Emerging technology lawyers Therese Craparo, Anthony Diana and Howard Womersley Smith discuss the rapid advancements in AI in the financial services industry. AI systems have much to offer but most bank compliance departments cannot keep up with the pace of integration. The speakers explain: If financial institutions turn to outside vendors to implement AI systems, they must work to achieve effective risk management that extends out to third-party vendors.  

----more----

Transcript:

Intro: Hello and welcome to Tech Law Talks, a podcast brought to you by Reed Smith's Emerging Technologies Group. In each episode of this podcast, we will discuss cutting edge issues on technology, data, and the law. We will provide practical observations on a wide variety of technology and data topics to give you quick and actionable tips to address the issues you are dealing with every day. 

Therese: Hello, everyone. Welcome to Tech Law Talks and our series on AI. Over the coming months, We'll be exploring the key challenges and opportunities within the rapidly evolving AI landscape. And today we'll be focusing on AI in banking and the specific challenges we're seeing in the financial services industry and how the financial services industry are approaching those types of challenges with AI. My name is Therese Craparo. I am a partner in our Emerging Technologies Group here at Reed Smith, and I will let my colleagues on this podcast introduce themselves. Anthony? 

Anthony: Hey, this is Anthony Diana, partner in the New York office of Reed Smith, also part of the Emerging Technologies Group, and also, for today's podcast, importantly, I'm part of the Bank Tech Group. 

Howard: Hello, everyone. My name is Howard Womersley Smith. I'm a partner in the Emerging Technologies Group at Reed Smith in London. As Anthony says, I'm also part of the Bank Tech Group. So back to you, Therese. 

Therese: All right. So just to start out, what are the current developments or challenges that you all are seeing with AI in the financial services industry? 

Anthony: Well, I'll start. I think a few things. Number one, I think we've seen that the financial services industry is definitely all in on AI, right? I mean, there's definitely a movement in the financial services industry. All the consultants have said this, that this is one of the areas where they expect AI, including gender of AI, to really have an impact. And I think that's one of the things that we're seeing is there's a tremendous amount of pressure from the legal and compliance departments because the businesses are really pushing to be AI forward and really focusing on AI. So one of the challenges is that this is here. It’s now. It's not something you can plan for. I think half of what we're seeing is AI tools are coming out frequently, sometimes not even with the knowledge of legal compliance, sometimes with knowledge of the business, where because it's in the cloud, they just put in an AI feature. So that is one of the challenges that we're dealing with right now, which is catch up. Things are moving really quickly, and then people are trying to catch up to make sure that they're compliant with whatever regs that are out there. Howard? 

Howard: I agree with that. I think that banks are all in with the AI hype cycle, and I certainly think it is a hype cycle. I think that generally the sector is at the same pace, and at the moment we're looking at an uptick of interest and procurement of AI systems into the infrastructure of banks. I think that, you know, from the perspective of, you know, what the development phase is, I think we are just looking at the stage where they are buying in AI. We are beyond the look and see, the sourcing phase, looking at the buying phase and the impingement of AI into those banks. And, you know, what are the challenges there for? Well, challenges are twofold. One, it's from an existential perspective. Banks are looking to increase shareholder value, and they are looking to drive down costs, help, and we've seen that too with dependency technology that banks have had over the past 15 or more years. AI is an advantage of that, and it's an ability for banks to impose more automation within their organizations and less focus on humans and personnel. And we'll talk a bit more about what that involves and the risks, particularly, that could be created from relying solely on technology and not involving humans, which some proponents of AI anticipate. 

Therese: And I think what's interesting, just picking up on what both of you are saying, in terms of how those things come together, including from a regulatory perspective, is that historically the financial industry has used variations of AI in a lot of different ways for trading analysis, for data analysis and the like. Like, so it's not, the concept of AI is not unheard of in the financial services industry, but I do think is interesting to talk about Howard talking about the hype cycle around generative AI. That's what's throwing kind of a wrench in the process, not just for traditional controls around, you know, AI modeling and the like, but also for business use, right? Because, you know, as Howard's saying, the focus is currently is how do we use all of these generative AI tools to improve efficiencies, to save costs, to improve business operations, which is different than the use cases that we've seen in the past. And at the same time, Anthony, as you're saying, it's coming out so quickly and so fast. The development is so fast, relatively speaking. The variety of use cases is coming across so broad in a way that it hasn't than before. And the challenges that we're seeing is that the regulatory landscape, as usual with technology, isn't really keeping up. We've got guidance coming from, you know, various regulators in the U.S. The SEC has issued guidance. FINRA has issued guidance. The CFPB has issued guidance. And all of their focus is a little bit different in terms of their concerns, right? There's concerns about ethical use and the use with consumers and the accuracy and transparency and the like. But there's concerns about disclosure and appropriate due diligence and understanding of the AI that's being used. And then there's concerns about what data it's being used on and the use of AI on highly confidential information like MNPI, like CSI, like consumer data and the like. And none of it is consolidated or clear. And that's in part because the regulators are trying to keep up. And they do tend not to want to issue strict guidance on technology as it's developing, right, because they're still trying to figure out what the appropriate use is. So we have this sort of confluence of brand new use cases, democratization, the ability to, you know, extend the use of AI very broadly to users, and then the speed of development that I think the financial services industry is struggling to keep up with themselves. 

Anthony: Yeah, and I think the regulators have been pretty clear on that point. Again, they're not giving specific guidance, I would say, but they say two of the things that they most are concerned with is like the AI washing, which is, and they've already done some finds where if you tout you're using AI, you know, for trading strategies or whatever, and you're not, that you're going to get dinged. So that's obviously going to be part of whatever financial services due diligence you're going to be doing on a product, like making sure that actually is AI is going to be important, because that's something the regulators care about. And then the other thing, as you said, is it's the sensitive information, whether it's material, non-public information. I expect, like you said, the confidential supervisory information, any AI touching on those things is going to be highly sensitive. And I think, you know, one of the challenges that most financial institutions have is they don't know where all this data is, right? Or they don't have controls around that data. So I think that's, you know, again, that's part of the challenge is as much as they're, you know, every financial institution is going out there saying, we're going to be leveraging AI extensively. And whether they are or not remains to be seen. There is potential regulatory issues with saying that and not actually doing it, which is, I think, somewhat new. And I think just, again, as we sort of talked about this, is are the financial institutions really prepared for this level of change that's going on? And I think that's one of the challenges that we're seeing, is that, in essence, they're not built for this, right? And Howard, you're seeing it on the procurement side a lot as they're starting to purchase this. Therese and I are seeing it on the governance side as they try to implement this, and they're just not ready because of the risks involved to actually fully implement or use some of these technologies. 

Therese: So then what are they doing? What do we see the financial services industry doing to kind of approach the management governance of AI in the current environment? 

Howard: Well, I can answer that from an operational perspective before we go into a government's perspective. From an operational perspective, it's what Anthony was alluding to, which is banks cannot keep up with the pace of innovation. And therefore, they need to look out into the market for technological solutions that advance them over their competitors. And when they're all looking at AI, they're all clambering over each other to look at the best solutions to procure and implement into their organizations. We're seeing a lot of interest from banks at buying