Consilienz, a software company using data analysis and visualization to combat financial crime, and cofounder Elisar Nurmagambetov were featured in the 2021 Forbes Next 1000. In this interview, Mr. Nurmagambetov speaks with Stop Modern Day Slavery to discuss the anti-trafficking applications of his company’s platform.
Let’s jump right in. Could you tell me a bit about yourself and what inspired you and your cofounder to start Consilienz?
Well, I’ve been in the financial services risk management sector for a while. There are two risks for any financial institution when it comes to financial crime: the risk of real institutional crime and the risk of getting fined, so a regulatory risk. And obviously, FIs are focused on getting fined and keeping up with regulatory requirements. But that doesn’t necessarily solve all the issues with financial crime. And as it is, money laundering today is three times more than it was thirty years ago. And criminal syndicates, organizations, human traffickers – they’re very creative. They’re very well-funded. They run like a very real business. They have their own accounting departments, business development departments, HR departments, technology departments, innovation departments, and so on. They’re very agile, and it’s the lack of ability to keep up with that creativity that creates a lot of those risks. Consilienz was started to help bridge that gap.
So, for example, the way criminal organizations would act is they’d set up a lot of shell corporations, they’d have a lot of fake people, a lot of synthetic identities. And fraud, and money laundering, and drug trafficking, and human trafficking are all very interconnected a lot of times. Basically, they’re really not sending any transactions or doing a lot of activity from a person who is on a watchlist or what looks like a high-risk company. Typically, traffickers would set up a structure where over ninety-eight percent of financial crime just goes undetected.
What we do is we look at all the data at the same time from a multitude of sources. It could be INTERPOL or FBI watchlists, it could be corporate records, it could be negative news and adverse media. It could be information sourced from the dark web or from escort advertisement services. And when you look at all of that together, you start seeing the same phone numbers, and the same addresses, and the same individuals appearing over and over in a lot of different lines of ‘business’ that are criminal. Then you can piece it all together and have the entire network of those non-obvious relationships of how a massage parlor could be a front for a human trafficking operation, and then that could also be owned by the same person who owns a hospital, but does not have a medical license anymore, has a revoked license for patient abuse, and that same person shares a phone number with somebody who’s at a very unrelated business, and at the same place of unrelated business, you have a cryptocurrency set up. For example, you have a John Smith. And let’s say somebody identified John Smith in adverse media for human trafficking. Now, how do you know that particular John Smith is the same John Smith who is your vendor, or the same John Smith that is a brother of Mike Smith, who has been arrested for human trafficking before and is on a watchlist?
It’s very hard sometimes to piece it all together, and that’s essentially what our software does.
That’s fascinating. So, say a customer comes to your platform — how do they use it to find this information?
We typically install it in a private cloud or on-premises. The customer could be a corporation, or it could be a bank, or it could be a federal government agency. We bring a lot of combined information from the open source and a lot of proprietary information from primary sources. There are companies that do adverse media screening and watchlists and they combine those datasets. So, we bring them all together, and then we also match it to whatever information, whatever data, is at the customer site. So, if it’s a bank, it could be the bank’s customers. If it’s a corporation, it could be corporate vendors or the supply chain, because when it comes to human trafficking, you’re not only thinking sex trafficking — it could also be forced labor. As a corporation, you’re looking to see if you’re sourcing any parts or services from somebody who’s somehow involved in human trafficking or who buys other sources down at the supply chain level from a region that has a risk of child labor or forced labor.
Or, let’s say you’re an investor, and you’re funding small businesses, and you see a chain of massage parlors, but then you also see the same addresses and phone numbers, and sometimes people, appear in the escort advertisement services. That is a human trafficking risk. And sometimes, you’ll also see the same person who could be a former convict or a fugitive. We’ve had cases of, say, PPP loan fraud, where somebody who is in prison for human trafficking is getting federal paychecks (federal loans) to pay salaries of their employees they have abused. There is a whole multitude of cases like that.
And how do Consilienz and its anti-trafficking applications contrast with other efforts to identify the financial activities of traffickers through platforms like Traffik Analysis Hub and Giant Oak?
We’re all on the same side, to be honest. And with Giant Oak, we’re part of the same organization called the Anti-Human Trafficking Intelligence Initiative. That organization serves as a hub and works with a number of other organizations out there from advocacy, to technology, to methodology, to experience.
The pandemic and the changes it might have made with the financial institutions – has that impacted how customers use your platform or the sort of uses you’ve seen with your platform?
That’s a great question. So, on one side, the pandemic caused a lot of new risks for financial institutions or organizations, or in other processes overall because so many things have changed. And you have to adjust to those risks, and in a sense, we [Consilienz] do help adjust to that.
Because we don’t do the detection ourselves, we would collect information, we would build out relationship networks, but on top of that banks typically overlay their own – it could be transaction monitoring systems, it could be risk detection systems. But if you feed incomplete information into them, obviously they will not detect as well. But if you feed a comprehensive set of data sets, of resolved entity networks, then it works much better.
The pandemic changed a lot of processes, and you have to think of a criminal enterprise as a business. And when something happens, they change that business. There was a spike in human trafficking and the way human traffickers operate. If you think about it, there is a difference between different types of sexual exploitation. It could be Asian massage parlors, which have one way of engaging victims and monetizing that. Then you have Eastern Europeans – they’re doing it completely differently. So, there are scenarios at the bank level, or at the government level, at the investigation level, where you would say, hey, if you’ve got a lot of transactions for expensive transportation in the middle of the week and then you have a lot of transactions at luxury hotels, then it could be a potential human trafficking risk. However, what our software would do is bring context. And that context becomes much more relevant when things change very quickly. So, that context would say this might be a businessperson that is traveling, and it might not be a risk. Or the same people that you’re looking at on the transaction side are also advertising on escort services. So that would bring a lot of context and help make a much faster and much more comprehensive decision on the investigation side. The pandemic itself changed a lot of processes and a lot of ways that traffickers would operate, and adjusting to that takes time. When you have the context, you adjust to that much quicker. So, in a sense, for our platform, the pandemic created more demand.
What potential does software like Consilienz have to combat trafficking going forward? What sort of future do you see in the field?
I really believe that the real way to effectively combat human trafficking and to do it up-scale is the economic factor. It’s the financial sector, it’s the private sector because we see human trafficking as a huge problem. We empathize with victims, and it’s important for us to do so. But human traffickers don’t think that way. For them, it’s product. And they have to move product, and in order to move product, they have to advertise it. And if there’s software like ours, incorporated with a lot of partners that collect the context information as well, and financial institutions, and corporations who are looking at it, then it makes it much harder for human traffickers to advertise. Because the moment they go and advertise, that’s a high risk of being caught. So, that becomes more expensive for them, and if it becomes more expensive for them, they start losing business interest. And I believe that’s really one of the most scalable ways to combat human trafficking.
Therese Majeski is a recent graduate from Cornell College, Iowa with a B.A. in psychology and a minor in applied statistics. She is an aspiring forensic linguist taking a gap year before grad school to write and volunteer. Whether through academics or journalism, Therese is passionate about using the power of language to achieve a more just world and effect positive change.
