A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums

A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums

In this paper, a flexible count regression model based on a bivariate compound Poisson distribution is introduced in order to distinguish between different types of claims according to the claim size. Furthermore, it allows us to analyse the factors that affect the number of claims above and below a...

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Bibliographic Details
Main Authors: Emilio Gómez-Déniz, Enrique Calderín-Ojeda
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Risks
Subjects:
aggregate claims
auto insurance
bayesian
bonus-malus
compound distribution
Online Access:https://www.mdpi.com/2227-9091/8/1/20
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spelling doaj-a35f85538eca4b49b4b399b9546653ac2020-11-25T02:16:10ZengMDPI AGRisks2227-90912020-02-01812010.3390/risks8010020risks8010020A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus PremiumsEmilio Gómez-Déniz0Enrique Calderín-Ojeda1Department of Quantitative Methods and TIDES Institute, University of Las Palmas de Gran Canaria, 35017 Las Palmas de Gran Canaria, SpainCentre for Actuarial Studies, Department of Economics, The University of Melbourne, Melbourne, VIC 3010, AustraliaIn this paper, a flexible count regression model based on a bivariate compound Poisson distribution is introduced in order to distinguish between different types of claims according to the claim size. Furthermore, it allows us to analyse the factors that affect the number of claims above and below a given claim size threshold in an automobile insurance portfolio. Relevant properties of this model are given. Next, a mixed regression model is derived to compute credibility bonus-malus premiums based on the individual claim size and other risk factors such as gender, type of vehicle, driving area, or age of the vehicle. Results are illustrated by using a well-known automobile insurance portfolio dataset.https://www.mdpi.com/2227-9091/8/1/20aggregate claimsauto insurancebayesianbonus-maluscompound distribution
collection DOAJ
language English
format Article
sources DOAJ
author Emilio Gómez-Déniz
Enrique Calderín-Ojeda
spellingShingle Emilio Gómez-Déniz
Enrique Calderín-Ojeda
A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums
Risks
aggregate claims
auto insurance
bayesian
bonus-malus
compound distribution
author_facet Emilio Gómez-Déniz
Enrique Calderín-Ojeda
author_sort Emilio Gómez-Déniz
title A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums
title_short A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums
title_full A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums
title_fullStr A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums
title_full_unstemmed A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums
title_sort survey of the individual claim size and other risk factors using credibility bonus-malus premiums
publisher MDPI AG
series Risks
issn 2227-9091
publishDate 2020-02-01
description In this paper, a flexible count regression model based on a bivariate compound Poisson distribution is introduced in order to distinguish between different types of claims according to the claim size. Furthermore, it allows us to analyse the factors that affect the number of claims above and below a given claim size threshold in an automobile insurance portfolio. Relevant properties of this model are given. Next, a mixed regression model is derived to compute credibility bonus-malus premiums based on the individual claim size and other risk factors such as gender, type of vehicle, driving area, or age of the vehicle. Results are illustrated by using a well-known automobile insurance portfolio dataset.
topic aggregate claims
auto insurance
bayesian
bonus-malus
compound distribution
url https://www.mdpi.com/2227-9091/8/1/20
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