Technical reserving in health insurance: A bootstrap approach

Authors

  • Ayyoub SAOUDI University Hassan 1st, Faculty of Economics and Management, LM2CE, Settat, Morocco
  • Fatima El Kassimi University Hassan 1st, Faculty of Economics and Management, LM2CE, Settat, Morocco
  • Jamal ZAHI University Hassan 1st, Faculty of Economics and Management, LM2CE, Settat, Morocco

Keywords:

Bootstrap, Technical reserves, Health insurance

Abstract

Bootstrap methods have long been used by actuaries to estimate technical reserves. The present work aims to illustrate the use of this method in health insurance, by exploiting the portfolio of claims paid by the insureds of a Moroccan mutual health insurance company over 12 months. This article aims to highlight the advantages of using the Bootstrap algorithm to predict the distribution of future claims expenses and estimate the standard error, to guarantee the solvency of the mutual in question and maintain its ability to meet these future commitments. The probability distribution used in this work is the Log-Normal, as it is best suited to the claims experience studied. Using this distribution, the ultimate cost of claims, the claims reserve, and its standard error have been estimated.

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References

A. SAOUDI, F. EL KASSIMI et J. ZAHI, «Technical reserving in nonlife insurance: A literature review of aggregated,» Journal of Integrated Studies In Economics, Law, Technical Sciences & Communication, 2023.

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T. Mack, «The standard error of Chain Ladder reserve estimates: recursive calculation and inclusion of a tail factor,» Astin Bulletin, p. 361–366, 1999.

Z. ORIANA, R. ENDRI, H. KLEIDA, L. ETLEVA et H. KOSTAQ, «Bootstrap Methods for Claims Reserving: R Language Approach,» WSEAS TRANSACTIONS on MATHEMATICS, pp. 252-259, 2022.

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Shapland et R. Mark, Using the ODP Bootstrap Model: A Practitioner’s Guide, Arlington, Virginia: Casualty Actuarial Society, 2016.

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Published

2023-07-06

How to Cite

SAOUDI, A., El Kassimi, F., & ZAHI, J. . (2023). Technical reserving in health insurance: A bootstrap approach. International Journal of Computer Engineering and Data Science (IJCEDS), 3(1), 13–17. Retrieved from https://ijceds.com/ijceds/article/view/55