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The Index, now in its third year, analyses money laundering losses, compliance costs, AML effectiveness and AI regulation across 42 markets. These are the three takeaways every compliance leader should know.
The three takeaways at a glance
- Money laundering losses fell for the first time, by $203 billion (USD) to $5.09 trillion (USD).
- The cost of AML compliance fell, by 4.9 per cent to $227.95 billion (USD), and is forecast to hold flat through 2027.
- $3.05 trillion (USD) is recoverable for economies, and $143.08 billion (USD) in AI-driven savings for financial institutions remains unrealised.
Download the full Napier AI / AML Index 2026–2027.
Takeaway 1: How much money is laundered globally each year?
The United Nations Office on Drugs and Crime (UNODC) estimated that 2% to 5% of global GDP is laundered annually. Our research found that an estimated $5.09 trillion (USD) was laundered globally last year, equivalent to 4.30 per cent of global GDP. Losses fell by $203 billion (USD), or 3.84 per cent, year-on-year – the first fall since the Index began.
The absolute fall is the figure that matters. Losses as a share of GDP dropped from 4.81 to 4.30 per cent, but nominal global GDP grew by 7.58 per cent over the same period.
“Losses have fallen, but not by enough, and economic growth is doing some of the work. Geopolitical disruption is handing criminals new opportunities. Governments that treat money laundering as recoverable value, not just regulatory cost, stand to gain most.”
Takeaway 2: What does AML compliance cost globally?
Global AML compliance cost an estimated $227.95 billion (USD) last year, down from $239.74 billion – a fall of $11.79 billion, or 4.9 per cent. It is the first year that losses and compliance spend have both fallen together and spend per dollar laundered improved from 4.53 to 4.48 cents.
The Index forecasts spend holding a broadly flat, at around $227.8 billion (USD), through 2027. That signals an efficiency turn rather than a pause before the next spike. It also raises the question compliance leaders now face: how to detect more financial crime without a budget that grows to match.
Takeaway 3: How much could AI save in AML compliance?
The Index estimates $143.08 billion (USD) in potential AI-driven savings remains unrealised across the 42 markets assessed. More broadly, $3.05 trillion (USD) could be returned to economies each year if every market matched the AML performance of the Index's strongest performer.
With compliance spend expected to plateau, better detection (not bigger budgets) is the route to that value. That depends on AI that is explainable, auditable, and with accountability owned by people.
Dr Janet Bastiman, Chief Data Scientist at Napier AI, 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 more robust underlying data, underpinned by AI, give compliance teams a more accurate picture of their financial risk, allowing them to focus on the largest money laundering threats.”
"But that AI must be explainable, and every automated decision must be explainable to a regulator. It requires human judgement both to own the decisions and to understand the patterns that criminals are using to stop illicit flows."
See the AI savings estimate for your market in the full report.
Beyond the headlines: what the full report reveals
The global improvement is uneven. Index scores run from one to ten, where lower is better, and the 42 markets spread widely:
- The Czech Republic
The strongest overall performer, with an Index score of 1.81. Canada ranks second.
- The United States
Ranks 16th of 42. An estimated $658.43 billion (USD) was lost to money laundering last year, equivalent to 2.1 per cent of GDP. It also holds the largest unrealised opportunity of any market, with $27.69 billion (USD) in potential AI-driven savings.
- Greece
New to the Index this year, records the strongest AML effectiveness score in the world.
- The United Kingdom
Ranks 24th of 42, up ten places on last year. An estimated $206.72 billion (USD) was lost to money laundering, equivalent to 5.16 per cent of GDP. The UK’s cost of compliance stands at $7.87 billion (USD), and a further $4.11 billion (USD) in potential AI-driven savings remains unrealised: the sixth largest opportunity across the 42 markets.
- Russia
Losses rose by $89.82 billion (USD) to $278.09 billion: more than Europe’s entire regional increase.
Frequently asked questions
What is the Napier AI / AML Index?
The Napier AI / AML Index is an annual research report from Napier AI, produced with GlobalData, that estimates money laundering losses and AML compliance costs across 42 markets. It ranks each market on AML attitude, AI/AML regulation, AML effectiveness, and total cost of ownership. The 2026 – 2027 edition is the third.
How much money is laundered globally each year?
The Napier AI / AML Index 2026 – 2027 estimates that $5.09 trillion (USD) is laundered globally each year, equivalent to 4.30 per cent of global GDP. That is $203 billion (USD) lower than the year before.
Did money laundering fall in 2025?
Yes. According to the Napier AI / AML Index 2026 – 2027, global money laundering losses fell by $203 billion (USD), or 3.84 per cent, in 2025. It is the first fall recorded across the Index's three editions.
Which country performs best on anti-money laundering?
The Czech Republic ranks first of 42 markets in the Napier AI / AML Index 2026 – 2027, with an Index score of 1.81, where lower is better. Canada ranks second and Spain third. Greece records the strongest AML effectiveness score.
How much could AI save in AML compliance?
The Napier AI / AML Index 2026 – 2027 estimates $143.08 billion (USD) in potential AI-driven savings remains unrealised across 42 markets. The United States holds the largest share, at $27.69 billion (USD).
About the research
The Napier AI / AML Index 2026 – 2027 is produced by Napier AI's Data Science team, led by Dr Janet Bastiman, in partnership with GlobalData. The global loss estimate is modelled across 161 countries, using expanded Financial Action Task Force (FATF) evaluation data, with detailed rankings for 42 markets.
Dr Janet Bastiman is Chief Data Scientist at Napier AI and was named in the Computing AI Leadership Index in 2026. She leads Napier AI's research on explainable AI and AI regulation in AML.
Get the full rankings, country data and research themes.
