AI-driven Market Manipulation and Limits of the EU law enforcement regime to credible deterrence - Alessio Azzutti (University of Hamburg, Institute of Law and Economics (ILE), 2022)
As in many other sectors of EU economies, 'artificial intelligence' (AI) has entered the scene of the financial services industry as a game-changer. Trading on capital markets is undoubtedly one of the most promising AI application domains. A growing number of financial market players have in fact been adopting AI tools within the ramification of algorithmic trading. While AI trading is expected to deliver several efficiency gains, it can also bring unprecedented risks due to the technical specificities and related additional uncertainties of specific 'machine learning' methods. With a focus on new and emerging risks of AI-driven market manipulation, this study critically assesses the ability of the EU anti-manipulation law and enforcement regime to achieve credible deterrence. It argues that AI trading is currently left operating within a (quasi-)lawless market environment with the ultimate risk of jeopardising EU capital markets' integrity and stability. It shows how 'deterrence theory' can serve as a normative framework to think of innovative solutions for fixing the many shortcomings of the current EU legal framework in the fight against AI-driven market manipulation. In concluding, this study suggests improving the existing EU anti-manipulation law and enforcement with a number of policy proposals. Namely, (i) an improved, 'harm-centric' definition of manipulation; (ii) an improved, 'multi-layered' liability regime for AI-driven manipulation; and (iii) a novel, 'hybrid' public-private enforcement institutional architecture through the introduction of market manipulation 'bounty-hunters'.
Keywords: G18; G28; G38; K14; K22; K42; O33; O38; 330; algorithmic trading; artificial intelligence; market manipulation; market integrity; effective enforcement; credible deterrence