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.
Research Date
Research Department
Research Journal
Journal of Business Analytics
Research Member
Research Publisher
Taylor & Francis publisher
Research Rank
Web of Science ( SCI Q3), Scopus (Q2)
Research Vol
7;4
Research Website
https://doi.org/10.1080/2573234X.2024.2393609
Research Year
2024
Research Abstract