How do you future‑proof financial data in a world moving at digital speed? In this episode of Tech Talks Daily, George Rosenberger, SVP NYFIX, sits down with Neil Hughes to unpack the biggest challenges and opportunities across capital markets—from data security and legacy systems to the surge of AI adoption.

George shares candid insights, real-world strategies, and how Broadridge is using tools to drive responsible innovation. If you’re curious about building resilience and smarter data strategies in financial services, this is a conversation you won’t want to miss.

Speaker 1: 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 modernize their operations in a way that keeps pace with both regulation and innovation. And my guest today is George Rosenberger, head of NY Fix at Broadridge Trading and Connectivity Solutions. 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 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, and how financial services can reimagine data security and connectivity to ultimately stay resilient. But enough for me. Let me introduce you to George right now. So a massive thank you for joining me on the show today. Yeah. Can you tell everyone listening a little about who you are and what you do?

Speaker 2: Sure. Thanks for having me. Pleasure to be here. So my name is George Rosenberger. I've 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, and I've had a good fortune to span a lot of different ways throughout capital markets. 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 NIFEX. NIFEX is the premier order routing network in the capital markets industry. It's part of Broadridge's Trading and Connectivity Solutions group. So I look after our NIFEX 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 and we're going to talk about today.

Speaker 1: 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 5th annual Digital Transformation and Next Gen. Technology study, 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?

Speaker 2: 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, 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 and vetting out who is using what technologies. What's the concerns out in the market? Are people worried about different themes? How are they adopting technology to cover those concerns? So that's really the goal of creating this document.

Speaker 1: 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?

Speaker 2: 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 organisations. Then you layer in leveraging third parties to help deliver these new tools, whether it's cloud providers, AI companies, other technology providers. That means you need to ensure that their data privacy and protection practices are not only in line with your organization's but with your clients requirements. Right. Because we have language and 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.

Speaker 1: And the study also describes data strategy as almost at the centre of gravity for digital transformation. So tell me a little bit more about what that means in practice and why it's now seen as such a real driver of innovation.

Speaker 2: It absolutely is. And and you know, we've all heard data's the new oil and all the and that's around the monetization aspect of it. But data's the, in my mind is the fuel that makes the car run, right? 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, 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.

Speaker 1: And it also seems that firms with strong data strategies are better positioned to take advantage of AI tools. What are you seeing in that regard?

Speaker 2: Absolutely. Firms with strong data foundations can utilize AI in a much more productive way. If your data is unstructured or incomplete, the outputs from any generative AI model are going to be less reliable. We’ve seen firms investing heavily in cleaning, labeling, and organizing their data so that when they bring AI into their workflow—whether that’s predictive analytics, chat interfaces, or automation—they’re getting meaningful insights rather than noise. The study showed that leading firms are already using AI not only to automate processes, but to enhance decision-making in risk management, compliance, and trading operations.

Speaker 1: That’s really interesting. There’s often the assumption that AI is replacing human decision-making, but what you’re describing sounds more like augmentation—AI helping humans make better, faster choices.

Speaker 2: Exactly. It’s not about replacing people; it’s about elevating their capabilities. Take the example of trade surveillance. AI can monitor thousands of transactions in real time and flag anomalies that would take humans hours or days to detect. The final decision still rests with an experienced compliance professional, but now they’re focusing on the 5 percent of cases that matter instead of wading through all the noise. It’s a partnership between people and technology that drives efficiency and improves outcomes.

Speaker 1: How do you see regulation evolving in this environment? Because AI introduces a new set of risks—data bias, explainability, and accountability, for instance. Are firms ready for that?

Speaker 2: Regulation is definitely catching up, and firms are proactively engaging with regulators to make sure they understand how AI models are being used. Transparency and governance are the big themes here. For instance, when we deploy AI tools at Broadridge, we always ensure there’s a human-in-the-loop process, that data is auditable, and that outcomes can be explained. The goal is to use AI responsibly—to augment workflows without compromising compliance or data integrity. Regulators appreciate that level of openness, and it ultimately builds trust in the technology.

Speaker 1: So if we zoom out for a moment, George, what’s your advice for firms that are still in the early stages of digital transformation and maybe feel overwhelmed by how fast the technology is moving?

Speaker 2: I’d say start small and be intentional. Pick one process or workflow where automation or data insights can make a measurable difference. Test it, measure the results, and build from there. Don’t try to boil the ocean. Also, make sure your teams are aligned—operations, technology, risk, and compliance all need to be part of the conversation. The firms that succeed are the ones that think holistically and treat transformation as a continuous journey, not a one-off project.

Speaker 1: That’s solid advice. Before we wrap up this segment, is there one key takeaway from this year’s Broadridge study that you think financial leaders should really pay attention to?

Speaker 2: Yes—the speed of adoption. Compared to just two years ago, the number of firms actively using AI and advanced data analytics has nearly doubled. That tells us the industry isn’t just talking about transformation anymore; it’s executing. The message is clear: stay proactive or risk falling behind. Digital resilience and adaptability are now the new competitive edge in financial services.

Speaker 1: That’s such a good point — being proactive rather than reactive. You mentioned earlier about connectivity and communication systems still being somewhat siloed in many organizations. How do firms start breaking those silos down in a practical way?

Speaker 2: It starts with having a unified data and connectivity strategy. Many firms have grown through acquisitions or legacy systems, and their platforms don’t always talk to each other. At Broadridge, we focus on helping clients build interoperable systems — whether that’s through APIs, standardized data formats, or middleware that enables seamless flow of information across business units. Once data moves freely and securely, you unlock efficiencies in trade processing, client onboarding, compliance reporting — essentially every area of the business. It’s a journey, but one that yields compounding returns.

Speaker 1: And when you combine that with AI, you’re effectively building intelligence into those connections, right?

Speaker 2: Exactly. Once systems are connected and data is standardized, AI can start to find patterns across silos. For example, if your post-trade data is connected with front-office analytics, AI can detect potential mismatches or inefficiencies before they become costly errors. This is where the next frontier lies — intelligent connectivity. It’s about integrating human expertise, machine intelligence, and connected infrastructure into a single ecosystem that continuously improves itself.

Speaker 1: That’s fascinating. I imagine culture plays a big role in that transformation as well — getting teams comfortable with new tools, new workflows, and even new ways of thinking.

Speaker 2: Absolutely. Technology alone isn’t enough. You need people who are open to learning and who see technology as an enabler rather than a threat. At Broadridge, we spend a lot of time on change management — training, workshops, and creating spaces for collaboration. When teams see that automation or AI isn’t replacing them but helping them focus on higher-value work, adoption accelerates naturally. Culture is the bridge between innovation and execution.

Speaker 1: That’s a great way to put it. Before we close, I’d love to hear your perspective on what’s next. What’s the next big shift you see coming in financial technology or connectivity over the next few years?

Speaker 2: I think we’ll see an acceleration of real-time, data-driven decision-making across the industry. Things like tokenized assets, embedded AI in trading systems, and more open, API-based networks will become the norm. Firms will also focus heavily on resilience — not just cyber resilience, but operational and data resilience. In a volatile world, being able to adapt instantly is a competitive advantage. The technology stack of the future will be flexible, intelligent, and interoperable by design.

Speaker 1: George, that’s an excellent note to end on. Thank you so much for sharing these insights — it’s been a really engaging and enlightening conversation.

Speaker 2: Thank you for having me. It’s been a pleasure discussing these topics, and I hope the listeners found it useful.

Speaker 1: And before we officially wrap up, where can listeners go if they want to read more about the Broadridge Global Survey or learn about some of the solutions you mentioned today?

Speaker 2: The best place is our website — broadridge.com. The full Global Survey report is available there, along with detailed insights, articles, and case studies. We also have dedicated resources around AI, connectivity, and digital transformation within financial services. It’s a great way to dive deeper and see how the industry is evolving.

Speaker 1: Excellent. We’ll make sure to include that link in the show notes as well. George, thank you again for joining me today and for shedding light on what it truly means to future-proof financial data and connectivity in this fast-changing environment.

Speaker 2: Thanks again for having me — it’s been a great discussion.

Speaker 1: And to everyone listening, thank you for tuning in. Be sure to check out our other episodes where we continue exploring innovation and technology shaping the financial world. Until next time, stay connected and stay curious.