Hidden Depths: the Effects of Extrinsic Data Collection on Consumer Insurance Contracts

Abstract

Commentators have predicted that the insurance industry will soon benefit from technological advancements, such as developments in Artificial Intelligence (‘AI’) and Big Data. The application of AI- and Big Data-powered tools promises cost reduction, the creation of innovative products, and the potential to offer more efficient and tailored services to consumers. However, these new opportunities are mirrored by new legal and regulatory challenges. This article discusses challenges facing Australian data protection law, focusing on (potential) collection of consumers' data by insurers from non-traditional sources. In particular, we examine situations in which consumers may not be aware that the data collected could end up being used to price insurance. In our analysis, we discuss two useful examples of such non-traditional data sources: customer loyalty schemes and social media. These may give rise to several concerning data practices, including a significant increase in the collection of consumers' data by insurers. We argue that datafication of insurer processes may fuel excessive data collection in the context of insurance contracts, generating a substantial risk of harm to consumers, especially in terms of discrimination, exclusion, and unaffordability of insurance. We complement our analysis with the discussion of Australian insurance-specific provisions, asking if, and how, the harms examined could be adequately addressed.

Keywords: Artificial intelligence; Big data; Consumer insurance; Privacy; Data protection