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Optimal Bonus-Malus System Design in Motor Third-Party Liability Insurance in Turkey: Negative Binomial Model

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  • Serpil Bülbül
  • Kemal Baykal

Abstract

One of the most significant instruments used in motor third-party liability insurance rating is bonus-malus system. The aim of the bonus-malus system is to provide a fairness of the premiums paid by ensuring everyone pays a premium that corresponds exactly to their own claim frequency. A balance of total amount of bonuses and maluses is very important to maintain the financial stability of the insurance companies. In Turkey, free tariff regime in motor third-party liability insurance has been adopted since 2014. In this study, an experience rating was employed via the insured’s individual claim experience by considering the drawbacks of using mandatory bonus-malus system. Data entailing information about the claim frequencies of automobiles over a year for motor third party liability policies were obtained from an insurance company. Optimal bonus-malus rates are determined by negative binomial model by using credibility theory, Bayesian approach and the principle of expected value premium.

Suggested Citation

  • Serpil Bülbül & Kemal Baykal, 2016. "Optimal Bonus-Malus System Design in Motor Third-Party Liability Insurance in Turkey: Negative Binomial Model," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(8), pages 205-205, August.
    • Handle: RePEc:ibn:ijefaa:v:8:y:2016:i:8:p:205
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    References listed on IDEAS

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    6. Frangos, Nicholas E. & Vrontos, Spyridon D., 2001. "Design of Optimal Bonus-Malus Systems With a Frequency and a Severity Component On an Individual Basis in Automobile Insurance," ASTIN Bulletin, Cambridge University Press, vol. 31(1), pages 1-22, May.
    7. Tremblay, Luc, 1992. "Using the Poisson Inverse Gaussian in Bonus-Malus Systems," ASTIN Bulletin, Cambridge University Press, vol. 22(1), pages 97-106, May.
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    Cited by:

    1. Azaare Jacob & Zhao Wu, 2020. "An Alternative Pricing System through Bayesian Estimates and Method of Moments in a Bonus-Malus Framework for the Ghanaian Auto Insurance Market," JRFM, MDPI, vol. 13(7), pages 1-15, July.
    2. Jacob Azaare & Zhao Wu & Bright Nana Kwame Ahia, 2022. "Exploring the Effects of Classical Auto Insurance Rating Variables on Premium in ARDL: Is the high Policyholders’ Premium in Ghana Justified?," SAGE Open, , vol. 12(4), pages 21582440221, October.
    3. Ajemunigbohun Sunday Stephen & Olowokudejo Folake Feyisayo & Adeleke Ismaila, 2022. "Claims Settlement and Risk Attitudes: Evidence from the Motor Insurance Policyholders," Studia Universitatis Babeș-Bolyai Oeconomica, Sciendo, vol. 67(2), pages 33-49, August.
    4. Ajemunigbohun SUNDAY, 2018. "Policyholder’s Experience of Claims Settlement Methodologies in Motor Insurance Business in Nigeria," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 5-11.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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