IDEAS home Printed from https://ideas.repec.org/p/ira/wpaper/200902.html
   My bibliography  Save this paper

Modelling the disability severity score in motor insurance claims: an application to the Spanish case

Author

Listed:
  • Miguel Santolino

    (Faculty of Economics, University of Barcelona)

  • Jean-Philippe Boucher

    (Département de Mathématiques, Université du Québec à Montréal)

Abstract

Bodily injury claims have the greatest impact on the claim costs of motor insurance companies. The disability severity of motor claims is assessed in numerous European countries by means of score systems. In this paper a zero inflated generalized Poisson regression model is implemented to estimate the disability severity score of victims in-volved in motor accidents on Spanish roads. We show that the injury severity estimates may beautomatically converted into financial terms by insurers at any point of the claim handling process. As such, the methodology described may be used by motor insurers operating in the Spanish market to monitor the size of bodily injury claims. By using insurance data, various applications are presented in which the score estimate of disability severity is of value to insurers, either for computing the claim compensation or for claim reserve purposes.

Suggested Citation

  • Miguel Santolino & Jean-Philippe Boucher, 2009. "Modelling the disability severity score in motor insurance claims: an application to the Spanish case," IREA Working Papers 200902, University of Barcelona, Research Institute of Applied Economics, revised Jan 2009.
    • Handle: RePEc:ira:wpaper:200902
    as

    Download full text from publisher

    File URL: http://www.ub.edu/irea/working_papers/2009/200902.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Larsen, Christian Roholte, 2007. "An Individual Claims Reserving Model," ASTIN Bulletin, Cambridge University Press, vol. 37(1), pages 113-132, May.
    2. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    3. Richard Lewis, 2006. "How Important are Insurers in Compensating Claims for Personal Injury in the U.K.?*," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 31(2), pages 323-339, April.
    4. Browne, Mark J & Puelz, Robert, 1999. "The Effect of Legal Rules on the Value of Economic and Non-economic Damages and the Decision to File," Journal of Risk and Uncertainty, Springer, vol. 18(2), pages 189-213, August.
    5. Phil Bell, 2006. "The Social Construction of Bodily Injury," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 31(2), pages 340-356, April.
    6. Mercedes Ayuso & Miguel Santolino, 2008. "Prediction of individual automobile RBNS claim reserves in the context of Solvency II," IREA Working Papers 200806, University of Barcelona, Research Institute of Applied Economics, revised May 2008.
    7. Yip, Karen C.H. & Yau, Kelvin K.W., 2005. "On modeling claim frequency data in general insurance with extra zeros," Insurance: Mathematics and Economics, Elsevier, vol. 36(2), pages 153-163, April.
    8. Hoyt, Robert E & Mustard, David B & Powell, Lawrence S, 2006. "The Effectiveness of State Legislation in Mitigating Moral Hazard: Evidence from Automobile Insurance," Journal of Law and Economics, University of Chicago Press, vol. 49(2), pages 427-450, October.
    9. Ayuso, Mercedes & Santolino, Miguel, 2007. "Predicting automobile claims bodily injury severity with sequential ordered logit models," Insurance: Mathematics and Economics, Elsevier, vol. 41(1), pages 71-83, July.
    10. England, P.D. & Verrall, R.J., 2002. "Stochastic Claims Reserving in General Insurance," British Actuarial Journal, Cambridge University Press, vol. 8(3), pages 443-518, August.
    11. Clarke, Kevin A., 2007. "A Simple Distribution-Free Test for Nonnested Model Selection," Political Analysis, Cambridge University Press, vol. 15(3), pages 347-363, July.
    12. Bae, S. & Famoye, F. & Wulu, J.T. & Bartolucci, A.A. & Singh, K.P., 2005. "A rich family of generalized Poisson regression models with applications," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 69(1), pages 4-11.
    13. Helen I. Doerpinghaus & Joan T. Schmit & Jason Jia‐Hsing Yeh, 2008. "Age and Gender Effects on Auto Liability Insurance Payouts," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(3), pages 527-550, September.
    14. Crocker, Keith J & Tennyson, Sharon, 2002. "Insurance Fraud and Optimal Claims Settlement Strategies," Journal of Law and Economics, University of Chicago Press, vol. 45(2), pages 469-507, October.
    15. Boucher, Jean-Philippe & Denuit, Michel, 2008. "Credibility premiums for the zero-inflated Poisson model and new hunger for bonus interpretation," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 727-735, April.
    16. Jean-Philippe Boucher & Michel Denuit & Montserrat Guillén, 2007. "Risk Classification for Claim Counts," North American Actuarial Journal, Taylor & Francis Journals, vol. 11(4), pages 110-131.
    17. Norberg, Ragnar, 1999. "Prediction of Outstanding Liabilities II. Model Variations and Extensions," ASTIN Bulletin, Cambridge University Press, vol. 29(1), pages 5-25, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael Artis & Ernest Miguélez & Rosina Moreno, 2009. "Assessing Agglomeration Economies in a Spatial Framework with Endogenous Regressors," SERC Discussion Papers 0023, Centre for Economic Performance, LSE.
    2. Juan Luis Jiménez & Jordi Perdiguero & Ancor Suárez, 2011. "Debating as a classroom tool for adapting learning outcomes to the European higher education area," IREA Working Papers 201109, University of Barcelona, Research Institute of Applied Economics, revised Jun 2011.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ayuso Gutierrez, M. Mercedes & Santolino Prieto, Miguel Á., 2008. "Prediction of individual automobile reported but not settled claim reserves for bodily injuries in the context of Solvency II = Predicción de las reservas individuales para siniestros del automóvil co," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 6(1), pages 23-41, December.
    2. Mercedes Ayuso & Miguel Santolino, 2008. "Prediction of individual automobile RBNS claim reserves in the context of Solvency II," IREA Working Papers 200806, University of Barcelona, Research Institute of Applied Economics, revised May 2008.
    3. Claudia Czado & Holger Schabenberger & Vinzenz Erhardt, 2014. "Non nested model selection for spatial count regression models with application to health insurance," Statistical Papers, Springer, vol. 55(2), pages 455-476, May.
    4. Mercedes Ayuso & Lluís Bermúdez & Miguel Santolino, 2011. "“Influence of the claimant’s behavioural features on motor compensation outcomes”," IREA Working Papers 201108, University of Barcelona, Research Institute of Applied Economics, revised Jun 2011.
    5. Mercedes Ayuso(universitat de Barcelona) & Miguel Santolino(Universitat de Barcelona), 2009. "Individual prediction of automobile bodily injury claims liabilities," Working Papers in Economics 220, Universitat de Barcelona. Espai de Recerca en Economia.
    6. Payandeh Najafabadi Amir T. & MohammadPour Saeed, 2018. "A k-Inflated Negative Binomial Mixture Regression Model: Application to Rate–Making Systems," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 12(2), pages 1-31, July.
    7. Francis Duval & Mathieu Pigeon, 2019. "Individual Loss Reserving Using a Gradient Boosting-Based Approach," Risks, MDPI, vol. 7(3), pages 1-18, July.
    8. Mercedes Ayuso & Miguel Santolino, 2012. "Forecasting the Maximum Compensation Offer in the Automobile BI Claims Negotiation Process," Group Decision and Negotiation, Springer, vol. 21(5), pages 663-676, September.
    9. Mat'uv{s} Maciak & Ostap Okhrin & Michal Pev{s}ta, 2019. "Infinitely Stochastic Micro Forecasting," Papers 1908.10636, arXiv.org, revised Sep 2019.
    10. Zhao, XiaoBing & Zhou, Xian, 2010. "Applying copula models to individual claim loss reserving methods," Insurance: Mathematics and Economics, Elsevier, vol. 46(2), pages 290-299, April.
    11. Jennifer S. K. Chan & S. T. Boris Choy & Udi Makov & Ariel Shamir & Vered Shapovalov, 2022. "Variable Selection Algorithm for a Mixture of Poisson Regression for Handling Overdispersion in Claims Frequency Modeling Using Telematics Car Driving Data," Risks, MDPI, vol. 10(4), pages 1-10, April.
    12. Mat'uv{s} Maciak & Ostap Okhrin & Michal Pev{s}ta, 2018. "Dynamic and granular loss reserving with copulae," Papers 1801.01792, arXiv.org.
    13. Zhao, Xiaobing & Zhou, Xian, 2012. "Modeling gap times between recurrent events by marginal rate function," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 370-383.
    14. Stephan M. Bischofberger, 2020. "In-Sample Hazard Forecasting Based on Survival Models with Operational Time," Risks, MDPI, vol. 8(1), pages 1-17, January.
    15. Mihaela DAVID, 2014. "Modeling The Frequency Of Claims In Auto Insurance With Application To A French Case," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 13, pages 69-85, June.
    16. Tzougas, George & Hoon, W. L. & Lim, J. M., 2019. "The negative binomial-inverse Gaussian regression model with an application to insurance ratemaking," LSE Research Online Documents on Economics 101728, London School of Economics and Political Science, LSE Library.
    17. Lee, Woojoo & Kim, Jeonghwan & Ahn, Jae Youn, 2020. "The Poisson random effect model for experience ratemaking: Limitations and alternative solutions," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 26-36.
    18. Crevecoeur, Jonas & Antonio, Katrien & Desmedt, Stijn & Masquelein, Alexandre, 2023. "Bridging the gap between pricing and reserving with an occurrence and development model for non-life insurance claims," ASTIN Bulletin, Cambridge University Press, vol. 53(2), pages 185-212, May.
    19. Jean‐Philippe Boucher & Michel Denuit & Montserrat Guillen, 2009. "Number of Accidents or Number of Claims? An Approach with Zero‐Inflated Poisson Models for Panel Data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(4), pages 821-846, December.
    20. Maciak, Matúš & Okhrin, Ostap & Pešta, Michal, 2021. "Infinitely stochastic micro reserving," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 30-58.

    More about this item

    Keywords

    Motor accident; disability severity; zero-inflated generalized Poisson model; disability scoring scale.;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ira:wpaper:200902. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alicia García (email available below). General contact details of provider: https://edirc.repec.org/data/feubaes.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.