Regulatory Space, Regulatory Intermediaries and Socio-Technical Systems: The Challenges and Opportunities of AI-Based Regulatory Technology

Regulatory governance scholars have long used the regulatory space metaphor to highlight the fragmentation of regulatory resources and capacities, and the dispersal of these resources and capacities among a multitude of actors engaged in the regulatory processes. Building upon the regulatory space metaphor, regulatory governance scholars have become increasingly interested in the role played by intermediaries in the regulatory process. To think in terms of regulatory space and regulatory intermediaries is fruitful as these concepts spotlight the variety of roles, relations, resources and capacities that contribute to the regulatory process. However, over the last number of years many organisations have begun to use technologies based upon forms of artificial intelligence (AI), such as machine learning and natural language processing, to automate, augment and aid their regulatory work. These technologies, known as RegTech, are now a key focus for policy makers and regulators, particularly in the area of financial regulation. Here, the increased use of AI-based RegTech has led to an increasingly complex socio-technical system in which regulation operates, which has been met with both optimism and concern by stakeholders. Drawing upon research focusing upon the use of AI-based RegTech in the financial sector, this paper addresses these developments in two way. Firstly, I argue that it is productive to now think about the regulatory process as a socio-technical system. Building upon this, I secondly seek to identify what I contend are the key opportunities and concerns brought about by the introduction of AI-based RegTech, and how financial regulators and policy makers have begun to tackles these issues.