Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data
Montserrat Guillén () and
Jens Perch Nielsenz ()
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Montserrat Guillén: Department of Econometrics, Riskcenter-IREA, Universitat de Barcelona
Jens Perch Nielsenz: Cass Business School, City University
No 2017-01, Working Papers from Universitat de Barcelona, UB Riskcenter
We show how data collected from a GPS device can be incorporated in motor insurance ratemaking. The calculation of premium rates based upon driver behaviour represents an opportunity for the insurance sector. Our approach is based on count data regression models for frequency, where exposure is driven by the distance travelled and additional parameters that capture characteristics of automobile usage and which may affect claiming behaviour. We propose implementing a classical frequency model that is updated with telemetrics information. We illustrate the method using real data from usage-based insurance policies. Results show that not only the distance travelled by the driver, but also driver habits, significantly influence the expected number of accidents and, hence, the cost of insurance coverage. This paper provides a methodology including a transition pricing transferring knowledge and experience that the company already had before the telematics data arrived to the new world including telematics information.
Keywords: tariff; premium calculation; pay-as-you-drive insurance; count data models (search for similar items in EconPapers)
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http://www.ub.edu/rfa/research/WP/UBriskcenterWP201701.pdf First version, 2017 (application/pdf)
Journal Article: Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data (2019)
Working Paper: Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:bak:wpaper:201701
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