.svg)
$5.09tn was lost to money laundering globally last year, equivalent to 4.30% of global GDP, according to new data from Napier AI. That’s despite recording the first year-on-year decline in global money laundering losses since Napier AI began analysing, with the figure falling by an estimated $203.33bn.
The findings come from the Napier AI / AML Index 2026–2027, in partnership with GlobalData. Led by Dr Janet Bastiman, Chief Data Scientist at Napier AI, the Index provides insight into the money laundering landscape across 42 global markets.
Money laundering fell as a share of GDP from 4.97% in 2023 to 4.88% in 2024 to 4.30% in 2025. While nominal GDP growth accounts for some of that difference, this year represents the first time the Napier AI / AML Index has found a reduction in the total value of illicit funds. This is the first sign that it is possible to outpace organised crime through anti-money laundering innovations.
Greg Watson, CEO of Napier AI, commented: “The scale of money laundering remains staggering even with promising signs of pushback in the fight against financial crime. For too long it has been assumed that the rising cost of financial crime was an inevitability, but our research proves otherwise.
"However, conflicts and rapidly changing sanctions regimes have resulted in an uneven regulatory environment and gaps in financial crime defences which criminals exploit. Our newest analysis traces these trends that create the border line of financial crime and outlines how geographic and political proximity impact risk exposure as much as domestic defences and regulatory red tape. So, despite the headline progress made, nations cannot afford complacency. Financial crime moves fast, so AML must innovate faster.”
An estimated $3.05tn in economic value could potentially be recovered globally if all assessed markets matched the AML performance of the strongest-performing nation. As governments worldwide push to stimulate economic growth and strengthen public finances, the Index identifies a significant untapped economic opportunity.
Dr. Janet Bastiman, Chief Data Scientist at Napier AI, commented: “Over $3 trillion in AML recovery offers huge potential for economies and organisations, and our data shows that spending more on compliance isn’t the only answer. Better detection and underlying data, underpinned by AI, gives compliance teams a more accurate picture of their financial risk and allowing them to focus on the largest money laundering threats.
"But that AI must be explainable, and every automated decision must be auditable by a regulator. It requires human judgement to both own the decisions and also understand the patterns that criminals are using, to successfully stop illicit flows.”
The Index also reports a fall in the cost of AML compliance, decreasing 4.9% from $239.74bn to $227.95bn, but holding fairly steady in relation to money laundering losses. The Index forecasts that compliance spending will remain relatively stable over the coming two years even as money laundering losses fall further.
Artificial intelligence provides a significant under utilised opportunity to keep compliance spending at bay, while not sacrificing the effectiveness of AML operations. $143.08bn in potential AI-driven savings currently remain unrealised across the 42 markets assessed, suggesting there is considerable scope to improve the efficiency and effectiveness of financial crime prevention.
However, cost reduction is not the sole motivation for institutions adopting AI, regulatory obligations continue to dominate investment decisions despite growing interest in AI from AML functions. The findings revealed that 64% of institutions noted meeting regulatory requirements is their top AML investment priority, compared with 20% prioritising new technology and 12% centred on hiring and training AML experts, suggesting financial institutions continue to approach AML primarily through the lens of compliance, with a focus on improved outcomes in risk-based approaches.
Encouragingly, 68%of financial crime professionals believe their existing AML engines are ready to support the data demands of AI, however realising the technology’s full potential will require institutions to address wider challenges around access to information, data sharing and collaboration.
The Index also reveals significant disparities in AML performance across global markets:
- The Strongest Performer: Czechia retained its position as the strongest overall performer across the 42 markets assessed.
- The Most AML Effectiveness: Greece, a new entrant to the Index, recorded the best AML effectiveness score.
- The Weakest Performer: Hong Kong ranked last overall despite a substantial reduction in money laundering losses.
- The UK totalled $206.72bn in losses, rising slower than the economy to cut the share of GDP from 5.53% to 5.16%.
- The United States recorded losses of $658.43bn, with the largest unrealised AI savings at $27.69bn.
- Canada was the second strongest performer, improving across almost every metric and rising from 8th place in the 25-26 Index.
- China was the most improved on overall Index ranking, moving up from 27th to 10th place and reducing losses to 3.51% of GDP. But it still posts the largest money laundering losses globally, recording $688.76 bn.
- Russia recorded a 47.7% year-on-year increase in money laundering losses to $278bn.
- Ukraine recorded its third consecutive annual decline in money laundering losses to 8.3% of GDP.
- The United Arab Emirates and Saudi Arabia hold the top two AI / AML regulation scores in the Index suggesting firms are happy with minimal red tape, but AML effectiveness remains among the weakest demostrating the role of the regulator in mandating risk-based approaches.
- France, Germany, the Netherlands and Poland spent more on compliance than their losses would predict, with the Index pointing to Poland’s overspend being linked to its border with Russia and Belarus.
