The global economic impact of AI technologies in the fight against financial crime

AI in financial crime prevention shows promise but carries significant risks: The paper finds that while AI adoption is occurring in anti-money laundering (AML) work, "current-generation Artificial Intelligence may offer more harm than benefit" in this context, suggesting the technology is being deployed faster than its capabilities warrant.

Realistic expectations are essential for responsible implementation: The research recommends that managers pursuing AI in AML must have "realistic expectations of Artificial Intelligence's benefits," indicating a gap between industry hype and actual performance that could lead to poor decision-making if not addressed.

An AI Ethics framework is necessary, not optional: The paper explicitly states that "safely pursuing AI in AML requires...using a framework for AI Ethics," positioning ethical governance as a prerequisite rather than an afterthought to AI deployment in sensitive financial sectors.

Regulatory oversight can slow innovation but serves an important function: The study identifies regulators as "natural blockers to innovation," suggesting that while regulation may impede rapid AI adoption, it plays a protective role in preventing premature or harmful deployment in financial crime prevention.

The industry faces a "pressurised situation" requiring careful navigation: The combination of rapid AI adoption, regulatory constraints, and current technological limitations creates tension that demands thoughtful implementation strategies rather than rushed deployment.