As a standard diligence process used by financial firms to assess customers with whom they are conducting business with, KYC is becoming an integral facet of achieving regulatory compliance mandated by different authorities. Besides being a legal requirement, KYC is a good business practice that allows organizations understand business objectives and suitability, as well as reduce risk from suspicious financial activities. To put it briefly, KYC is the process of identifying your customers and verifying their sources of funds. Getting to know the detailed information of customers protects both parties involved in a business transaction and relationship. Additionally, KYC serves an important aspect of financial services that can offer superior service. Moreover, preventing money laundering, and illegitimate money frauds is at the top of the agenda for the corporate world.
What are the trends and challenges you’ve witnessed happening with respect to the KYC and financial sector?
Knowing where your clients are obtaining their income, gauging their financial status, and obtaining their complete financial portfolio and background are aspects of KYC requirements, which is a burdensome process. During a time when a massive group of population accesses financial services, KYC becomes even more cumbersome. For that reason, institutions are looking for innovative solutions and methods for executing KYC, as being entangled in business relationships with clients conducting shady dealings, is a significant risk.
Can you shed some light on strategies that you come up with while you address those challenges?
We are an organization founded by industry professionals, experts in compliances, and forensic investigators. We blend a team of data scientists to solve some of the challenges for relating KYC for our clients. We leverage AI to process and speed read all the articles on the internet, understand if that article is about a subject of interest, understand what the story is about and how relevant it is with KYC. What we try to achieve is to mimic the process that human researchers would do if assigned the same task. The advantage here is that we can do it in much faster, scalable, and consistent way. One of the most important things in KYC is making sure that you have a consistent replica or transparent process, which you put in place when the compliance department comes in to check the process. The use of AI allows a process to be highly scalable and consistent besides reducing the effort to review the hidden frauds. This way the analyst can spend more time processing relevant information. We also use AI to categorize risk events such as money laundering, frauds, criminal activity etc. Through AI we prioritize and triage the set of information that requires primary focus. The result is you are really helping scale a human resource team to channel their best efforts in the right direction.
"Knowing where your clients are obtaining their income, gauging their financial status, and obtaining their complete financial portfolio and background are aspects of KYC requirements and this is a burdensome process as well"
Our organization is built around subject matter experts. So both the SMEs and data scientists have to work together in this process. The compliance experts need to appreciate the value of technology and the technology should be aligned in a way to help the subject matter experts. Quite often data scientists will solve a problem mathematically or algorithmically without really understanding the problem. This will produce results that may be technically correct, but which may not make any sense from a logical point of view. We want to build models that make sense; they make processes much more highly scalable. The real solution is to ask the right questions, formulate the right hypothesis, and then search the information to verify whether those hypotheses hold up.
A major challenge that organizations face is dealing with false positives. While processing massive amounts of data sets the chances of occurrences of false positives are very high. However, on the bright side, technology is capable of getting into that process and captures those false positives. For now, I think organizations need really define what tests and measures, they can execute to make the processes more transparent. There is a lot of noise and big claims out there in the market place. ML has the ability to learn from every time a bad guy is uncovered or is identified as being associated with an organization and that learning loop is going to make investments in technology even more valuable in the future.
Could you talk about your approach to identifying the right partnership providers from the lot?
We want to build the best solutions out there and so we focus on expertise on AI. We like to work with vendors that have excellence in the part of the KYC process. We are agnostic who we work with, we integrate with lots of different sources and different platform providers because we think we are adding a unique value. We like to put out fair amount of spot leadership around best practices in KYC. Lot of regulations are risk based, the expectations are that financial institutions should take reasonable measures to investigate their clients. Technology gives you the ability to undertake research that is far more comprehensive and investigations that give them leverage when it comes to managing the risks effectively
We need to recognize that any new technology that comes out at first looks little bit like a magic. It is hard to explain and understand. Moreover, it does not seem like it has an appropriate place in the whole business setting. You really need to educate yourself around what technology can do in this scenario. When innovations such as I-phones and laptops were introduced, people were hesitant to use it at first. They waited to see what other people were doing until they got ahead of the game. One small piece of advice is to educate oneself around the capabilities of the technology for exploiting most of it.