Author
Listed:
- Reza Hajipour Farsangi
- Ghadir Mahdavi
- Majid Jafari Khaledi
- Murat Büyükyazıcı
- Mitra Ghanbarzadeh
Abstract
Purpose - This study aims to price the risk contribution of general Takaful at the level of tariff cells, considering a spatial dependency framework. Design/methodology/approach - Three different models, including a generalized linear model, a generalized linear mixed model (GLMM) and a spatial generalized linear mixed model (SGLMM), according to the actuarial modeling of general Takaful, are used to price pure risk contribution (PRC). Findings - The results reveal that the SGLMM yields more accurate predictions of the PRC compared to the other models, emphasizing the significance of spatial modeling in this context. Following the estimation of the PRC, the gross contribution according to the mechanism of Takaful models is calculated considering the spatial model. Practical implications - Considering the similarities between Takaful and insurance, this study addresses the pricing of general Takaful within different Takaful models through a spatial dependency framework, such that the practical implications of the study are applicable for running Takaful's business in both Islamic and non-Islamic countries. Originality/value - Most studies consider only the social or practical view of Takaful. This study contributes to the broader knowledge and understanding of Takaful by presenting a conceptual understanding of Takaful and then investigates the practical application of pricing risk contribution using innovative modeling of claim frequency and severity at the level of tariff cells.
Suggested Citation
Reza Hajipour Farsangi & Ghadir Mahdavi & Majid Jafari Khaledi & Murat Büyükyazıcı & Mitra Ghanbarzadeh, 2024.
"Pricing risk contribution of general Takaful by spatial generalized linear mixed models at the level of tariff cells,"
International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 17(4), pages 811-830, July.
Handle:
RePEc:eme:imefmp:imefm-01-2024-0027
DOI: 10.1108/IMEFM-01-2024-0027
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