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 embarked on a comprehensive review of the client's compliance procedures and products, with a particular focus on transaction data, which can often be associated with regulatory red flags.
This involved a detailed examination of the client's operational policies and an in-depth analysis of their BSA/AML models, Transaction Monitoring, and Sanctions Screening processes within the client's TM and Screening systems.
To facilitate this analysis, we implemented an SQL server environment. This allowed for rigorous testing of the current system logic within the TM system. A series of tests were run, simulating various scenarios related to different types of transactions to assess the system'ss performance and response under different conditions. This helped identify any potential discrepancies or inefficiencies in the system.
In parallel, we conducted a thorough audit of the client's transaction data. The data, integral to the client's TM system, was examined for quality and integrity, ensuring that it was accurate, complete, and reliable. Each data point related to different types of transactions was cross-verified against multiple sources, and a series of tests were run to detect any inconsistencies or errors.
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.