Using risk analytics to prevent accidents before they occur – the future of insurance

Montserrat Guillen and Alberto Cevolini ()
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Alberto Cevolini: Universty of Bologna, Postal: Dipartimento di Scienze Politiche e Sociali, Strada Maggiore 45, Bologna, https://www.unibo.it/sitoweb/alberto.cevolini2/en

Journal of Financial Transformation, 2021, vol. 54, 76-83

Abstract: While insurance was originally devised as a safety net that steps in to compensate for financial losses after an accident has occurred, the information generated by sensors and digital devices now offers insurance companies the opportunity to transform their business by considering prevention. We discuss a new form of risk analytics based on big data and algorithmic prediction in the insurance sector to determine whether accidents could indeed be prevented before they occur, as some now claim is possible. We will use the example of motor insurance where risk analytics is more advanced. Finally, we draw conclusions about insurance’s new preventive role and the effect it may have on the policyholders’ behavior.

Keywords: big data; pricing; motor insurance; telematics (search for similar items in EconPapers)
JEL-codes: C13 G22 G52 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:ris:jofitr:1672

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