3430: Broadridge AI, NYFIX, and the New Data Strategy for Financial Services

[00:00:04] What does it really mean to future-proof financial data in an age where every transaction, every connection, is a potential vulnerability? Well, financial services leaders are currently under increasing pressure not just to protect sensitive information, but also to modernise their operations in a way that keeps pace with both regulation and innovation.

[00:00:28] And my guest today is George Rosenberger, and he's going to be bringing a front row perspective on how firms can move beyond siloed communication systems and start to prepare for a digital-first, maybe even AI world. And drawing on insights from Broadridge's latest global survey, he's also going to share with us what's working, what isn't,

[00:00:55] and how financial services can reimagine data security and connectivity to ultimately stay resilient. But before I introduce today's guest, I want to thank our sponsors, Careerist. Because here's the truth, you don't need to know how to code or learn how to code to have a career in tech. Let's bust that myth straight away. And Careerist QA Bootcamp is a proven launchpad for career changes.

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[00:02:20] Can you tell everyone listening a little about who you are and what you do? Sure. Thanks for having me. Pleasure to be here. So my name is George Rosenberger. I spent my life in capital markets. It wasn't a career that I thought I would ever be in, but I so happened to land my first job at Morgan Stanley, fell in love with capital markets, with trading.

[00:02:46] And I've had the good fortune to span a lot of different ways throughout capital markets. So I've been on the retail side, the wealth side, the exchange side, the broker-dealer side, and now the software side. So right now, I am the general manager for NYFIX. NYFIX is the premier order routing network in the capital markets industry. It's part of Broadridge's trading and connectivity solutions group.

[00:03:16] So I look after our NYFIX customers, whether it's for order routing, post-trade matching, or some of the new evolving technology that we're building using these AI tools that we're going to talk about today. Looking forward to it. And before we do, one of the things that put you on my radar was when I was reading that Broadridge had released its fifth annual digital transformation and next-gen technology study,

[00:03:43] which ultimately gathered insights from, I think, over 500 technology and operations leaders in financial services. And for anybody listening, hearing about this for the first time, what was the main goal of this research? Sure. I mean, this is the fifth year that we've done it. And the goal is really to raise awareness around digital trends and really to help benchmark where the industry is relative to different initiatives. You know, we hear about a lot of these topics on a daily basis.

[00:04:13] But until we do a deeper dive into a firm's readiness, it's hard to ascertain how broadly the technology or the techniques are really being used. So by going through this study, it really helps the discovery process around that in vetting out who is using what technologies, what's the concerns out in the market? Are people worried about different themes?

[00:04:40] How are they adopting technology to cover those concerns? So that's really the goal of creating this document. And one of the headline findings from that, I think it was 41% of leaders still see data security as a major challenge. So why is securing financial data still proving such a persistent hurdle, even with today's advanced tools and this age of AI that we find ourselves?

[00:05:10] Sure. Well, I mean, data security is paramount to any organization, right? Protecting the data, whether it's proprietary data or client data, is a constant focus for organizations. Then you layer in leveraging third parties to help deliver these new tools, whether it's cloud providers, AI companies, other technology providers.

[00:05:34] That means you need to ensure that their data privacy and protection practices are not only in line with your organizations, but with your clients requirements, right? Because we have language in our client agreements that we're going to safeguard their data. So we need to make sure that any subcontractor or organization that we use has that same language in place and that same protection policy.

[00:06:05] And the study also describes data strategy as almost the center of gravity for digital transformation. So tell me a bit more about what that means in practice and why it's now seen as such a real driver of innovation. It absolutely is. And, you know, we've all heard data is the new oil and all the, and that's around the monetization aspect of it. But data is the, in my mind, is the fuel that makes the car run, right?

[00:06:33] If your data strategy is not well thought out, you're not going to achieve the performance you're expecting from the vehicle, right? And it will break down over time. So you need to have a proper data strategy in place. And there's a lot of different aspects of data strategy, whether it's data procurement, cleansing, data normalization, your hygiene around the data.

[00:06:58] What's your data governance policy, the data warehousing techniques and extracts you're going to do from that data warehouse. So without the proper data strategy, firms will not succeed in driving innovation and change. And I suppose unsurprisingly, respondents ranked cloud, cybersecurity and AI as the top three technologies in their operations.

[00:07:25] But more than a third still don't have cybersecurity built into their core system. So what's stopping firms from closing this gap? Because it's quite a breathtaking start, really. It really is. And, you know, cybersecurity is a constantly evolving topic. And it's always at the forefront of our thoughts. In fact, you know, just in the recent month, I can name four firms that had pretty severe cyber attacks.

[00:07:52] And when you look at the study, it's pretty astounding how long some of the recovery times are for firms if they were to have a cyber breach. And that's because these new cyber attackers that are coming in, whether it be ransomware or something else, can really lock you out of your own systems.

[00:08:13] So, you know, too often I think firms dedicate more resources towards revenue producing projects and don't focus enough on the security aspect of it. That's why it's important for firms to have a dedicated CISO, someone who's in charge of information security, have a clear strategy when it comes to data security and how they're going to protect against cyber attacks.

[00:08:40] And then constantly working with the business, whether it's through committees or some type of governance process to make sure we are well protected. And something else that stood out for me, ironically, is how many business leaders are currently concerned with Gen. AI and its ability to almost lie confidently to you. Or maybe it's disillusioned. I don't know.

[00:09:03] But your research showed a disconnect between how digitally mature firms think they are and the actual reality of their operational execution. Seems kind of ironic there. So how can listeners get a more honest picture of where they stand? Yeah. And I think it comes back to measuring your results, right? A lot of people want to digitize some part of their business. But what's the efficacy of those efforts?

[00:09:32] How much time was saved? Was the shareholder experience improved? What's the true ROI of doing these projects? Because these projects should not be undertaken lightly. There is a lot of operational overhead that goes with them. There's a lot of hitting costs when it comes to cloud compute, storage, the amount of resources it takes to bring a project to bear.

[00:10:00] So all of those things need to be factored in. You have to have a good plan and strategy going in. But I think just making sure that you're constantly doing those checks to see what is the efficacy of what I'm doing and is it returning the results that I expect? And on the topic of AI, generative AI adoption has jumped from 40% to 72% in just a year.

[00:10:27] Yet still, so many firms rightly remain cautious about regulation, security, data quality concerns. And this is a topic I'm seeing more and more. I was at Broadcom's VMware Explorer last week. There was a lot of talk around the private cloud and allowing businesses to leverage AI and keeping their data private and in-house. So how can businesses better capture AI's benefits without exposing themselves to unnecessary risk?

[00:10:56] Because this is a topic that we're hearing more and more at the moment, isn't it? Absolutely. And it's a topic we're going to continue to hear about. So, you know, again, around data privacy and what firms could do to protect themselves. I think, one, using proven AI models, right, constantly training those models. The concept of private clouds is always there, right? We all know that all technology is exploitable.

[00:11:22] So, it's up to us to mitigate the risk wherever possible, but also be able to create and co-innovate with our clients. So, it's up to us talking to our customers, understanding what their tolerance and threshold is for innovation, right? The risk-reward around, is this a public cloud, private cloud solution?

[00:11:46] I think one of the other things that firms need to focus on is having a very strong data governance committee and policy. So, we have a data governance committee that's comprised of legal, risk management, technology, business. You know, we get in the room, we talk about every single new AI initiative. Who's going to use it? What's the expected benefits? How are we going to build it? Where is it going to be housed? How are we protecting it?

[00:12:15] You know, so, I think that is just good practice that firms need to instill everywhere. And then just, lastly, broad-based education within the firms. Knowing and educating associates about, you know, the data that they put in the AI tools. What's appropriate? What's not appropriate? What's the difference between a public and private cloud? When does data get exposed to the masses?

[00:12:43] Just making sure that we have that education, that broad education throughout the organization helps make everybody a little smarter about it. And I think legacy technology and an increasing technical debt come up time and time again. And a blame for being a barrier to everything from personalization to cyber resilience. But when replacing it entirely isn't realistic.

[00:13:09] What are some smart steps to modernize data collection and integration? Is there anything that business leaders could be doing? Because I know so many get dragged down with this legacy tech problem. Absolutely. And this is something that we see time and time again, just internally and even with our partners and clients. Legacy tech is one of the biggest barriers to innovation, right? So the first thing we need to do is look into those legacy platforms.

[00:13:38] And I'm saying, what are the limitations of it? Next, once we've identified the limitations, that's really where then the hard work starts is, what data do we want to extract from that platform? What formats that data in? Do we have the right to use the data? What are the limitations of use? How's the data need to be cleansed or augmented in order to get to the final repository where we're going to store that data?

[00:14:06] What's that target system look like? And how are we going to build tools to leverage that data and extract it so we can create value for our clients, right? So it's about building, identifying those legacy systems and the data that's in it. How do we surgically extract that data out? What's the job to do that?

[00:14:28] And then how do we keep that hygiene going so that if there are changes in the legacy system, those changes get reflected in the new platform? So it's about taking the data out and commingling it with other data so you have a workable data set that you could use for whatever initiative you're planning. And we've seen so many big changes over the last five years.

[00:14:54] And in that five years of running this survey, George, I've got to ask, I mean, you've got a unique long-term view here. Is there a particular trend in digital transformation that has maybe surprised you, either because it's happened faster or maybe even slower than you expected? In five years of running this, any big surprises? Sure. Sure. I mean, for me, the thing that jumps right off the page is just the speed of innovation is absolutely staggering.

[00:15:20] You know, if we looked a couple of years ago, everything was about blockchain. Then we got into cryptocurrency and stable coins, and everybody thought blockchain was going to replace all communication, you know, within financial services. And that hasn't come to fruition, but there are plenty of applications where blockchain has helped. But the one thing that's just constant is the rate of change.

[00:15:49] And, you know, we get AI model one in place. And before you know it, AI model three is ready. And now AI five is ready. And every single time you need to then refactor your models and understand, well, what's appropriate for what I'm trying to accomplish? Should I upgrade to the latest model? Do I stay on the model that I'm on? What's the benefit of doing those upgrades? So it is just constantly evolving.

[00:16:16] And that's the fun part of the business is watching it. And look at just compute power. I mean, compute power alone is unbelievable. What used to take us an entire data center to run something out of can now be done in the cloud and spun up very quickly and with a lot less effort and a lot less resources. So it's just it's a true technology has been a true enabler for the business.

[00:16:45] Yeah, 100 percent with you. And with this incredible speed of technological change and innovation, I think as a result of that, there's a real pressure on every single person listening to this podcast to be in an almost state of continuous learning. So I've got to ask, where or how do you self-educate? How do you keep up to speed with this pace? Well, I have a bit of an advantage.

[00:17:08] We have a Broadridge AI Academy that we built and those guys are masterful in their classes. So I take all the AI classes I can to try to understand all the advancements in that technology. Also, just constantly reading up on new developments. Look, we see it every single day, right? It's in the media. It's in the markets. We see stocks move and we try to understand, well, you know, what's the energy needs? Why is nuclear up so much?

[00:17:38] And it all comes down to compute and understanding who are the big data center providers? And why is there so much pressure to get these data centers more power and, you know, all the different chip providers? I'm just constantly trying to educate myself on the whole ecosystem, the technology ecosystem that's really fueling this AI, you know, resurgence that's coming out now.

[00:18:05] Is there anything particular that excites you around AI or any actionable steps that you'd leave everyone listening for how they can shift away from, I don't know, siloed communication systems and how you at Broadridge are supporting asset managers and broker deals in this digital first AI world that we find ourselves? Yeah, I think everybody's trying to find that magic bullet, right? What's a use case where you can really apply AI and have it be useful?

[00:18:35] You know, what we've been doing to try to help hedge funds and asset managers is we built something called Algo Copilot. And, you know, that's using AI and other techniques to really help traders make a better informed decision on which broker and which strategy to use when executing an order. And we've seen some very good results from early adopters.

[00:19:01] And the goal of that is, again, trying to build better financial lives for our clients. And how can we help them save money, innovate, and do their job more effectively? And for anybody listening, if they want to find out more information about that digital transformation and next-gen tech study, or just find out more information about you and your work, or just dig a little bit deeper on anything we talked about today, where would you like to point them? Sure.

[00:19:28] I mean, Broadridge.com is a great landing spot. You know, there you can learn about the company. Certainly, you could get into the Broadridge Trading Connectivity Solution segment under our GTO division, and you could learn all about a lot of the things that we're doing in AI and in trading space. And I'll add links to everything there.

[00:19:52] And I would urge everyone listening to check out the links that I'll post here as well, so people can find out more information on that and how they can maybe learn a thing or two from this conversation today. And how they can accelerate the modernization and transformation of operations, which has now become a non-negotiable factor, especially when moving past so many different challenges. And that understanding there isn't a one-size-fits-all approach. But just thank you for starting this conversation today.

[00:20:21] I'm really interested in what people listening are taking away. But thank you. Thank you for joining us. Absolutely, Neil. Thank you for your time. So, big question. How ready is your organization to adapt your data strategy to ensure it's fit for a future where cybersecurity, compliance and connectivity are all inseparable?

[00:20:45] I think George has given us a lot to think about today when it comes to shifting away from outdated systems, paying off that technical debt and building trust in financial data flows. But this is just me and George talking. I want to hear your thoughts, your experiences, and your insights. What steps do you think the industry should be taking to truly future-proof its data collection? Please, I implore you.

[00:21:15] Share your perspective. Let's keep this conversation going. TechTalksNetwork.com, TechBlogWriterOutlook.com. Just DM me at Neil C. Hughes on just about every social channel out there, so I'm easy to find. But I've taken up far too much of your time today, so I'm going to walk off into the sunset now, and I will return again tomorrow. Thanks for listening. Bye for now.