DocumentCode :
1916159
Title :
Computational modeling of 1994 A.M. Best life/health insurer ratings
Author :
Sabot, Gary
Author_Institution :
Sabot Assoc. Inc., Weston, MA, USA
fYear :
1997
fDate :
23-25 Mar 1997
Firstpage :
107
Lastpage :
115
Abstract :
The insurance industry is the major intermediator of long term credit in the U.S., and insurance ratings agencies have become powerful de facto regulators of insurance company investment policy and hence of capital allocation for the economy as a whole. If the rating process can be shown to be dishonest, arbitrary, or even simply lacking in rigor, the implications for the proper role of insurance ratings in capital markets are highly significant. The article examines the relationship between the A.M. Best Company´s assigned Life/Health insurer ratings, 1994 edition, and the hundreds of quantitative and qualitative factors that A.M. Best discusses in its explanation of its rating system. The results indicate that company ratings are largely determined by company size and cash flow. Using tree modeling with only a few quantitative factors, with no additional qualitative input, it was possible to predict 49% of insurer´s A.M. Best ratings exactly, and 99% if a miss by one rating in either direction is allowed. A simpler linear model was able to predict ratings with corresponding accuracies of 98% and 82%
Keywords :
digital simulation; financial data processing; insurance data processing; investment; modelling; 1994 A.M. Best life/health insurer ratings; capital allocation; capital markets; cash flow; company size; computational modeling; de facto regulators; economy; insurance company investment policy; insurance industry; insurance ratings agencies; linear model; long term credit; qualitative factors; quantitative factors; ratings prediction; tree modeling; Asset management; Books; Computational modeling; Insurance; Investments; Predictive models; Publishing; Regulators; Tail; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Financial Engineering (CIFEr), 1997., Proceedings of the IEEE/IAFE 1997
Conference_Location :
New York City, NY
Print_ISBN :
0-7803-4133-3
Type :
conf
DOI :
10.1109/CIFER.1997.618922
Filename :
618922
Link To Document :
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