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Good drivers pay less: A study of usage-based vehicle insurance models

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Listed:
  • Bian, Yiyang
  • Yang, Chen
  • Zhao, J. Leon
  • Liang, Liang

Abstract

Usage-based insurance (UBI) has been attracting more and more attention; however, two open research questions are how behavioral data of drivers affects driving risk and how driver behavior should affect UBI pricing schemas. This paper proposes a driver risk classification model to evaluate the risk level of drivers based on in-car sensor data. A Behavior-centric Vehicle Insurance Pricing model (BVIP) and a vehicle premium calculation prototype are developed in this paper. Based on empirical data, our research results show that BVIP achieves better accuracy in terms of risk-level classification and the prototype achieves good performance in terms of effectiveness and usability.

Suggested Citation

  • Bian, Yiyang & Yang, Chen & Zhao, J. Leon & Liang, Liang, 2018. "Good drivers pay less: A study of usage-based vehicle insurance models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 20-34.
    • Handle: RePEc:eee:transa:v:107:y:2018:i:c:p:20-34
    DOI: 10.1016/j.tra.2017.10.018
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    References listed on IDEAS

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    7. Omid Ghaffarpasand & Mark Burke & Louisa K. Osei & Helen Ursell & Sam Chapman & Francis D. Pope, 2022. "Vehicle Telematics for Safer, Cleaner and More Sustainable Urban Transport: A Review," Sustainability, MDPI, vol. 14(24), pages 1-20, December.

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