Global money laundering cost the world $5.09tn last year, equivalent to 4.30% of global GDP, according to fresh research from Napier AI. Yet beneath the eye-watering headline sits a significant shift: for the first time since Napier AI began its analysis, the total value of laundered funds has actually fallen, dropping by an estimated $203.33bn year on year.
The figures come from the Napier AI / AML Index 2026–2027, produced in partnership with GlobalData and led by Napier AI chief data scientist Dr Janet Bastiman. The Index assesses the money laundering landscape across 42 global markets.
According to Napier AI, money laundering as a share of GDP has slipped from 4.97% in 2023 to 4.88% in 2024, and now to 4.30% in 2025. Although nominal GDP growth explains part of that trend, the absolute decline marks the first evidence that anti-money laundering (AML) innovation can genuinely outpace organised crime.
Napier AI CEO Greg Watson said, “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.”
The economic prize is substantial. Napier AI estimates that $3.05tn could potentially be recovered worldwide if every assessed market matched the AML performance of the strongest nation, an opportunity that will resonate with governments seeking growth and healthier public finances.
Napier AI chief data scientist Dr Janet Bastiman said, “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.”
Compliance costs also eased, falling 4.9% from $239.74bn to $227.95bn, and Napier AI expects spending to stay broadly stable over the next two years even as losses continue to decline. Meanwhile, $143.08bn in potential AI-driven savings remain untapped across the 42 markets.
Still, regulation rather than cost drives investment. Some 64% of institutions named meeting regulatory requirements as their top AML priority, against 20% prioritising new technology and 12% focused on hiring and training experts. Encouragingly, 68% of financial crime professionals believe their AML engines are ready for the data demands of AI, though data sharing and collaboration remain hurdles.
The Index exposes stark regional differences. Czechia kept its crown as the strongest overall performer, while new entrant Greece posted the best AML effectiveness score. Hong Kong ranked last despite sharply reducing its losses. Canada climbed from eighth to second, improving on almost every metric.
China was the most improved market, jumping from 27th to 10th and cutting losses to 3.51% of GDP, although at $688.76bn it still records the world’s largest losses. The US followed with $658.43bn in losses and the largest unrealised AI savings at $27.69bn. The UK’s losses reached $206.72bn, but grew slower than its economy, reducing their GDP share from 5.53% to 5.16%.
Russia saw losses surge 47.7% to $278bn, while Ukraine logged a third straight annual decline to 8.3% of GDP. The UAE and Saudi Arabia hold the top two AI / AML regulation scores, yet their AML effectiveness remains among the weakest, underlining the regulator’s role in mandating risk-based approaches. France, Germany, the Netherlands and Poland all spent more on compliance than their losses would suggest, with Napier AI linking Poland’s overspend to its borders with Russia and Belarus.
For more insights, read the full report here.
Copyright © 2026 RegTech Analyst
Copyright © 2026 RegTech Analyst
