Automating High-Risk Entity Reviews to Reduce Errors, Improve Efficiencies, and Ensure CDD Compliance

Federal bank regulatory agencies require that financial institutions regularly review and segment all their customers based on risk. While the Customer Due Diligence (CDD) Rule, which amended BSA regulations in 2018, does not stipulate how often reviews should be carried out, the expectation is that high-risk customers should be reviewed “periodically.” For many financial institutions, dormant or declining accounts deemed “high-risk” for one reason or another must be examined on a regular basis. Accounts considered moderate or “low-risk,” although reviewed less frequently, must still be evaluated occasionally, adding to a bank’s workload.

A significant problem for many institutions, however, is that High-Risk Entity Reviews (HRERs) are a very time-consuming, onerous, costly and inconsistent requirement — especially when it comes to highly active entities. In most cases, human investigators must manually sift through multiple databases and websites to determine customer risk. Lack of access to data, competing AML/BSA priorities, human biases, and staffing issues can easily produce backlogs and errors in systems that lack efficiency and consistency.

To better understand how financial institutions can ensure CDD compliance while reducing errors, improving efficiencies, and lowering costs, let’s briefly examine four key HRER challenges that many institutions face right now.

The Frequency of HRERs

Most institutions now schedule annual HRERs, but they do so begrudgingly. Many would prefer to do without the high costs and extra burden on resources. But how do you unwind something that the majority are doing? Any sudden stop or change in frequency will give regulators cause to question the shift.

To avoid attracting unwanted and unnecessary attention from regulatory agencies, financial institutions need to maintain a regular and responsible HRER schedule, and look for other ways to lessen the time, resource, and cost burden on their business.

The Onerous HRER Workload

To investigate a possible financial crime based on a TMS alert, investigators need to look for specificity around the transaction. They compare the reason for the alert with the purpose of the account for a single transaction. For a HRER, however, investigators have far more to contend with. They must:

• Examine the entire relationship, the set of transactions in practice, and any patterns they reveal.
• Gather information, collect adverse media, conduct a sentiment analysis.
• Establish whether or not the entity’s transactions are in line with the business they do and if the counterparties are legitimate or not.

With so much work required (averaging seven to 10 hours per case), it stands to reason that many institutions don’t see the value behind doing so much work if they’re already monitoring transactions on an ongoing basis. However, it must be remembered that the consequences of not doing HRERs properly and regularly far outweigh the cost and effort of doing them right.

The Staffing Requirements Balance Act for HRERs

To maximize profitability, institutions naturally staff for minimum need. Some hire specialists to take care of the day-to-day work, so that they can assign HRERs to their most experienced and efficient analysts. Others bring in senior staff with specific HRER expertise. However, for many reasons, backlogs can develop.

The global pandemic increased backlogs and made staffing problems worse. Fraud attempts increased, as did the level of alerts throughout due to the sudden uptick in online activity. But the workforce was unable to cope as it was forced to adjust to a less structured, distraction-heavy remote environment.

The only way institutions can realistically overcome staff-related challenges and avoid the significant backlogs they cause is by turning to advanced technologies, including AI, machine learning, and automation. However, the path to digital transformation requires attention.

The Perception of Artificial Intelligence Automating HRERs

Two very different perceptions of automated HRERs currently push and pull institutions in opposite directions. On the one hand, you have the regulators and their examiners, with increasing technology expectations. On the other, you have many financial institutions held back by the belief that technology is expensive and available only to large institutions.

While the regulator itself is not specifically pushing AI for HRERs, they are looking for innovation. They’re seeing what’s available and learning how technology is being applied. They’re identifying with what leading-edge institutions are doing and forming opinions on how quickly other institutions should be doing the same thing. The regulatory expectations are moving, and institutions must be prepared to meet them.

The challenge many institutions face, however, is the belief that advanced technology built to revolutionize financial crime identification is beyond their means right now. Fortunately, for the right solutions, costs are reasonable and designed to integrate into their existing systems. Institutions need to swiftly take advantage and avoid being left behind. If they become too out-of-date, they risk not being able to capitalize on the new technologies and the significant cost savings they deliver.

How to Create an Effective and Efficient HRER Program

The path to successful and profitable automation of an institution’s HRER process is easier and faster than believed. Automating these processes creates the efficiencies that institutions need to advance and speed their HRER work. One large financial institution is a case in point. Its team was spending 10 hours, on average, per report (1,200 reports annually). Using QuantaVerse, the time spent on each report was reduced to three hours per investigation.

The QuantaVerse High-Risk Entity Report documents risk discovered by the QuantaVerse Financial Crime Investigation Platform. The platform automates the research work required to assess entity risk, such as adverse media, jurisdiction, transactional relationships, and typologies that indicate potential money laundering.

“The High-Risk Entity Report makes the review process more efficient and provides better insights to financial institutions as they conduct on-going entity risk reviews,” explained David McLaughlin, CEO and Founder of QuantaVerse. “Customers using our High-Risk Entity Report can expect to more than double the efficiency of their teams while getting more complete and consistent analysis with fewer errors.”

If you want to get started quickly with the QuantaVerse HRER Fast Start, please visit: https://quantaverse.net/try-ai.