Faculty Research Workshop: The Impact of Artificial Intelligence on the Global Financial Trading Ecosystem-Assessing the Implications for Regulatory Governance through the Lens of Complexity Theory by Alessio Azzutti

On 14 September 2022, CBFL Research Associate, Alessio Azzutti, gave a presentation on, ‘The Impact of Artificial Intelligence on the Global Financial Trading Ecosystem-Assessing the Implications for Regulatory Governance through the Lens of Complexity Theory’ at the NUS Faculty of Law Research Workshop. The seminar was moderated by CBFL Academic Fellow, Hu Ying.

Abstract 

Global capital markets can be understood as ‘complex adaptive systems’. Technology innovation and adaptation are driving the current system evolution in global financial trading towards the digital age. Advances in Artificial Intelligence (AI), particularly its subfield of Machine Learning (ML) methods and techniques, within the ramification of algorithmic trading, are transforming the financial ecosystem by contributing to the transition to an emerging ‘machine’ ecology.

In increasingly algorithmic-dominated global capital markets, AI and ML are seen today as key drivers of growing system ‘complexity’. Due to the systematic and transformative nature that AI/ML research and applications have on the organization and functioning of capital markets, global financial regulators face today the challenge of addressing multiple and often conflicting objectives. Namely, they need to address the additional risks and sources of system imbalance introduced by AI without stifling innovation and competition that is beneficial for society. The additional uncertainties driven by enhanced system complexity manifest themselves in at least three different, although interrelated, ways. (I) AI affects the increasingly heterogeneous category of market actors (e.g., with new tech(-enabled) companies adding to traditional industry players), their relations and composition. (II) The widespread use of AI and associated technologies alter the market behavior of market participants. As a consequence, (III) AI also changes the interactions between the various elements of the socio-technical system of global capital markets (i.e. market agents, their relations, combination and behavior), with important implications for the overall governance of the financial ecosystem’s evolution and order. Altogether, these changing dynamics can hamper our ability to understand and control the impacts of technological innovation on financial stability and market integrity.

In examining all these issues, this project evaluates the implications of AI for capital market regulation by using ‘complexity theory’ as a theoretical framework to understand and disentangle the multiple sources of rising system complexity introduced by continuous progress and the widespread adoption of AI within the financial industry. The resulting analysis has a twofold purpose. It develops a novel conceptualization of the elements and dynamics underpinning modern capital markets in order to appreciate the main drivers of system complexity introduced by AI. Further, it provides new insights into fostering innovation in the regulatory science of capital markets, thus, supporting the governance of AI-driven global capital markets.

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