Optimizing Automobile Insurance Pricing: A Generalized Linear Model Approach to Claim Frequency and Severity

Abstract

Morocco's insurance sector, particularly auto insurance, is experiencing significant growth despite economic challenges. To remain competitive, companies must innovate and adjust their pricing to meet customer expectations and strengthen their market position. Traditionally, actuaries have used the linear model to assess the impact of explanatory variables on the frequency and severity of claims. However, this model has limitations that do not always accurately reflect the reality of claims or costs, especially in auto insurance. Our study adopted the generalized linear model (GLM) to address these shortcomings, enabling a more precise statistical analysis that better aligns with market realities. This paper examines the application of GLM to model the total claim burden of an automobile portfolio and establish an optimal rate. The steps include data processing and analysis, segmentation of rating variables, as well as the selection of appropriate distributions using statistical tests such as the Wald test and the deviance test, all performed using SAS software.