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PREDICTIVE CLAIM SCORES FOR DYNAMIC MULTI-PRODUCT RISK CLASSIFICATION IN INSURANCE

Published online by Cambridge University Press:  04 November 2020

Robert Matthijs Verschuren Open the ORCID record for Robert Matthijs Verschuren [Opens in a new window]
Robert Matthijs Verschuren*
Affiliation:
Amsterdam School of Economics University of Amsterdam Roetersstraat 11, 1018 WB, Amsterdam The Netherlands E-Mail: [email protected]
*
E-Mail: [email protected]
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Abstract

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It has become standard practice in the non-life insurance industry to employ generalized linear models (GLMs) for insurance pricing. However, these GLMs traditionally work only with a priori characteristics of policyholders, while nowadays we increasingly have a posteriori information of individual customers available across multiple product categories. In this paper, we therefore develop a framework to capture this a posteriori information over several product lines using a dynamic claim score. More specifically, we extend the bonus-malus-panel model of Boucher and Inoussa (2014) and Boucher and Pigeon (2018) to include claim scores from other product categories and to allow for nonlinear effects of these scores. The application of the proposed multi-product framework to a Dutch property and casualty insurance portfolio shows that customers’ individual claims experience can have a significant impact on the risk classification. Moreover, it indicates that considerably more profits can be gained by accounting for their multi-product claims experience.

Keywords

Multi-product risk profilesdynamic claim scorebonus-malus systemsgeneralized additive modelscross-selling potentialinsurance pricingC23C52G22
Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 51 , Issue 1 , January 2021 , pp. 1 - 25
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© 2020 by Astin Bulletin. All rights reserved

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