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Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data

Ayuso, M., Guillén, M. and Nielsen, J. P. (2018). Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data. Transportation, doi: 10.1007/s11116-018-9890-7

Abstract

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 paramete rs that capture characteristics of automobile usage and which may affect claiming behaviour . We propose implement ing 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 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.

Publication Type: Article
Additional Information: This is a post-peer-review, pre-copyedit version of an article published in 'Transportation'. The final authenticated version is available online at: https://link.springer.com/article/10.1007/s11116-018-9890-7
Publisher Keywords: tariff, premium calculation, pay-as-you-drive insurance, count data models.
Departments: Cass Business School > Actuarial Science & Insurance
URI: http://openaccess.city.ac.uk/id/eprint/19160
[img] Text - Accepted Version
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