44
Views
0
CrossRef citations to date
0
Altmetric
Feature Articles

Bivariate Poisson Credibility Model and Bonus–Malus Scale for Claim and Near-Claim Events

, ORCID Icon &

References

  • Apley, D. W., and J. Zhu. 2016. Visualizing the effects of predictor variables in black box supervised learning models. Journal of the Royal Statistical Society Series B 82:1059–86. 10.1111/rssb.12377
  • Ayuso, M., M. Guillen, and J. P. Nielsen. 2019. Improving automobile insurance ratemaking using telematics: Incorporating mileage and driver behaviour data. Transportation 46:735–52. 10.1007/s11116-018-9890-7
  • Boucher, J.-P., S. Côté, and M. Guillen. 2017. Exposure as duration and distance in telematics motor insurance using generalized additive models. Risks 5:54. 10.3390/risks5040054
  • Cheung, E. C., W. Ni, R. Oh, and J. K. Woo. 2021. Bayesian credibility under a bivariate prior on the frequency and the severity of claims. Insurance: Mathematics and Economics 100:274–95. 10.1016/j.insmatheco.2021.06.003
  • Chevalier, A., K. Coxon, A. J. Chevalier, E. Clarke, K. Rogers, J. Brown, S. Boufous, R. Ivers, and L. Keay. 2016. Predictors of older drivers’ involvement in rapid deceleration events. Accident Analysis & Prevention 98:312–19. 10.1016/j.aap.2016.10.010
  • Corradin, A., M. Denuit, M. Detyniecki, V. Grari, M. Sammarco, and J. Trufin. 2022. Joint modeling of claim frequencies and behavioral signals in motor insurance. ASTIN Bulletin 52:33–54. 10.1017/asb.2021.24
  • De Ceunynck, T. 2017. Defining and applying surrogate safety measures and behavioural indicators through site-based observations. PhD diss., Department of Technology and Society, Lund University.
  • Denuit, M., M. Guillen, and J. Trufin. 2019. Multivariate credibility modeling for usage-based motor insurance pricing with behavioral data. Annals of Actuarial Science 13:378–99. 10.1017/S1748499518000349
  • Denuit, M., and Y. Lu. 2021. Wishart-Gamma random effects models with applications to nonlife insurance. Journal of Risk and Insurance 88:443–81. 10.1111/jori.12327
  • Dionne, G., and C. Vanasse. 1992. Automobile insurance ratemaking in the presence of asymmetrical information. Journal of Applied Econometrics 7:149–65. 10.1002/jae.3950070204
  • Duval, F., J.-P. Boucher, and M. Pigeon. 2022. How much telematics information do insurers need for claim classification? North American Actuarial Journal 26:570–90. 10.1080/10920277.2021.2022499
  • Friedman, J. H. 2008. Greedy function approximation: A gradient boosting machine. Annals of Statistics 29:1189–232.
  • Fu, C., and T. Sayed. 2021. Comparison of threshold determination methods for the deceleration rate to avoid a crash (DRAC)-based crash estimation. Accident Analysis & Prevention 153:106051. 10.1016/j.aap.2021.106051
  • Gao, G., S. Meng, and M. Wüthrich. 2019. Claims frequency modeling using telematics car driving data. Scandinavian Actuarial Journal 2019:143–62. 10.1080/03461238.2018.1523068
  • Gao, G., S. Meng, and M. Wüthrich. 2022. What we can learn from telematics car driving data: A survey. Mathematics and Economics 104:185–99. 10.1016/j.insmatheco.2022.02.004
  • Gao, G., H. Wang, and M. Wüthrich. 2022. Boosting Poisson regression models with telematics car driving data. Machine Learning 111:243–72. 10.1007/s10994-021-05957-0
  • Gomez-Deniz, E. 2016. Bivariate credibility bonus–malus premiums distinguishing between two types of claims. Insurance: Mathematics and Economics 70:117–24. 10.1016/j.insmatheco.2016.06.009
  • Guillen, M., J. Nielsen, and A. M. Pérez-Marín. 2021. Near-miss telematics in motor insurance. Journal of Risk and Insurance 88:569–89. 10.1111/jori.12340
  • Guillen, M., J. P. Nielsen, A. M. Pérez-Marín, and V. Elpidorou. 2020. Can automobile insurance telematics predict the risk of near-miss events? North American Actuarial Journal 24:141–52. 10.1080/10920277.2019.1627221
  • Norberg, R. 1976. A credibility theory for automobile bonus system. Scandinavian Actuarial Journal 1976:92–107. 10.1080/03461238.1976.10405605
  • Oh, R., J. H. Kim, and J. Y. Ahn. 2022. Designing a bonus–malus system reflecting the claim size under the dependent frequency–severity model. Probability in the Engineering and Informational Sciences 36:963–87. 10.1017/S0269964821000188
  • Oh, R., K. S. Lee, S. C. Park, and J. Y. Ahn. 2020. Double-counting problem of the bonus–malus system. Insurance: Mathematics and Economics 93:141–55. 10.1016/j.insmatheco.2020.04.008
  • Oh, R., P. Shi, and J. Y. Ahn. 2020. Bonus–malus premiums under the dependent frequency–severity modeling. Scandinavian Actuarial Journal 2020:172–95. 10.1080/03461238.2019.1655477
  • Park, S. C., J. H. Kim, and J. Y. Ahn. 2018. Does hunger for bonuses drive the dependence between claim frequency and severity? Insurance: Mathematics and Economics 83:32–46. 10.1016/j.insmatheco.2018.09.002
  • Pechon, F., J. Trufin, and M. Denuit. 2018. Multivariate modelling of household claim frequencies in motor third-party liability insurance. ASTIN Bulletin 48:969–93. 10.1017/asb.2018.21
  • Pinquet, J. 1998. Designing optimal bonus–malus systems from different types of claims. ASTIN Bulletin 28:205–20. 10.2143/AST.28.2.519066
  • Pitrebois, S., M. Denuit, and J.-F. Walhin. 2003. Setting a bonus–malus scale in the presence of other rating factors: Taylor’s work revisited. ASTIN Bulletin 33:419–36. 10.1017/S0515036100013544
  • Pitrebois, S., M. Denuit, and J.-F. Walhin. 2006. Multi-event bonus–malus scales. Journal of Risk and Insurance 73:517–28. 10.1111/j.1539-6975.2006.00186.x
  • So, B., J.-P. Boucher, and E. Valdez. 2021. Synthetic dataset generation of driver telematics. Risks 9:58. 10.3390/risks9040058
  • Sun, S., J. Bi, M. Guillen, and A. M. Pérez-Marín. 2021. Driving risk assessment using near-miss events based on panel Poisson regression and panel negative binomial regression. Entropy 23:829. 10.3390/e23070829
  • Tan, C. I., J. Li, J. S. H. Li, and U. Balasooriya. 2015. Optimal relativities and transition rules of a bonus–malus system. Insurance: Mathematics and Economics 61:255–63. 10.1016/j.insmatheco.2015.02.001
  • Taylor, G. 1997. Setting a bonus–malus scale in the presence of other rating factors. ASTIN Bulletin 27:319–27. 10.2143/AST.27.2.542055
  • Tzougas, G., and A. P. di Cerchiara. 2021. The multivariate mixed negative binomial regression model with an application to insurance a posteriori ratemaking. Insurance: Mathematics and Economics 101:602–25. 10.1016/j.insmatheco.2021.10.001
  • Verschuren, R. M. 2022. Frequency–severity experience rating based on latent Markovian risk profiles. Insurance: Mathematics and Economics 107:379–92. 10.1016/j.insmatheco.2022.09.007
  • Zheng, L., T. Sayed, and M. Essa. 2018. Validating the bivariate extreme value modeling approach for road safety estimation with different traffic conflict indicators. Accident Analysis & Prevention 123:314–23. 10.1016/j.aap.2018.12.007

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.