Determining the Credibility Factor and Premium Using Bayesian Credibility Theory for Policy Decisions and Implementation: Evidence from Ghana

Abstract

Estimates of future expected values are always dependent on the distribution of insurance claims. Therefore, the importance of determining these distributions cannot be overemphasized. This study seeks to determine the credibility factor and premium using Bayesian credibility theory. Secondary data collected from Dormaa Municipal Health Insurance Scheme and Dormaa Presbyterian Hospital was analyzed using the Statistical Package for Social Science (SPSS), Excel spreadsheet, Easy fit by applying Bayesian credibility theory through descriptive analysis and frequency distribution.

It was found that the data submitted by 28 health facilities to Dormaa Municipal Health Insurance Scheme follows Normal Distribution and the sample claims from Dormaa Presbyterian Hospital follows lognormal distribution. The posterior distribution for the municipal health Insurance Scheme was also found to be normal distribution. The credibility factor estimate was 0.830 indicating that there is more reliance on the sample used. With this credibility factor, the expected Aggregate premium is supposed to be 24.281 Ghana Cedis.