DELAWARE, October 21, 2025 – 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, making it one of the largest single markets impacted in dollar terms, second only to China. Yet, despite this, financial institutions spent nearly $60bn annually on financial crime compliance, a fraction compared to the scale of losses. 

Its losses only equate to 2.5 per cent of GDP, half of the global figure, reflecting strong frameworks, with compliance spending offsetting less than 9 per cent of laundered funds. 

Regulatory shifts are creating mixed signals. The rollback of the Corporate Transparency Act in March 2025 weakened corporate ownership disclosure, while new FinCEN real estate rules, due to take effect in December 2025, tighten oversight of property transactions. Most recently, the US Treasury further announced a major relaxation of Suspicious Activity Report (SAR) obligations, easing the bureaucratic burden on US financial institutions and allowing compliance teams to focus on more efficient, technology-led AML processes. 

This move reflects a growing recognition of AI’s role in improving detection accuracy and is expected to influence similar regulatory thinking in Europe and beyond. However, this shift does not mean regulators should take their foot off the pedal. Strong oversight and supervisory vigilance remain essential. Alongside sanctions under the FEND Off Fentanyl Act, these developments show how uneven enforcement continues to leave gaps for criminals to exploit. 

Looking ahead, Napier AI estimates that advanced technology, including AI, could deliver up to $23.4 billion in potential compliance savings each year, while North America as a whole could block $171bn in dirty money through AI-enabled strategies. While the US has one of the largest absolute savings potential from AI adoption, an estimated $23.4 billion annually, this represents only 0.9 per cent of GDP. 

By contrast, markets such as Hong Kong (4.0 per cent) and France (3.5 per cent) stand to see far greater relative impact. The data suggests that, despite its scale, the US financial system is already performing comparatively well in curbing illicit flows, with AI offering incremental rather than transformative gains in the context of its overall economy. 

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 burden is not only financial, but operational. US compliance teams are overwhelmed by high alert volumes, with many systems still generating excessive false positives. 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.