Risk Classification by Fuzzy Inference

Per-Johan Horgby
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Per-Johan Horgby: Department of Economics, School of Economics and Commercial Law, Göteborg University, Vasagatan 1, S-411 80 Göteborg, Sweden

The Geneva Risk and Insurance Review, 1998, vol. 23, issue 1, 63-82

Abstract: Traditionally, policyholders in life insurance are classified in simple mortality tables, most often according to only a few risk characteristics. Instead of a risk classification according to the numerical rating system, this article describes how to classify by using a fuzzy inference methodology. By defining risk factors as fuzzy sets, it is shown that an insurer can utilize multiple prognostic factors that are imprecise and vague. The presented fuzzy risk classification provides a more realistic way of modeling mortality risks since it allows for compensations and interactions between multiple risk factors. The Geneva Papers on Risk and Insurance Theory (1998) 23, 63–82. doi:10.1023/A:1008682014796

Date: 1998
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