Name: Future of Finance 2024: Navigating Risks and Rewards of Latest Technologies
Uploaded: 2024-05-16
Duration: 17 min 38 s
Description: Tal Cohen, President, Nasdaq, Inc. Katherine Wetmur, Managing Director and Chief Information Officer, Cyber, Data, Risk and Resilience, Morgan Stanley Moderator: Luisa Beltran, FORTUNE

Tal Cohen, President, Nasdaq, Inc. Katherine Wetmur, Managing Director and Chief Information Officer, Cyber, Data, Risk and Resilience, Morgan Stanley Moderator: Luisa Beltran, FORTUNE

Future of Finance 2024: Navigating Risks and Rewards of Latest Technologies

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Hi, everybody. Thanks for coming today. So we're just gonna dive right in. Um So in the past few years, we've seen some major changes to market dynamics. There's rising regulatory scrutiny and clients have changed their expectations. Ty can you speak about the regulatory changes involving T plus one, basil three and how it's impacting the capital markets in the banking sector? But first, what is T plus one, T plus one is T plus one is just one day faster than T plus two, but it's a settlement cycle for equities and other asset classes. So when you execute a security, you, you need to settle that security settle and clear that security today, it's T plus two, 48 hours after that transaction. And that's being brought in to T plus 24 hours. And that requires the industry to invest in automation tools and processes that allow them to ensure that they're not taking undue risk as a result of bringing their settlement cycle. So, yeah, so I'll talk a little bit about it. Yeah, and, and so, and that was the tip of the iceberg when you mentioned T plus one and baseball three end game. There's just a number of regulations and a number of changes and they're regional, they're global and they're going downstream in terms of the impact that it's having. And the three themes that we hear from customers are really, really consistent. It's one they want to streamline and comply and they want to streamline. Comply. In the following way. They want a better man explosion, regulatory costs and obligations while simultaneously complying with enhanced liquidity and capital requirements, really not easy to do. And that's a big piece of work. But once they've done that, they're talking to us about simplifying and standardizing. That's kind of the second theme I'm hearing from customers where these organizations become very complex, operationally, complex and there's lots of silos and they want to break down those silos that introduce operational and financial risk. And then once they've done that, we're talking to clients about modernizing and digitizing and this is clients' ability to keep up with forces of change, forces of disruption, whether that's competitive or emerging technology. So a number of customers are looking for leaders in this space, but just as importantly as somebody who understands the challenges they face. Each of those challenges requires a real deep understanding of how those institutions work. Katherine, can you talk about modernization efforts? Yes, I mean, I tell spoke quite a bit about it, right? Is all of the all the items you mentioned we're having to implement, right? So T plus one balls of end game any of these things and there's a significant amount of work. So the focus that we've been having in our technology area at Morgan Stanley is saying, whenever we have an opportunity, um thinking about process changes, so process optimization or business processes or regulatory requirements is how can we also think about modernizing our technology stack? You have an opportunity to do some of these things together when you have big projects that are going to require a lot of work, it's an opportunity to do that and the more that we modernize our applications and more that we modernize our technology, we become much more nimble. So back to some of the comments you made earlier, how do you automate more? How do you do more straight through processing? How do we make sure that we're using modern tech to do it? How can we make changes really quickly? How can we be more api driven all of that has been a big focus of what we're doing in our modernization play? How can we make sure we can scale? Should we use cloud? Can we use bursting all of that is needed as we think about all of these big regulatory projects? Great. So everyone's talking about gen A I today and we're gonna continue with it. Um Morgan Stanley was the first mover with its partnership with Open A I. Katherine. Can you tell us about the challenges this created? Sure so I'll talk a little bit about it. I mean, it was, it was very exciting for us to be, um, a first mover in one of the, the financial industry, um, lead in working with Open A I. Um, and what we found with it is we learned a significant amount from Open A I that came with a lot of expertise and they learned stuff from us of how to deal with a financial regulated institution. Um So the first thing we learned is you got to make sure you're picking the right use case. There's so many generative A I use cases people have and you got to make sure you're using one that you can implement, you can implement in the time you want. It has an impact on your businesses and you can learn from and you minimize the risk with. So what did originally working with? Open A I is, we said, let's look at something in our advisors area. Our advisor could do work with our clients better if they can have more information at their fingertips and be able to answer their questions faster. So we said, ok, so let's look at how we can create a chat bot. We call it A I at Morgan Stanley assistant. We didn't name it a name, you know, like a lady's name or a man's name. We said it's an A I, it's not a person and that A I can assist our advisor by them asking questions to that. A and the key thing that we did, which was very important as we looked at everything. We didn't want any data loss. We didn't want any hallucinations. We didn't want these things. So we curated our own data. It's only going against the data that we have in Morgan Stanley. We also made sure we put all the controls around it. It meant when we were first starting out a lot of conversation with people in the privacy side, people in our legal people, in our cyberspace, people in our information security area and making sure we were choosing the right use case for that. And, um, you know, we're going to continue to do more and more, but I think it's just the beginning is that you have to make sure you're building some of these guardrails to start with and a lot of these products earlier on didn't have those guard rails in them. You're starting to see a lot more of that happen and we've had to build some of those ourselves. So when did you introduce it? Um, we introduced it about a year ago, we spent about six months building it and a key thing with it is we constantly get feedback from our advisors. So the advisors enjoy using it, but we did some things like this, gives thumbs up, thumbs down. Did it give you the answer you're wanting? Did it not? And that you're able to read to on that very quickly and how many advisers use it now? Um, thousands fast. And so is that a thumbs up or is it a thumbs up? It's definitely a thumbs up and it makes them quicker, makes them quicker and able to answer questions without having to go through reams of paper and look things up. Tal You guys also just announced the launch of your gen a feature for market surveillance technology. How's it going? Yeah, very exciting. So yesterday we announced it really a quarter our mission. So when we think about A I, whether it's Chen A I or algorithmic A I, the first question we ask is, is these are these use cases, are they going to deliver our mission in a bigger way in a better way? And one of the missions we have in NASDAQ is to ensure the integrity of the market and ensure investor confidence. And so we have a surveillance solution that Morgan Stanley and others use exchanges use and regulators use. And what we've done is we have announced that we're going to have a gen a co pilot investigation, co pilot and the way that it works, it is really cool. It allows an analyst to truncate the investigation time and increases the efficacy of each investigation. The way it works is the surveillance tool will generate alert of a potential market abuse or market manipulation really serious issue. Now that analyst now needs to undertake a number of manual activities once that alert is generated and it could take hours. In fact, it takes 4 to 6 hours every time an analyst needs to look at something. But what if we can have Genai? I provide the context and a summary of all that extensive information and provide that to the analyst shaving off about two hours of 33% of the investigation time. What that allows is the analyst now focuses on higher value, makes a better assessment of the situation and the client can scale that across their operations. So it has lots of benefits in terms of productivity. It lives up to our ambitions to make sure that we're protecting the market. And really importantly is the guard wells that we do. And Catherine mentioned this. So we've been, we've not only been putting this into POC, we're just out of PC, we're going to use it for our own markets. And that's really important for our clients to understand if we're using it for our own markets. That's a proof point that I think is, is really powerful. And so we'll look at use cases like this is one of many, we probably have 15 to 20 Po CS that we're running, but they have to be specific use cases with an understanding of how we're going to deliver value to our clients and we want to do it safely and responsibly. So, is it a thumbs up? It's a thumbs up. I mean, we haven't launched it yet, but the POC uh like I said, it showed a reduction of 33% in the investigation time. And think about what that means in today's dynamic markets where market manipulation, the way it was done in 1999 is not the way it's being done today with the advancements of technology. So putting intelligent tools in the hands of our clients so that they can better surveil the markets and we can help them and be their partner. That's terrific. That's, that's meeting our mission every day, all day long. Interesting. So, but with all the focus on A I, people are forgetting about cyberattacks, Kathy. Can you talk about that? What do you, what are big banks doing? I don't think we ever forget about cyber attacks but, but I was wondering how I do wanna thank Hal because I'm very excited that it's gonna take us half the time to deal with any of our alerts going forward. So that's a very important thing for us. And um it will be worth then going through the paperwork of all the model control as we bring the new products in. Um but on the on the cyber side, um and all the everybody right, you, you can't open a paper any day and not see some kind of cyber event, hearing something about fishing, something happened to individuals, something happening to companies. Um And we don't look at ever celebrating anybody having a bad day. Right. You know, nobody, we don't want to see that anywhere. So, we work very collectively across all the banks. All of our C OS, um, that's our chief information, security officers. We know each other at all the different, um, um, industries across all of our, um, banks. We work very closely together. We all sit on very, um, types of industry groups, whether it's F SI A or the ARC, which is a resiliency group. And um we're doing a lot of things, right? So you talked about um A I, you know, the amount of data that every single bank has to collect on any day to understand malwares, to understand any anomalies, to look at detections, to understand business, email compromise. There's a tremendous amount that all the banks do for that. We have to also protect our perimeter. Think about all the amount of emails we get the amount of file uploads, the amount of things that people are pulling off the internet, we have to protect our perimeter to make sure things aren't coming in through those routes and everybody's having to do those same things. And it's really a big data challenge, right? The amount of data that you're looking at to find these anomalistic behaviors is huge. So it's a huge technology challenge and we're all working together, fighting the good game in this space has A I increased. The cyber attacks are you seeing different sort of cyber attacks. I say, I say one thing you see in, you know, a little bit, you talked about how the world is changing. Also in, in the AM L space. You see that in any kind of the fraud areas, the cyber areas, you know, think about the phishing type emails you used to get, you'd look at them and go well, this wasn't written by somebody who really knows me. This wasn't a sophisticated actor. Now you anything very targeted, you know, people will look up, you know what kind of role somebody has, the type of job, something will be targeted at you. And it looks very much like something you should have gotten, right? A mail that makes sense and you click on it and now you have some malware exposed to you. So we're seeing more sophistication because the A I tools are now writing some of these things for them, right? So, you know, there's a positive on the A I tools and then that's maybe the negative of it. Same things with fake web sides. It's very simple to create things that used to take more sophistication to do before that is allowing it to be much easier for people to do. Also with just being able to automate, you can just automate attacks, anybody trying to do an attack, it doesn't have to be successful 100% of the time if they can try a million times one in a million is good. Right. So the new technology you see are just allowing things to be at a much higher pace and a much higher speed and that's what we're having to defend against. Yeah, I just add on, on what Catherine said. She made a number of good points. The way to think about A I and in the way that we think about it in the product for our red tech products is we're going to help our clients get to the right answer faster. And, and regulators expect us to surveil our markets, for example, or monitor our customers activity in real time. They also expect us to make connections between different patterns. They expect us to understand what's going on one side of the market and the other side of the market. And so A I could be really, really effective in allowing us to be much better at detecting those trends in real time and be that extra layer of defense because we know that A I can be weaponized, we understand that. But on the other side of that, we need to use it to make sure that we're making or the human element of it better. So A I is effectively like the best teammate, a surveillance analyst can have and that's how we think about it. Great. So with all these technologies that we're having all these emerging technologies and all the new capabilities, what do you think is it a blessing or a curse? I'll take that one. So to make it a blessing and not a curse, you need to do the following. You can never embrace emerging technology unless you've made the upfront investment. So for us, we're talking about A I for us to be able to embrace A I at NASDAQ or Morgan Stanley. You need to have invested in a couple of things. One is managing your data, you've got to know your data. You heard that right? Two, you've got to invest in the cloud, understand the cloud and the potential three is you've got to have a really mature posture on the infosec side. And fourth, you need to have great governance. You need to understand that governance is a lubricant for A I and these technologies. And then the last one and very importantly, you have to upskill your workforce, you have to bring your workforce with you when you're, when you're taking these emerging technologies into the market because your clients expect you to be a user and knowledgeable about these technologies. So that that requires a cultural change potentially. So it's investments, it's a cultural change and it's being committed to being a leader in a particular space. If that's your ethos, that's our ethos at NASDAQ, we need to be committed. And what that means is we need to start using it ourselves. We need to start getting uncomfortably comfortable with the technology within NASDAQ for us to then have a conversation with our clients. Have you increased investment, financial wise? Like, what's that? Have you increased your investment? We, well, it started for us in 2016 and we started with a small team. That team is absolutely increased. But the roi you know, the, the win rate, you have a lot of pcs, some of them are not going to work. So the win rate is one aspect of it. But if you can get it in production and you have the right use case, the RO I on this can be extremely high, extremely high. So that's the way to think about it because to Catherine's point, the automation and the drive and the productivity gains and the efficiency gains, you can recognize well pay for that investment up front when we do. And so we have a centralized team as well. So we're also making sure that anything is ubiquitous across the firm. You don't want to develop the same capability 34 or five times which a lot of firms I think are struggling with right now. So we've centralized it which allows us to make the investment and allows us to scale the investment. Katherine blessing or curse. Yeah, I, I say it's a blessing um for some of the same reasons that how said it's, you know, we've done many of the same things. We, we've named a, you know, a chief officer in A I, we've also um put a centralized team together, we have a centralized governance group. And I think all of that is actually very important because you could start building many different things and not using some of the same technology. Um I just imagine, you know, you had an assistant every day instead of you going, looking at how many times you go look up something online or go look over here and you're trying to bring everything together or you're trying to read a document, you wanna have somebody just quickly tell you, you know, paraphrase exactly what was there? There will be huge game changers, right? Huge time saves for everybody. Same things. You're in meetings, if that meeting minutes could be taken for you and then you can disseminate it out to people that weren't there. You take notes, all of these types of things are gonna become really helpful to folks to make them more productive. And I think that's the thing that we're gonna gain out of this and those are the, some of the easier type use cases if you think about it's really the productivity that everybody's gonna have. And I think that's a blessing. Do you use a I personally do I use it? Yes, I use the chat GP T and stuff like that. What do you have? I've asked it many different things. Sometimes it doesn't come back with the right answers though. I think that's the key back to your data. Right. Is that oftentimes and this is what we, you know, very important I said earlier is that we're curating our own data. You have to be very careful of the data that you have and you got to make sure your data is good. Otherwise it can answering the question in an old way is an example like it's no longer relevant because it's not current. So I think those are also going to bring out new roles in organizations as data curation type roles. Yeah, just to build on what Catherine said, we say this all the time. And as a I wasn't designed to be right. It was designed to give you an answer. And now it's your job to understand if that's the right answer and understand how you want to train it if it's not the right answer and what data it needs to get to the right answer. So a simple question like what's the price of an apple? You need to understand context to get that right. You know, how far do I live from the supermarket? Where am I am I buying from wholesaler? All these simple things, this reasoning that needs to happen. So you just need to understand the limitation of the tool and how you invest in the tool and what you're going to get out of it because it's not just a source of truth and we've run out of time. So I thank everybody for coming today and weren't my panelists. Wonderful. Yeah. And our moderator.