Methodology
What's behind the Basel AML Index?
- Shortfalls in the AML framework
- Corruption and fraud
- Poor financial transparency and standards
- Poor public transparency and accountability
- Weak political rights and rule of law
High risk
Data sources
The aim of the Basel AML Index is to provide a holistic picture of money laundering risk. Risk, as measured by the Basel AML Index, is defined as a country's vulnerability to money laundering and related financial crimes and its capacities to counter these threats. The Index does not attempt to measure the actual amount of money laundering activity.
The 17 indicators differ in focus and scope. We choose indicators based on several criteria, including their relevance, methodology, country coverage, public access and the availability of recent data. The indicators and their weighting are reviewed annually by an independent expert group.
Click the indicators below to learn what they measure and why they are important.
Domain 1: Quality of AML/CFT/CPF framework (50%)
Domain 2: Corruption and fraud risks (17.5%)
Domain 3: Financial transparency and standards (17.5%)
Domain 4: Public transparency and accountability (5%)
Domain 5: Political and legal risks (10%)
Scaling and weighting
Most indicators chosen for the Basel AML Index have their own scoring system. To achieve a unified coding system, individual indicator scores (variables) are collected and normalised using the min–max method into a 0–10 system, where 10 indicates the highest risk level.
As with any composite index, each variable then receives a weight to aggregate all scores into one score. The variables differ in quality, coverage and relevance, with some components being more applicable than others in assessing money laundering risk.
The Basel AML Index uses an expert weighting scheme (or so-called “participatory approach”), whereby experts assign a weight for a variable based on their in-depth knowledge and expertise in the matter. The expert weighting method includes a degree of subjectivity, which is mitigated through an annual expert review meeting.
Notes and limitations
Use of terms
The Basel AML Index contains some jurisdictions that are not countries or whose status is disputed. We use “jurisdictions” throughout as a catch-all term.
We also use “financial crime” as a catch-all term for illegal activities that involve the misuse of the financial system, financial services or financial instruments for personal or organisational gain. In the Basel AML Index, it includes not only money laundering but predicate offences such as corruption and bribery, human and drug trafficking, fraud and scams, plus the financing of terrorism and proliferation of weapons of mass destruction.
Data availability
Data collection for the 2025 Public Edition of the Basel AML Index was finished on 10 November 2025 and does not reflect developments after that date. The Expert Edition is updated quarterly.
There is not always a complete set of 17 indicators available for all jurisdictions. The overall score is calculated based on available data only.
Only jurisdictions with sufficient data to calculate a reliable risk score are included in the Public Edition of the Basel AML Index. Russia remains excluded from the Basel AML Index Public Edition in 2025 based on the FATF's suspension of Russian membership. The Expert Editions cover 203 jurisdictions, providing risk scores for each indicator and details of the available data.
Data quality and limitations
Limited and inconsistent data quality remains a key challenge, particularly for financial crimes with a cross-border dimension. Fraud is a clear example: definitions and scope vary widely across jurisdictions, the crime is inherently complex and often transnational, and data are generally scarce due to under-reporting and the absence of harmonised global standards.
Other cross-border financial crime indicators face similar constraints. Scores and rankings should be considered with caution.
In contrast to financial risk models based purely on statistical calculations, the Basel AML Index evaluates regulatory, legal, political and financial factors that influence a jurisdiction’s vulnerability to money laundering and related financial crimes. The Index relies partially on perception-based indicators such as Transparency International's Corruption Perceptions Index.
Transforming qualitative data into quantitative data does not fully overcome the limitations of perception-based indicators. Unlike financial risk models, jurisdiction risk models cannot be used as a solid basis for prediction or for calculating potential loss connected to money laundering or related offences.
Risk levels
The overall score of each jurisdiction in the Basel AML Index Expert Edition is categorised as follows:
- Lower risk: Less than 4.70
- Medium risk: 4.70–6.08
- Higher risk: More than 6.08
This uses the Jenks natural breaks classification statistical method, which results in a more nuanced distribution among risk categories. This only applies to the Expert Edition and to the overall score. See the blog for deeper explanation.
Comparability of results
The Basel AML Index methodology is reviewed each year to ensure that it continues to accurately capture money laundering and related risks. This may affect the comparability of the results over the years.
Comparability between jurisdictions is also hampered by a lack of full coverage by FATF fourth-round evaluations. FATF data, which assess the quality of a jurisdiction’s systems to counter money laundering, terrorist financing and proliferation financing, makes up 35 percent of the total risk score in the Basel AML Index. The FATF methodology was revised in 2013 (fourth round of evaluations) in order to assess not only technical compliance with the FATF Recommendations but the effectiveness of the systems according to 11 Immediate Outcomes.
Although coverage with fourth-round evaluations is increasing, several jurisdictions still have evaluations based on older methodologies. To mitigate this issue, the Public Edition of the Basel AML Index only includes those that have gone through at least a fourth-round evaluation, as well as meet the minimum requirement of at least 65 percent of data availability across all indicators.
Fifth-round evaluations are only just commencing. Given that the FATF’s methodological change is not as great as between the third and fourth rounds, we do not envisage adjusting the methodology to account for this for the time being.
Use for compliance or risk assessment purposes
Due to the above limitations, we recommend that the Basel AML Index Expert Edition, rather than the Public Edition, should be used for compliance or risk assessment purposes.
Use of the Expert Edition should also form part of a comprehensive, risk-based compliance programme along with additional indicators and procedures relevant to the organisation's specific needs.
Reflecting the progress of grey-listed jurisdictions
The Basel AML Index methodology includes a small adjustment mechanism to better reflect the progress of jurisdictions that have graduated from the FATF's grey list of jurisdictions subject to increased monitoring.
Jurisdictions that graduate from the grey list have necessarily made efforts to improve their AML systems in line with an action plan agreed with the FATF. However, the FATF does not reassess the effectiveness of their systems. This makes it likely that the jurisdiction's risk score on paper does not fairly reflect their progress in reality.
To remedy this, the Basel AML Index methodology assumes that jurisdictions that have graduated from the grey list have improved the effectiveness of their systems to at least a moderate level.
For example, before being placed on the grey list, a Caribbean jurisdiction was assessed as having the lowest score (0) in six of the FATF's 11 effectiveness criteria. After being removed from the grey list, the methodology assumes it has now achieved a moderate level (1) of effectiveness in those six criteria.
Want to learn more?
Watch our short videos to understand what's behind the Basel AML Index and how you can use it for jurisdiction risk assessments.