Artikel

Multivariate credibility in bonus-malus systems distinguishing between different types of claims

In the classical bonus-malus system the premium assigned to each policyholder is based only on the number of claims made without having into account the claims size. Thus, a policyholder who has declared a claim that results in a relatively small loss is penalised to the same extent as one who has declared a more expensive claim. Of course, this is seen unfair by many policyholders. In this paper, we study the factors that affect the number of claims in car insurance by using a trivariate discrete distribution. This approach allows us to discern between three types of claims depending wether the claims are above, between or below certain thresholds. Therefore, this model implements the two fundamental random variables in this scenario, the number of claims as well as the amount associated with them. In addition, we introduce a trivariate prior distribution conjugated with this discrete distribution that produce credibility bonus-malus premiums that satisfy appropriate traditional transition rules. A practical example based on real data is shown to examine the differences with respect to the premiums obtained under the traditional system of tarification.

Language
Englisch

Bibliographic citation
Journal: Risks ; ISSN: 2227-9091 ; Volume: 6 ; Year: 2018 ; Issue: 2 ; Pages: 1-11 ; Basel: MDPI

Classification
Wirtschaft
Subject
Bayesian
bonus-malus system
claim number
claim size
conjugate distribution

Event
Geistige Schöpfung
(who)
Gómez-Déniz, Emilio
Calderín-Ojeda, Enrique
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2018

DOI
doi:10.3390/risks6020034
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Gómez-Déniz, Emilio
  • Calderín-Ojeda, Enrique
  • MDPI

Time of origin

  • 2018

Other Objects (12)