2006 Seminar on Reinsurance
Parameter Risk – Where Does it
Come From and Why
Rich Lino
Consulting Actuary, Pinnacle Actuarial Resources
Sources of Parameter Risk
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Catastrophe exposure
Pricing
Loss development
Changes in business mix
Other changes in parameter risk
Actions to mitigate parameter risk
Catastrophe Risk
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Accuracy of exposure data
Weather cycles: 2006 predictions are for
150% to 200% of last century average (ISODr. Gray)
Model revisions
Impact of growth in exposed areas
Earthquake below long-term average?
PCS Loss To Property Direct WP
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
`
19731988
19891996
19972005
19732005
Source: ISO-PCS for Cat; AM Best for DWP
Pricing
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Average price level change
Impact of changes in terms/conditions/limits
Miscoding of class, tier, E&S Vs. Standard Lines
Price monitor for new business
Changes in mix of business
Winner’s Curse
Direct Writtten Premium - Property to Nominal GDP
1.00%
0.95%
0.90%
0.85%
0.80%
0.75%
0.70%
0.65%
Source: AM Best DWP; Property Estimated; BEA GDP
20
05
20
03
20
01
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
19
83
19
81
19
79
19
77
19
75
19
73
0.60%
CMP Accident Year Net Ultimate Loss and ALAE Ratio (LHS).
Direct Earned Premium and AY Loss Amount to GDP (Right Scale).
150%
4.50
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
-
Loss Ratio
125%
100%
75%
50%
1975
1980
1985
1990
1995
Years
Loss Ratio
CY DEP
AY Loss
2000
Per $1,000 GDP
Source: AM Best and Pinnacle Estimates
Loss Development
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Cycle- Reserve weakening, payment slowdown
will bias ultimates on the low side in soft markets
and vice versa
Variations by Company – Base, Cycle
Variations by Layer
Changes in terms/conditions/limits can affect
development
Industry Aggregate-Med Mal Total
Ultimate Using "LDFs As Of Y/E" Vs. 2004 Estimate of Ultimate
Data As Of
Incurred LDFs
Year-End
AY x
AY x-1
AY x-2
1996
85%
96%
98%
1997
86%
88%
92%
1998
81%
86%
88%
1999
80%
83%
88%
2000
87%
91%
89%
2001
94%
98%
99%
Mean
85%
90%
92%
Changes in Business Mix
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Prices declining, more exposure per premium
dollar
More adverse winner’s curse causes lower
retention
Lower retention means more new business per
premium dollar
Severe winner’s curse on new business
Failure to adjust creates parameter risk
Drivers of Parameter Risk - WC
Base
1997-2000
2000-2003
Base Price Vs. Exposure
0%
-4%
6%
Tiers/Schedule Rating
0%
-10%
9%
R/N Retention
80%
86%
82%
R/N Quality
97%
98%
92%
New Business %
20%
35%
15%
New Quality Vs. Renewal
115%
130%
118%
Parameter Risk From Reinsurer’s Perspective
Other Potential For Parameter Risk
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Offering limits not previously available
Value of information not provided (cyclical)
Buy downs of limit – asymmetric information
Self-insurers moving in and out of the market
Impact of acquisitions on pricing assumptions
Cycle of ISO/NCCI pricing adequacy
MGA cycle
Optimism/pessimism cycle
Other Potential For Parameter Risk, cont’d
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Multi-year policies – direct and assumed
Loosening terms and conditions
Loosening underwriting standards
Adverse selection as top tier companies
refine rating structures
Impact of changing mix of TPAs
Beware high growth and “fighting claims”
Actions to mitigate parameter risk
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Measure all aspects of price change
Monitor industry and client reserve adequacy
Monitor total change in industry price & L/R
Focus audits on new business
Model impact of winner’s curse in soft market
Pursue identification of turning points
Set data quality standards and keep them
Refine pricing by account
Source: Pinnacle calculations from AM Best data base