{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:39:57Z","timestamp":1760060397420,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T00:00:00Z","timestamp":1756425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Research Council (ERC)","award":["833749"],"award-info":[{"award-number":["833749"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>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\u2019 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.<\/jats:p>","DOI":"10.3390\/bdcc9090225","type":"journal-article","created":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T16:18:15Z","timestamp":1756484295000},"page":"225","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Can Telematics Improve Driving Style? The Use of Behavioral Data in Motor Insurance"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6971-893X","authenticated-orcid":false,"given":"Alberto","family":"Cevolini","sequence":"first","affiliation":[{"name":"Department of Education and Human Sciences, University of Modena and Reggio Emilia, 42121 Reggio Emilia, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4283-2994","authenticated-orcid":false,"given":"Elena","family":"Morotti","sequence":"additional","affiliation":[{"name":"Department of Political and Social Sciences, University of Bologna, 40125 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3075-292X","authenticated-orcid":false,"given":"Elena","family":"Esposito","sequence":"additional","affiliation":[{"name":"Department of Political and Social Sciences, University of Bologna, 40125 Bologna, Italy"},{"name":"Faculty of Sociology, Bielefeld University, 33615 Bielefeld, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6176-5939","authenticated-orcid":false,"given":"Lorenzo","family":"Romanelli","sequence":"additional","affiliation":[{"name":"Swiss Re Europe S.A., Rappresentanza per l\u2019Italia, 20121 Milan, Italy"}]},{"given":"Riccardo","family":"Tisseur","sequence":"additional","affiliation":[{"name":"Swiss Re Europe S.A., Rappresentanza per l\u2019Italia, 20121 Milan, Italy"}]},{"given":"Cristiano","family":"Misani","sequence":"additional","affiliation":[{"name":"Swiss Re Europe S.A., Rappresentanza per l\u2019Italia, 20121 Milan, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,29]]},"reference":[{"key":"ref_1","unstructured":"Albrecht, P. 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