2018
DOI: 10.1080/1600910x.2018.1503609
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Who, or what, is insurtech personalizing?: persons, prices and the historical classifications of risk

Abstract: She co-edited Markets and the Arts of Attachment with Franck Cochoy and Joe Deville and is author of Devising Consumption: cultural economies of insurance, credit and spending (Routledge, 2014) and Advertising: a cultural economy (2004).

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Cited by 53 publications
(30 citation statements)
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“…The insurtech, sometimes rendered as insuretech, neologism refers, broadly speaking, to the appearance of market entrants and processes originating in the tech industries cf. McFall and Moor (2018). 5.…”
Section: The Contributionsmentioning
confidence: 99%
“…The insurtech, sometimes rendered as insuretech, neologism refers, broadly speaking, to the appearance of market entrants and processes originating in the tech industries cf. McFall and Moor (2018). 5.…”
Section: The Contributionsmentioning
confidence: 99%
“…However, while banks typically have only access to senders’ account transactions, that is, where, when, how much was paid, non-bank regulated payment services can also generate data detailing the networks of connections between senders and recipients—and link those connections back to data points from online platforms and their ecologies. These large amounts of individually and relationally produced digital data points then are used in corporate analyses to yield aggregated and patterned preferences, for personalized recommendations, targeted marketing, credit scoring (Kear, 2017), insurances (McFall and Moor, 2018), and even prices (Moor and Lury, 2018). Certainly, monetary transactions and products purchased have been recorded and analyzed for many decades, yet the digital data produced in digital payments are “qualitatively and quantitatively different” than before (O’Dwyer, 2019: 8).…”
Section: Payments: Infrastructures and Digital Datamentioning
confidence: 99%
“…Solidaristic elements persist even within a predominantly privatized insurance system. Insurance is solidaristic because it transforms entities into grouped, risk-bearing categories (McFall & Moor, 2018; Meyers & Van Hoyweghen, 2018). Risk has to be grouped because it cannot be calculated at an individual level.…”
Section: Concepts and Organized Practices Of Solidaritymentioning
confidence: 99%
“…Research on how this challenge is being handled in insurance is scant, notwithstanding the frequency with which insurance is invoked as an exemplar of the privacy, surveillance and societal concerns raised by big data. There are extant applications of behavioural tracking data, for example in car insurance, being used for risk assessment (McFall & Moor, 2018; Meyers, 2018) but the industry remains some way from the scenarios presented in the epigraphs. There are many sector and location specific reasons for this.…”
Section: Introductionmentioning
confidence: 99%