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Layering (AML Stage)

Overview

Layering is the second stage of money laundering where criminals obscure the origin of illicit funds through a sequence of complex transactions. Techniques include rapid transfers between accounts and jurisdictions, use of shell or front companies, trade misinvoicing, conversion into crypto or commodities, and funneling via money mules.

The objective is to break audit trails and complicate attribution. Effective controls combine real-time monitoring (velocity, jurisdiction risk), graph analytics to reveal circular flows and hubs, and red-flag scenarios aligned to current typologies. Institutions strengthen interdiction by linking alerts to case management, enriching with KYC/KYB/UBO context, and escalating to EDD where warranted. Clear SAR/STR narratives should reconstruct timelines, beneficiaries, and rationale for suspicion.

Layering is adaptive; programs must review scenarios against emerging channels (instant payments, cross-border fintech corridors) and tune thresholds to reduce false negatives while keeping alert volumes manageable.

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Transaction Monitoring

Monitor transactions in real-time and analyse past behaviour to identify suspicious activities and ensure regulatory compliance across the user journey.

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Database Verification

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Related Terms

Funds Flow Analysis

Graph Analytics

Suspicious Activity/Transaction Report (SAR/STR)

FAQ

How does layering differ from placement?

Placement injects cash into the system; layering obscures its origins via complex movements, often across borders and asset types. Controls pivot from cash thresholds to pattern and network detection during this phase.

What are common layering red flags?

Rapid pass-through transfers, circular money flows, inconsistent trade documentation, and links to high-risk jurisdictions or shell entities. Combining these signals increases investigative precision and reduces alert noise.

Which controls detect layering best?

Graph analytics, funds-flow reconstruction, jurisdiction screening, and adaptive scenarios that consider counterparties, amounts, and time windows. Feedback loops from confirmed cases refine rules and models.

How do we document cases?

Build a clear timeline, identify entities and links, quantify exposure, and tie patterns to typologies. Strong narratives improve SAR quality and regulatory credibility.