Who benefits from AI in money laundering in Europe: The organised criminals or the aml services?

Artificial Intelligence (AI) has been exerting a growing influence on financial security, particularly in the area of anti-money laundering (AML). This study examines the relationship between AI adoption and AML effectiveness across selected European countries between 2017 and 2023. Employing a panel data econometric model, the analysis incorporates AI Vibrancy Scores, governance indicators, and economic variables to assess the multifaceted impact of AI integration. The findings reveal that greater AI adoption is generally associated with improved AML performance, as reflected by a statistically significant negative relationship between the AI Vibrancy Score and the Basel AML Index. However, the incorporation of a quadratic term indicates an inverted U-shaped relationship, suggesting that while moderate levels of AI adoption enhance AML outcomes, excessive integration may introduce systemic vulnerabilities exploitable by financial criminals. Governance variables – most notably the Rule of Law and Control of Corruption – emerge as key enablers of effective AI-driven AML strategies. Furthermore, factors such as public perception of AI and the presence of responsible AI governance frameworks significantly influence the success of AI applications in AML contexts. These results underscore the necessity of balanced AI policy development, robust institutional frameworks, and international regulatory coordination to harness AI’s potential while mitigating its associated risks.