Modeling Vehicle Accident Risks in Auto Insurance: An Application of Generalized Linear Models in the Context of the National Insurance Company, Regional Directorate of Setif, Algeria

This study investigates risk distribution models in the context of auto insurance in emerging markets, with a focus on the National Insurance Company (SAA), regional directorate of Setif, Algeria.The research applies generalized linear models (GLM) and factor analysis to model the frequency of vehicle accidents and their associated risks.A comprehensive approach is employed, beginning with a discussion of the techniques used for data collection and preliminary descriptive analysis.Following this, a theoretical framework is established for understanding the risk distribution models, highlighting the role of GLM in the modelling of accident frequencies within the insurance industry.Different types of factor analysis, including basic coefficient analysis, cross-factor analysis, generalized cross-factor analysis, and mixed factor analysis, are examined in relation to their applicability to insurance risk modelling.Subsequently, generalized linear models are implemented to derive a robust model for accident frequency, utilizing R software for analysis.The results reveal that the pricing system of the National Insurance Company is influenced by multiple, non-deterministic factors, which complicate the prediction of accident rates and insurance costs.These findings underscore the importance of incorporating various risk factors into pricing strategies, rather than relying on deterministic models.The study highlights the necessity of considering a broader range of factors in the development of pricing systems, particularly in emerging markets where data may be incomplete or subject to considerable variability.Furthermore, the use of Mixed Poisson models is suggested as an effective approach for capturing the non-linear relationship between various risk factors and accident occurrence.This research contributes to the existing body of knowledge by providing a nuanced understanding of the application of GLM and factor analysis in the auto insurance sector, particularly in emerging markets.