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Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data

Author

Listed:
  • Mercedes Ayuso

    () (Department of Econometrics, Riskcenter-IREA, Universitat de Barcelona)

  • Montserrat Guillén

    () (Department of Econometrics, Riskcenter-IREA, Universitat de Barcelona)

  • Jens Perch Nielsen

    () (Cass Business School, City University)

Abstract

We show how data collected from a GPS device can be incorporated in motor insurance ratemaking. The calculation of premium rates based upon driver behaviour represents an opportunity for the insurance sector. Our approach is based on count data regression models for frequency, where exposure is driven by the distance travelled and additional parameters that capture characteristics of automobile usage and which may affect claiming behaviour. We propose implementing a classical frequency model that is updated with telemetrics information. We illustrate the method using real data from usage-based insurance policies. Results show that not only the distance travelled by the driver, but also driver habits, significantly influence the expected number of accidents and, hence, the cost of insurance coverage. This paper provides a methodology including a transition pricing transferring knowledge and experience that the company already had before the telematics data arrived to the new world including telematics information.

Suggested Citation

  • Mercedes Ayuso & Montserrat Guillén & Jens Perch Nielsen, 2017. "Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data," Working Papers 2017-01, Universitat de Barcelona, UB Riskcenter.
  • Handle: RePEc:bak:wpaper:201701
    as

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    File URL: http://www.ub.edu/rfa/research/WP/UBriskcenterWP201701.pdf
    File Function: First version, 2017
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    References listed on IDEAS

    as
    1. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2014. "Causality and contagion in EMU sovereign debt markets," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 12-27.
    2. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    3. Xavier Piulachs & Ramon Alemany & Montserrat Guillen, 2014. "A joint longitudinal and survival model with health care usage for insured elderly," Working Papers 2014-07, Universitat de Barcelona, UB Riskcenter.
    4. Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "Mortality and Longevity Risks in the United Kingdom: Dynamic Factor Models and Copula-Functions," Working Papers 2015-03, Universitat de Barcelona, UB Riskcenter.
    5. Pilar Abad & Helena Chuliá, 2014. "“European government bond market integration in turbulent times”," IREA Working Papers 201424, University of Barcelona, Research Institute of Applied Economics, revised Oct 2014.
    6. Catherine Donnelly & Russell Gerrard & Montserrat Guillén & Jens Perch Nielsen, 2015. "Less is more: increasing retirement gains by using an upside terminal wealth constraint," Working Papers 2015-02, Universitat de Barcelona, UB Riskcenter.
    7. Donnelly, Catherine & Gerrard, Russell & Guillén, Montserrat & Nielsen, Jens Perch, 2015. "Less is more: Increasing retirement gains by using an upside terminal wealth constraint," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 259-267.
    8. Jaume Belles-Sampera & Montserrat Guillén & Miguel Santolino, 2015. "What attitudes to risk underlie distortion risk measure choices?," Working Papers 2015-05, Universitat de Barcelona, UB Riskcenter.
    9. Leo Guelman & Montserrat Guillen & Ana M. Pérez-Marín, 2014. "Optimal personalized treatment rules for marketing interventions: A review of methods, a new proposal, and an insurance case study," Working Papers 2014-06, Universitat de Barcelona, UB Riskcenter.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    tariff; premium calculation; pay-as-you-drive insurance; count data models;

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