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Erschienen in: Journal of Business Ethics 1/2020

04.05.2019 | Original Paper

Fairness in Uncertainty: Some Limits and Misinterpretations of Actuarial Fairness

verfasst von: Sylvestre Frezal, Laurence Barry

Erschienen in: Journal of Business Ethics | Ausgabe 1/2020

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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.

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Fußnoten
1
For Baker the two conceptions also reflect different cultural backgrounds (see Baker 2002); for Lehtonen and Liukko, recent developments in marketing that downplay mutuality and solidarity in insurance contribute to the current predominant conception of insurance as a bilateral contract (Lehtonen and Liukko 2015).
 
2
Daston insists that the changed perception towards insurance did not come from new technological capacities but from new social and cultural values (Datson 1987).
 
3
Baker (2002) distinguishes between five kinds of responsibility: responsibility as trustworthiness and autonomy are less relevant to our endeavor here. Causal responsibility is involved in the moral responsibility of the accidents. The transfer of burden to society, at least of work accidents, is visible for instance on the no fault systems adopted in work compensation insurance at the end of the nineteenth century (Ewald 1986). Collective responsibility as social accountability and solidarity also result from this transfer.
 
4
Although, as will be discussed below, the distribution of the cost between the members of the group will determine the level of solidarity embedded in the pooling.
 
5
According to Thiery and Schoubreck, actuarial practices follow the aggregate approach. This is true as long as the information is scarce; however, as they also notice, insurers aim to decrease subsidizing solidarity as much as possible through increasing classification (Thiery and Van Schoubroeck 2006, pp. 195–196).
 
6
Foucault gives as an example the changing approach to diseases and the type of rationalization implied by vaccination: one knows that some will die from the vaccine, but on overall, in the aggregate, the population is better off than without any vaccination (Foucault 2004, pp. 61–62).
 
7
And actually, when explicitly emphasized by a policyholder, this argument is generally nothing but a way to express the desire of paying not “a fair price,” but a lower price.
 
8
Rawls might be an exception here, as he tried to legitimate the group approach with methodological individualism; the veil of ignorance allows him to re-construct the Kantian “enlarged mentality,” based on the individual alone (Rawls 2005).
 
9
Yet the collective level does not by itself grant a situation of plurality, as the latter really depends on the number of observed occurrences, as will be shown below on the example of catastrophes.
 
10
Knight (1985, pp. 224–225) distinguishes three types of situations: a priori probabilities, which are purely mathematical as in a dice throw, for example; statistical probabilities, or the empirical observed frequency within a class of events considered to be homogeneous; and estimates, for which there is “no valid basis of any kind for classifying instances” [his italics]. In accordance with our analysis above, we consider that the distinction between these last two categories does not necessarily depend on the intrinsic nature of the phenomenon but also on the observer’s position relative to the phenomenon.
 
11
See for instance Camerer (1989) or Barberis (2013). For concrete and recent examples of observations disagreeing with standard expectation based theories, see for example Barreda-Tarrazona et al. (2014).
 
12
See Dionne and Rothschild (2014) for a thorough analysis of the moral hazard issue and (Baker 1994) for a historical approach.
 
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Metadaten
Titel
Fairness in Uncertainty: Some Limits and Misinterpretations of Actuarial Fairness
verfasst von
Sylvestre Frezal
Laurence Barry
Publikationsdatum
04.05.2019
Verlag
Springer Netherlands
Erschienen in
Journal of Business Ethics / Ausgabe 1/2020
Print ISSN: 0167-4544
Elektronische ISSN: 1573-0697
DOI
https://doi.org/10.1007/s10551-019-04171-2

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