1. 1999 CLRS September 1999 Scottsdale, Arizona
Basic Track II
1999 CLRS
September 1999
Scottsdale, Arizona

2. Introduction Topics Covered
Comparison of Results from Paid and Incurred LDMs
Reasonableness Checks
Historical Ratios
Ultimate Levels
Current Year Sensitivity Analysis
Rate Level Adequacy
Claim Frequency & Severity
Claim Closure Rate
Adequacy of Case Reserves
Importance of Tail Factors

3. Comparison of LDM Projections

4. Comparison of Loss Development Methods
Underlying
Assumptions
PLDM: No changes in the payment pattern
ILDM: No changes in case reserve adequacy
PLDM: “Hard” data; no estimates involved
ILDM: Uses all the available information
Pro
PLDM: May generate large, volatile loss
development factors & take longer to
develop to ultimate
ILDM: Uses case reserves, which are
estimates, to develop estimates of
ultimate losses
Con

5. Key Assumptions & Potential Problems
Sample Problems
Claims settlement patterns unchanging
Case reserving practices & philosophies
unchanging
No claim processing changes
Policy limits have no impact on loss
development
Loss development unaffected by changing
loss cost trends
No change in mix of business
No cyclical loss development
No data anomalies
Increasing delays in claim closing rates
Conscious effort to improve case reserve
adequacy;
Introduction of new case reserving
procedures
Change in data processing;
Revised claim payment recording
Increasing frequency of full policy limits
claims;
Changing policy limits
Surges in inflation;
Increased litigation;
Diminished policy defenses
Changes in reinsurance coverages;
Increased long-tail exposures;
Introduction of new or revised coverages
Claims settlement or reserving impacted
by business underwriting cycles
Catastrophic or unusual losses reflected in
loss experience;
Unusual claim settlement/reporting delays

6. Comparison of Estimated Reserves

7. Formulas to Derive IBNR Reserves
Once an estimate of ultimate loss has been obtained, the arithmetic of IBNR is simple.
Ultimate Losses
Minus
Paid Losses
Case Reserves
Ultimate Losses
Minus
Reported Losses
Unpaid Losses
Minus
Case Reserves

8. Other Reserving Methods Tested
Discussed in subsequent CLRS sessions
Expected Loss Technique
Bornhuetter-Ferguson Method
Severity/Frequency Method
Many, many others
Note that development method may also be applied to claim counts.

9. Development Method on Claim Counts

10. Reported Counts DM: RTR Factors Selected

11. Reported Counts DM: Projection

12. Reasonableness
Ultimate losses should be measured for reasonableness against relevant indicators:
premium
loss ratios
exposures or number of policies
frequency, pure premium
claim counts
severity
Assumptions & methods should be documented and subjected to sensitivity analysis.

13. Reasonableness Checks: Ultimate Loss Ratios

14. Reasonableness Checks: Frequency & Severity

15. Reasonableness Checks: Pure Premium

16. Sensitivity Analysis: Current Year Analysis
Improvements in results may stem from:
Higher rates
Lower claim frequency
Lower claim severity
Better results would appear to be present if:
Claims were being processed or paid more slowly
Case reserves were less adequate
Mix of business is different

17. Sensitivity Analysis: Ratios
Review historical relationships
Losses
Reported losses to paid
Claim counts
Settlement rate
Ratio of claims closed with no payment to total closed claims
Losses and Claim Counts
Severities or average values

18. Sensitivity Analysis: Ratios - Examples

19. Sensitivity Analysis: Rate Level Adequacy
Increases in average premium are primarily due to:
Changes in the mix of business.
Rate increases.
If the changes in average premium in the latest two years are due
to rate increases, then that would explain much of the improvement
in loss ratios.
If the changes are due to shifts in the mix of business, then the improvement
in the loss ratios may or may not be real. Further investigation would be
needed to understand what the shift was and whether the different business
types have varying loss development characteristics.

20. Sensitivity Analysis: Claim Severity
There is no consistent pattern in severity, except that it has generally increased over the years. This is typical, as we expect severity to increase due to inflation.
The very small increase in severity that is forecast for the current year is unusual. In the same year, claim frequency has increased. Perhaps there is an increase in the number of small dollar claims? This would be a good question to ask the Claim Department.

21. Sensitivity Analysis: Claim Closure Rate
In the past few years, claims have been closing more rapidly. This would imply that claims are being paid more rapidly and that the paid loss development factor is probably too high. One of the major assumptions of the PLDM (consistent payment patterns) has been violated.

22. Sensitivity Analysis: Case Reserve Adequacy

23. Sensitivity Analysis: Case Reserve Adequacy
In general, we expect increasing numbers:
1. Across the rows because smaller claims settle more quickly; and
2. Down the columns due to inflation.
It is important to understand the company’s case reserving philosophy and procedures to be able to interpret trends in the data. Many changes in case reserve procedures can be monitored by talking to the Claims Department.
Changes in case reserve adequacy affect incurred loss development patterns. For example, if case reserves were less adequate in the current accident year, greater future development would be expected for those accidents than was typical in the past. Use of historical loss development factors in this situation would underestimate future development and lead to inadequate overall reserve estimates.

24. Sensitivity Analysis: Case Reserve Adequacy
The fit of the average case 12 months implies an annualized trend rate of 19%! This rate is substantially higher than industry trend rates for private passenger automobile liability, which are in the range of 8% to 10%.

25. Frequency/Severity Projection Method
A line or another curve can be fitted through actual values for accident years 1993 through The fitted points for the current year can be used as estimates for the ultimate frequency and severity.
R-squared is a measure of how well a fitted curve matches the data. The value can range from 0 to 1.00, where 1.00 indicates a perfect fit.

26. Frequency/Severity Projection Method

27. Selection of Tail Factors
How much difference does the tail factor selection make?

28. Selection of Tail Factors
Ultimate losses increase by 2% or $1.8 million.
Loss reserves also increase by $1.8 million; however, the 2% increase in the tail factor represents a 7% increase in overall reserve levels!
IBNR reserves are increased by an even higher percentage as a result of an increase of 2% in the tail factor