Strategic Reinsurance and Explainable AI

This study explores the strategic determinants that impact reinsurance purchase decisions in the P&C insurance industry using the Shapley Additive exPlanations explainable artificial-intelligence (XAI) framework, or SHAP library. Key determinants such as financial considerations, competition, and industry demand for reinsurance are considered to identify their impact on different levels of ceding. The XAI process ranks these determinants based on their influence on reinsurance purchases, and identifies clear relationships between these determinants and ceding levels. For instance, an increase in writing a specific product type can lead to a lower incentive to hedge more within that product type. Additionally, this methodology also reveals more complex relationships between determinants and reinsurance purchases based on their values. Finally, the study includes a machine learning significance test for each determinant impacting insurance purchases.

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Publication Details

Journal
Journal of Finance Issues
Published
2025-09-17
DOI
https://doi.org/10.58886/jfi.v23i2.10099
Primary Topic
Insurance and Financial Risk Management
Type
article
Field-Weighted Citation Impact
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article

Strategic Reinsurance and Explainable AI

Eric R. Brisker, Sampan Nettayanun
Journal of Finance Issues
Insurance and Financial Risk Management
article

Strategic Reinsurance and Explainable AI

Eric R. Brisker, Sampan Nettayanun
article en

Abstract

This study explores the strategic determinants that impact reinsurance purchase decisions in the P&C insurance industry using the Shapley Additive exPlanations explainable artificial-intelligence (XAI) framework, or SHAP library. Key determinants such as financial considerations, competition, and industry demand for reinsurance are considered to identify their impact on different levels of ceding. The XAI process ranks these determinants based on their influence on reinsurance purchases, and identifies clear relationships between these determinants and ceding levels. For instance, an increase in writing a specific product type can lead to a lower incentive to hedge more within that product type. Additionally, this methodology also reveals more complex relationships between determinants and reinsurance purchases based on their values. Finally, the study includes a machine learning significance test for each determinant impacting insurance purchases.

Journal of Finance IssuesVol. 23(2)
University of Akron (US), Naresuan University Hospital (TH)
Openalex Percentile: Top 66%
Insurance and Financial Risk Management
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Strategic Reinsurance and Explainable AI — Eric R. Brisker, Sampan Nettayanun · Journal of Finance Issues (2025) | TGRS Research Map | TGRS