Preliminary Selection of Risk Factors in P&C Ratemaking

By Florian Pechon, Julien Trufin, Michel Denuit

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Abstract

This paper proposes efficient statistical tools to detect which risk factors influence insurance losses before fitting a regres-sion model. The statistical procedures are nonparametric and designed according to the format of the variables commonly encountered in P&C ratemaking: continuous, integer-valued (or discrete) or categorical. The proposed approach improves the current practice favoring chi-square independence tests in contingency tables, avoiding the arbitrary preliminary banding of the variables under consideration. An example with motor insurance data illustrates the usefulness of the tools proposed in this paper. One of the conclusions of this numerical illustration is that zero-modified regression models are necessary to capture the impact of risk factors.

Keywords Risk classification, variable selection, Cramer’s V, likelihood ratio test, Cramer-von Mises statistics, copulas

Citation

Pechon, Florian, Julien Trufin, and Michel Denuit, "Preliminary Selection of Risk Factors in P&C Ratemaking," Variance 13:1, 2020, pp. 124-140.

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Mission Statement

Variance (ISSN 1940-6452) is a peer-reviewed journal published by the Casualty Actuarial Society to disseminate work of interest to casualty actuaries worldwide. The focus of Variance is original practical and theoretical research in casualty actuarial science. Significant survey or similar articles are also considered for publication. Membership in the Casualty Actuarial Society is not a prerequisite for submitting papers to the journal and submissions by non-CAS members is encouraged.