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Introduction gu1’s AML monitoring helps you comply with anti-money laundering regulations by automatically detecting suspicious patterns, generating alerts, and facilitating regulatory reporting.
Regulations Covered
FATF Recommendations Financial Action Task Force international standards
BSA/AML (USA) Bank Secrecy Act and Anti-Money Laundering regulations
6AMLD (Europe) Sixth Anti-Money Laundering Directive
UIF (LATAM) Financial Intelligence Units across Latin America
Detectable Patterns 1. Structuring (Smurfing) Multiple transactions just below reporting thresholds to avoid detection.
Indicators:
Multiple transactions near $10,000 threshold
Consistent amounts across multiple days
Same origin/destination entities
Round amounts
2. Rapid Movement (Layering) Funds moving quickly through multiple accounts to obscure origin.
Indicators:
Multiple transfers in short time
Funds passing through multiple intermediaries
Immediate withdrawals after deposits
Complex transaction chains
3. High-Risk Countries Transactions involving FATF grey list or sanctioned countries.
Indicators:
Countries under increased monitoring
Sanctioned jurisdictions
Non-cooperative territories
4. Politically Exposed Persons (PEPs) Transactions involving individuals with prominent public functions.
Indicators:
PEP database matches
Family members of PEPs
Close associates
High-value transactions
5. Round Dollar Amounts Unusually round amounts that may indicate structuring or cash placement.
Indicators:
Frequent exact round amounts (1000 , 1000, 1000 ,
Patterns of similar round amounts
Inconsistent with normal behavior
6. Cash-Intensive Businesses Higher scrutiny for businesses with high cash volumes.
Indicators:
MCC codes for cash-intensive industries
High cash deposit frequency
Inconsistent transaction patterns
Unusual cash-to-revenue ratios
Production-Ready AML Rules 1. Structuring Detection - $10K Threshold { "name" : "Structuring Detection - $10K Threshold" , "category" : "aml" , "priority" : 900 , "enabled" : true , "evaluationMode" : "async" , "targetEntityTypes" : [ "transaction" ], "conditions" : { "operator" : "AND" , "conditions" : [ { "field" : "amountInUsd" , "operator" : "GREATER_THAN" , "value" : 9000 }, { "field" : "amountInUsd" , "operator" : "LESS_THAN" , "value" : 10000 }, { "field" : "metadata.transactionsSameOriginLast7d" , "operator" : "GREATER_THAN_OR_EQUAL" , "value" : 3 } ] }, "actions" : [ { "type" : "generate_alert" , "config" : { "severity" : "high" , "type" : "possible_structuring" , "message" : "Entity {{originEntityId}} has {{metadata.transactionsSameOriginLast7d}} transactions near $10K threshold in last 7 days" } }, { "type" : "create_investigation" , "config" : { "priority" : "high" , "assignToTeam" : "aml_compliance" , "requiresSAR" : true } } ] }
2. Rapid Movement - Layering Detection { "name" : "Rapid Movement - Layering Pattern" , "category" : "aml" , "priority" : 850 , "enabled" : true , "evaluationMode" : "async" , "targetEntityTypes" : [ "transaction" ], "conditions" : { "operator" : "AND" , "conditions" : [ { "field" : "type" , "operator" : "EQUALS" , "value" : "TRANSFER" }, { "field" : "metadata.entityTransferChainLength" , "operator" : "GREATER_THAN" , "value" : 3 }, { "field" : "metadata.chainTotalTime" , "operator" : "LESS_THAN" , "value" : 3600 }, { "field" : "amount" , "operator" : "GREATER_THAN" , "value" : 5000 } ] }, "actions" : [ { "type" : "generate_alert" , "config" : { "severity" : "high" , "type" : "rapid_movement" , "message" : "Funds moved through {{metadata.entityTransferChainLength}} entities in {{metadata.chainTotalTime}} seconds - Amount: ${{amount}}" } }, { "type" : "create_investigation" , "config" : { "priority" : "high" , "assignToTeam" : "aml_compliance" } } ] }
3. High-Risk Country Monitoring { "name" : "High-Risk Country Transaction" , "category" : "aml" , "priority" : 900 , "enabled" : true , "evaluationMode" : "async" , "targetEntityTypes" : [ "transaction" ], "conditions" : { "operator" : "AND" , "conditions" : [ { "field" : "metadata.involvedCountries" , "operator" : "INTERSECTS" , "value" : [ "AF" , "KP" , "IR" , "SY" , "MM" , "YE" ] }, { "field" : "amountInUsd" , "operator" : "GREATER_THAN" , "value" : 1000 } ] }, "actions" : [ { "type" : "generate_alert" , "config" : { "severity" : "critical" , "type" : "high_risk_country" , "message" : "Transaction involving high-risk countries: {{metadata.involvedCountries}} - Amount: ${{amountInUsd}}" } }, { "type" : "create_investigation" , "config" : { "priority" : "critical" , "assignToTeam" : "aml_compliance" , "requiresImmediateAction" : true } } ] }
4. PEP Transaction Monitoring { "name" : "PEP Transaction Alert" , "category" : "aml" , "priority" : 950 , "enabled" : true , "evaluationMode" : "async" , "targetEntityTypes" : [ "transaction" ], "conditions" : { "operator" : "AND" , "conditions" : [ { "field" : "metadata.originEntityIsPEP" , "operator" : "EQUALS" , "value" : true }, { "field" : "amountInUsd" , "operator" : "GREATER_THAN" , "value" : 10000 } ] }, "actions" : [ { "type" : "generate_alert" , "config" : { "severity" : "high" , "type" : "pep_transaction" , "message" : "PEP {{originEntityId}} ({{metadata.pepPosition}}) - Transaction: ${{amountInUsd}}" } }, { "type" : "create_investigation" , "config" : { "priority" : "high" , "assignToTeam" : "aml_compliance" , "enhancedDueDiligence" : true } } ] }
5. Round Dollar Amount Pattern { "name" : "Round Amount Structuring Pattern" , "category" : "aml" , "priority" : 800 , "enabled" : true , "evaluationMode" : "async" , "targetEntityTypes" : [ "transaction" ], "conditions" : { "operator" : "AND" , "conditions" : [ { "field" : "amount" , "operator" : "MODULO_EQUALS" , "value" : 0 , "divisor" : 1000 }, { "field" : "metadata.roundAmountTransactions30d" , "operator" : "GREATER_THAN" , "value" : 5 }, { "field" : "amount" , "operator" : "GREATER_THAN" , "value" : 5000 } ] }, "actions" : [ { "type" : "generate_alert" , "config" : { "severity" : "medium" , "type" : "round_amount_pattern" , "message" : "Entity {{originEntityId}} has {{metadata.roundAmountTransactions30d}} round amount transactions in 30 days" } } ] }
6. Cash-Intensive Business Monitoring { "name" : "Cash-Intensive Business - Enhanced Monitoring" , "category" : "aml" , "priority" : 850 , "enabled" : true , "evaluationMode" : "async" , "targetEntityTypes" : [ "transaction" ], "conditions" : { "operator" : "AND" , "conditions" : [ { "field" : "mccCode" , "operator" : "IN" , "value" : [ "5813" , "7995" , "7999" , "9399" ] }, { "field" : "type" , "operator" : "EQUALS" , "value" : "DEPOSIT" }, { "field" : "origin.paymentMethod" , "operator" : "EQUALS" , "value" : "CASH" }, { "field" : "amount" , "operator" : "GREATER_THAN" , "value" : 5000 } ] }, "actions" : [ { "type" : "generate_alert" , "config" : { "severity" : "medium" , "type" : "cash_intensive_business" , "message" : "Cash-intensive business (MCC: {{mccCode}}) - Cash deposit of ${{amount}}" } } ] }
Reporting Thresholds United States (FinCEN) Report Type Threshold Timeframe CTR (Cash Transaction Report) $10,000 Single day SAR (Suspicious Activity Report) $5,000 (known) Suspicious activity SAR $25,000 (unknown) Suspicious activity FBAR (Foreign Bank Account) $10,000 Aggregate balance
European Union (6AMLD) Report Type Threshold Timeframe STR (Suspicious Transaction Report) No threshold Suspicious activity High-Value Transaction €10,000 Single transaction Cross-Border Declaration €10,000 Cash movement
Latin America Country Report Type Threshold Brazil COAF R$ 10,000 Mexico UIF $7,500 USD Argentina UIF $10,000 USD Colombia UIAF $10,000 USD Chile UAF $10,000 USD
Compliance Workflow { "reportType" : "SAR" , "reportDate" : "2024-10-28T00:00:00Z" , "filingInstitution" : { "name" : "Your Institution" , "ein" : "12-3456789" , "address" : "123 Main St, City, State, ZIP" }, "subject" : { "entityId" : "customer_001" , "name" : "John Doe" , "dateOfBirth" : "1980-01-01" , "ssn" : "XXX-XX-1234" , "address" : "456 Oak Ave, City, State, ZIP" }, "suspiciousActivity" : { "type" : "structuring" , "dateBegin" : "2024-10-01" , "dateEnd" : "2024-10-28" , "totalAmount" : 45000.00 , "description" : "Subject conducted 5 transactions between $9,000-$9,999 over 14 days, pattern consistent with structuring to avoid CTR reporting threshold." }, "transactions" : [ { "date" : "2024-10-01" , "amount" : 9500.00 , "type" : "DEPOSIT" , "method" : "CASH" }, { "date" : "2024-10-05" , "amount" : 9800.00 , "type" : "DEPOSIT" , "method" : "CASH" } ], "narrative" : "Over a 14-day period, the subject made 5 cash deposits, each between $9,000 and $9,999, totaling $45,000. The pattern, timing, and amounts suggest deliberate structuring to avoid the $10,000 CTR threshold. Subject has no business activity justifying these cash volumes. Previous transaction history shows average deposits of $500-$1,000. Enhanced due diligence revealed no legitimate source for these funds." , "filedBy" : { "name" : "Jane Smith" , "title" : "AML Compliance Officer" , "phone" : "555-0123" , "email" : "jane.smith@institution.com" } }
Best Practices ✅ DO
Risk-Based Approach
Focus resources on highest risk
Adjust thresholds by customer risk profile
Enhanced due diligence for high-risk
Document Everything
Record all decisions
Maintain audit trail
Document reasoning
Regular Training
Train all relevant staff
Update on new regulations
Test knowledge periodically
Monitor Effectiveness
Track detection rates
Measure false positives
Review filed reports
Timely Reporting
File SARs within required timeframes
Don’t delay investigations
Maintain required records
❌ DON’T
Don’t Tip Off Subjects
Never inform subjects of SAR filing
Maintain confidentiality
Train staff on tipping off rules
Don’t Use Static Thresholds
Adjust for inflation
Consider currency differences
Use risk-based approach
Don’t Ignore Patterns
Look beyond individual transactions
Analyze relationships
Consider temporal patterns
Don’t Rush Investigations
Thorough analysis required
Gather all evidence
Document properly
KPIs and Metrics AML Program Effectiveness { "amlMetrics" : { "alertsGenerated" : 450 , "alertsReviewed" : 445 , "investigationsOpened" : 89 , "sarsFiledTimely" : 23 , "sarsFiledLate" : 0 , "averageInvestigationTime" : "18 hours" , "falsePositiveRate" : 0.78 , "detectionRate" : 0.93 , "regulatoryFindings" : 0 } }
Monthly AML Report -- Monthly SAR filing summary SELECT DATE_TRUNC( 'month' , filed_date) as month , COUNT ( * ) as sars_filed, SUM (total_amount) as total_suspicious_amount, AVG (investigation_time_hours) as avg_investigation_time, COUNT ( DISTINCT subject_id) as unique_subjects FROM sar_filings WHERE filed_date > NOW () - INTERVAL '12 months' GROUP BY month ORDER BY month DESC ;
Pattern Detection Effectiveness -- Most effective AML rules SELECT pattern_type, COUNT ( * ) as alerts_generated, SUM ( CASE WHEN resulted_in_sar THEN 1 ELSE 0 END ) as sars_generated, ROUND ( 100 . 0 * SUM ( CASE WHEN resulted_in_sar THEN 1 ELSE 0 END ) / COUNT ( * ), 2 ) as conversion_rate, SUM (suspicious_amount) as total_amount_flagged FROM aml_alerts WHERE created_at > NOW () - INTERVAL '90 days' GROUP BY pattern_type ORDER BY conversion_rate DESC ;
Integration with Intelligence All AML alerts automatically:
Consolidate into investigations
Track across related entities
Maintain complete timeline
Enable team collaboration
Generate audit trail
Export SAR-ready reports
Next Steps
Fraud Detection Real-time fraud prevention
Merchant Monitoring Monitor merchants and acquirers
Rules Configuration Create custom rules
