(July 20): With the ever-growing number of legislative and regulatory requirements, the Anti-money Laundering (AML) or Know Your Customer (KYC) processes get more and more complex. Astonishingly, Celent reported that AML/KYC analysts spend on average 50–65% of their time on data gathering – low-skilled and boring task. Sounds like huge room for improvement to make employees more satisfied with their day-to-day to-dos. Let’s take a closer look at this.
A day in the life of data collector?
Eighty per cent.
Some banks reported even higher numbers: 80% of analysts’ time dedicated to data collection. That’s roughly 6.4 hours a day. 32 hours a week. 128 hours a month. That’s a lot. Long hours spent on manual tasks that basically boils down to pulling data from different sources. Yet, the analyst is there to deliver a certain result: to analyze data in order to spot any suspicious information, activity or connections that might lead to money laundering.
One might think: get more people on-board and problem solved. Indeed, financial institutions keep on hiring people to get AML/KYC duly done, but there is still a huge hole to be filled in. According to the survey conducted by Thomas Reuters on the impact of global changes in KYC regulation, top pain points among financial institutions are insufficient people resources just next to the amount of regulatory changes.
The invisible gorilla of KYC
Take the famous invisible gorilla test. In a nutshell, there are 2 teams: 3 people wearing black shirts and 3 people wearing white shirts. Now, here comes the task: count the passes between people in white shirts. Simple as that. During the test, a strange thing happens: out of nowhere a gorilla enters the scene and walks it through. The outcome is astonishing: half of the people watching the experiment and counting the passes don’t notice the presence of gorilla. How so? Well, when you do a mentally absorbing task, you may miss other things.
How does it translate to AML/KYC operations? Here is the tricky point: the manual data collection tasks might actually distract AML/KYC analysts from what they are hired for. Kind reminder: that’s in some cases 80% of their time. Repetitive, time-consuming, yet mentally absorbing tasks.
Collect data from multiple sources (internal, external), extract the relevant information, store them, upload them to the system. Oh no! The customer screening is not done yet. Hurry up! And the analyst ends up with a review that is not approved during the quality check process because an important factor related to suspicious activity was missed. Too much time on data gathering, not enough for proper assessment. When you’re too busy with drawing dots, you may run out of time to connect them to see a big picture.
The story unfolds. The KYC process has significant implications on the FI’s business. Again, Thomas Reuters survey on corporate customers found that 89% were not satisfied with the KYC process, and in consequence, 13% had changed their financial institution relationship.
Automate and accelerate
But technology is here to help. The implementation of Robotic Process Automation in the AML/KYC field has the potential to relieve some pain points on multiple levels: the customer and employee satisfaction, the quality of KYC checks, and the overall operational efficiency.
So, how it works in practice: in place of browsing through multiple sources and trying to spot the relevant info, the analyst gets a neatly organized report that combines essential data from internal and external data sources. Plus automatic screenshots from websites for data backup. It means that manual work is reduced to a minimum. RPA technology can also speed up the process of searching and analyzing negative media news based on defined keywords. Automating the most common tasks frees up the analysts’ time, reduces the number of potential errors and in consequence accelerates the AML/KYC process. Not to mention, the positive impact on customer satisfaction, with possible shorter time-to-yes and fewer documents sent back and forth.
The pursuit of customer and employee satisfaction
There is hardly ever one simple solution to a complex problem. The AML/KYC operations are too sensitive to turn them off, optimize them all, get the perfect solutions and simply replace the old ones.
Financial institutions can start the process transformation with small improvements that may turn out to have a giant impact. Letting the RPA technology do the low-skilled, routine tasks of pulling data from different sources and turning them into valuable insights for further customer due diligence process is one of the examples. By taking manual, prone-to-error data collection off the table, financial institutions can focus on developing skills and talents that are meaningful to people and the organization. And the chances to spot the gorilla increase. Employees that are busy with to-dos that help them master their talents and spark their interest stay longer.
Paulina Powązka is a business solutions consultant at Comarch.
