Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/195783 
Year of Publication: 
2017
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 5 [Issue:] 4 [Publisher:] MDPI [Place:] Basel [Year:] 2017 [Pages:] 1-23
Publisher: 
MDPI, Basel
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.
Subjects: 
pricing
statistical inference
GAM models
pay-as-you-drive
usage-based insurance
GPS-based insurance
accident risk
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Creative Commons License: 
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Document Type: 
Article
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