Artificial intelligence technologies in banking: challenges and opportunities for anti-money laundering in the context of EU regulatory initiatives

Abstract

Purpose AI capabilities enable banks for more effective anti-money laundering (AML). Regulatory initiatives, including the Sixth Anti-Money Laundering Directive (AMLD6) and the AI Act, impose various requirements on AI-systems developers and users. Therefore, this paper aims to discuss the challenges banks face in the AML framework when implementing AI-systems, as well as the need to balance legal compliance with AI’s technological potential. Design/methodology/approach The discussion on the challenges of AI adoption in banking, considering regulatory initiatives and the search for balance between legal constraints and AI’s technological capabilities, is based on a critical approach. Findings The AI Act provides developers and users with clear requirements and obligations to minimize the negative consequences of AI development. The rapid pace of digital transformation underscores the need for effective global AML standards. Despite ongoing advancements in AI regulation and AML efforts, the challenge of aligning legal requirements – particularly in terms of explainability, confidentiality, impartiality and data security of AI-systems – with the AI’s technological capabilities in the banking sector remains unresolved. The necessity for the EU to develop specific regulations for AI use in finance has been emphasized. Originality/value The paper highlights the key challenges in balancing regulatory compliance with the AI’s technological capabilities used by banks to detect transactions potentially related to money laundering. The focus is placed on current regulatory initiatives, as well as the experience of leading countries in implementing AI-based AML tools.