For our client, adherence to the Bank Secrecy Act (BSA) and Anti-Money Laundering (AML) rules is crucial. These regulations, enforced by the NY Department of Financial Services and the Federal Reserve Board, require robust systems for detecting and reporting potential financial crimes.
To ensure compliance, BSA/AML Model Validation, Transaction Monitoring, and Sanctions Screening Tuning Analysis are regularly conducted. This process involves testing and adjusting systems to improve accuracy, reduce false positives, and align with regulatory guidelines like the FRB'ss SR 11-7. This commitment to regulatory compliance is essential for avoiding penalties and maintaining the integrity of the financial system.
We began with a detailed examination of the client's BSA/AML compliance policies and the design documentation of their TM and screening models. To empirically test the system logic, we implemented a controlled SQL server environment. This allowed for rigorous, independent testing by simulating a wide array of transaction scenarios and sanction list matches, thereby assessing detection accuracy and identifying inefficiencies.
In parallel, we conducted a forensic audit of the transaction data feeding the systems. We verified the quality, accuracy, and reliability of key data points through source cross-referencing and completeness checks, ensuring the models operated on a foundation of sound information. This integrated approach ensured a holistic evaluation of both system performance and data integrity.
We also identified overlapping alert results from certain scenarios, suggesting potential inefficiencies. Based on these findings, we recommended system adjustments and the removal of overlapping scenarios to enhance regulatory compliance and improve the efficiency of the client's financial crime detection systems.