Insurance Claim Classification: A new Genetic Programming Approach

محورهای موضوعی : Risk Management

Alireza Bahiraie ¹ (Faculty of Mathematics, Statistics & Computer Science, Semnan University 35131-19111, Semnan, Iran)
Farbod Khanizadeh ² (Insurance Research Centre (IRC), Tehran 1998758513, Iran)
Farzan Khamesian ³ (Insurance Research Centre (IRC), Tehran 1998758513, Iran)

تاریخ دریافت : 1400/01/14 تاریخ پذیرش : 1400/06/16 تاریخ انتشار : 1401/01/12

کلید واژه: Genetic Programming, Insurance Claim, Classification, supervised Learning,

چکیده مقاله :

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.

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