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The Faculty of Law, Economics and Finance of the ����ͷ�� is pleased to invite you to this NCER FutureFinTech Conference on 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, ����ͷ��

• 09.15 – 09.30

  Introductory speech

  Stanisław Tosza, Associate Professor in Compliance and Law Enforcement, Faculty of Law, Economics and Finance, ����ͷ��

• 09.30 – 10.15

  Keynote speech – “Rethinking data access in the context of Anti-Money Laundering – a closer look into AML registers”

  Eleni Kosta, Professor of Technology Law and Human Rights, Tilburg Institute for Law, Technology and Society, Tilburg ����ͷ��versity

Panel I – Knowing Your Customer through Artificial Intelligence
Chair: Julia Sinnig, Assistant Professor, Faculty of Law, Economics and Finance, ����ͷ��

• 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, ����ͷ��

  Using AI to know your customer: Challenges for fundamental rights

  Olivier Voordeckers, Postdoctoral researcher, Faculty of Law, Economics and Finance, ����ͷ��

• 11.45 – 12.00

  Coffee break

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

• 12.00 – 13.30

  Leveraging machine learning to detect suspicious transactions

  Anis Kacem, Research scientist, Interdisciplinary Centre for Security, Reliability and Trust, ����ͷ��

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

  Umut Turksen, Professor in Law, Research Centre for Financial & Corporate Integrity, Coventry ����ͷ��versity

  Legal perspectives on AI adoption in Financial Intelligence ����ͷ��ts

  Andra Giurgiu, Délégué à la protection des données, Cellule de Renseignement Financier, Parquet Général du Grand-Duché de Luxembourg

• 13.30 – 14.30

  Lunch break

Panel III – Automated anti-money laundering compliance vs. GDPR-compliance
Chair: Stanisław Tosza, Associate Professor in Compliance and Law Enforcement, Faculty of Law, Economics and Finance, ����ͷ��

• 14.30 – 16.00

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

  Sallam Abualhaija, Research scientist, Interdisciplinary Centre for Security, Reliability and Trust, ����ͷ��

  AML-purpose AI and GDPR compliance

  Anthony Cardinaux, Lawyer at Kaufhold & Réveillaud

  AML-purpose AI and data sharing

  Magdalena Brewczyńska, Post-doctoral researcher, Tilburg ����ͷ��versity

• 16.00 – 16.15

  Coffee break

Panel IV – Explainability of AI-generated AML-compliance decisions
Chair: Raphaël Frank, Assistant Professor/Senior Research Scientist, Interdisciplinary Centre for Security, Reliability and Trust, ����ͷ��

• 16.15 – 17.45

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

  Céline Castets-Renard, Canada Research Chair Holder in International and Comparative AI Law, ����ͷ��versity 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

  Salomé Lannier, Postdoctoral researcher, Faculty of Law, Economics and Finance, ����ͷ��

  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, ����ͷ��

• 17.45 – 18.00

  Closing remarks

  • Stanisław Tosza, Associate Professor in Compliance and Law Enforcement, Faculty of Law, Economics and Finance, ����ͷ��
  • Raphaël Frank, Assistant professor/Senior research scientist, Interdisciplinary Centre for Security, Reliability and Trust, ����ͷ��
  • Djamila Aouada, Assistant professor/Senior research scientist, Interdisciplinary Centre for Security, Reliability and Trust, ����ͷ��

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