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JOINT MODELING OF CLAIM FREQUENCIES AND BEHAVIORAL SIGNALS IN MOTOR INSURANCE

Published online by Cambridge University Press:  07 October 2021

Alexandre Corradin ,
Michel Denuit ,
Marcin Detyniecki ,
Vincent Grari ,
Matteo Sammarco  and
Julien Trufin Open the ORCID record for Julien Trufin [Opens in a new window]
Alexandre Corradin
Affiliation:
AXA/GO/REV, Paris, France
Michel Denuit
Affiliation:
Institute of Statistics, Biostatistics and Actuarial Science (ISBA/LIDAM), UCLouvain, Louvain-la-Neuve, Belgium
Marcin Detyniecki
Affiliation:
AXA/GO/REV, Paris, France
Vincent Grari
Affiliation:
AXA/GO/REV, Paris, France
Matteo Sammarco
Affiliation:
AXA/GO/REV, Paris, France
Julien Trufin*
Affiliation:
Department of Mathematics, Université Libre de Bruxelles (ULB), Bruxelles, Belgium E-Mail: julien.trufin@ulb.ac.be
*
E-Mail: julien.trufin@ulb.ac.be
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Abstract

Telematicsdevices installed in insured vehicles provide actuaries with new risk factors, such as the time of the day, average speeds, and other driving habits. This paper extends the multivariate mixed model describing the joint dynamics of telematics data and claim frequencies proposed by Denuit et al. (2019a) by allowing for signals with various formats, not necessarily integer-valued, and by replacing the estimation procedure with the Expected Conditional Maximization algorithm. A numerical study performed on a database related to Pay-How-You-Drive, or PHYD motor insurance illustrates the relevance of the proposed approach for practice.

Keywords

Risk classificationpremium calculationdriving behaviormixed modelsmultivariate credibilitypanel dataC13C33C38

Information

Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 52 , Issue 1 , January 2022 , pp. 33 - 54
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The International Actuarial Association

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