Weekly dynamic motor insurance ratemaking with a telematics signals bonus-malus score

Abstract We present a dynamic pay-how-you-drive pricing scheme for motor insurance using telematics signals. More specifically, our approach allows the insurer to apply penalties to a baseline premium on the occurrence of events such as hard acceleration or braking. In addition, we incorporate a bonus-malus system (BMS) adapted for telematics data, providing a credibility component based on past telematics signals to the claim frequency predictions. We purposefully consider a weekly setting for our ratemaking approach to benefit from the signal’s high-frequency rate and to encourage safe driving via dynamic premium corrections. Moreover, we provide a detailed structure that allows our model to benefit from historical records and detailed telematics data collected weekly through an onboard device. We showcase our results numerically in a case study using data from an insurance company.

Authors

Institutions

Publication Details

Journal
Astin Bulletin
Published
2024-11-11
DOI
https://doi.org/10.1017/asb.2024.30
Citations
7
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
4.96

Funders

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article

Weekly dynamic motor insurance ratemaking with a telematics signals bonus-malus score

Juan Sebastian Yanez, Montserrat Guillén, Jens Perch Nielsen
7 citations
Astin Bulletin
Statistical Methods in Clinical Trials
4.96
article

Weekly dynamic motor insurance ratemaking with a telematics signals bonus-malus score

Juan Sebastian Yanez, Montserrat Guillén, Jens Perch Nielsen
article en
7 citations

Abstract

Abstract We present a dynamic pay-how-you-drive pricing scheme for motor insurance using telematics signals. More specifically, our approach allows the insurer to apply penalties to a baseline premium on the occurrence of events such as hard acceleration or braking. In addition, we incorporate a bonus-malus system (BMS) adapted for telematics data, providing a credibility component based on past telematics signals to the claim frequency predictions. We purposefully consider a weekly setting for our ratemaking approach to benefit from the signal’s high-frequency rate and to encourage safe driving via dynamic premium corrections. Moreover, we provide a detailed structure that allows our model to benefit from historical records and detailed telematics data collected weekly through an onboard device. We showcase our results numerically in a case study using data from an insurance company.

Astin BulletinVol. 55(1)
City, University of London (GB), Universidad de Londres (MX), Universitat de Barcelona (ES)
Institució Catalana de Recerca i Estudis Avançats, Fonds de recherche du Québec – Nature et technologies, Agencia Estatal de Investigación
Openalex Percentile: Top 4%
Statistical Methods in Clinical Trials
4.96
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Weekly dynamic motor insurance ratemaking with a telematics signals bonus-malus score — Juan Sebastian Yanez, Montserrat Guillén, et al. · Astin Bulletin (2024) | TGRS Research Map | TGRS