ROBOtic Process Automation in Anti-Money Laundering (AML) COMPliance
The ROBOCOMP project addresses the increasing use of automation, particularly machine learning tools, in Anti-Money Laundering (AML) compliance by financial institutions. It aims to understand and contribute to the development of these tools while critically analysing the existing legal framework and its implications. This interdisciplinary project brings together legal scholars and computer scientists to foster better RegTech solutions.
The project at a glance
About
The ROBOCOMP project investigates the increasing integration of automation, especially machine learning tools, in Anti-Money Laundering (AML) compliance within financial institutions. This interdisciplinary initiative unites legal experts and computer scientists from the University of Luxembourg’s Faculty of Law, Economics and Finance (FDEF) and the Interdisciplinary Centre for Security, Reliability and Trust (SnT), along with its two research groups – the Ubiquitous and Intelligent Systems Research Group and the Computer Vision, Imaging & Machine Intelligence Research Group.
The aim is to enhance understanding of these technologies while critically evaluating the existing legal framework and its implications. Focusing on AML compliance, ROBOCOMP seeks to improve machine learning tools and explore the legal ramifications of their use. The project’s research aligns with the theme of “Compliance by Design”, fostering collaboration, cross-disciplines and examining how compliance regulations shape technological advancement. ROBOCOMP delves into the automation of due diligence processes and the legal consequences of utilising AI tools for AML/Know Your Customer (KYC) compliance, contributing to the evolution of vetted AI technology. Researchers assess information gathering methods to enhance these processes.
Key objectives include analysing beneficial ownership, transactions, and legal challenges, while leveraging technology and compliance by design to address these issues. Ultimately, ROBOCOMP aims to create technological tools that address identified legal challenges, ensuring compliance by design and fostering the development of advanced RegTech solutions. The project focuses on three different objectives. First, the project aims to develop a methodology for collecting open-access data from European business and beneficial owner registries, facilitating the analysis of complex relationships to identify anomalies and fraudulent activities. Second, ROBOCOMP intends to create an AI tool that monitors transactions and detects unusual financial patterns or compliance breaches. Finally, the project examines the level of automation in the Luxembourg financial sector’s AML compliance efforts and the associated legal implications, particularly regarding the protection of affected individuals.
Organisation and Partners
Faculty of Law, Economics and Finance (FDEF)
Department of Law
Interdisciplinary Centre for Security, Reliability and Trust (SnT)
Computer Vision, Imaging and Machine Intelligence (CVI2)
