Since the financial crisis in 2008, regulators in the United States and abroad have been fining financial institutions at a record pace. It’s no wonder, considering that almost 70 percent of the illicit money used to fund organizations trafficking drugs, weapons, human beings and even supporting terrorist activity flows through legitimate institutions. Despite this clamp down on anti-money laundering (AML) enforcement, only 1 percent of these illegal funds is routinely seized and frozen.
While there are numerous headline-grabbing examples of multimillion-dollar fines levied against institutions that willfully violate AML laws, there are even more cases of fines handed down to businesses that unwittingly commit violations. Although many of these fines, on their face, are just a drop in the bucket for these massive institutions, the damage to their brand can have long-standing repercussions to their bottom line.
This is why failing to establish and implement adequate AML procedures leaves financial businesses unable to properly prevent, detect and report suspicious activity.
This is compounded by the fact that the legacy software banks often use to collect and qualify customer data becomes less effective with each policy change, and the data itself less useful as a result.
The latest data and software can keep banks on the cutting edge
At ACAMS Hollywood 2017, I discussed how financial institutions can take ownership of executing the right internal AML policies to help them better understand their customers and assess risk. By accessing publicly available databases, firms can verify new-account Ultimate Beneficial Ownership (UBOs) and implement a ratings system that flags customers that may put banks at risk for non-compliance. To read more highlights from the presentation, check out the coverage provided by the Wall Street Journal here.
The goal is for financial institutions to implement a relationship-based approach to transaction monitoring that utilizes a variety of data sets to help better contextualize the parties involved. The benefits of seeking out a relationship-based system are many, including a reduced number of false positives and improved detection of false negatives that will ultimately ease AML investigations while reducing their overall cost.
Our systems are designed to help customers find, link and visualize the complete customer story by unifying data that used to live in silos. By embracing graph databases, the story that each customer’s transactions is trying to tell comes to the fore as trends and relationships that might not have been evident on the outset begin to emerge.
Learn more about our solutions to helping firms combat AML noncompliance by reading our report, “Improve AML Compliance with a Relationship-Based Approach,” authored in collaboration with Forbes.