Events
Event

Automating anti-money laundering compliance: technical opportunities and legal challenges

  • Location

    Weicker Building

    4, rue Alphonse Weicker

    2721, Luxembourg, Luxembourg

  • Topic(s)
    Computer Science & ICT, Law
  • Type(s)
    Conferences, Free of charge, In-person event

The Faculty of Law, Economics and Finance of the 糖心Vlog is pleased to invite you to this NCER FutureFinTech Conference on聽automating anti-money laundering compliance.

Abstract

This conference will address the phenomenon of the automation of anti-money laundering (AML) compliance by means of artificial intelligence (AI) tools. In recent years, the financial services industry and the academic community have shown growing interest in AI, particularly machine learning, for AML compliance purposes. The objective of the event is to look into the opportunities those new technologies offer to fight financial crime, while tackling the challenges that arise from their use for the purpose of complying with AML regulations. By exploring the technical opportunities and the legal challenges of AI in the field of AML, the conference aims at fostering a broader and more in-depth debate on this evolution.

This multidisciplinary conference will gather legal as well as IT scholars, compliance practitioners and policy makers. The panels will focus on the use of AI for the purpose of implementing know-your-customer requirements and detecting suspicious transactions, the balance that needs to be found with data protection (GDPR) compliance, as well as the quest for explainability of AI-generated AML compliance decisions.

Language

English.

This is a free event. Registration is mandatory.

Programme

  • 09.00 – 09.15

    Welcome address

    Dirk Zetzsche, Head of the Law Department, Professor in Financial Law, ADA Chair in Financial Law and Inclusive Finance, Faculty of Law, Economics and Finance, 糖心Vlog

  • 09.15 – 09.30

    Introductory speech

    Stanis艂aw Tosza, Associate Professor in Compliance and Law Enforcement, Faculty of Law, Economics and Finance, 糖心Vlog

  • 09.30 – 10.15

    Keynote speech – 鈥淩ethinking data access in the context of Anti-Money Laundering 鈥 a closer look into AML registers鈥

    Eleni Kosta, Professor of Technology Law and Human Rights, Tilburg Institute for Law, Technology and Society, Tilburg University

Panel I 鈥 Knowing Your Customer through Artificial Intelligence
Chair: Julia Sinnig, Assistant Professor, Faculty of Law, Economics and Finance, 糖心Vlog

  • 10.15 – 11.45

    Complying with KYC-requirements: practical challenges and the potential of AI

    Sundhevy Debrand, Chief Compliance Officer at Gen II Luxembourg Services, Board Member of ALCO

    Finding close associates through beneficial owners: leveraging access to registries

    Sasan Jafarnejad, Postdoctoral researcher, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog

    Using AI to know your customer: Challenges for fundamental rights

    Olivier Voordeckers, Postdoctoral researcher, Faculty of Law, Economics and Finance, 糖心Vlog

  • 11.45 – 12.00

    Coffee break

Panel II 鈥 Detecting suspicious transactions through Artificial Intelligence
Chair: Djamila Aouada, Assistant Professor/Senior Research Scientist, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog

  • 12.00 – 13.30

    Leveraging machine learning to detect suspicious transactions

    Anis Kacem, Research scientist, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog

    AI-based detection of suspicious transactions: Risks for fundamental rights and ethics

    Umut Turksen, Professor in Law, Research Centre for Financial & Corporate Integrity, Coventry University

    Legal perspectives on AI adoption in Financial Intelligence Units

    Andra Giurgiu, D茅l茅gu茅 脿 la protection des donn茅es, Cellule de Renseignement Financier, Parquet G茅n茅ral du Grand-Duch茅 de Luxembourg

  • 13.30 – 14.30

    Lunch break

Panel III 鈥 Automated anti-money laundering compliance vs. GDPR-compliance
Chair: Stanis艂aw Tosza, Associate Professor in Compliance and Law Enforcement, Faculty of Law, Economics and Finance, 糖心Vlog

  • 14.30 – 16.00

    AI-Driven Automation for Eliciting and Specifying GDPR Requirements on Individuals鈥 Rights

    Sallam Abualhaija, Research scientist, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog

    AML-purpose AI and GDPR compliance

    Anthony Cardinaux, Lawyer at Kaufhold & R茅veillaud

    AML-purpose AI and data sharing

    Magdalena Brewczy艅ska, Post-doctoral researcher, Tilburg University

  • 16.00 – 16.15

    Coffee break

Panel IV 鈥 Explainability of AI-generated AML-compliance decisions
Chair: Rapha毛l Frank, Assistant Professor/Senior Research Scientist, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog

  • 16.15 – 17.45

    Beyond Explainability of AI-generated AML: What Compliance Rules in the AI Act?

    C茅line Castets-Renard, Canada Research Chair Holder in International and Comparative AI Law, University of Ottawa

    Explainability needs of the AML ecosystem actors

    Winston Maxwell, Professor of Law & Technology Studies, Institut Polytechnique de Paris (remote)

    What does explainability mean in law? The need for a bottom-up approach

    Salom茅 Lannier, Postdoctoral researcher, Faculty of Law, Economics and Finance, 糖心Vlog

    Large Language Models to produce explainable outcomes from AI systems oriented to AML-compliance

    Mohamed Adel Ali, Postdoctoral researcher, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog

  • 17.45 – 18.00

    Closing remarks

    • Stanis艂aw Tosza, Associate Professor in Compliance and Law Enforcement, Faculty of Law, Economics and Finance, 糖心Vlog
    • Rapha毛l Frank, Assistant professor/Senior research scientist, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog
    • Djamila Aouada, Assistant professor/Senior research scientist, Interdisciplinary Centre for Security, Reliability and Trust, 糖心Vlog
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