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How Do Unisex Rating Regulations Affect Gender Differences in Insurance Premiums?

Author

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  • Vijay Aseervatham

    (Munich Risk and Insurance Center, LMU Munich, Schackstrasse 04, Munich 80539, Germany. E-mails: aseervatham@bwl.lmu.de; lex@bwl.lmu.de)

  • Christoph Lex

    (Munich Risk and Insurance Center, LMU Munich, Schackstrasse 04, Munich 80539, Germany. E-mails: aseervatham@bwl.lmu.de; lex@bwl.lmu.de)

  • Martin Spindler

    (Max Planck Institute for Social Law and Social Policy/Munich Center for the Economics of Aging, Amalienstrasse 33, Munich 80799, Germany.)

Abstract

As of 21 December 2012, the use of gender as an insurance rating category is prohibited in the EU. Any remaining pricing disparities between men and women will now be traced back to the reasonable pricing of characteristics that happen to differ between the groups or to the pricing of characteristics that differ between sexes in a way that proxies for gender. Using data from an automobile insurer, we analyse how the standard industry approach of simply omitting gender from the pricing formula, which allows for proxy effects, differs from the benchmark for what prices would look like if direct gender effects were removed and other variables did not adjust as proxies. We find that the standard industry approach will likely be influenced by proxy effects for younger and older drivers. Our method can simply be applied to almost any setting where a regulator is considering a uniform pricing reform.

Suggested Citation

  • Vijay Aseervatham & Christoph Lex & Martin Spindler, 2016. "How Do Unisex Rating Regulations Affect Gender Differences in Insurance Premiums?," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 41(1), pages 128-160, January.
    • Handle: RePEc:pal:gpprii:v:41:y:2016:i:1:p:128-160
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    Citations

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    Cited by:

    1. Shan Huang & Martin Salm, 2020. "The effect of a ban on gender‐based pricing on risk selection in the German health insurance market," Health Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 3-17, January.
    2. David A. Cather, 2020. "Reconsidering insurance discrimination and adverse selection in an era of data analytics," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(3), pages 426-456, July.
    3. Huang, Shan & Salm, Martin, 2020. "The effect of a ban on gender-based pricing on risk selection in the German health insurance market," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29(1), pages 3-17.
    4. Mercedes Ayuso & Montserrat Guillen & Jens Perch Nielsen, 2019. "Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data," Transportation, Springer, vol. 46(3), pages 735-752, June.
    5. 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.
    6. Mercedes Ayuso & Montserrat Guillen & Ana María Pérez-Marín, 2016. "Telematics and Gender Discrimination: Some Usage-Based Evidence on Whether Men’s Risk of Accidents Differs from Women’s," Risks, MDPI, vol. 4(2), pages 1-10, April.

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