This Research Summary was first published in the IIB Bulletin, 2015, Vol. 1, Iss. 3, pp8-9
https://iib.gov.in/IRDA/Articles/IIB%20Bulletin%20Q3%202014-15.pdfCo-Author: Vishnuvardhan Pallreddy, IIB
Joseph A. Boor, FCAS, Ph.D. has been a working
casualty actuary since 1979 and a Fellow of the Casualty Actuarial Society
since 1988. Over a long and varied career he has had roles as diverse as
regulator, Chief Actuary, consultant, and regional actuary. Currently, he works
as an actuary for the Office of Insurance Regulation of the State of Florida in
Tallahassee, Florida. He is the author of several published articles, including
theoretical contributions to the theory of credibility and the optimum
weightings of years of data and single-topic ratemaking papers on the
complement of credibility in pricing and tail factors in loss reserving. He has
a Bachelor’s of Arts degree in Mathematics from Southern Illinois University in
Carbondale, a Master of Science degree in Mathematics from Florida State
University, and a Doctor of Mathematics degree from Florida State University.
Complements have a special role in ratemaking
exercises where the data is sparse or has high deviation from the mean over the
years and hence has low credibility. “The Complement of Credibility” paper by
Joseph A. Boor (1996) provides a good overview of the qualities and
effectiveness of a good credibility complement and explains different
credibility components commonly used. The paper also looks at the practical
aspects of selecting a complement.
Overview
According to the paper, “The complement of the
credibility deserves at least as much actuarial attention as the base statistic
(historical loss data)”. Special attention should be given to its unbiasedness and
accuracy. In some cases, interdependence must be avoided. Ease of computation
and implementation must be reasonable. Explainability of statistics used must
be considered, too.
Fundamental
Principles
The paper explains a few issues that an Actuary must
consider before selecting the complement of credibility:
Practical Issues: Complement should be readily
available. The best possible statistic to use is the next year’s loss costs
which are unknown. It has to be chosen from the available statistics. Ease of
computation would also be a factor to consider as it involves time, costs and
also increased chances of error.
Competitive Market Issues: The rates that are
eventually produced will be subject to market competition. If rates are too
high or too low, the outcome will not be desirable. So, the rate should be
neither too high nor too low over a large number of loss cost estimates
(unbiasedness) and the rate should have as low an error variance as possible
(accuracy).
Regulatory Issues: Regulators typically
require that the rates are not inadequate, not excessive, and not unfairly
discriminatory. This implies that rates should be as unbiased as possible. It
could also be implied that rates should be as accurate as possible, as highly
inaccurate rates pose a greater risk of insolvency through random inadequacies.
Statistical Issues: For greater accuracy,
error variance should be lower. If complement of credibility has low error
variance in its own right and relatively independent of base statistic (which
receives the credibility), the resulting rate will be more accurate.
When both the base statistic and complement are
unbiased, the predictions are generally best when there is actually a negative
correlation between the two errors (that is, they offset) but this rarely
occurs in practice. So, a complement of credibility is best when it is
statistically independent of the base statistic.
Based on the above four issue that must be considered
by an Actuary when selecting a complement, Boor summarizes the desirable
qualities that a complement of credibility should have:
1. Accuracy
as predictor of next year’s mean loss costs
2. Unbiasedness
as a predictor of next year’s mean subject expected losses
3. Independence
from the base statistic
4. Availability
of data
5. Ease
of computation
6. Explainable
relationship to the subject loss costs
Commonly used
Components
Boor goes on to compare different types of
complements used by Actuaries for First Dollar Ratemaking and Excess
Ratemaking. Few often used methods for First Dollar ratemaking discussed in the
paper are:
·
Using loss costs of a larger group including the
class-Bayesian Credibility
·
Using loss costs of a larger related class
·
Harwayne’s method
·
Trending present rates
·
Applying the rate change from a larger group to
present rates; and
·
Using competitors’ rates
For Excess Ratemaking, the four methods discussed in
the paper are:
·
Increased limits factors
·
Derivation from a lower limits analysis
·
Analysis reflecting the policy limits sold by
the insurer; and
·
Fitted curves
The use of the complement of credibility may differ
from case to case, depending on the “availability of data” and reasonability of
effort. For example, in the case of excess (or large) losses, fitted curves
uses data available with the Insurers and is generally unbiased, but is complex
to compute and may be difficult to communicate as well.
For pure premium ratemaking, using competitors’’
rates may be easy to use, especially for new companies or companies with low
experience, but may suffer from inter-company difference in portfolio mix and
may be harder to obtain.
“In Harwayne’s method, actuaries use countrywide
(excepting the base state being reviewed) class data to supplement the loss
cost data for each class, but they adjust countrywide data to remove overall
lost cost differences between states (or provinces)”.
Many such practical insights on the above listed
methods are provided in the paper along with the model itself and examples. As
the Indian market moves towards an era of ratemaking, his paper is a valuable
guide to the choice of a complement of credibility. The paper can be read at
the following link: https://www.casact.org/pubs/proceed/proceed96/96001.pdf
Reference:
Boor, Joseph. A., “The
Complement of Credibility" (Proceedings of the Casualty Actuarial Society,
Vol. LXXXIII, Part 1, No. 158, 1996,
32p; https://www.casact.org/pubs/proceed/proceed96/96001.pdf
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