Skip to main content

Money Laundering

Last Updated: 2025-02-17 Status: Complete

Money laundering is the process of making illegally obtained money appear legitimate. Payment platforms are attractive targets for launderers because they process large volumes of transactions quickly. Understanding how laundering works is essential for building effective detection systems.

Quick Reference​

StageGoalPayment Platform Risk
PlacementEnter financial systemProcessing illicit funds
LayeringObscure originComplex transaction patterns
IntegrationUse as legitimateMerchant payouts

The Three Stages of Money Laundering​

Stage 1: Placement​

The first stage involves getting illicit cash into the financial system.

MethodDescriptionDetection
StructuringBreaking large amounts into smaller depositsTransactions just under $10K
SmurfingUsing multiple people to make depositsMultiple accounts, same patterns
Cash-intensive businessMixing illicit cash with legitimateUnusual cash volumes
Currency exchangeConverting to different currenciesMultiple currency transactions

PayFac Risk:

  • Sub-merchants used to process fraudulent transactions
  • Fake sales to move cash through card network

Stage 2: Layering​

The second stage creates complex transaction patterns to obscure the money's origin.

MethodDescriptionDetection
Multiple transfersMoving money between accountsRapid fund movement
Shell companiesUsing fictitious businessesNo real business activity
International transfersMoving across jurisdictionsCross-border patterns
Trade-based launderingOver/under invoicingPrice discrepancies

PayFac Risk:

  • Transactions between related merchants
  • Complex refund patterns
  • International settlement manipulation

Stage 3: Integration​

The final stage reintroduces "cleaned" money into the legitimate economy.

MethodDescriptionDetection
Real estate purchaseBuying propertyLarge purchases, cash
Business investmentInvesting in companiesUnusual investment sources
Luxury goodsHigh-value purchasesCash purchases of luxury items
Loan repaymentPaying back fake loansLoans from unusual sources

PayFac Risk:

  • Merchant payouts to criminal accounts
  • Legitimate-appearing business revenue

Common Laundering Patterns​

Structuring (Smurfing)​

Breaking large amounts into smaller transactions to avoid reporting thresholds:

Red Flags:

  • Transactions consistently just under $10,000
  • Multiple transactions on consecutive days
  • Round or near-round amounts
  • Same person, multiple accounts

Round-Trip Transactions​

Money sent out and returned through different channels:

Red Flags:

  • Funds return to origin
  • Multiple intermediaries
  • Small "fees" deducted at each step

Trade-Based Laundering​

Using trade transactions to move value:

PatternExample
Over-invoicing importsPay $100K for $50K goods
Under-invoicing exportsReceive $50K for $100K goods
Multiple invoicingInvoice same goods multiple times
Phantom shipmentsPay for goods never shipped

Shell Company Networks​

Using fictitious or dormant companies:

PayFac-Specific Risks​

Merchant Account Laundering​

Criminals obtain merchant accounts to process fraudulent transactions:

SchemeMethodDetection
Fake salesProcess cards for non-existent salesNo real customers, high refund rate
Transaction launderingProcess for other businessesInconsistent business type
Bust-outProcess heavily, then disappearSudden volume spike, then abandonment

Sub-Merchant Risks​

RiskDescription
Identity fraudFake business identities
Business frontLegitimate front for illicit activity
CollusionMerchant and cardholder colluding
AggregationProcessing for unauthorized third parties

Red Flags for Payment Platforms​

Transaction-Level Red Flags​

Red FlagPattern
Round amounts$1,000, $5,000, $10,000 exactly
Threshold avoidance$9,999, $9,800 repeatedly
Rapid velocityMany transactions in short time
Unusual timingTransactions at odd hours
Geographic mismatchTransaction locations don't match business

Merchant-Level Red Flags​

Red FlagPattern
Inconsistent volumeSudden spikes without explanation
High refund rateExcessive refunds/voids
Minimal chargebacksSuspiciously low for high-risk MCC
Address discrepanciesBusiness address issues
Ownership changesFrequent beneficial owner changes

Network-Level Red Flags​

Red FlagPattern
Related merchantsTransactions between connected merchants
Common customersSame customers across many merchants
Coordinated activitySynchronized transaction patterns
Cross-border flowsUnusual international patterns

Risk Assessment​

High-Risk Industries​

IndustryRisk Factors
Money servicesDirect cash handling
Gambling/gamingCash-intensive, anonymous
Precious metalsHigh-value, portable
Real estateLarge transactions, cash
Virtual currencyPseudonymous, cross-border

High-Risk Geographies​

CategoryExamples
FATF blacklistCountries identified as high-risk
SanctionedOFAC-sanctioned jurisdictions
Tax havensKnown for secrecy
Conflict zonesAreas with limited oversight

Risk Scoring Factors​

FactorHigher RiskLower Risk
Business typeCash-intensive, high-valueRetail, services
GeographyHigh-risk countriesDomestic, low-risk
Customer typeAnonymous, shell companyEstablished business
Transaction patternsUnusual, complexConsistent, explainable
OwnershipComplex, nomineeClear, verified

Detection Approaches​

Rules-Based Detection​

Rule CategoryExamples
Threshold> $10K single transaction
Velocity> 5 transactions in 10 minutes
PatternRound amounts, just under reporting
GeographicTransactions from high-risk countries
RelationshipTransactions between related parties

Machine Learning Detection​

ApproachApplication
Anomaly detectionIdentify unusual patterns
ClusteringGroup similar suspicious behavior
Network analysisMap transaction relationships
Behavioral analysisDetect changes from baseline

References​

Share: