Optimal Bonus-Malus Premium with the Claim Frequency Distribution is Negative Binomial and the Claim Severity Distribution is Truncated Weibull
DOI:
https://doi.org/10.25077/jmua.15.2.179-195.2026Keywords:
Negative Binomial, optimal Bonus-Malus system, risk premium, truncated WeibullAbstract
The optimal bonus-malus system is a system for determining the amount of premium in the next period based on the frequency and severity of claims filed by policyholders in the previous period. In this article, we study the insurance premium formula using the optimal bonus-malus system with the claim frequency has a negative binomial distribution and the claim severity has a truncated Weibull distribution. The method to derive the bonus-malus formula uses a Bayes solution with a quadratic loss function. The formula obtained has been also applied to the data of motor vehicle insurance to calculate the risk premium that must be paid by the policyholder. From the calculation results, the insurance premiums that use the optimal bonus-malus system with a truncated Weibull distribution are more profitable for both the company and the insurer than the Weibull distribution.
Downloads
References
[1] Mert, M. & Saykan, Y., 2005, On a Bonus-Malus system where the claim frequency distribution Is Geometric and the claim severity distribution Is Pareto, Hacettepe J. Math. Stat., Vol. 34: 75–81
[2] Bulbul, D. & Baykal, M., 2016, Optimal Bonus-Malus System Design in Motor Insurance Using Negative Binomial Models, International Journal of Economics and Finance, Vol. 8: 45–56
[3] Pratama, A.S., Nurrohmah, S., & Novita, M., 2020, Determination of net premium rates on bonus-malus system based on frequency and severity distribution, Journal of Physics: Conference Series, Vol. 1442: 6–10
[4] Ni, W., Constantinescu, C., & Pantelous, A.A., 2014, Bonus–Malus systems with Weibull distributed claim severities, Ann. Actuar. Sci., Vol. 8: 217–233
[5] Oh, R., Kim, J., & Park, S., 2020, Designing a Bonus-Malus System Reflecting Claim Size Under Dependent Frequency-Severity Models, arXiv preprint arXiv:2003.01860
[6] Moumeesri, A. & Pongsart, T., 2022, Bonus-malus premiums based on claim frequency and the size of claims, Risks, Vol. 10: 181
[7] Azaare, J. & Wu, Z., 2020, An alternative pricing system through Bayesian estimates and method of moments in a bonus-malus framework for the Ghanaian auto insurance market, Journal of Risk and Financial Management, Vol. 13: 143
[8] Simeunovi´c, I., Domazet, I., & Zubovi´c, J., 2016, Modelling a bms-based auto mobile liability rating system: the serbian case, Ekonomika Preduzeca, Vol. 64 361–370
[9] Tzougas, G., 2020, Em estimation for the poisson-inverse gamma regression model with varying dispersion: an application to insurance ratemaking, Risks,Vol. 8: 97
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Departemen Matematika dan Sains Data FMIPA UNAND

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All articles published in Jurnal Matematika UNAND (JMUA) are open access and licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). This license allows published content to be freely accessed, shared, redistributed, and adapted for any purpose, including commercial use, provided that the applicable license conditions are followed.
Copyright Holder
The copyright of articles published in Jurnal Matematika UNAND is held by the Departemen Matematika dan Sains Data, Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA), Universitas Andalas (UNAND), in accordance with the journal's stated copyright policy.
Author Rights
Under the CC BY-SA 4.0 license, authors may share, distribute, and reuse their published articles, subject to the applicable license conditions. These rights include:
-
Self-Archiving: Authors may deposit their published articles in institutional repositories, personal websites, or academic platforms.
-
Reuse: Authors may reuse their published work in subsequent publications, research, teaching materials, or other lawful purposes, provided that appropriate attribution is maintained.
-
Distribution: Authors may share and distribute their published articles without requiring additional permission under the terms of the license.
Creative Commons License (CC BY-SA 4.0)
Under the CC BY-SA 4.0 license, users are free to:
-
Share: Copy and redistribute the material in any medium or format.
-
Adapt: Remix, transform, and build upon the material for any purpose, including commercial purposes.
These permissions are subject to the following conditions:
-
Attribution: Users must give appropriate credit to the original author(s), retain relevant copyright notices, provide a link to the license, and indicate if changes were made. Attribution must not imply endorsement by the author(s), copyright holder, or journal.
-
ShareAlike: If users remix, transform, or build upon the material, they must distribute their contributions under the same CC BY-SA 4.0 license or a compatible license.
-
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from exercising the rights granted by the license.
For more information about the CC BY-SA 4.0 license, please visit:
https://creativecommons.org/licenses/by-sa/4.0/
Third-Party Content
Third-party materials, including figures, tables, photographs, and illustrations, are covered by the article's CC BY-SA 4.0 license only when their inclusion under that license is authorized.
Materials excluded from the license must be clearly identified with appropriate copyright notices and attribution. Authors are responsible for obtaining any necessary permissions, while users must comply with the applicable licensing terms or permissions when reusing excluded materials.
Copyright and Licensing Information
Copyright and licensing information should be clearly displayed on each published article's landing page and included in the full-text versions (HTML and PDF), where applicable, to ensure transparency regarding copyright ownership and permitted reuse.



