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@inproceedings{1205458,
author = {Kafková, Silvie},
address = {Amsterdam},
booktitle = {Procedia Finance and Economics},
doi = {http://dx.doi.org/10.1016/S2212-5671(15)00354-8},
editor = {Iacob, AI},
keywords = {annual claim frequency; generalized linear model; bonus.-malus system; analysis of deviance},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Amsterdam},
pages = {216-222},
publisher = {Elsevier B.V.},
title = {Bonus-Malus Systems in Vehicle Insurance},
year = {2015}
}
TY - JOUR
ID - 1205458
AU - Kafková, Silvie
PY - 2015
TI - Bonus-Malus Systems in Vehicle Insurance
PB - Elsevier B.V.
CY - Amsterdam
KW - annual claim frequency
KW - generalized linear model
KW - bonus.-malus system
KW - analysis of deviance
N2 - Actuaries in insurance companies try to design a tariff structure that will fairly distribute the burden of claims among policyholders. Therefore they try to find the best model for an estimation of the insurance premium. The paper deals with an estimate of a priori annual claim frequency and application of bonus-malus system in the vehicle insurance. In this paper, analysis of the portfolio of vehicle insurance data using generalized linear model (GLM) is performed. Based on large real-world sample of data from 67 857 vehicles, the present study proposes a classification analysis approach addressing the selection of predictor variables. The models with different predictor variables are compared by the analysis of deviance. Based on this comparison, the model for the best estimate of annual claim frequency is chosen. Then the bonus-malus (BM) system is used for each class of drivers and Bayesian relative premium is calculated. Finally a fairer premium for different groups of drivers is proposed.
ER -
KAFKOVÁ, Silvie. Bonus-Malus Systems in Vehicle Insurance. Online. In Iacob, AI. \textit{Procedia Finance and Economics}. Amsterdam: Elsevier B.V., 2015. s.~216-222. ISSN~2212-5671. Dostupné z: https://dx.doi.org/10.1016/S2212-5671(15)00354-8. [citováno 2024-04-23]
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