Money laundering is draining economies worldwide, with an estimated $5.5tn lost each year across global markets. This equates to 5% of global GDP laundered globally each year as financial crime contributes to economic volatility globally. But the research from Napier AI, in partnership with GlobalData, reveals that $3.3tn could be returned to global economies with AI-powered anti-money laundering (AML) strategies.

The study estimates that regulated firms could save up to $183bn a year in compliance costs by implementing AI-driven systems.

Napier AI/AML Index 2025-2026: 40 global markets ranked

The Napier AI/AML Index 2025-2026 provides 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.

The analysis finds that China, the US, Germany and India are among the hardest hit by money laundering losses in absolute terms. Meantime, 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 US, almost $730bn is laundered annually. This is equivalent to 2.5% 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% of GDP lost to illicit finance. In Germany the annual cost is more than $209bn, or 4.5% of GDP.

UK: Money laundering equates to 5.35% of GDP

In the UK, money laundering drains $195bn each year, accounting for 5.35% of GDP. This represents a deterioration compared with the previous year. This is 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. 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.

AI adoption is starting to make an impact

Greg Watson, CEO at Napier AI, 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 $5.2tn, 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.

Tariffs: New vulnerabilities for financial crime emerge

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% of industry respondents described AI as “very useful” for transaction flagging. Some 27% ranked it as the single most effective tool in detecting suspicious activity within AML processes.