使用机器学习技术的回馈贡献模型

Q2 Economics, Econometrics and Finance Journal of Islamic Monetary Economics and Finance Pub Date : 2023-09-02 DOI:10.21098/jimf.v9i3.1681
Yassine Kouach, Abderrahim El Attar, Mostafa Elhachloufi
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引用次数: 0

摘要

由于新成立的摩洛哥回教保险经营者需要管理风险,摩洛哥保险和社会福利管理局授权中央再保险公司创建一个回教保险窗口,以对回教保险业务进行再保险。然而,主要的挑战是通过确保遵守伊斯兰教法,确定适合摩洛哥伊斯兰保险部门的ReTakaful模式。考虑到这一点,本文旨在通过机器学习算法确定摩洛哥回教税行业的最佳回教税贡献模型。通过比较各算法的性能,选择最佳模型。本研究取得的结果证明了使用机器学习算法计算ReTakaful贡献的潜力,这些贡献更适合ReTakaful操作员,更适合ReTakaful操作员。
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RETAKAFUL CONTRIBUTIONS MODEL USING MACHINE LEARNING TECHNIQUES
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.
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来源期刊
CiteScore
1.90
自引率
0.00%
发文量
19
审稿时长
24 weeks
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