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ML/TF: Money Laundering/Terrorist Financing

Definition

Money laundering (ML) is the process by which criminals disguise the origin of illegally-obtained funds so that they appear legitimate.

Terrorist financing (TF) involves the movement or collection of funds or other assets, knowing they will be used, or with reasonable grounds to suspect they will be used, to carry out terrorist acts, support terrorist organisations or individuals, or procure weapons of mass destruction.

The two phenomena are distinct but overlapping: ML typically deals with proceeds of crime while TF may involve funds derived from either legal or illegal sources; both exploit vulnerabilities in financial systems and pose serious threats to the integrity of economies, financial institutions, and national security.

Explanation

While money laundering enables criminals to integrate illicit proceeds into the financial system, terrorist financing uses similar mechanisms for different ends.

Both ML and TF may use layering, integration, structuring, cross-border transfers, shell companies, trade-based methods, and virtual asset services.

ML supports a broad range of predicate offences such as drug trafficking, corruption, tax evasion, human trafficking, and organised crime.

TF may draw on such proceeds or on seemingly legitimate funds (charities, donors, front companies) and direct them toward terrorist actions or groups.

Financial institutions, payment service providers, custodians, and other regulated entities must therefore design their AML/CFT frameworks to cover both money laundering and terrorist financing.

The international standard-setter Financial Action Task Force (FATF) describes both under its recommendations and expects jurisdictions to criminalise the offences, set up preventive measures, ensure transparency of beneficial ownership, and apply customer-risk assessments. 

The policy rationale is clear: unchecked ML/TF undermines trust in financial systems, encourages corruption and crime, disrupts capital flows, and may funnel resources to extremist actors or destabilising organisations. 

ML/TF in AML/CFT Frameworks

Financial crime-risk frameworks must address ML and TF comprehensively. Key intersections include:

  • Understanding customer, product, geography, channel, and third-party risk exposures where ML/TF is more likely.
  • Designing screening and monitoring systems that detect both proceeds-based laundering and financing of terrorism.
  • Recognising that TF may not require a criminal predicate offence but still poses a high risk, rules must cover both legal and illegal funds.
  • Coordinating sanctions screening, suspicious activity reporting, transaction monitoring, and enhanced due diligence in an integrated manner.
  • Ensuring governance, audit, and oversight mechanisms cover ML/TF risk, with senior management and board involvement in setting risk appetite and strategy.

Key Components

Elements of Money Laundering

Money laundering typically unfolds in three stages:

  • Placement – Illicit funds are introduced into the financial system (for example, via deposits, cash-intensive businesses, or real-estate purchases).
  • Layering – Funds are moved, converted, or disguised to break the link to their origin (for example, via shell companies, complex transfers, trade-based laundering, or virtual assets).
  • Integration – Funds re-enter the economy, appearing legal (for example, via investment, luxury goods purchase, or corporate ownership).

Mechanisms of Terrorist Financing

Terrorist financing often involves:

  • Funds from illicit activities such as drug trafficking, smuggling or kidnapping.
  • Funds from legitimate sources such as donations, charities, business profits or crowdfunding.
  • Movement of funds through remittance services, informal value transfer systems, trade mis-invoicing, or virtual asset services.
  • Use of cash, direct transfers, front companies, or charities as a cover to support terrorist operations, recruitment, propaganda, or procurement of weapons.

Common ML/TF Vulnerabilities

Regulated entities face particular exposures:

  • High-volume, high-speed transactions with limited verification (for example, cross-border payments or VASPs).
  • Products with anonymity or minimal identity checks (for example, prepaid cards, crypto wallets, chain transfers).
  • Geographies with weak AML/CFT frameworks, high corruption, conflict zones, or active terrorist groups.
  • Third-party relationships, agents, or intermediaries with limited oversight (for example, introducers or onboarding brokers).
  • Charity or non-profit sectors with large donation flows, cross-border movement, and weak financial controls, which may be abused for TF.

Examples of ML/TF Scenarios

  • A criminal network deposits cash into a series of shell companies, wires funds across jurisdictions, trades in over-invoiced imports, and then invests in luxury real estate, classic ML layering and integration.

  • A charity operating in a conflict zone receives large donor funds, funnels them through informal networks, and transfers them to a front company supplying a terrorist group, a TF scenario via misuse of the humanitarian framework.

  • A virtual asset service provider enables deposited crypto from multiple anonymous sources, converts it via multiple wallets, and transfers it to a darknet marketplace funding extremist content, hybrid ML/TF through virtual assets.

  • Cross-border remittances from diaspora communities are routed through informal agents into conflict areas with limited transparency, enabling both ML and possible terrorist financing.

  • A legitimate business is used to commingle illicit proceeds with legitimate revenue, paying employees, buying goods, and exporting them under-invoiced; some of the funds are diverted to an extremist organisation, combined ML and TF risk.

Impact on Financial Institutions

  • Financial institutions may face significant regulatory, criminal, and civil penalties if involved, even inadvertently, in ML/TF schemes, including heavy fines, sanctions, and reputational damage.

  • Correspondent banking relationships may be terminated if an institution is identified as facilitating ML/TF risk for other banks or jurisdictions.

  • Investigation, remediation, and compliance costs can escalate rapidly when ML/TF exposures emerge, especially where cross-border complexity is involved.

  • Reputational risk is heightened: customers, markets, and counterparties lose trust in institutions that fail to manage ML/TF risks effectively.

  • Operational burden increases: more resources are required for customer due diligence, transaction monitoring, screening, training, auditing, and reporting.

Challenges in Managing ML/TF Risk

  • Terrorist financing may use low-value but high-impact transactions, making detection through traditional amount-based thresholds inadequate.
  • Rapid evolution of virtual assets, digital payments, remittance networks, and fintech innovations creates new vulnerabilities that may not be addressed by legacy systems.
  • Shell companies, complex ownership structures, and opaque networks make beneficial ownership identification and source of funds checks difficult.
  • Coordinating ML/TF controls across jurisdictions is challenging due to differing regulations, inconsistent enforcement, cross-border data restrictions, and cultural variations.
  • Balancing innovation, service convenience, and risk control is difficult. Institutions must embed strong controls without unnecessarily hindering legitimate customers.
  • Over-reliance on alerts and high false positives can desensitise compliance teams and reduce focus on true high-risk activities.

Regulatory Oversight & Governance

International and domestic regulatory frameworks drive ML/TF prevention efforts:

  • The FATF issues recommendations setting international standards, requiring criminalisation of ML and TF, targeted financial sanctions, customer due diligence, and information sharing. 
  • The Basel Committee on Banking Supervision provides guidelines on sound management of ML/TF risk in banking operations.
  • The International Monetary Fund emphasises the role of AML/CFT frameworks in preserving financial integrity, stability, and inclusion. 
  • National regulators mandate suspicious transaction/activity reporting, sanction screening, customer risk assessments, and audits.
  • Internal audit, compliance, and senior management oversight are critical: institutions must document ML/TF risk assessments, embed controls, monitor performance, and adjust to emerging threats.

Importance of ML/TF Compliance

Managing ML/TF risk is not optional; it is central to the integrity of financial systems and investor confidence.

Robust AML/CFT controls enable institutions to:

  • Detect and report suspicious transactions before they inflict damage.
  • Protect themselves and their clients from being exploited for criminal or terrorist purposes.
  • Maintain access to international financial markets, correspondent banks, and fintech partnerships.
  • Uphold regulatory compliance and avoid sanctions, fines, or licence revocations.
  • Build trust with stakeholders, including shareholders, clients, regulators, and the public.
  • Support global efforts to combat organised crime, corruption, terrorism, and proliferation.

As digital finance, cryptocurrencies, open banking, and globalisation accelerate, the overlap between ML and TF will intensify.

Institutions must invest in intelligence-led, risk-based frameworks that adapt to emerging typologies and technologies.

Related Terms

  • Suspicious Transaction Reporting
  • Customer Due Diligence (CDD)
  • Beneficial Ownership
  • Trade-Based Money Laundering (TBML)
  • Virtual Asset Service Provider (VASP)
  • Targeted Financial Sanctions

References

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