Napier asserts that the figure, which amounts to roughly 5% of global GDP, demonstrates the scope of financial crime, which contributes to global instability and weakens economic resilience. The most recent Napier AI / AML Index 2025–2026 was created in collaboration with GlobalData and the data science team at Napier AI, led by Dr. Janet Bastiman.
The report looks at 40 global markets and ranks them according to how well their frameworks for financial crime compliance work. It also looks at how artificial intelligence (AI) is influencing the fight against money laundering and financing of terrorism. According to the report, regulated firms could collectively save as much as $183bn a year by adopting AI-driven compliance systems.
By reducing illicit financial flows, global economies could also recover more than $3.3 trillion annually. These projections highlight the economic potential of AI to transform compliance operations, cutting inefficiencies and minimising the risks associated with outdated manual processes.
Among the countries hit hardest by money laundering losses in absolute terms are China, the United States, Germany, and India. Meanwhile, smaller economies such as the United Arab Emirates, Romania, and South Africa experience the steepest losses relative to GDP, pointing to a disproportionate strain on emerging markets.
According to the estimates in the report, nearly $730 billion, or 2.5% of GDP, is laundered annually in the United States. Brazil bears one of the heaviest burdens, accounting for almost 8% of GDP, while Germany loses more than $209 billion annually, or 4.5 percent of GDP. Money laundering costs the United Kingdom $195 billion annually, or 5.35 percent of GDP. This problem is getting worse because of rising compliance costs and London’s continued role as a hub for cross-border capital. On the other hand, early adoption of AI and strengthened regulatory frameworks have resulted in incremental improvements in markets like Canada and Australia. The human and operational cost of financial crime is also becoming increasingly apparent.
In suspicious activity monitoring, compliance teams in major markets are overwhelmed by false positives. While teams in Nigeria process between 3,000 and 5,000 alerts per day, UK financial institutions handle between 250 and 300 alerts per day compared to 2,000 in Australia. Every day, compliance professionals in Uganda receive approximately 600 alerts.
These figures demonstrate how time-consuming and resource-intensive manual compliance can be, as well as how it directly relates to financial losses. The Index also highlights that several leading economies, including the UK, Germany and Brazil, have experienced a worsening of money laundering impacts relative to GDP. The uneven progress underscores that while AI is beginning to make an impact, the overall value of illicit financial flows remains alarmingly high.
“Our findings show that while global money laundering remains a multi-trillion-dollar problem, there is clear evidence that AI adoption is beginning to make an impact,” Greg Watson, CEO of Napier AI, stated. The difficulty lies in the fact that compliance teams are still overwhelmed by alerts and waste time pursuing false positives. Smarter systems can help cut down on noise, improve detection, and actually save money. “The potential for AI-driven efficiency gains is enormous for nations like Brazil and the United Kingdom, where the impact on GDP is disproportionately high.
The most recent results show a steady rise in financial crime when compared to the index from last year, which showed global losses of $5.2 trillion USD. But the deterioration in markets like the UK underlines that the fight is far from over and the need for explainable, compliance first AI has never been greater.
“The speed of introduction of tariffs this year is a central reason why money laundering has remained rife, creating a breeding ground for financial crime. New opportunities for money laundering and financial crimes have emerged as businesses and supply chains reorganize in response to tariffs. Criminal organizations are manipulating payments, falsifying invoice data, and routing shipments through third countries to conceal their true origin. The introduction of AI, which can assist in the detection of suspicious activity and improve the accuracy of alerts, has the potential to play a pivotal role in navigating these risks and can save economies hundreds of billions of dollars.
The financial services industry’s level of optimism regarding AI’s role in compliance is also evident in the Index results. 73% of respondents said AI was “very useful” for flagging transactions, and 27% said it was the best technology for detecting suspicious activity. According to these findings, financial institutions increasingly view AI as a necessary tool for globally modernizing AML and CFT strategies.