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Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and em-pirical Bayes estimates produce by matching rst and second empirical moments; subsequently, a constrainedBayes estimate is recommended to use in case the research objective is to produce a histogram of the estimatesconsidering the location and dispersion. The well-known squared error loss function exclusively emphasizes theprecisionofestimationandmayleadtobiasedestimators. Thus, thebalanced lossfunction issuggestedto reectboth goodness of t and precision of estimation. In insurance pricing, the accurate location estimates of riskand also dispersion estimates of each risk group should be considered under proper loss function. In this paper,by applying these two ideas, the benet of the constrained Bayes estimates and balanced loss function will bediscussed; in addition, application eectiveness will be proved through an analysis of real insurance accidentdata.Keywords: Balanced loss function, constrained Bayes estimate, insurance pricing.

Application of Constrained Bayes Estimation under Balanced Loss Function in Insurance Pricing