The partial damage loss cover ratemaking of the automobile insurance using generalized linear models

TL;DR

This paper presents a methodology using generalized linear models to accurately estimate pure premiums for partial damage cover in automobile insurance, considering various influential factors.

Contribution

It introduces a novel approach to compute pure premiums for partial damage loss cover using GLMs with specific influential variables identified.

Findings

Key variables affecting claim frequency include car age, insured's age, and region.

Claim severity is most influenced by car value, type, make, and insured's gender.

The methodology provides a structured way to estimate premiums based on multiple factors.

Abstract

It is illustrated a methodology to compute the pure premium for the automobile insurance (claim frequency and severity) using generalized linear models. It is obtained the pure premium for the partial damage loss cover (PPD) using a set of automobile insurance policies with an exposition of a year. It is found that the most influential variables in the claim frequency are the car production year, the insured's age, and the region's subscription policy and the most influential variables in the claim severity are the car's value, type and make and the insured's gender.