## Nordic-Baltic Regional Technical Assistance Project — Financial Flows Analysis, AML/CFT Supervision, and Financial Stability (High-Level Summary)

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**Canonical URL:** [Nordic-Baltic Regional Technical Assistance Project — Financial Flows Analysis, AML/CFT Supervision, and Financial Stability (High-Level Summary)](https://www.imf.org/-/media/files/publications/hls/2023/english/hlsea2023012.pdf)

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### Project scope and objectives
- Provide technical assistance to Denmark, Estonia, Finland, Iceland, Latvia, Lithuania, Norway, and Sweden on Anti-Money Laundering/Countering the Financing of Terrorism (AML/CFT).
- Leverage a novel data-analysis methodology to:
  - Analyze potentially high-risk financial flows to and from the region.
  - Assess the AML/CFT domestic and regional supervisory landscape related to banks and virtual assets (CASPs).
  - Evaluate potential implications of financial integrity shocks on financial stability.
- JEL Classification Numbers: F39
- Keywords: Anti-Money Laundering, Combatting the Financing of Terrorism, Money Laundering Shocks, Financial Stability, Illicit Financial Flows, Machine Learning, and Risk-Based Supervision

### Background and motivation
- Recent high-profile AML/CFT breaches in the Nordic-Baltic region (including ABLV, Danske Bank, Nordea, Swedbank) exposed vulnerabilities in cross-border payments by non-residents and risk-based supervision.
- Notable facts from the Danske-related events:
  - Danske Bank’s Finland-based Sampo Bank was acquired in 2007 and had an Estonian branch where during 2007–2013, 44% of all deposits came from non-resident customers.
  - These customers conducted around 7.5 million transactions with an aggregated flow of money added up to approximately 200 billion euros.
  - The Estonian branch was forced to close in 2019.
  - The bank pled guilty in the U.S., forfeiting $2 billion and incurring an additional fine for EUR 470 million in Denmark.
- The six largest cross-border Nordic banks account for 40 to 75 percent of lending in the region.
- Foreign branches and subsidiaries account for the majority of banking sector assets in Estonia, Latvia and Lithuania.

### Key findings — financial flows and ML/TF risk landscape
- Cross-border financial flows:
  - The Nordic-Baltic region’s cross-border financial flows have increased steadily since 2013.
  - Aggregate financial flows are highly material, including after adjustment to GDP and the value of deposits.
  - The region’s flows have a significant geographic reach, driven by open, large, and advanced Nordic economies.
- Country-level risk analysis:
  - Depth of geographic ML/TF risk analysis differs across countries.
  - Authorities commonly use FATF grey list, European Commission higher-risk third country list, and non-cooperative tax jurisdictions lists to identify higher-risk countries.
  - IMF staff developed economic fundamentals and outlier detection analyses to support targeted, up-to-date understanding of higher ML risk countries and payment trends.
- ML/TF risk modeling and data:
  - Countries have invested in ML/TF risk models and have advanced risk assessment frameworks.
  - Gaps remain in advanced data collection and analysis, particularly transaction-level cross-border payments data.
  - Tailoring risk models to crypto asset service providers (CASPs) needs increased focus.
- Supervision:
  - Active AML/CFT supervision has advanced, with targeted supervisory strategies, coordinated regional efforts, and resource assessments.
  - Supervisory colleges and thematic inspections are underutilized opportunities for cross-border coordination and targeted oversight.
  - Market entry controls, resourcing, specialized tools, and regional information exchange are important for supervising CASPs.
- Financial stability implications:
  - Quantifying financial stability impact of money laundering shocks is understudied; studies on AML/CFT failings’ impact on liquidity and funding are scarce.
  - Preliminary analysis indicates banks facing FI events experienced:
    - A sharp equity price decline for the affected bank, and to a lesser extent other domestic and regionally exposed banks.
    - An increase in credit risk around FI events for affected banks and banks with similar cross-border exposures.
    - Deterioration of liquidity for the affected bank as measured by deposit flows; other domestic banks may see short-term substitution benefits.
    - Possible contagion effects on liquidity at the regional level.

### Analytical tools and data methods used
- IMF staff developed an unsupervised machine learning algorithm to monitor global financial flows to detect unusual and potentially suspicious patterns using transactional payments data and indicators of higher (weak AML/CFT regime, higher economic crimes, financial secrecy, and harmful tax practices) and lower (underlying trade and investments) ML risks.

### Summary of recommendations
- Enhance understanding and monitoring of cross-border financial flows and non-resident activities:
  - Consider developing a national mechanism for comprehensive monitoring of cross-border financial flows, especially in countries with the most material cross-border payments.
  - Incorporate additional data sources (e.g., macro-economic variables such as trade and investments) and information on business models and foreign linkages into national/sectoral risk assessments.
  - Develop country-specific assessments of higher-risk jurisdictions, focusing on those with the most material financial flows and coordinating with all relevant AML/CFT-relevant agencies, including tax administration.
- Strengthen supervisory frameworks and cross-border cooperation:
  - Strengthen supervisory ML/TF risk assessment of banks with greater focus on inherent risk (in particular, product risk).
  - Enhance collection and analysis of more granular information (including transaction-level data) supported by increased automation and exploration of data analytics tools.
  - Assess adequacy of supervisory resources on an ongoing basis against changes in size and risk profiles of supervised entities (including CASPs).
  - Leverage supervisory colleges and establish joint AML/CFT supervisory strategies for the highest-risk cross-border banks; ensure strong coordination between prudential and AML/CFT supervisors.
  - Proactively identify unauthorized CASPs, leverage regional platforms to share sector-specific information, and develop CASP-specific supervisory strategies.
- Further work on financial stability analysis and stress testing:
  - Explore further the impact of AML failings on financial stability, supported by AML/CFT supervisors, prudential supervisors, and financial stability experts.
  - Calibrate stress test scenarios featuring FI issues and apply them where relevant to banks more vulnerable to FI issues, relying on financial flow analysis and supervisory ML/CFT risk assessments.

*Prepared by Grace Jackson, Maksym Markevych, Pierre Bardin, Alexander Malden, Antoine Bouveret (consultant), Santiago Texidor Mora, and Indulekha Thomas — High-Level Summary Technical Assistance Report (Nordic-Baltic Regional Technical Assistance Project).*

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_Source: https://www.imf.org/-/media/files/publications/hls/2023/english/hlsea2023012.pdf_