Money laundering continues to undermine the global economy, draining an estimated $5.5tn every year according to new research by Napier AI.
The report reveals that around 5% of global GDP is laundered annually, underscoring the scale of financial crime and its contribution to worldwide economic instability, Napier claimed.
The findings come from the Napier AI / AML Index 2025–2026, produced in partnership with GlobalData and Napier AI’s Data Science team, led by Dr Janet Bastiman. The Index ranks 40 global markets based on the effectiveness of their financial crime compliance frameworks and explores how artificial intelligence (AI) is reshaping anti-money laundering (AML) and counter-terrorist financing (CFT) efforts.
The report suggests that AI could offer a powerful financial lifeline. Napier AI estimates that regulated firms could collectively save as much as $183bn in annual compliance costs through the adoption of AI-driven systems. On a macroeconomic level, countries could recover more than $3.3tn a year by reducing illicit financial flows through smarter, data-led crime prevention.
Large economies are among the hardest hit by laundering losses in absolute terms. China, the United States, Germany and India top the list, while smaller nations such as the United Arab Emirates, Romania and South Africa experience the most severe impacts relative to GDP.
In the US, almost $730bn is laundered each year—around 2.5% of GDP—making it one of the biggest markets affected after China. Brazil faces an even steeper challenge, with illicit activity estimated to account for nearly 8% of its GDP. In Germany, losses exceed $209bn, or 4.5% of GDP, while the UK sees around $195bn vanish to laundering annually, representing 5.35% of GDP.
The UK’s deterioration compared to last year highlights the persistent pressure on compliance teams, particularly as London remains a global hub for capital flows. Despite significant AI investment, results have yet to materialise. By contrast, early adopters like Canada and Australia have begun to see modest improvements due to proactive regulation and tighter oversight.
Beyond the financial damage, the operational burden on compliance departments remains immense. Teams across the world are inundated with thousands of daily alerts—most of which turn out to be false positives. UK institutions typically face between 250 and 300 alerts a day, while in Australia this figure is around 2,000. In Nigeria, it can reach as high as 5,000, with Uganda recording roughly 600. This overload correlates with GDP losses, highlighting how stretched systems allow financial crime to persist.
The Index also notes a worsening picture across multiple economies, including the UK, Germany and Brazil, where the proportion of GDP lost to money laundering has risen. The data underlines that progress remains uneven and that both developed and emerging markets continue to face significant threats from illicit finance.
Napier AI CEO Greg Watson said, “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. The challenge is that compliance teams are still drowning in alerts, wasting time chasing false positives. Smarter systems can help reduce the noise, sharpen detection, and deliver real economic savings.
“For countries like Brazil and the UK, where the GDP impact is disproportionately high, the opportunity for AI-driven efficiency gains is enormous. Compared with last year’s index, where global losses stood at $5.2 trillion USD, the latest results indicate steady growth of financial crime. 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. As businesses and supply chains reorganise in response to tariffs, new vulnerabilities for money laundering and financial crimes have emerged, with criminal organisations manipulating payments, falsifying invoice data, and routing shipments through third countries to conceal their true origin. The introduction of AI can play a central role in navigating these risks, helping to detect suspicious activity and increasing the accuracy of alerts, which can save economies hundreds of billions.”
The report highlights widespread optimism about AI’s potential in AML efforts. According to the Index, 73% of surveyed industry professionals describe AI as “very useful” for transaction flagging, while 27% regard it as the single most effective tool for identifying suspicious activity. The findings suggest that AI-powered compliance is becoming not only a regulatory advantage but a macroeconomic necessity.
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