Aplicación del análisis discriminante al estudio de la siniestralidad en el ramo del seguro de automóviles.

  1. Melgar Hiraldo, Mª Carmen
  2. Ordaz Sanz, José Antonio
Anales de ASEPUMA

ISSN: 2171-892X

Year of publication: 2013

Issue: 21

Type: Article

More publications in: Anales de ASEPUMA


Knowing the policy-holders� characteristics that are more related to the occurrence of accidents could be a matter of great interest for the insurance industry. This issue can be approached from different points of view depending on the purpose of the research: to determine the variables that influence, and how they do in the likelihood of accidents, the number of incurred claims, or the probability to belong to the group of clients with accidents or with not, for example. So, there are many statistical and econometric techniques that could be used for this task: discrete choice models like logit or probit, count data models, or multivariate analysis techniques, among others. In this paper we will focus more closely on the latter approach by applying discriminant analysis to the data provided by a multinational insurance company that works in the Spanish market for auto insurance. The aim is thus to determine the characteristics of the insured that most contribute to the occurrence of accidents and the way that they do in that sector.

Bibliographic References

  • Abbring, J.H.; Chiappori, P.A.; Heckman J.J.; Pinquet, J. (2003). “Adverse Selection and Moral Hazard in Insurance: Can Dynamic Data Help to Distinguish?”. Journal of the European Economic Association, 1 (Papers and Proceedings), pp. 512-521.
  • Allen, D.M. (1974). “The Relationship Between Variable Selection and Data Augmentation and a Method for Prediction”. Technometrics, 16, pp. 125-127.
  • Boyer, M.; Dionne, G. (1989). “An Empirical Analysis of Moral Hazard and Experience Rating”. Review of Economics and Statistics, 71, pp. 128-134.
  • Chiappori, P.A.; Salanié, B. (2000). “Testing for Asymmetric Information in Insurance Markets”. Journal of Political Economy, 108, 1, pp. 56-78.
  • Cohen, A. (2005). Asymmetric Information and Learning: Evidence from the Automobile Insurance Market. Review of Economics and Statistics, 87, 2, pp. 197-207.
  • Dionne, G.; Gouriéroux, C. Vanasse, C. (1999). “Evidence of Adverse Selection in Automobile Insurance Markets”. En Dionne, G. y Laberge-Nadeau, C. (eds.): Automobile Insurance: Road Safety, New Drivers, Risks, Insurance Fraud and Regulation, Kluwer Academic Publishers, pp. 13-46, Montréal.
  • Hair, J.F. Jr.; Anderson, R.E.; Tatham, R.L. Black, W.C. (1999). “Análisis Multivariante”, 5ª ed. Prentice Hall Iberia, Madrid. HUBERTY, C.J. (1994). “Applied Discriminant Analysis”. Wiley-Interscience, Nueva York.
  • Lee, A.H.; Stevenson, M.R.; Wang, K. y Yau, K.K.W. (2002). “Modeling Young Driver Motor Vehicle Crashes: Data with Extra Zeros”. Accident Analysis and Prevention, 34, 4, pp. 515-521.
  • Melgar, M.C. (2011). “Utilización de los modelos inflados de ceros en la estimación del número de siniestros en el seguro de automóviles”. En Ayuso, M. (ed.): Métodos cuantitativos en economía del seguro del automóvil, pp. 35-51. Barcelona.
  • Melgar, M.C.; Ordaz, J.A. y Guerrero, F.M. (2005). ”Diverses Alternatives pour Déterminer les Facteurs Significatifs de la Fréquence d’Accidents dans l’Assurance Automobile”. Assurances et Gestion des Risques - Insurance and Risk Management, 73, 1, pp. 31-54.
  • Ordaz, J.A. y Melgar, M.C. (2010). “Covariate-Based Pricing of Automobile Insurance”. Insurance Markets and Companies: Analyses and Actuarial Computations, 1, 2, pp. 92-99.
  • Ordaz, J.A.; Melgar, M.C. y Khan, M.K. (2011). “An Analysis of Spanish Accidents in Automobile Insurance: The Use of the Probit Model and the Theoretical Potential of Other Econometric Tools”. Equilibrium, 6, 3, pp. 117-134.
  • Richaudeau, D. (1999). “Automobile Insurance Contracts and Risk of Accident: An Empirical Test Using French Individual Data”. Geneva Papers on Risk and Insurance Theory, 24, 1, pp. 97-114.
  • Shankar, V.; Milton, J. y Mannering, F. (1997). “Modeling AccidentFrequencies as Zero-Altered Probability Processes: an Empirical Inquiry”. Accident Analysis and Prevention, 29, 6, pp. 829-837.
  • Sharma, S. (1998). “Applied Multivariate Techniques”. John Wiley & Sons, Nueva York