From Actuarial to Behavioural Valuation. The impact of telematics on motor insurance
Keywords:adverse selection, behavioural valuation, telematics motor insurance, algorithmic prediction, subsidisation, risk transfer
Algorithmic predictions are used in insurance to assess the risk exposure of potential customers. This article examines the impact of digital tools on the field of motor insurance, where telematics devices produce data about policyholders’ driving styles. The individual’s resulting behavioural score is combined with their actuarial score to determine the price of the policy or additional incentives. Current experimentation is moving in the direction of proactivity: instead of waiting for a claim to arise, insurance companies engage in coaching and other interventions to mitigate risk. The article explores the potential consequences of these practices on the social function of insurance, which makes risks bearable by socialising them over a pool of insured individuals. The introduction of behavioural variables and the corresponding idea of fairness could instead isolate individuals in their exposure to risk and affect their attitude towards future initiatives.
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Copyright (c) 2022 Alberto Cevolini, Elena Esposito
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