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Bloomberg
Adena Friedman, CEO of Nasdaq and
Nasdaq is primarily a stock exchange platform, but according to Friedman it has also expanded into financial technology offerings and supporting financial institutions in their day-to-day operations. The company acquired Verafin, a provider of anti-financial-crime management software, in 2021.
As part of that extension into digital tools, Friedman is particularly focused on helping banks with the challenge of addressing fraud and financial crimes.
Enhanced security and fraud mitigation was highlighted as a major concern among banks and other financial institutions in
“One thing I’ve noticed is banks have really changed their mindset on this issue from being something that frankly went from competitive to cooperative in terms of collaborating to solve the problem,” Friedman told American Banker.
What follows is a transcript of a conversation between American Banker and Adena Friedman about what she’s seeing in the world of tech infrastructure and how banks are using technology to combat financial crime.
This transcript is edited for length and clarity.-
How do you work with banks today?
We have solutions across anti-financial crime, surveillance, reporting and then trade infrastructure technology that serve our whole banking clientele. We are an anti-financial-crime provider across the smallest community banks all the way up to the largest banks in the world. Our 2,600 U.S. clients are really using our anti-financial-crime solutions, and then the top several hundred banks use our trade infrastructure, regulatory reporting and surveillance tools. So we really are a complete solution provider to midsize and large banks and an anti-financial-crime provider across everyone.
You talk to bank CEOs a lot. What are they most concerned about right now?
There’s been one persistent concern, which has been anti-financial-crime management and the challenges they have — the ever-changing, evolving nature of that role that they play on the front lines of helping to keep the financial network safe and secure. The second concern has been managing the myriad of data in order to meet all of their regulatory compliance needs.
That’s really where we’ve decided to focus our time, attention, resources and expertise because they definitely saw us as someone who could help them solve those problems. They saw us as a natural extension to surveillance, which was a core capability we’ve had for many, many years. In terms of regulatory reporting, we’re highly regulated ourselves. We understand the need to have the right relations to the regulators. We understand the regulations inherently. Now being a technology provider allows us to be that partner to them.
When we talk to bankers, we hear how concerned they are about financial crime and fraud and they almost feel helpless in some ways. What should they be doing that they’re not doing now?
First of all, let’s acknowledge how fast the problem is. So $3 trillion is going through the system. Half a trillion dollars is lost to fraud globally on an annual basis. That’s a huge problem. Governments across the world have put banks on the front lines of trying to stop that. Now there is a collective action opportunity, and there are certain cases where you see actually good collaboration between the public and private sector.
One of the biggest challenges with the problem is that it changes every day. Criminals do not maintain the same behavior if something stops working for them because we’ve found a way to close that door. They’ll just look for the next open door. So it’s kind of a forever moving and ever-evolving challenge.
What’s interesting now in the United States is as we’ve been doing a better job, I think, of protecting the digital rails, they’re going back to check fraud.
What we’ve done is focused on our check fraud solution. We’re rolling out a new version of it that allows us to use the consortia data lake more effectively in identifying the payor or payee. We’re looking at the check, digitally reading it, interpreting it and actually using AI against it. It’s super interesting to try to figure out how you can make it so the banks are more effective in stopping that.
Then there’s also the physical branch level. A friend of a friend of mine was subject to a scam, and she was insistent that she had to pay a lot of money to someone who was ultimately a scammer. I know this person, and she could not afford to have that happen to her. She walked into the branch and the branch manager just didn’t let it happen. The teller alerted the branch manager, and they really had to talk her off the ledge, but they did. That’s why it is also training: physical, emotional and technological, all working together.
The one thing we’ve been really focusing regulators on, though, is allowing banks to use AI more effectively here. There are lots of reasons to have good guardrails on the use of AI across every industry, including the financial industry. But there are also certain opportunities here where we’re playing defense and you’re against, frankly, an enemy actor who is using the best capabilities possible. They have no laws or rules that they follow, so they’re going to be using the technology to the best of its ability. If the banks are not able to use the technology to the best of their ability, you’re basically tying a hand behind their back. So we’re working with regulators and legislators to look at AI on a use-case basis as opposed to a blanket basis from a regulatory perspective.
AI is obviously a huge buzzword right now, but it’s also a very serious trend inside banks. What are the most interesting ways that you see bankers using AI?
There’s offense, defense and efficiency. In customer care, it’s a great way to be more consistent with your answers in every way, both in terms of tone and in giving the right answer. You could train your customer support people much faster and make them more productive more quickly, which I think is very important. There’s obviously the offense from a trading and investing perspective, using AI to find alpha.
I think that the regulators are very focused on making sure that it’s being used for the right purpose from a defense perspective. We also need to bring more AI capabilities in protecting the markets too, and we do use AI in that way and are very focused on that. On defense it’s using a Bayesiana model and more algorithmic AI to root out the alerts. But then you can use generative AI to go out and research potential entities, bring back everything you’ve learned about them, write the report and just have it. Instead of having someone do that all manually, it’s curated for them to look at, review, approve and send. You’re going to save a ton of time just by automating all of that processing, and that’s going to make the banks even more efficient.
What is the coolest thing you’ve seen recently in financial services tech, not at Nasdaq?
I get to go out and see how technology is being used in really unique ways. I would say there’s some physical things, like robotics, that are being brought into every industry including finance. I find robotics really interesting because robotics is not in our space. We’re a digital company and we don’t have manufacturing, but I’ve seen robotics in terms of bringing more capabilities into thinking about managing cash.
There are incredible capabilities that are being brought into the markets in terms of really thinking about managing risk in the markets very effectively using algorithmic AI while also finding alpha. More and more of our broker dealer clients are using AI in material ways to manage their lives in the capital markets, which allows them to deploy liquidity a lot more efficiently and manage risk more effectively. That’s the name of the game in terms of being effective in generating alpha in markets.
We’re using AI a lot to also manage our technology, even with our strike management in the options world. Little things like that can make the whole system more efficient, and I think everyone’s looking for those ways.
Those are the two things I’ve seen: robotics are cool and developing very quickly, and algorithmic AI continues, in my opinion, to be a really good use case.
