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Bayesian analysis of insurance risk model with parameter uncertainty
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 Title & Authors
Bayesian analysis of insurance risk model with parameter uncertainty
Cho, Jaerin; Ji, Hyesu; Lee, Hangsuck;
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In the Heckman-Meyers model, which is frequently referred by IAA, Swiss Solvency Test, EU Solvency II, the assumption of parameter distribution is key factor. While in theory Bayesian analysis somewhat reflects parameter uncertainty using prior distribution, it is often the case where both Heckman-Meyers and Bayesian are necessary to better manage the parameter uncertainty. Therefore, this paper proposes the use of Bayesian H-M CRM, a combination of Heckman-Meyers model and Bayesian, and analyzes its efficiency.
Bayesian;CRM;insurance risk;parameter uncertainty risk;
 Cited by
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