Citation

Guillén M, Nielsen JP, Ayuso M, Pérez-Marín AM. Risk Anal. 2019; 39(3): 662-672.

Affiliation

Department of Econometrics, Riskcenter-IREA, Universitat de Barcelona, Barcelona, Spain.

Copyright

(Copyright © 2019, Society for Risk Analysis, Publisher John Wiley and Sons)

DOI

10.1111/risa.13172

PMID

30566751

Abstract

Most automobile insurance databases contain a large number of policyholders with zero claims. This high frequency of zeros may reflect the fact that some insureds make little use of their vehicle, or that they do not wish to make a claim for small accidents in order to avoid an increase in their premium, but it might also be because of good driving. We analyze information on exposure to risk and driving habits using telematics data from a pay-as-you-drive sample of insureds. We include distance traveled per year as part of an offset in a zero-inflated Poisson model to predict the excess of zeros. We show the existence of a learning effect for large values of distance traveled, so that longer driving should result in higher premiums, but there should be a discount for drivers who accumulate longer distances over time due to the increased proportion of zero claims. We confirm that speed limit violations and driving in urban areas increase the expected number of accident claims. We discuss how telematics information can be used to design better insurance and to improve traffic safety.

© 2018 Society for Risk Analysis.

Language: en

Keywords

Mileage; pay-as-you-drive; usage-based insurance