Global money laundering losses reached $5.09tn last year, according to new research from Napier AI. That figure is equal to 4.30% of global GDP. It also marks the first year-on-year fall in illicit flows since Napier AI began tracking the problem, with losses dropping by an estimated $203.33bn.
The figures come from the Napier AI / AML Index 2026–2027, produced with GlobalData. Dr Janet Bastiman, chief data scientist at Napier AI, led the study, which looks at money laundering across 42 markets worldwide. As a share of GDP, laundering fell from 4.97% in 2023 to 4.88% in 2024, and then to 4.30% in 2025. Nominal GDP growth explains part of that decline. Even so, Napier AI says this is the first time its Index has recorded an actual fall in the total value of illicit funds. The firm sees this as early evidence that anti-money laundering (AML) innovation can 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.”
Napier AI estimates that $3.05tn of economic value could be recovered if every market in the Index matched the AML performance of the strongest nation. With governments under pressure to boost growth and repair public finances, the research presents this as a large and largely untapped opportunity.
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 fell over the period. Spending dropped 4.9%, from $239.74bn to $227.95bn, while staying broadly in line with money laundering losses. Napier AI expects compliance spending to hold steady over the next two years, even as losses continue to decline. The Index puts unrealised AI-driven savings at $143.08bn across the markets studied.
Regulation, however, is still the main driver of investment. In the survey, 64% of institutions named meeting regulatory requirements as their top AML priority. By comparison, 20% put new technology first and 12% prioritised hiring and training. On a more positive note, 68% of professionals said their AML engines are ready to handle the data demands of AI. Napier AI cautions that unlocking AI’s full value will also depend on better data access, data sharing and collaboration.
Performance varied widely from market to market:
- Czechia kept its place as the strongest overall performer.
- Greece, new to the Index, recorded the best AML effectiveness score.
- Canada rose from eighth to second place.
- China was the most improved market, climbing from 27th to 10th. It still recorded the largest losses globally, at $688.76bn.
- The US posted losses of $658.43bn and the largest unrealised AI savings, at $27.69bn.
- The UK’s losses reached $206.72bn, while its share of GDP fell from 5.53% to 5.16%.
- Russia’s losses rose 47.7% to $278bn.
- Hong Kong ranked last overall.
- The UAE and Saudi Arabia led on AI / AML regulation scores but were among the weakest on effectiveness.
- Poland’s compliance overspend was linked to its borders with Russia and Belarus.
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