Using Expert Claims Systems
and Reserving Issues
CAS Spring Meeting
San Diego, CA
May 21, 2002
Considerations for The Potential
Use of a Model
• Potential Uses of a Predictive Model
Reserving Tool
 Settlement Tool
 Triage Tool

Considerations for The Potential
Use of a Model
• Pros
Greater Consistency
 Quicker Responsiveness to Inflation and Claim
Characteristic Shifts
 Better Ability to Triage Resources & Priorities
 Improved Allocation of Loss
 Makes Resources Available for Other Tasks
 Potential for Better Data Quality

Considerations for The Potential
Use of a Model
• Cons
Impact on Actuarial Methods
 Potential Loss of Expertise
 Cost to Implement and Maintain
 Creates Higher Budget for Settlement ???

Considerations While
Building a Model
• Build Internally or License From Vendor

Issues: Expertise, Cost, Black Box,
Maintenance
• Determination of Explanatory Variables
Vendor’s Minimum Requirements
 Intuitive and Non-Intuitive Factors
 How Many Variables?
 Data Quality and Availability Issues

Considerations While
Building a Model
• Data Quality and Availability Issues

Historical

Was the variable captured?




How completely?
How accurately?
Is the information readily available?
Has the variable changed its meaning over time?
Considerations While
Building a Model
• Data Quality and Availability Issues

Prospective




Will the variable be populated when needed?
Will the variable be updated in a timely manner
when it changes?
Who will be responsible for entry and data quality
going forward?
Is the variable dependant on a derivation or is it
input directly?
Effect on Actuarial Practices
• Initial Measurement of Impact
Triangles of Paid-to-Incurred Ratios Can Be
Analyzed to Gauge The Impact
 For a Relatively Stable Book of Business, The
Paid-to-Incurred Ratios Emerge in a Consistent
Pattern
 Deviation of “Post Model” Pattern From
Historical Pattern Provides a Rough Estimate of
the Impact

Effect on Actuarial Practices
• Initial Measurement of Impact
Need to Account for the Pace of
Implementation
 Useful to Perform Initial Measurement For
Different States, Loss Limits and Valuation
Dates When Statistically Possible
 Results From Initial Measurement Can Indicate
Areas of Change That May Impact Actuarial
Practices

Effect on Actuarial Practices
Paid to Incurred Ratio
Accident Year
1997
1998
1999
2000
-----------------Valuation-----------------12
15
18
21
.435
.489
.600
.647
.426
.491
.597
.642
.466
.520
.611
.662
.499
.556
.623
.644
Difference in Paid to Incurred Ratio Versus Accident Year 2000
Accident Year
1997
1998
1999
-----------------Valuation-----------------12
15
18
21
.064
.067
.023
(.003)
.073
.065
.026
.002
.033
.036
.012
(.018)
Effect on Actuarial Practices
• Issues for Loss Projections

Ultimate Loss Projections






Limitations on Incurred Loss Methods During
Transition
Paid Loss Methods
Berquist/Sherman Method
Use Findings from Initial Measurement of Impact
Patterns Eventually Settle Into New Incurred Pattern
Incurred Losses Usually More Volatile Anyway
Effect on Actuarial Practices
• Issues for Loss Projections

Other Areas Impacted

Internal Evaluations of Market Segments




Potentially Better
Replacing General IBNR With Specific Exposure Related
Case Reserve
Critical for Actuaries to Make Sure Pieces Balance
Situations Where Raw Incurred Losses Are Used


Accident Year
Calendar Year
Effect on Actuarial Practices
• Importance of Monitoring Usage
Identification of Areas Where the Model Has
Issues
 Identification of Emerging Trends
 Effect on Loss Statistics
 Identification of Reserve Process Issues
 Preparation for the Next Update

Evaluating and Updating
The Model
• Accuracy Testing

Runoff Studies

Compare Performance Versus Control Groups



Posted Results of Segment Using Model Versus Segment
Not Using Model
» Same Time Frame, Different Populations
» Different Time Frame, Same Populations
Model Versus Posted Results
Model Versus Expectations
Evaluating and Updating
The Model
• Accuracy Testing

Runoff Studies (cont.)

Levels to Measure Relative Accuracy



Aggregate
Case Level
Critical to Consider Potential Biases


Mix Issues
Open Claims
Evaluating and Updating
The Model
• Important to Keep The Model Updated

Claim Environment is Dynamic




Best Practices Changes
Societal Changes
Technology Changes
Regulatory/Statute Changes
Data Underlying The Model Can Become
Obsolete Quickly
 Data Quality is Likely Improving

Evaluating and Updating
The Model
• Important to Keep The Model Updated
Frequent Updates Soften The Magnitude of
Version Changes
 Frequent Updates Keep The Model Responsive
as Possible
 Tradeoff of Time and Resources

Evaluating and Updating
The Model
• Considerations in Model Updating

Document Material Changes



Best Practices
Acquisitions
Book of Business Shifts
Gather The Opinions of the Model Users
 Review The Inventory of Model Variables


Possible Additions? Possible Removals?

Data Quality Changed? Marginal Explanatory Value?
Evaluating and Updating
The Model
• Considerations in Model Updating

Test Preliminary Model Update


Does It Address Known Issues?
Does Anything Appear Counter-Intuitive?
Any Changes in the Way The Model is Used?
 Communication is Important
