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Title: A posteriori ratemaking using bivariate Poisson models
Author: Bermúdez, Lluís
Karlis, Dimitris
Keywords: Models lineals (Estadística)
Assegurances d'automòbils
Variables (Matemàtica)
Anàlisi de regressió
Linear models (Statistics)
Automobile insurance
Variables (Mathematics)
Regression analysis
Issue Date: Feb-2017
Publisher: Taylor and Francis
Abstract: Recently, different bivariate Poisson regression models have been used in the actuarial literature to make an a priori ratemaking taking into account the dependence between two types of claims. A natural extension for these models is to consider a posteriori ratemaking (i.e. experience rating models) that also relaxes the independence assumption. We introduce here two bivariate experience rating models that integrate the a priori ratemaking based on the bivariate Poisson regression models, extending the existing literature for the univariate case to the bivariate case. These bivariate experience rating models are applied to an automobile insurance claims data-set to analyse the consequences for posterior premiums when the independence assumption is relaxed. The main finding is that the a posteriori risk factors obtained with the bivariate experience rating models are significantly lower than those factors derived under the independence assumption.
Note: Versió postprint del document publicat a:
It is part of: Scandinavian Actuarial Journal, 2017, vol. 2017, num. 2, p. 148-158
Related resource:
ISSN: 0346-1238
Appears in Collections:Articles publicats en revistes (Matemàtica Econòmica, Financera i Actuarial)

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