An Alternative Pricing System through Bayesian Estimates and Method of Moments in a Bonus-Malus Framework for the Ghanaian Auto Insurance Market

Azaare Jacob and Zhao Wu
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Azaare Jacob: School of Management and Economics, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West High- Tech Zone, Chengdu 611731, China
Zhao Wu: School of Management and Economics, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West High- Tech Zone, Chengdu 611731, China

JRFM, 2020, vol. 13, issue 7, 1-15

Abstract: This paper examines the current No-Claim Discount (NCD) system used in Ghana’s auto insurance market as inefficient and outmoded and, therefore, proposes an alternative optimal Bonus-Malus System (BMS) intended to meet the present market conditions and demand. It appears that the existing BMS fails to acknowledge the frequency and severity of policyholders’ claims in its design. We minimized the auto insurance portfolios’ risk through Bayesian estimation and found that the risk is well fitted by gamma, with the claim distribution modeled by the negative binomial law with the expected number of claims (a priori) as 14%. The models presented in this paper recognize the longevity of accident-free driving and fully reward higher discounts to policyholders from the second year when the true characteristics of the hidden risks posed to the pool have been ascertained. The BMS finally constructed using the net premium principle is very optimal and has reasonable punishment and rewards for both good and bad drivers, which could also be useful in other developing economies.

Keywords: bonus-malus system; Ghana; Bayesian estimation; negative binomial distribution; auto insurance; Markovian process (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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