By Lee GarfFinancial institutions have come a long way when it comes to utilizing next-gen technologies such as artificial intelligence and machine learning throughout their operations. We may all remember a time of skepticism. Recently this change was reflected strongly in an informal NICE Actimize customer survey which revealed that almost 90 percent of financial institutions acknowledge that they are already on the “path to AI” in terms of integrating AI’s advanced analytics into their compliance platforms, with only 11 percent of respondents not currently considering AI In their strategic planning efforts.
It didn’t seem so long ago that some regulators were hesitant to adopt new AI technologies, but now that they have seen AI’s powerful ability to analyze large amounts of data and identify unusual patterns, they are largely embracing the advancements. Experiencing first-hand the efficiencies that AI-driven approaches bring to a multitude of functions, particularly with respect to newer regulations, they have settled into a more adoptive stance.
In the survey that included nearly 100 respondents from compliance and surveillance personnel within global banks, a strong 60 percent noted that behavioral monitoring and conduct risk may be the number one area of value, likely due to this year’s increase in remote work management. And with behavior and conduct key, 18 percent said that remote working for traders and regulated users was a chief concern, with a solid 20 percent of respondents checking the box that this was their biggest challenge.
Even in the work-at-home environment, regulatory compliance has not abated and regulators are making it imperative for banks to adopt better ways of monitoring ever-changing activities. Even with employees working from home, financial institutions must remain fully compliant.
Financial firms historically take a conservative approach to adopting new technology. However, given the rapid shift to unified communications solutions (Microsoft Teams, Zoom, WebEx, etc.) and mobile communications due to the current environment, the benefits of AI and machine learning become critical. There are multiple forces at play. First, if the financial institution simply banned these types of communication channels, employees would be challenged to do their jobs. Second, compliance could be signaling to bad actors that no one is watching. This will drive nefarious behavior into the shadows, and there are unfortunately bigger shadows to deal with when working remotely.
Finally, employees have already been pushing firms to adopt these new ways of communicating, and firms want to make their employees happy, especially if they are revenue-generating employees.
Burden of communications data is huge
Regulators expect firms to be proactive and take reasonable steps when it comes to monitoring—no matter the location of the regulated employee. Looking at the recent MAR review, regulators have greater latitude to deem a trading firm “negligent” if it isn’t taking proactive steps to put processes and procedures in place to reduce market abuse. Under Regulation Best Interest (Reg BI), wealth management units of banks need to ensure they are not “mistreating” their clients by giving investment advice that is not in the clients best interest. What are our recommendations? What are we seeing? We think the right approach is to allow employees to use recordable channels of communications (UC, chat, text message). The technology is available to monitor Teams, mobile devices, WhatsApp, and so on accurately.
We also think a more connected organization leads to a safer one. Bringing together siloed data from across the bank can lead to better detection of otherwise hard-to-detect crimes. One area we’re seeing demand for this is around anti-money laundering detection within capital markets. Banks can consolidate data from AML teams and surveillance to better detect nefarious activity and bring together previously siloed data.
Why can’t banks do this manually or why do home-grown solutions not work? Banks that try to build internal trade compliance solutions end up with even more siloed systems that do not provide an accurate view of risk or efficient workflow processes. Vendor solutions used by hundreds of firms globally have so many built-in best practices that are looked on favorably by regulators. Then there is the cost of maintaining these systems. What seemed like the low-cost route quickly becomes very expensive since this isn’t the bank’s main business and they don’t have access to the cost benefits of scale.
Financial services firms are looking to AI/ML to help generate insights from oceans of data in this environment. Today, firms are adopting natural language processing, and applying it to real-time trade event reconstruction, saving firms countless hours on expensive investigations. We’re also assisting firms with behavioral risk detection, where we use AI to find clear patterns within vast data sets. This is helping firms dial in on risks especially when employees are working from home. We can spot changes in communications patterns, or changes in trade patterns.
Additionally, regulations require customers to accurately record and retain communications, in many cases for seven years, and under a number of regulations firms need to be able to turn around reporting requests quickly—in some cases 72 hours under MiFID II. Again, here is another example where AI provides support and massive process improvements in meeting these tight deadlines.
Clearly banks are saying “yes” to many forms of artificial intelligence, as our survey indicates, and are welcoming the many opportunities that the technology brings to make their compliance operations more effective and efficient. And when AI is coupled with another technology advancement—the increasing adoption of an agile cloud environment—the year ahead for financial institutions and their compliance teams looks better than ever.
Lee Garf is general manager, Financial Markets Compliance, NICE Actimize.