Exposure as Duration and Distance in Telematics Motor Insurance Using Generalized Additive Models

Jean-Philippe Boucher, Steven Côté and Montserrat Guillen
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Jean-Philippe Boucher: Département de Mathématiques, Université du Québec à Montréal (UQAM); Montréal, QC H3C 3P8, Canada
Steven Côté: Département de Mathématiques, Université du Québec à Montréal (UQAM); Montréal, QC H3C 3P8, Canada
Montserrat Guillen: Department of Econometrics, Riskcenter-IREA, Universitat de Barcelona, 08007 Barcelona, Spain

Risks, 2017, vol. 5, issue 4, 1-23

Abstract: In Pay-As-You-Drive (PAYD) automobile insurance, the premium is fixed based on the distance traveled, while in usage-based insurance (UBI) the driving patterns of the policyholder are also considered. In those schemes, drivers who drive more pay a higher premium compared to those with the same characteristics who drive only occasionally, because the former are more exposed to the risk of accident. In this paper, we analyze the simultaneous effect of the distance traveled and exposure time on the risk of accident by using Generalized Additive Models (GAM). We carry out an empirical application and show that the expected number of claims (1) stabilizes once a certain number of accumulated distance-driven is reached and (2) it is not proportional to the duration of the contract, which is in contradiction to insurance practice. Finally, we propose to use a rating system that takes into account simultaneously exposure time and distance traveled in the premium calculation. We think that this is the trend the automobile insurance market is going to follow with the eruption of telematics data.

Keywords: pricing; statistical inference; GAM models; pay-as-you-drive; usage-based insurance; GPS-based insurance; accident risk (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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