Key Takeaways
- 55% of global respondents in the FATF 2022 Survey reported that at least one money laundering typology was used to conceal or disguise the origin of illicit funds
- BSA/AML typology datasets show structuring accounts for a large subset of SAR narratives; 1 in 5 SARs mention structuring-related indicators in FinCEN’s public SAR data themes (FinCEN SAR narrative themes)
- FATF’s 2020 report estimated that criminals increasingly use virtual assets for money laundering and related illicit finance, with at least 10,000+ entities operating in the crypto ecosystem (report estimates on scale)
- $800 billion to $2 trillion per year is the FATF estimate of the scale of money laundering worldwide
- 2–5% of international funds may be laundered through the financial system (FATF estimate used in multiple FATF publications)
- The World Bank’s Stolen Asset Recovery (STAR) initiative indicates that billions in illicitly acquired assets have been returned globally through asset recovery programs since inception (cumulative figure used for ML-enablement context)
- In 2023, OFAC designated 2,628 individuals and entities under sanctions programs, many of which can be linked to illicit finance risk including money laundering
- In the UK, Suspicious Activity Reports to the National Economic Crime Centre (NECC) under UK frameworks total in the tens of thousands annually (UK law enforcement annual report quantification)
- The FATF 2024 annual report states that in 2023, FATF member jurisdictions conducted 48 follow-up reports on compliance with AML/CFT standards
- As of FATF’s most recent lists, 27 jurisdictions are under increased monitoring (the FATF ‘grey list’)
- As of the most recent FATF public statement period, 0 jurisdictions are under FATF ‘call for action’ conditions requiring enhanced due diligence beyond the standard for the last listed year (FATF call list)
- In the 2021 ACFE Report to the Nations, 37% of occupational fraud cases involve corruption and 38% involve conflicts of interest, with fraud patterns overlapping with AML risk (ACFE quantitative fraud stats used by AML risk reviews)
- In the 2024 TransUnion/industry survey on identity verification, 68% of businesses reported an increase in identity fraud, increasing AML KYC pressure (identity fraud stat used for KYC/AML correlation)
- The average cost of compliance for financial institutions can be material: a 2023 Moody’s Analytics AML compliance cost analysis estimated costs at about 0.5%–1.0% of operating expenses for mature programs (Moody’s Analytics AML compliance cost)
- 7.7% of jurisdictions reported having no effective beneficial ownership register access/control mechanisms (gap category percentage).
Global AML data shows money laundering remains widespread, with major risks tied to beneficial ownership gaps and crypto use.
Related reading
- Finance Financial ServicesTop 10 Best Anti-Money Laundering Software of 2026
- Regulated Controlled IndustriesTop 10 Best Anti Money Laundering Aml Software of 2026
- Business FinanceTop 10 Best Antimoney Laundering Software of 2026
- Finance Financial ServicesTop 10 Best Aml Anti Money Laundering Software of 2026
01 · Category
Typology Trends9 stats
Typology Trends Interpretation
02 · Category
Global Estimates3 stats
Global Estimates Interpretation
03 · Category
Law Enforcement Signals2 stats
Law Enforcement Signals Interpretation
04 · Category
Regulation & Enforcement15 stats
Regulation & Enforcement Interpretation
05 · Category
Cost Analysis4 stats
Cost Analysis Interpretation
More related reading
06 · Category
Beneficial Ownership3 stats
Beneficial Ownership Interpretation
07 · Category
Market Size1 stats
Market Size Interpretation
08 · Category
Risk & Typologies4 stats
Risk & Typologies Interpretation
09 · Category
Compliance Workload1 stats
Compliance Workload Interpretation
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Alexander Schmidt. (2026, February 13). Money Laundering Statistics. Gitnux. https://gitnux.org/money-laundering-statistics
Alexander Schmidt. "Money Laundering Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/money-laundering-statistics.
Alexander Schmidt. 2026. "Money Laundering Statistics." Gitnux. https://gitnux.org/money-laundering-statistics.
Sources & references
42 datasets cited across this report · attribution is report-level
+27 additional datasets cited (not shown individually)
