More and more, regulators are examining AML and terrorist financing monitoring software solutions to see if they are tuned correctly; and citing financial institutions who fail to meet the regulatory standards. One issue for both regulators and these institutions is the creation of excessive volumes of “false positive” activity alerts, or alerts on activity that after evaluation, is not determined to be suspicious.
Insights and guidance from ACA's team of experienced compliance and technology professionals.
On April 18, the Financial Crimes Enforcement Network (FinCEN) announced that they have imposed their first-ever penalty on a peer-to-peer cryptocurrency exchange for violating AML regulations, among other violations.
Every anti-money laundering (AML) program should be reviewed periodically to confirm that the program is performing efficiently and effectively. Analytics can play a big role in this review by providing new insights that support evidence-based decision-making.
ACA Telavance is delighted to moderate a panel at the The Institute of Internal Auditors (IIA), New York Chapter Annual Audit Conference. Dan Collins, Managing Director, will lead a discussion about regulatory expectations for internal audit of BSA/AML and sanctions, including:
Michael Held, Executive Vice President of the Legal Group at the Federal Reserve Bank of New York, spoke at the 1LoD Summit in New York on April 2, 2019.
We are excited to speak at the FIBA AML Compliance Conference on March 13th. Uday Gulvadi, Director of Internal Audit and Risk, will join a panel to discuss his thoughts on the Beneficial Ownership Rule.
The Three Lines of Defense Model has gained popularity as the de facto model for organizing governance, risk management and internal control roles and responsibilities since the Institute of Internal Auditors (IIA) published “The Three Lines of Defense in Effective Risk Management and Control,” position paper in 2013. The IIA recently announced that they would embark on a key project to refresh and update this document.
Analytical segmentation modeling (ASM) is one way to design an effective AML monitoring strategy through the development of a quality model to achieve segmentation. ASM involves combining customer or bank accounts with similar properties and transaction behavior to make it easy for banks to formulate risk signals based on their various classes of customers. This model sets threshold levels for the segments monitored by identifying patterns based on the groups of similar customers and/or accounts.
On February 8, Krebs on Security reported that a number of AML compliance professionals at credit unions and other financial institutions have recently been t
Technology is an essential weapon for financial services firms in the battle against anti-money laundering (AML). The Office of the Comptroller of the Currency (OCC) issued a joint statement with other regulators earlier this month encouraging financial institutions to try new and innovative ways of combating AML. Three types of technology – advanced analytics, software robots, and artificial intelligence (AI) – could help make it easier to detect and prevent money laundering, as well as comply with existing regulations and follow the guidance of this joint statement.
While the financial institutions have the desire to improve the data quality and availability, data governance is often driven by external regulations to implement a program to ensure requirements outlined in DFS Part 504 regulation are met.