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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 con daños corporales pendientes de liquidación en el contexto de Solvencia II

Author

Listed:
  • Ayuso Gutierrez, M. Mercedes

    (Departament d’Econometria, Estadística i Economia Espanyola, Universitat de Barcelona)

  • Santolino Prieto, Miguel Á.

    (Departament d’Econometria, Estadística i Economia Espanyola, Universitat de Barcelona)

Abstract
Automobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported but not Settled claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project, a statistical model is implemented for reserve estimation. Lognormality on empirical cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The severity is predicted by means of a heteroscedastic multiple choice model, because evidence has found that the variability in the latent severity of individuals travelling by car is not constant. It is shown that this methodology improves the accuracy of reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners. = Los siniestros del automóvil con daños corporales suelen permanecer sin liquidar durante largos periodos después del accidente. Una adecuada estimación por siniestros comunicados pero no liquidados es por tanto de vital importancia para los aseguradores. Siguiendo las recomendaciones incluidas en el proyecto de Solvencia II, se implementa un método estadístico para la estimación de la reserva. En concreto, se observa que el coste de compensación se distribuye lognormalmente para diferentes niveles de gravedad del daño corporal. La provisión individual del siniestro la estimamos asignando el valor esperado de compensación media según la gravedad predicha de la lesión de la víctima, para la cual también se calcula el límite superior. La gravedad la predecimos mediante un modelo heterocedástico de elección múltiple, porque hallamos evidencias de que la variabilidad en la gravedad latente no es constante para los individuos que viajaban en un turismo. Se demuestra que la metodología propuesta mejora la precisión en la estimación de las reservas en todas las etapas, en comparación con la valoración subjetiva que ha sido tradicionalmente hecha por los peritos de la compañía.

Suggested Citation

  • 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.
    • Handle: RePEc:pab:rmcpee:v:6:y:2008:i:1:p:23-41
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    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.
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    More about this item

    Keywords

    automobile accident; Solvency II; bodily injury claims; individual reported but not settled reserve (RBNS). ; accidente de automóvil; Solvencia II; siniestros con daños corporales; reserva individual para siniestros pendientes de liquidación;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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