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Deriving Credibility Premiums Under Different Bayesian Methodology

Emilio Gómez Déeniz

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Abstract

Credibility theory is a set of quantitative methods that allows an insurer to adjust future premiums based on past experience. Generally, the credibility expression obtained is written as a weighted sum of the sample mean and the collective premium, the premium to be charged to a collective of policyholders in a portfolio. The weighted factor is referred to as the credibility factor. In this paper, a review of credibility theory is presented and new credibility formulae are obtained in a simple and extensive Bayesian methodology.

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Credibility theory is a set of quantitative methods that allows an insurer to adjust future premiums based on past experience. Generally, the credibility expression obtained is written as a weighted sum of the sample mean and the collective premium, the premium to be charged to a collective of policyholders in a portfolio. The weighted factor is referred to as the credibility factor. In this paper, a review of credibility theory is presented and new credibility formulae are obtained in a simple and extensive Bayesian methodology.

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Available abstract

Credibility theory is a set of quantitative methods that allows an insurer to adjust future premiums based on past experience. Generally, the credibility expression obtained is written as a weighted sum of the sample mean and the collective premium, the premium to be charged to a collective of policyholders in a portfolio. The weighted factor is referred to as the credibility factor. In this paper, a review of credibility theory is presented and new credibility formulae are obtained in a simple and extensive Bayesian methodology.

Key concepts: Credibility, Credibility theory, Bayesian probability, Portfolio, Set (abstract data type), Econometrics, Expression (computer science), Modern portfolio theory

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