AgentSkillsCN

Validate Aml Transaction

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SKILL.md

Skill: Validate AML Transaction

Domain

financial_services

Description

Validates transactions against anti-money laundering rules including suspicious activity detection, sanctions screening, and regulatory reporting triggers.

Tags

AML, compliance, sanctions, BSA, financial-crime, KYC

Use Cases

  • •Transaction monitoring
  • •Suspicious activity detection
  • •Sanctions screening
  • •SAR filing determination

Proprietary Business Rules

Rule 1: Pattern Detection

Identification of structuring, layering, and other suspicious patterns.

Rule 2: Sanctions Screening

OFAC and international sanctions list matching.

Rule 3: Risk Scoring

Transaction risk scoring based on multiple factors.

Rule 4: SAR Threshold Analysis

Determination of SAR filing requirements.

Input Parameters

  • •transaction_id (string): Transaction identifier
  • •transaction_details (dict): Transaction information
  • •customer_info (dict): Customer profile
  • •account_history (list): Recent account activity
  • •counterparty_info (dict): Counterparty details
  • •geographic_data (dict): Location information

Output

  • •risk_score (float): Transaction risk score
  • •alerts (list): Generated alerts
  • •sanctions_result (dict): Sanctions screening results
  • •sar_recommendation (dict): SAR filing determination
  • •required_actions (list): Required compliance actions

Implementation

The validation logic is implemented in aml_validator.py and references data from CSV files:

  • •transaction_thresholds.csv - Reference data
  • •risk_scoring.csv - Reference data
  • •red_flags.csv - Reference data
  • •alert_thresholds.csv - Reference data
  • •velocity_rules.csv - Reference data
  • •parameters.csv - Reference data.

Usage Example

python
from aml_validator import validate_aml

result = validate_aml(
    transaction_id="TXN-2026-001",
    transaction_details={"amount": 9500, "type": "wire", "currency": "USD"},
    customer_info={"id": "CUST-001", "risk_rating": "medium", "occupation": "import_export"},
    account_history=[{"date": "2025-12-01", "amount": 9200, "type": "wire"}],
    counterparty_info={"name": "ABC Corp", "country": "AE"},
    geographic_data={"origin_country": "US", "destination_country": "AE"}
)

print(f"Risk Score: {result['risk_score']}")

Test Execution

python
from aml_validator import validate_aml

result = validate_aml(
    transaction_id=input_data.get('transaction_id'),
    transaction_details=input_data.get('transaction_details', {}),
    customer_info=input_data.get('customer_info', {}),
    account_history=input_data.get('account_history', []),
    counterparty_info=input_data.get('counterparty_info', {}),
    geographic_data=input_data.get('geographic_data', {})
)