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Predicate Offense

Definition

A predicate offense is an underlying criminal act that generates illicit proceeds which are later laundered through the financial system.

In AML/CFT regimes, a predicate offense is any crime whose proceeds become the subject of money laundering.

Once a predicate offense occurs, any attempt to disguise, move, convert, or integrate the resulting funds into the legitimate economy constitutes money laundering.

Predicate offenses vary across jurisdictions but generally include a broad range of serious crimes such as fraud, corruption, drug trafficking, terrorism-related offences, human trafficking, tax crimes, environmental crimes, cyber-enabled crimes, and organised criminal activity.

FATF Recommendations require jurisdictions to criminalise money laundering for a wide scope of predicate offenses to strengthen global financial integrity.

Explanation

The concept of predicate offense serves as the foundation for AML/CFT frameworks.

Money laundering cannot occur unless there are illicit proceeds derived from an underlying criminal activity.

These activities can be domestic, foreign, or transnational in nature.

Once generated, the illicit proceeds typically undergo placement, layering, and integration stages to obscure their origin.

Different jurisdictions may vary in terms of which offenses qualify as predicates.

However, FATF standards encourage an “all serious crimes” approach, meaning that virtually any offence punishable by a certain threshold (for example, one year or more of imprisonment) can serve as a predicate offense.

Predicate offenses also include tax crimes and newer typologies such as cyber-fraud, ransomware attacks, illegal wildlife trade, environmental offences, and sanctions evasion.

This breadth ensures that AML/CFT systems remain adaptable to emerging threats.

Predicate Offenses in AML/CFT Frameworks

AML/CFT regimes rely on clear classification of predicate offenses to support effective supervision, enforcement, and reporting.

Key areas where predicate offenses intersect with AML/CFT frameworks include:

  • Criminalisation of money laundering must cover proceeds from a wide range of predicate offenses.
  • Financial institutions must be able to detect and report potentially suspicious activity linked to known predicate categories.
  • Risk assessments at national and institutional levels must consider exposure to predicate-offense typologies.
  • Supervisory expectations require firms to map typologies to transaction-monitoring scenarios, red flags, and sector-specific risks.
  • Cross-border cooperation mechanisms rely on common definitions of predicate offenses to facilitate information exchange, mutual legal assistance, and extradition.

Because criminals adapt their methods rapidly, financial institutions must maintain typology intelligence that reflects both traditional and emerging predicate-offense trends.

Key Components of Predicate Offenses

Nature of Illicit Proceeds

Predicate offenses generate proceeds that may be:

  • Cash-based (e.g., drug trafficking, extortion).
  • Asset-based (e.g., misappropriated funds, corrupt payments, stolen property).
  • Digitally derived (e.g., ransomware, online fraud, crypto-enabled schemes).
  • Mixed or hybrid proceeds where fiat, virtual assets, and physical assets intersect.

Regulatory and Legal Foundations

Most AML laws define predicate offenses through:

  • Explicit enumerated lists (e.g., corruption, narcotics, human trafficking).
  • A threshold test categorising serious crimes as predicates.
  • Specific offence categories tied to sectoral vulnerabilities such as securities fraud, environmental crimes, or cybercrime.
  • FATF-aligned definitions that expand predicate-offense coverage to new forms of organised and digital crime.

Connection to Money Laundering

Once a predicate offense generates illicit value, criminals attempt to conceal:

  • The source of funds.
  • The ownership structure.
  • The movement or layering of transactions.
  • The end use or integration of proceeds.

This connection legally transforms follow-on activity into money laundering, triggering regulatory obligations such as reporting, freezing, and investigation.

Common Predicate Offenses

Predicate offenses span traditional criminal activity, economic crimes, and modern cyber-enabled offences. Common categories include:

  • Drug trafficking and narcotics operations generating large cash proceeds.
  • Fraud, bribery, and corruption, including procurement fraud and abuse of public office.
  • Human trafficking, migrant smuggling, and exploitation networks.
  • Tax crimes, including evasion and false reporting.
  • Environmental crimes, such as illegal mining, logging, and wildlife trafficking.
  • Cybercrime, including ransomware, phishing, identity theft, and digital payment fraud.
  • Terrorism and terrorist financing.
  • Organised crime and racketeering, including gambling, extortion, and counterfeit goods.
  • Sanctions evasion, where illicit proceeds arise from unlawful economic activity conducted in prohibited jurisdictions.

Risk Indicators and Red Flags Linked to Predicate Offenses

Detecting predicate-offense activity requires a risk-based approach supplemented by typology-driven indicators.

Common red flags include:

  • Unusual or unexplained wealth inconsistent with customer profile.
  • Large cash deposits potentially linked to narcotics or organised crime.
  • Rapid movement of funds across multiple accounts without economic rationale.
  • Use of shell companies, nominees, or opaque structures often tied to corruption or fraud.
  • High-risk cross-border transfers linked to jurisdictions associated with trafficking or cybercrime.
  • Transactions routed through industries vulnerable to predicate offenses (e.g., casinos, metals trading, construction).
  • Incoming funds from digital wallets associated with ransomware or darknet markets.

Examples of Predicate-Offense Scenarios

Public Corruption and Kickbacks

A public official receives illicit payments from contractors in exchange for awarding tenders.

The proceeds are routed into offshore companies and later layered through investment accounts.

Cyber-Fraud and Account Takeover

A criminal group steals funds through digital account takeover attacks.

The proceeds are rapidly transferred through crypto mixers and cashed out via money mules.

Illegal Wildlife Trafficking

Proceeds from the sale of endangered species are channelled through shell exporters and hidden within trade documentation to disguise their origin.

Tax Evasion

A business underreports income and channels untaxed proceeds into personal investment accounts, masking their illicit nature as legitimate profits.

Human Trafficking

Traffickers deposit structured cash proceeds into various accounts, routing funds through remittance corridors to obscure victim-exploitation networks.

Impact on Financial Institutions

Failure to detect activity linked to predicate offenses exposes institutions to severe consequences:

  • Regulatory sanctions, enforcement actions, and financial penalties.
  • Heightened reputational damage associated with facilitating serious crimes.
  • Loss of correspondent banking relationships due to exposure to illicit flows.
  • Increased compliance costs linked to remediation, investigations, and system enhancements.
  • Legal exposure for willful blindness or inadequate AML systems and controls.

Institutions must therefore build robust typology libraries, update risk assessments, and design targeted monitoring rules that map to predicate-offense behaviours.

Challenges in Detecting Predicate-Offense Activity

Financial institutions face complex obstacles in identifying predicate-offense proceeds:

  • Criminals employ increasingly sophisticated, technology-enabled methods to move funds.
  • Blurring between traditional and digital predicate offenses complicates risk classification.
  • Cross-border fragmentation inhibits access to information such as law-enforcement intelligence or beneficial ownership registries.
  • False positives in monitoring systems may obscure genuine red flags.
  • Rapid creation of new predicate-offense typologies (e.g., deepfake-enabled fraud, AI-powered scams) outpaces system updates.

Institutions must combine intelligence-led analytics, machine learning, behavioural anomaly detection, and targeted alerts to detect activity aligned with predicate-offense risks.

Regulatory Oversight & Governance

Supervisory authorities emphasise that institutions must:

  • Understand and document exposure to relevant predicate offenses.
  • Maintain policies, procedures, and governance frameworks aligned with FATF Recommendations.
  • Conduct ongoing monitoring and enhanced due diligence in high-risk segments.
  • Provide regulators and FIUs with timely access to customer and transaction data.
  • Train staff on emerging typologies and sector-specific predicate-offense risks.
  • Integrate financial-crime intelligence sources, including public advisories and law-enforcement reports.

A strong governance model ensures that predicate-offense typologies are embedded across onboarding, monitoring, escalation, and reporting practices.

Importance of Addressing Predicate Offenses in AML/CFT Compliance

Understanding and mitigating predicate-offense risk is essential for protecting financial integrity.

Effective AML/CFT programmes enable institutions to:

  • Identify suspicious activity at an early stage by mapping behaviours to known predicate-offense typologies.
  • Strengthen controls around high-risk customer segments and industries.
  • Support intelligence-led investigations internally and with regulators.
  • Reduce exposure to fines, sanctions, and reputational harm.
  • Improve cross-border cooperation and information sharing.

Moreover, predicate offenses continue to evolve alongside technological, geopolitical, and economic change.

Institutions must maintain dynamic, risk-based AML frameworks that adapt to new forms of criminality.

Related Terms

  • Money Laundering
  • Beneficial Ownership
  • Suspicious Transaction Report (STR)
  • Terrorist Financing
  • Sanctions Evasion
  • Organised Crime

References

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