selected for
Management Reports
• Compare Output to Industry Loss Cost
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Addressing the Challenges: Thoughts
Resource
• Control Mission Creep
• Automate Mechanical Controls
• Limit Users
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Loss Rating Opportunities
• Remedy Experience Rating Credibility Limitation
• Client Specific Loss Development.
• Capture more years than Experience Rating.
• Capture Non-Standard Severity Curve
• Greater insight into insured operations.
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X-Mod Credibility Limitations
NCCI Experience Rating Plan
Credibility
1.00
0.80
Z(p)
0.60
Z(e)
0.40
Z*
0.20
20
,0
00
5,
00
0
10
,0
00
1,
00
0
50
0
25
0
10
0
50
-
Expected Loss(000s) Limited to 10%SRP
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I.e. 25 x State Avg. Claim Cost
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Loss Rating: Company Example
Credibility:
• Actuary Determines Expected Claim Count Yielding 100%
Credibility
• Only Accounts with 100% Credibility in 1st $10K Qualify
• ELPPF Curves Determine Expected Count by Layer
• Expected Claim Count Determines Credibility in Layer
Subjectivity:
• Loss Limitation Set Where 100% Credibility Ends
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Loss Rating Opportunities:
Loss Rating Adds Most Value Where:
• XMod Credibility Inappropriate
• Severity Curve Can be Shown to Differ Materially From
ELPPFs
FIGHT THE CREEP
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Disclaimer:
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•
In preparing this Presentation, Willis Re has relied upon data provided by external data sources. No
attempt has been made to independently verify the accuracy of this data. Willis Re does not represent or
otherwise guarantee the accuracy or completeness of such data, nor assume responsibility for the result
of any error or omission in the data or other materials gathered from any source in the preparation of this
Presentation. Willis Re shall have no liability in connection with results stemming from the analysis
including but not limited to any errors, omissions, inaccuracies, or inadequacies associated with the data.
Willis Re expressly disclaims any and all liability to any third party in connection with this Presentation.
•
In preparing this Presentation, Willis Re has used procedures and assumptions that Willis Re believes are
reasonable and appropriate. However, there are many uncertainties inherent in actuarial analyses. These
include, but are not limited to, issues such as limitations in the available data, reliance on client data and
outside data sources, the underlying volatility of loss and other random processes, uncertainties that
characterize the application of professional judgment in estimates and assumptions, reinsurance
collectability, etc. Ultimate losses, liabilities and claims depend upon future contingent events, including,
but not limited to, unanticipated changes in inflation, laws, and regulations. As a result of these
uncertainties, the actual outcomes could vary significantly from Willis Re’s estimates in either direction.
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•
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request. Willis Re actuaries are available to answer questions about this Presentation.
•
The statements and opinions included in this Presentation are those of the individual speakers and do not
necessarily represent the views of Willis Re or its management.
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