RETAKAFUL CONTRIBUTIONS MODEL USING MACHINE LEARNING TECHNIQUES

Kouach Yassine (), Attar Abderrahim El () and Hachloufi Mostafa El ()
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Kouach Yassine: University Hassan II of Casablanca, Morocco
Attar Abderrahim El: University of Hassan II Casablanca, Morocco
Hachloufi Mostafa El: University of Hassan II Casablanca, Morocco

Journal of Islamic Monetary Economics and Finance, 2023, vol. 9, issue 3, 511 - 532

Abstract: Driven by the need to manage risk by the newly created Moroccan Takaful operators, the Moroccan Insurance and Social Welfare Control Authority has authorized the Central Reinsurance Company to create a ReTakaful window for the purpose of reinsuring Takaful operations. Nevertheless, the main challenge is determining the appropriate ReTakaful model for the Moroccan Islamic insurance sector by ensuring compliance with Shariah. With this in mind, this article aims to determine the optimal ReTakaful contributions model for the Moroccan Takaful industry via Machine Learning algorithms. We select the best model by comparing the performance of each algorithm. The achieved results of this study demonstrate the potential of using Machine Learning algorithms to compute ReTakaful contributions that are more suitable for Takaful operators and more optimal for the ReTakaful operator.

Keywords: ReTakaful; Takaful; Reinsurance; Treaty; Machine learning; Probability of ruin (search for similar items in EconPapers)
JEL-codes: C51 C52 C53 G22 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:idn:jimfjn:v:9:y:2023:i:3g:p:511-532

DOI: 10.21098/jimf.v9i3.1681

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