Work

Can Telematics Improve Driving Style? The Use of Behavioral Data in Motor Insurance

Year: 2025

Type: article

Abstract: Motor insurance can use telematics data not only to understand individual driving style but also to implement innovative coaching strategies that feed back to the drivers, through an app, the aggregated information extracted from the data. The purpose is to encourage an improvement in their driving style. A precondition for this improvement is that drivers are digitally engaged, that is, they interact with the app. This paper proposes a narrow understanding of the term engagement, referring to users’ interactions with the app. This interaction is also a behavior producing specific data that can be tracked and used by insurance companies. Based on the empirical investigation of the dataset of a company selling a telematics motor insurance policy, our research investigates if there is a correlation between engagement with the app and improvement of driving style. The analysis distinguishes different groups of users with different driving abilities, and takes into account time differences. Our findings contribute to clarifying the methodological challenges that must be addressed when exploring engagement and coaching effectiveness in proactive insurance policies. We conclude by discussing the possibility and difficulties of tracking and using second-order behavioral data related to policyholder engagement with the app.

Source: Big Data and Cognitive Computing

DOI: 10.3390/bdcc9090225

Authors: Alberto Cevolini, Elena Morotti, Elena Esposito, Lorenzo Romanelli, Riccardo Tisseur, Cristiano Misani

Institutions: University of Modena and Reggio Emilia, University of Bologna, Bielefeld University, Swiss Re (Switzerland)

Language: English

Topic: Insurance and Financial Risk Management

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,172

Funder: H2020 European Research Council