Supply chain strategy for managing risk for health insurance: An application of Bayesian model

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In this paper, the research done is about the risk distribution model estimation on health insurance claims using Bayesian. The objective is to derive a health insurance risk model and determine the amount of net premium for each insured age group in health insurance. The sample of this study is the participant of health insurance in the Bandung area, Indonesia, especially for the insured who live in flood-prone areas. The estimation of the Poisson and Gamma distribution parameter is performed using the Bayesian method, which Open BUGS involves Markov Chain Monte Carlo (MCMC) the simulation technique.

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