Predicting motor insurance claim incidence using generalized and tree-based models: A comparative statistical approach

Predicting motor insurance claim incidence using generalized and tree-based models: A comparative statistical approach

Type of the article: Research Article AbstractAccurate prediction of motor insurance claim frequency is necessary for efficient risk management, underwriting, and policy pricing. Predictive performance of Poisson Generalized Linear Models (GLMs), Decision Trees, and Generalized Additive Models (GAM...

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Bibliographic Details
Main Author: Eslam Abdelhakim Seyam
Format: Article
Language:English
Published: LLC "CPC "Business Perspectives" 2025-08-01
Series:Insurance Markets and Companies
Subjects:
claim frequency
decision trees
generalized additive models
generalized linear models
motor insurance
predictive modeling
Online Access:https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22707/IMC_2025_02_Seyam.pdf
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https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/22707/IMC_2025_02_Seyam.pdf

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