AI, insurance, discrimination and unfair differentiation. An overview and research agenda

• URL: http://arxiv.org/abs/2401.11892v3
• Date: Wed, 30 Oct 2024 14:57:36 GMT
• Title: AI, insurance, discrimination and unfair differentiation. An overview and research agenda
• Authors: Marvin van Bekkum, Frederik Zuiderveen Borgesius, Tom Heskes,
• Abstract summary: Insurers seem captivated by two trends enabled by Artificial Intelligence (AI) First, insurers could use AI for analysing more and new types of data to assess risks more precisely: data-intensive underwriting. Second, insurers could use AI to monitor the behaviour of individual consumers in real-time: behaviour-based insurance. While the two trends bring many advantages, they may also have discriminatory effects on society.
• Score: 0.6144680854063939
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Insurers underwrite risks: they calculate risks and decide on the insurance premium. Insurers seem captivated by two trends enabled by Artificial Intelligence (AI). (i) First, insurers could use AI for analysing more and new types of data to assess risks more precisely: data-intensive underwriting. (ii) Second, insurers could use AI to monitor the behaviour of individual consumers in real-time: behaviour-based insurance. For example, some car insurers offer a discount if the consumer agrees to being tracked by the insurer and drives safely. While the two trends bring many advantages, they may also have discriminatory effects on society. This paper focuses on the following question. Which effects related to discrimination and unfair differentiation may occur if insurers follow data-intensive underwriting and behaviour-based insurance? Researchers and policymakers working in other sectors may also find the paper useful, as the insurance sector has decades of experience with statistics and forms of AI. Moreover, some questions that arise in the insurance sector are important in other sectors too.

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