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Enhancing operational efficiency of insurance companies: a fuzzy time series approach to loss ratio forecasting in the Egyptian market

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  • Ahmed A. Khalil
  • Zaiming Liu
  • Ahmed Ali

Abstract

This article analyses the crucial significance of loss ratio (LR) evaluation in assessing the operational efficiency of insurance companies. Fuzzy time series (FTS) models are effective in modelling non-linear with uncertainties and providing adequate performance with limited data availability, which overcomes the shortage of conventional models used in Egyptian insurance market literature. This paper aims to introduce a comprehensive analysis of LR of the property and casualty sectors. Moreover, review and compare various forecasting FTS techniques to discuss the effectiveness of using FTS methods in forecasting LR. The suggested method is based on results from tests done with four models that had Huarng 465 partitions and interval length parts of 5, 10, 50, and 100. The results show LR prediction improved significantly. Yu and Cheng’s models using a Huarng 465 partition for training data and the Yu model with 100 partitions for testing data had high accuracy and low error.

Suggested Citation

  • Ahmed A. Khalil & Zaiming Liu & Ahmed Ali, 2024. "Enhancing operational efficiency of insurance companies: a fuzzy time series approach to loss ratio forecasting in the Egyptian market," Journal of Business Analytics, Taylor & Francis Journals, vol. 7(4), pages 318-336, October.
    • Handle: RePEc:taf:tjbaxx:v:7:y:2024:i:4:p:318-336
    DOI: 10.1080/2573234X.2024.2393609
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