Health insurance pricing using CART decision trees algorithm

Authors

  • Fatima EL KASSIMI Université Hassan premier
  • Jamal ZAHI University Hassan 1st, Faculty of Economics and Management, LM2CE

Keywords:

Pricing, health insurance, machine learning, decision tree, CART.

Abstract

Compulsory health insurance is intended to cover, in terms of medical care and expenditures, a heterogeneous set of insureds in terms of their health status; these insureds present different levels of risk and a wide range of health conditions. However, in Morocco, compulsory levies are collected independently of the health status, making low-risk people bear the cost of care instead of high-risked ones. Nevertheless, these levies must be based on the risk presented by the insured so that the rate of contribution is proportional to the risk that the insurance company bears. The purpose of this paper is to propose a different approach to pricing in health insurance, based on machine learning methods, namely CART algorithm.

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Published

2022-09-27

How to Cite

EL KASSIMI, F., & ZAHI, J. . (2022). Health insurance pricing using CART decision trees algorithm. International Journal of Computer Engineering and Data Science (IJCEDS), 2(3). Retrieved from https://ijceds.com/ijceds/article/view/45

Issue

Vol. 2 No. 3 (2022): Volume 2. Issue 3

Section

Articles

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Copyright (c) 2022 Fatima EL KASSIMI, Jamal ZAHI

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