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LONDON, 21 October– Money laundering is draining economies worldwide, with an estimated $5.5 trillion USD lost each year across global markets, according to new research from Napier AI.
This equates to 5 per cent of global gross domestic product (GDP) laundered globally each year as financial crime contributes to economic volatility around the world.
The findings from the Napier AI / AML Index 2025 - 2026, in partnership with GlobalData and Napier AI’s Data Science team, led by Dr Janet Bastiman, provide a comprehensive insight into the impact of artificial intelligence (AI) on anti-money laundering and counter terrorist financing (AML/CFT). The Index ranks 40 global markets based on their effectiveness in financial crime compliance.
Napier AI estimates that regulated firms could save as much as $183 billion USD a year in compliance costs by implementing AI-driven systems, while global economies could recover more than $3.3 trillion USD annually by reducing illicit flows.
The analysis finds that China, the United States, Germany and India are among the hardest hit by money laundering losses in absolute terms, while smaller economies such as the United Arab Emirates, Romania and South Africa suffer the steepest losses relative to GDP.
Financial crime continues to exact a heavy toll on national economies. In the United States, almost $730 billion is laundered annually, equivalent to 2.5 per cent of GDP, making it one of the largest single markets impacted in dollar terms, second only to China. Brazil faces one of the heaviest proportional burdens, with nearly 8 per cent of GDP lost to illicit finance, while in Germany the annual cost is more than $209 billion USD, or 4.5 per cent of GDP.
In the United Kingdom, money laundering drains $195 billion USD each year, accounting for 5.35 per cent of GDP. This represents a deterioration compared with the previous year, driven by rising compliance costs and London’s continuing role as a global hub for foreign capital flows. The AI investment has been heavy, and it has not yet started paying off. By contrast, countries such as Canada and Australia have recorded modest improvements, benefitting from early AI adoption and the closing of regulatory loopholes.
The burden is not only financial but also operational. Compliance teams across the world are struggling with the daily volume of suspicious activity alerts, many of which turn out to be false positives. In the UK, institutions typically deal with between 250 and 300 alerts a day, while in Australia the figure is closer to 2,000. In Nigeria, compliance teams face between 3,000 and 5,000 alerts every single day, and in Uganda the figure is around 600. These volumes correlate closely with GDP losses, demonstrating how overstretched systems allow criminal activity to slip through the cracks.
This points to a headline increase in the overall value of illicit flows. Several major economies, including the UK, Germany and Brazil have seen worsening impacts relative to GDP, highlighting that progress is uneven and that the burden of financial crime remains acute in both developed and emerging markets.
Greg Watson, CEO at Napier AI, commented:
“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 Napier AI / AML Index also highlights the potential for AI to transform financial crime compliance. In surveys conducted for the Index, 73 per cent of industry respondents described AI as “very useful” for transaction flagging, while 27 per cent ranked it as the single most effective tool in detecting suspicious activity within AML processes.
