Machine learning based methods for ratemaking health care insurance
Amal Ben Hamida,
Manel Kacem,
Christian de Peretti
et al.
Abstract:In insurance, proposing an accurate premium that is adjusted to the insured risk profile allows companies to better manage their portfolios and to be more competitive. Machine learning methods have recently been adopted for various improvements in insurance ratemaking, especially in the automobile industry. These models are specifically used to mine potential data information and to build a predictive model for a variable of interest using explanatory variables. In this paper, we aim to provide a pricing metho… Show more
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