Fuzzy Techniques of Pattern Recognition in Risk and Claim Classification - Proceedings AFIR 1994 - Orlando, United States

Applications of fuzzy set theory (FST) to property casualty and life insurance have emerged in the last few years through the work of Lemaire (1990), Cummins and Derrig (1991, 1993) and Ostaszewski (1993). This paper continues that line of research by providing an overview of fuzzy pattern recognition techniques. We utilize them in clustering for risk and claim classification. The classic clustering problem of grouping towns into rating territories (DuMouchel (1983), Conger (1987)) is revisited using these fuzzy methods and 1988-1991 Massachusetts automobile insurance data. The new problem of classifying claims in terms of suspected fraud is also addressed using these same fuzzy methods and data drawn from a study of 1989 bodily injury liability claims in Massachusetts.