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Anti Money Laundering (AML)

Overview

Anti Money Laundering refers to the laws, regulations, and institutional controls that prevent, detect, and report laundering and terrorist financing. Core program elements include a written policy, a designated compliance officer, training, independent testing, customer due diligence, screening, transaction monitoring, investigations, and regulatory reporting such as SAR and CTR filings. A risk assessment informs controls, scenarios, and staffing. Governance requires board oversight, model validation, data lineage, and quality management.
Effective AML programs integrate fraud and cyber signals, use graph analytics for networks, and employ continuous monitoring and event driven reviews. Documentation and audit trails are essential to demonstrate effectiveness to regulators. When executed well, AML frameworks reduce exposure, safeguard customers, and protect access to correspondent banking and payment networks.

FAQ

What makes an AML program effective?

Risk based controls aligned to products and geographies, quality data, tuned scenarios, trained staff, and documented evidence of decisions and outcomes.

How do fraud and AML work together?

Shared signals and link analysis improve both. Fraud detects intent quickly, while AML focuses on typologies and reporting obligations.

What are common deficiencies?

Weak risk assessments, stale data, poor model governance, delayed filings, and inadequate QA. Regular reviews and remediation plans address these gaps.

How is effectiveness shown to regulators?

Metrics such as precision and recall, timely filings, coherent SAR narratives, and evidence driven tuning tied to confirmed cases.