Corporate anti-money-laundering (AML) and customer due diligence (CDD) teams use automated risk-analysis tools to improve operational efficiency and screen customers and vendors who may represent an unacceptably high risk to the institution. But if potentially risky customers are routinely rejected simply because an automated system flagged them, or because avoiding them seems more efficient, AML/CDD teams may be inadvertently missing opportunities to develop some excellent business relationships.
Why? Because automated screening programs flag customers as high risk for many different reasons. Depending on how know-your-customer (KYC) risk parameters have been set up, a system may be giving too much weight to factors that aren’t relevant or misclassifying some lower-risk customers as high risk for reasons that don’t represent a legitimate threat.
In any case, a high-risk score alone does not provide the context necessary to understand a customer’s true risk. If AML/CDD teams are not taking the time to investigate why a customer was flagged, and whether the reasons for flagging them justify refusing to onboard them, there is a very real possibility that worthwhile customers are being turned away for no good reason.
Use risk scores to dig deeper
There are hundreds of reasons why a customer might receive an unfavorably high-risk score. Maybe the business was flagged because it was involved in a lawsuit that has already been resolved—in their favor. Or maybe the business changed ownership, and the system is really flagging the previous owners. Maybe the customer was once the victim of identity theft. Or their line of business was miscategorized as a money-laundering risk. Or the business was mistakenly associated with another high-risk business with a similar name.
It doesn’t matter what the reason is—the point is that if AML/CDD teams rely too heavily on risk scores and don’t make the effort to better understand what is driving the risk, the institution may be undermining itself by embracing false notions of security and efficiency. As a best practice, KYC protocols should be layered so that teams can review flagged accounts to determine if the highlighted factors are worth investigating further. Additionally, the overall efficiency of an automated risk-assessment tool should, in theory, give AML/CDD teams ample time to conduct deeper investigations into high-risk customers.
Study: Automation does more than just save time
To test that theory, Thomson Reuters recently commissioned Forrester Research to conduct an independent study of its CLEAR ID Confirm and Risk Inform solutions for due diligence and fraud prevention. Forrester interviewed several Thomson Reuters customers to find out what the quantifiable benefits of using CLEAR ID Confirm and Risk Inform were for their respective organizations. They told Forrester that using these tools not only freed up more time for investigations but also made the investigations themselves more effective and efficient by pulling together detailed risk information on high-risk accounts into a comprehensive report that was easy to understand and interpret.
According to Forrester’s report, the two CLEAR solutions made general risk assessments 40% faster, reducing the amount of time employees had to spend on routine risk assessments. These programs also made it 20% easier to investigate vendors and other customers who were labeled as high risk, assess the factors that were driving their risk scores up, and determine if those factors were important enough to avoid taking them onboard.
One user said: “CLEAR allows us to give more attention to higher-risk accounts that we still may be able to approve and do business with. CLEAR lets us take a deeper dive and, for instance, know the exact legal issues in the customer’s background.” Furthermore, this user appreciated the transparency of the provided reports, saying, “The information and where it’s coming from is pretty much self-explanatory.”
In such cases, CLEAR users used a full report customized to their KYC risk threshold for different types of businesses. Interviewees said that the underlying data in each report was extensive, current, and accurate and that after reading the reports, the decision about whether to onboard a new customer or not was relatively obvious. Interviewees also appreciated the transparency of the reports regarding where the data was coming from, and how easy it was to identify the data that mattered most to them, particularly when it pertained to criminal histories and legal issues.
Understand your customer’s story
No risk-assessment tool is perfect, and how an institution chooses to use them is an important consideration that is sometimes overlooked. Relying too heavily on risk scores to make onboarding decisions opens up the risk of allowing potentially great partnerships to slip through the cracks and go to a competitor. Every customer or vendor has a unique story, after all, and taking the time to understand that story can both strengthen AML efforts and open up the possibility of building better business relationships that can pay large dividends down the road.
Learn more about how your AML or CDD team can benefit from implementing an automated risk assessment tool.