Preliminary selection of risk factors in P&C ratemaking

Florian Pechon (), Julien Trufin and Michel Denuit ()
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Florian Pechon: Université catholique de Louvain, LIDAM/ISBA, Belgium
Julien Trufin: ULB
Michel Denuit: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2020014, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: This paper proposes efficient statistical tools to detect which risk factors influence insurance losses before fitting a regression 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: Simulation; Copulas/Multi-Variate Distributions; Risk Pricing; Risk Evaluation Models (search for similar items in EconPapers)
Date: 2020-07-03
Note: In: Variance : advancing the science of risk - Vol. 13, no.1, p. 124-14 (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2020014

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