Alessio 
AZZUTTI

 

Alessio is a Research Associate at the Centre for Banking & Finance Law, NUS. Before joining the Centre, Alessio was a Research Associate with the ‘Law, Finance, & Technology’ programme at the Institute of Law & Economics of the University of Hamburg, where he is also pursuing his doctoral studies in Law. Previously, Alessio obtained an LL.M. in Law and Economics at Utrecht University in August 2018 and an M.Sc. in Finance and Risk Management at the University of Florence in July 2016. Thanks to his interdisciplinary academic background, Alessio can be considered a ‘hybrid’ researcher at the intersection of finance, economic law and technology studies. His current research focuses on the implications of technological innovation for banking, payments, capital markets law and crime from an interdisciplinary perspective. He is also a member of the European Banking Institute Young Researchers Group.

FULL BIOGRAPHY

Contact

aazzutti@nus.edu.sg
(65) 6601 2931
Block B, LT-02-01

Education

Ph.D Candidate in Law (Universität Hamburg)

LL.M. Law and Economics (Utrecht University)

M.Sc. in Finance and Risk Management (University of Florence)

In Residence

1 August 2022 to 30 September 2023

Presentations

  • “Artificial Intelligence in Finance: Legal and Regulatory Challenges”, organised by Centre for AI and Digital Governance, Singapore Management University (SMU), (8 May 2023)
  • “Good Administration in AI-Driven Banking Decisions”, CBFL Working Paper Presentation (20 April 2023)
  • “Artificial Intelligence Systems and EU Law Enforcement – Between Effectiveness and the Rule of Law”, organized by The Jean Monnet Network on EU Law Enforcement (EULEN) and the University of Castilla-La Mancha (UCLM) (Toledo, 23-24 March 2023)
  • “AI Trading and Market Manipulation – Challenges for Financial Regulators”, AI Café  (22 February 2023) via Zoom
  • “The Regulation of AI Trading from an AI Life Cycle Perspective”, Junior Corporate Law Scholars Workshop (AY 2022-23), 28 November 2022 via Zoom
  • “Data in Financial Services – Open Finance” Panel 2, Cyberspace Conference organised by Masaryk University, 25-26 November 2022 via Zoom
  • “‘Good Administration’ in AI-Driven EU Banking Supervision”, Young Scholars Initiative organised by Amsterdam Center for Law & Economics, 27-28 October 2022 via Zoom (with Pedro Magalhães Batista, University of Leeds)
  • “The Impact of Artificial Intelligence on Global Capital Markets’ Ecosystem: Assessing the Implications for Regulatory Governance through the Lens of ‘Complexity Theory”, NUS Faculty  of Law Research Workshop,  14 September 2022

Selected Publications

Book Chapter

  • Azzutti, A., “The Algorithmic Future of EU Market Conduct Supervision: A Preliminary Check” in Böffel, L. and Schürger, J. (eds) Digitalisation, Sustainability, and the Banking and Capital Markets Union. EBI Studies in Banking and Capital Markets Law (Palgrave Macmillan, Cham, 2022) https://doi.org/10.1007/978-3-031-17077-5_2 
  • Azzutti, A., W.G. Ringe & H.S. Stiehl, “Regulating AI trading from an AI lifecycle perspective” in Nydia Remolina and Aurelio Gurrea-Martinez (eds)’s  Artificial Intelligence in Finance (Elgar Online, 2023) https://doi.org/10.4337/9781803926179

Articles

  • A. Azzutti, W.G. Ringe & H.S. Stiehl, ‘Künstliche Intelligenz und Marktmanipulation.’ (2022) 34(6) Zeitschrift für Bankrecht und Bankwirtschaft 341-356, https://doi.org/10.15375/zbb-2022-0604
  • Azzutti, A., W.G. Ringe & H.S. Stiehl, ‘The Regulation of AI Trading from an AI Life Cycle Perspective’ (2022) European Banking Institute Working Paper Series 2022 – no. 130, http://dx.doi.org/10.2139/ssrn.4260423
  • Azzutti, A., ‘AI trading and the limits of EU law enforcement in deterring market manipulation.’ (2022) 45 Computer Law & Security Review: The International Journal of Technology Law and Practice 105690 https://doi.org/10.1016/j.clsr.2022.105690
  • Azzutti, A., W.G. Ringe & H.S. Stiehl, ‘Machine Learning, Market Manipulation and Collusion on Capital Markets: Why the ‘Black Box’ Matters.’ (2021) 43 University of Pennsylvania Journal of International Law 79
  • Banking Law
  • Capital Market Law
  • Algorithmic Trading Regulation
  • Digitalization of money
  • Law & Technology
  • AI Law

Research Project

Artificial Intelligence and Algorithmic Trading: A Comparative Study of Different Regulatory Cultures and Approaches through the Lens of ‘Complexity Theory’

This project aims to study and analyse different cultures and approaches to regulating risks stemming from technological innovation in the field of algorithmic trading by applying insights from ‘complexity theory’ as a methodological framework.

Today’s capital markets, which are increasingly globalised and interconnected but fragmented, can be understood as complex dynamic systems. Whereas markets become increasingly complex and sophisticated network systems involving a growing number of different actors beyond traditional industry players such as investment firms (e.g., tech companies), global financial regulators face growing challenges in safeguarding financial stability while fostering technological innovation. Indeed, AI trading is generally proposed to deliver several efficiency gains for a wide range of market participants and society. However, it can also lead to new ethical-legal issues due to machine learning methods’ technical specificities (e.g., data-reliance, the ‘black-box’ problems, and increasing levels of system autonomy) and the potential to cause disruptions and other market failures (e.g., market manipulation).

Through an interdisciplinary research methodology between law and technology, enriched by insights from ‘complexity theory’ applied to global capital markets, this project intends to examine and compare different regulatory frameworks for the governance of AI-driven algorithmic trading and electronic trading platforms in selected jurisdictions in order to identify diversities and similarities among so-called Western and Asian legal systems in mastering the growing complexity led by advances in algorithmic trading technology.

 

 

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