Soft Computing

, Volume 23, Issue 9, pp 2863–2875 | Cite as

A “pay-how-you-drive” car insurance approach through cluster analysis

  • Maria Francesca Carfora
  • Fabio Martinelli
  • Francesco MercaldoEmail author
  • Vittoria Nardone
  • Albina Orlando
  • Antonella Santone
  • Gigliola Vaglini


As discussed in the recent literature, several innovative car insurance concepts are proposed in order to gain advantages both for insurance companies and for drivers. In this context, the “pay-how-you-drive” paradigm is emerging, but it is not thoroughly discussed and much less implemented. In this paper, we propose an approach in order to identify the driver behavior exploring the usage of unsupervised machine learning techniques. A real-world case study is performed to evaluate the effectiveness of the proposed solution. Furthermore, we discuss how the proposed model can be adopted as risk indicator for car insurance companies.


Insurance Risk analysis OBD CAN Cluster analysis Machine learning 



This work has been partially supported by H2020 EU-funded projects NeCS and C3ISP and EIT-Digital Project HII and PRIN “Governing Adaptive and Unplanned Systems of Systems” and the EU project CyberSure 734815.

Compliance with ethical standards

Conflict of interest

All authors declare that there is no conflict of interest

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

This article does not contain any studies with animals performed by any of the authors.

Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Istituto per le Applicazioni del Calcolo “M. Picone”Consiglio Nazionale delle RicercheNaplesItaly
  2. 2.Istituto di Informatica e TelematicaConsiglio Nazionale delle RicerchePisaItaly
  3. 3.Department of EngineeringUniversity of SannioBeneventoItaly
  4. 4.Department of Bioscience and TerritoryUniversity of MolisePescheItaly
  5. 5.Department of Information EngineeringUniversity of PisaPisaItaly

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