Title of article
Insurance Claim Classification: A new Genetic Programming Approach
Author/Authors
Bahiraie, Alireza Faculty of Mathematics, Statistics & Computer Science - Semnan University, Semnan , Khanizadeh, Farbod Insurance Research Centre (IRC), Tehran , Khamesian, Farzan Insurance Research Centre (IRC), Tehran
Pages
10
From page
437
To page
446
Abstract
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.
Keywords
Genetic Programming , Supervised Learning , Classification
Journal title
Advances in Mathematical Finance and Applications
Serial Year
2022
Record number
2702153
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