The holistic dream, now delayed
According to our own recent conversations, as many as 95% of financial institutions’ employees are working from home during the current Coronavirus pandemic.
So, how do you ensure those employees are meeting the highest standards of conduct in a Work-From-Home (WFH) environment?
Before COVID-19, the answer was holistic surveillance — the analysis of structured and unstructured data including behavioral analytics, eComms monitoring, and voice interactions. At least, that was what many banks were working toward.
Now, though, as most people work from home, there is less data to tap, because you cannot count on most of the things you could in the office environment — whether it’s looking over peoples’ shoulders, having them card in and out of a building, or having them use office assets.
This has created a scarcity of sources, and when you have a scarcity of sources you have to go deeper to find the signal in the noise, because you can’t go wider anymore. You’re not putting together a bunch of different pieces. Instead, you’re looking for clues that weren’t obvious until after the fact.
The holistic approach has been disrupted, which means that surveillance has to get smarter.
The pandemic has exposed many brittle legacy systems and made it imperative that banks move beyond them. Those banks that fail to implement more advanced technologies stand to be left behind in the “new normal.” For example, banks that limit their analysis to lexicons and keywords are realizing it is extremely difficult to calibrate them to incorporate new data channels and new WFH realities.
Furthermore, in a “BYOO, Bring-Your-Own-Office” scenario, it is untenable to simply throw more people at a problem to handle the tidal wave of communications. As a result, forward-thinking banks are turning to Artificial Intelligence, Machine Learning, and Natural Language Understanding (NLU) to help augment their internal compliance team’s experts.
Understanding human language is the best source of information and knowledge
The utility of understanding human language versus that of other “signals” has been a matter of debate for some time. In the remote-working environment, there are a handful of sources that account for most data — chats, emails, phone calls, recorded Zoom sessions, and other signals from voice. Human language – what people are saying to whom and when – are now the primary sources for monitoring in a distributed environment. To gather any more data would be tantamount to spying in someone’s home.
While we should all applaud the IT teams for making it possible to continue work from home, we should recognize that, in order to honor the privacy of employees, we must focus on the few legitimate channels where we can listen and understand the real risks to companies, their reputations, their customers, and their employees.
Adapting to the new normal must become normal
WFH communications, distributed workforces, disrupted offshore resources, fast-moving regulatory changes — it’s adapt or die.
Adaptability is in the very DNA of every successful communications analytics system. And since AI naturally evolves, incorporating it into your surveillance process will ensure your institution will always be on top of employee behavior in the context of changing regulatory realities.
Tim Estes is the Founder and CEO of Digital Reasoning, an artificial intelligence firm that partners with the majority of the top 20 largest global investment banks.