Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/106488
Title: A priori ratemaking using bivariate Poisson regression models
Author: Bermúdez, Lluís
Keywords: Anàlisi de regressió
Accidents de circulació
Bootstrap (Estadística)
Tarifes
Regression analysis
Traffic accidents
Bootstrap (Statistics)
Rates
Issue Date: 2009
Publisher: Elsevier B.V.
Abstract: In automobile insurance, it is useful to achieve a priori ratemaking by resorting to generalized linear models, and here the Poisson regression model constitutes the most widely accepted basis. However, insurance companies distinguish between claims with or without bodily injuries, or claims with full or partial liability of the insured driver. This paper examines an a priori ratemaking procedure when including two different types of claim. When assuming independence between claim types, the premium can be obtained by summing the premiums for each type of guarantee and is dependent on the rating factors chosen. If the independence assumption is relaxed, then it is unclear as to how the tariff system might be affected. In order to answer this question, bivariate Poisson regression models, suitable for paired count data exhibiting correlation, are introduced. It is shown that the usual independence assumption is unrealistic here. These models are applied to an automobile insurance claims database containing 80,994 contracts belonging to a Spanish insurance company. Finally, the consequences for pure and loaded premiums when the independence assumption is relaxed by using a bivariate Poisson regression model are analysed.
Note: Versió postprint del document publicat a: https://doi.org/10.1016/j.insmatheco.2008.11.005
It is part of: Insurance Mathematics and Economics, 2009, vol. 44, num. 1, p. 135-141
Related resource: https://doi.org/10.1016/j.insmatheco.2008.11.005
URI: http://hdl.handle.net/2445/106488
ISSN: 0167-6687
Appears in Collections:Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

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