Fuzzy Trends in Property-Liability Insurance Claim Costs

Accuracy in forecasting expected loss costs may well be the most important determinant of the ultimate profitability of a cohort of property-liability insurance policies. The existing literature on claim cost forecasting focuses on the selection of the "best" forecasting model or method, discarding information provided by closely ranked alternatives. In this article, we emphasize the selection of a "good" forecast rather than a forecasting model, where goodness is defined using multiple criteria that may be vague or fuzzy. Fuzzy set theory is proposed as a mechanism for combining forecasts from alternative models using multiple fuzzy criteria. The fuzzy approach is illustrated using forecasts of automobile bodily injury liability pure premiums. We conclude that fuzzy set theory provides an effective method for combining statistical and judgmental criteria in actuarial decision making.

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