Insurance Claim Classification: A new Genetic Programming Approach

Advances in Mathematical Finance and Applications

مقاله 11، دوره 7، شماره 2، تیر 2022، صفحه 437-446   

نوع مقاله: َApplied-Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2021.1927097.1580

نویسندگان

Alireza Bahiraie^{* 1}؛ Farbod Khanizadeh²؛ Farzan Khamesian²

¹Faculty of Mathematics, Statistics & Computer Science, Semnan University 35131-19111, Semnan, Iran

²Insurance Research Centre (IRC), Tehran 1998758513, Iran

چکیده

In this study we provide insurance companies with a tool to classify the risk level and predict the possibility of future claims. The support vector machine (SVM) and genetic programming (GP) are two approaches used for the analysis. Basically, in Iran insurance industry there is no systematic strategy to evaluate the car body insurance policy. Companies refer mainly to the world experience and employ it to rate the premium. An insurance claim dataset provided by an Iranian insurance company with a sample size of 37904 is considered for programming and analysis. According to the structure of the dataset, a supervised learning algorithm was used to describe the underlying relationships between variables.

کلیدواژه‌ها

Genetic Programming؛ Supervised Learning؛ Classification؛ Insurance Claim

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