Fairness in Uncertainty: Some Limits and Misinterpretations of Actuarial Fairness
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ORIGINAL PAPER
Fairness in Uncertainty: Some Limits and Misinterpretations of Actuarial Fairness Sylvestre Frezal1 · Laurence Barry2,3,4 Received: 30 October 2018 / Accepted: 27 April 2019 © Springer Nature B.V. 2019
Abstract The recent proliferation of new data and technologies enables increasingly finer personalization of products and prices in every domain. In insurance, this revives and enlarges old debates around fairness that have never been completely settled. We will argue that the commonly accepted “actuarial fairness” as based on the “individual cost of risk” derives in fact from a conflation: while it indicates the average cost for a group of insureds from the perspective of an insurance company—and is therefore sound from a business profitability viewpoint—it is arguable whether it represents the “fair price” for the individual insured. We first show in a historical perspective the intertwinement of conceptions of fairness with knowledge, in order to point to the alternative to actuarial fairness for insurance. We then describe the intrinsic difference between the insured and the insurer (or portfolio manager) when underwriting an insurance contract. Finally, we build on this distinction to discuss the meaning of fairness in insurance prices. We thus hope to re-center the debate around insurance fairness on its underlying solidarity mechanisms rather than technical and actuarial considerations. Keywords Actuarial fairness · Insurance fairness · Classification · Insurance solidarity · Risk apprehension
Introduction With the rise of social networks, the arrival of connected objects, the development of information technology, and advances in the data sciences, big data enables increasingly finer personalization of products. In domains other than insurance, studies already show that online prices are adjusted to customers according to the way they are tagged by marketing agencies, rather than the cost of production (Turow et al. 2015). In insurance, the possibility to adjust the premium to the individual risk, also called “actuarial fairness,” is empowered by these new technologies, as a vast array of new parameters are made available for a fine tuning * Laurence Barry [email protected] Sylvestre Frezal [email protected] 1
Covéa, 86‑90 rue Saint‑Lazare, 75009 Paris, France
2
Political Science Department, Hebrew University of Jerusalem, Jerusalem, Israel
3
Chaire PARI, Paris, France
4
Datastorm, 60 rue Etienne Dolet, 92240 Malakoff, France
of risk measurement and pricing. Some of the data at stake do not necessarily affect risks though, but rather characterize the individual in his or her propensity to buy or cancel a contract (Siegel 2016). The emergence of data science revives and enlarges, we would like to argue, old debates around the fairness of insurance prices that have never been completely settled. In this endeavor, insurance regulators have a specific role to play. Yet driven by the same desire to avoid unfair discrimination and trying to put limits on the
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