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Age as a Variable in Insurance Pricing and Risk Classification

Author

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  • Mary Kelly

    (Haskayne School of Business, University of Calgary, Calgary, AB T2N 1N4, Canada.)

  • Norma Nielson

    (Haskayne School of Business, University of Calgary, Calgary, AB T2N 1N4, Canada.)

Abstract

This paper examines the use of age in the delivery of personal insurance to Canadians. We find that age is a reliable classification variable and one that can be practically implemented. Primary concerns about age as a classification variable centre around the issue of social acceptability. In particular, we focus on age and auto insurance where, unlike life and health insurance, there exists no strong intuitive causal relationship. In North America, the frequency and severity of auto accidents are highly correlated with age, in a nonlinear relationship. The data produce a distinctive U-shape curve when accident history is graphed against age. However, heterogeneity in driving abilities for both younger and older ages emphasizes that this relationship is one of correlation. To assess whether there exists a “better” classification variable, this paper explores possible alternatives to age. In the end, none of the variables examined captures a driver's risk with the same degree of accuracy as can be achieved using age. The Geneva Papers (2006) 31, 212–232. doi:10.1057/palgrave.gpp.2510082

Suggested Citation

  • Mary Kelly & Norma Nielson, 2006. "Age as a Variable in Insurance Pricing and Risk Classification," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 31(2), pages 212-232, April.
    • Handle: RePEc:pal:gpprii:v:31:y:2006:i:2:p:212-232
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    Citations

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    Cited by:

    1. Jacob Azaare & Zhao Wu & Bright Nana Kwame Ahia, 2022. "Exploring the Effects of Classical Auto Insurance Rating Variables on Premium in ARDL: Is the high Policyholders’ Premium in Ghana Justified?," SAGE Open, , vol. 12(4), pages 21582440221, October.
    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. Donatella Porrini, 2015. "Risk Classification Efficiency and the Insurance Market Regulation," Risks, MDPI, vol. 3(4), pages 1-10, September.

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