• 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