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Auto Insurance Claims Modeling Techniques by Francesco Castellani is a document available to read on EtoBox.

This document summarizes a study that models the frequency of auto insurance claims using Poisson and negative binomial models. The study uses data from a French auto insurance portfolio to estimate models for claim frequency. It finds that the negative binomial model provides a better fit for the data compared to the Poisson model, due to overdispersion in the data. The study identifies several risk factors that influence claim frequency, such as the age, gender, occupation and location of the policyholder

Author
Francesco Castellani
Language
EN