From Actuarial to Behavioural Valuation: The Impact of Telematics on Motor Insurance

Algorithmic predictions are used in insurance to assess the risk exposure of potential customers, for the purpose of improving how the problem of adverse selection is tackled. This paper examines the impact of digital tools in the field of motor insurance, where telematics devices produce data about the behaviour of the insured party. 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 occur, insurance companies engage in coaching and other interventions to mitigate the risk. Such practices may have consequences for the social function of insurance, whose traditional aim has been not to reduce risks, but to make them 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 the future.