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The added value of dynamically updating motor insurance prices with telematics collected driving behavior data

Author

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  • Henckaerts, Roel
  • Antonio, Katrien

Abstract

We analyze a novel dataset collecting the driving behavior of young policyholders in a motor third party liability (MTPL) portfolio, followed over a period of three years. Driving habits are measured by the total mileage and the distance driven on different road types and during distinct time slots. Driving style is characterized by the number of harsh acceleration, braking, cornering and lateral movement events. First, we develop a baseline pricing model for the complete portfolio with claim history and self-reported risk characteristics of approximately 400,000 policyholders each year. Next, we propose a methodology to update the baseline price via the telematics information of young drivers. Our approach results in a truly usage-based insurance (UBI) product, making the premium dependent on a policyholder's driving habits and style. We highlight the added value of telematics via improvements in risk classification and we put focus on managerial insights by analyzing expected profits and retention rates under our new UBI pricing structure.

Suggested Citation

  • Henckaerts, Roel & Antonio, Katrien, 2022. "The added value of dynamically updating motor insurance prices with telematics collected driving behavior data," Insurance: Mathematics and Economics, Elsevier, vol. 105(C), pages 79-95.
    • Handle: RePEc:eee:insuma:v:105:y:2022:i:c:p:79-95
    DOI: 10.1016/j.insmatheco.2022.03.011
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    Citations

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    Cited by:

    1. Chih-Te Yang & Yensen Ni & Mu-Hsiang Yu & Yuhsin Chen & Paoyu Huang, 2023. "Decoding the Profitability of Insurance Products: A Novel Approach to Evaluating Non-Participating and Participating Insurance Policies," Mathematics, MDPI, vol. 11(13), pages 1-16, June.
    2. Marian Reiff & Erik Šoltés & Silvia Komara & Tatiana Šoltésová & Silvia Zelinová, 2022. "Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 803-842, September.
    3. Sojung Kim & Marcel Kleiber & Stefan Weber, 2022. "Microscopic Traffic Models, Accidents, and Insurance Losses," Papers 2208.12530, arXiv.org, revised Nov 2023.

    More about this item

    Keywords

    Usage-based insurance; Pricing; Telematics; Driving behavior; Profits; Client retention;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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