Jim Jockle: Welcome to Trading Tomorrow navigating trends in capital markets. I'm your Jim Jockle. In my decade plus of working with Numerix's Global Leader in Capital Market's Risk Management Technology, I have launched our Thought Leadership Division, a place where insights, innovation and expertise converge, just like this podcast. Through my journey in the financial realm, I've had the privilege of witnessing firsthand how the capital market's landscape has transformed. The complex dance of market trends in innovative technology has redefined how the finance industry operates, with game-changing innovations just around the corner. We now stand at a crossroads, one where it is more crucial than ever to understand the interplay between these realms. That's what we do here. We talk about current and future processes and technologies you need to be aware of moving forward.

For this episode, we focus on fascinating research released by Broadridge in their third annual Digital Transformation and NextGen Technology Study. To develop these findings, they surveyed 500 C-level executives and direct reports across the buy and sell side from 18 countries, and the results are fascinating from 71% saying AI is changing the way they work, to 60% believing blockchain and DLT will become the core financial market infrastructure in the next 10 years, to 35% affirms boosting spending on cybersecurity. This study provides essential insights into where the industry is headed and what technology is gravitating towards. But today we want to look past the numbers and give further context into the trends driving these statistics. Joining us for this conversation are two esteemed members of the Broadridge team Prakash Neelakantan and Matthew Nelson. Prakash is the Vice President of Corporate Strategy at Broadridge Financial Solutions and is primarily responsible for blockchain and digital asset strategy. He's helped define and articulate Broadridge's strategy in the emerging digital assets and crypto markets.

Matthew or Matt, lead strategy and business development for Broadridge Asset Management Solutions. Their SaaS technology powers more than 600 traditional asset managers, hedge funds and fund administrators, with a complete front to back middle asset class solution. Matt has over 25 years’ experience in the securities industry, spanning asset management and financial technology. Gentlemen, thank you so much for joining us today. Thanks, Jim, pleasure to be here. So, I want to start with some of your overarching thoughts. This is your third annual report and right now you're gathering research for the fourth and looking back. Over the past few years, have you seen a change in the way the financial industry has embraced digital transformation, and do you see more or less of a willingness to embrace new technologies?

Matt Nelson: Yeah, I mean the short answer is huge change and yes, in terms of a willingness to embrace. You know, as you said, this is the third time and we're working on our fourth version of the study now. Really, the big theme that we've seen in our interpretation of the theme is that we're really sit on the cusp of a new phase in digital transformation. If you think back three years to when we started doing this, it was very much about digitizing the user experience, big data analytics still hugely important, no question about that, and we'll talk more about that as we go along. But now you kind of flip to. The last year has been all about artificial intelligence. It was almost something was about 11 months ago that ChatGPT was made public and since then you can't turn on the news, business or otherwise, without hearing AI. So obviously we want to talk quite a bit about that today.

So, there's been a change in the tech itself and the way that firms are adopting it and looking to leverage their transformation, and also kind of the pace, really the pace of transformation within those firms. Again, kind of going back three years, we were right coming out of the pandemic which really did force a huge acceleration in digital transformation, so you know where workforces went home. At the same time, clients were looking for a new level of data, and this wasn't pandemic related. This is just sort of generational and tech evolution. But with that switch, we needed to be able to process trades more efficiently. We need to get data out fast. We needed to bring in new internal and external sources of data. So, all these things were weighing on and really have accelerated this path of digital transformation over the past few years, like the.

Maybe one of the most telling numbers in the survey is that in the most recent version, firms were spending around 27% of their overall IT budget on digital transformation. You flip that back to the even just last year's study; it was only 11%. So, it's more than doubled in just one year and it's really broad. You know we'll talk more about some of the various areas that are being spent, but it's not just digitizing process, it's blockchain, distributed ledger, tokenization, artificial intelligence, machine learning, and all these areas have really Accelerate of the last of the last few years and it's you know they're all huge topics in the industry today.

Jim Jockle: In terms of. In terms of that, that Delta, what would you say is the driver, is that the technology is becoming more tangible to the end user and therefore garnering even more interest and excitement.

Prakash Neelakantan: Yeah, I would say that's very much true, Jim. Actually see, for instance, something like chat GPT. It's much more Experienced for the average user, right, and so it can be realized and impact actually the productivity of every individual and so people expect more and actually they can also see the benefits quickly, right, unlike, say, back an infrastructure or somebody puts a service in the cloud etc. Those kind of, by the time the change percolates, time to the end consumer of that information or service. Right, it takes time. Right here you can see the visible impact quickly. I think that's been the big change.

I would also add one more thing actually to what Matt said. If you see, while the rise of AI and ChatGPT was one of the key themes, the others flip side of it, when we talked about blockchains and DLT, for instance, the previous two years saw kind of crypto being discussed as an asset class, potentially a new major asset class, etc. But we saw over the last 18 months Right, in a sense, at 12 months, I would say 12 to 18 months crypto winter, the, the scandals and the scams actually unraveling right and and and and what it's done is actually it's revived the underlying technology and use of the underlying technology of blockchain, more than just actually the speculative use of crypto coins, etc. Right, and so there has been a revived interest that I would say actually in tokenization of assets, real use of DLT to improve actually processes in the capital markets.

Matt Nelson: Yeah, that's. That's a really good point, that that I think again, kind of looking back a few years ago, everything was about you know, crypto. We were waiting for institutions to adopt crypto and portfolios. We saw sort of the launch of first ETFs and trusts and you know institutional products and we all assume that hedge funds and other speculative investors would, would be, would be adopting the technology. Now, yeah, but to Prakash's point, there's been this crypto winter, so now the focus really has shifted towards the technology that's underlying them. Well, you know, maybe that's still coming, maybe that institutional demand is coming. I think most people are waiting for some sort of regulatory clarity, but the technology has really sort of surpassed the, the coins themselves or the current digital currencies themselves in terms of the attention that they're getting up and FTX and others didn't help the argument, if you will, but you know I thought it was very interesting and specifically around.

Jim Jockle: You know blockchain and distributed ledger in the in the, in the report You're, you know you found 27% of firms saying they're actually increasing their investments into these technologies and that's only 1% less than AI and machine learning, and I do want to get back to it because you know you can't have a chat without chat GPT. But have you? You know, have you personally seen or heard? You know how big a priority Blockchain and distributed ledgers are becoming and? If so, what? What are the drivers?

Prakash Neelakantan: I would say I do not know the weather, whether the 1% difference is truly reflective. I would say, if you look at budgets, right, and then Matt, you can add to this, right, I would say the budgets are more skewed towards AI implementations today than blockchain Right and DLT. But what has happened is actually that there have been a few specific use cases Actually of blockchain technology which are kind of been validated and people who understood the true value that when you kind of digitize and tokenize assets, existing assets actually right, you can actually, through small blockchain and smart contracts, kind of make the current processes around transacting and settling these, these products like repos for instance, more efficient, right. So anything in today's world actually of high yield right, the drive is to leveraging your assets actually more efficiently and if the efficient moment of assets, whether it's collateral or otherwise, allows that, then they see a real need and they see this technology kind of allowing that and actually that's the push which is kind of actually driven adoption of DLT. I would say.

The other side of it is actually the crypto universe has seen actually no allocations, right, and so they're saying, okay, can we take other kind of alternative assets and actually kind of make it more usable and tokenizable actually, and usable and transactable more efficiently and distributed to a broader kind of investor base and that's a potential use case everybody's been exploring. So those are the two kind of drivers, but I would not say that the one person truly reflects actually DLT adoption versus AI kind of focus Right. I think it will be more skewed towards AI, a little bit more right than actually DLT.

Matt Nelson: Yeah, I'll be interested to see where the results come out this year, given the buzz and then the uptake, the adoption of AI that we started to see, you know, interesting. I think that three to five years ago distributed ledger was a solution looking for a problem. Right, we people under we're starting to understand the technology because at that point we really only thought of it in the, in the cryptocurrency space. And then some real use cases have ticked up and we could certainly talk about our distributed ledger repo product that broad reaches launched.

There's others out there, that is sort of targeted green fields, areas where there wasn't really Well established embedded technology in place. Rather it was fragmented, manual, some voice. So bringing real efficiency and optimization, you know, in the case of repo, liquidity and minimizing counterparty risk and kind of all these really tangible benefits has, has, is really delivered. I mean, this is where distributed ledger is really hit the hit the mark as a, as an underpinning technology. But yeah, I think again I agree with Prakash I'm not sure that that delta from the survey, the last iteration of the survey, is going to hold up as we, as we go to this year. I think there's a lot of exploratory and sandbox work going around a distributed ledger in other areas, but I would imagine that the pace of, of adoption of of a right now is, is, is is significant, is very high.

Jim Jockle: I mean, I'm probably using chat GPT every day at this point in my own work, and I know many others are as well, so I do want to stay on distributed ledger, ledger and blockchain for a minute. You know, the study also predicted that blockchain and BLT could change the value proposition of firms that currently play a central role in financial services, and some of the conclusions based on the survey say that they may have to reconsider where they fit in a world of tokenization and decentralized finance. You know, perhaps you can explain that a little bit further. And where is this where? Where are these conclusions coming from?

Prakash Neelakantan: The general, the general team about DLT has been that it will disintermediate many of the blockchains, will disintermediate many of the current institutions and the services that they provide. Now it's now, I would say, in practical reality is nearly now 10 years, or I would say nine years, where this technology has been kind of explored and tested out and kind of use cases being identified and things like that. The original kind of vision is still not rectified in any fashion. What we have found is actually specific use cases like if kind of efficient use of capital and collateral through tokenization in some fashion. Yes, that's a use case that people can kind of identify, realize immediately, given the demands for capital today, and that I think has driven some of the adoption.

Whether it has disrupted the current model of operations? No, would it potentially? Yes, it could kind of partially disrupt or reject the responsibilities of players across Right and it might make it easier for some of the original, whether it's an issuer of a bond or whether it's actually trading quarter parties Right to, because of automation and not use all the services of some of their intermediaries Right, some of that could be embedded actually in smart contracts, in the blockchain Right, but it still doesn't take away the legal entities and their roles and responsibilities in the process.

That needs lots of regulatory change and validation before something like that happens. Right, and I would say so. I would say, more than disruption, it will make it more efficient, I would say right, that's the path people are looking for. More efficient, I think, transactions right, and potentially newer products that could be serviced actually out of these.

Because when we talk about DeFi, defi is a very generic term Right, but the reality is what you want is composable financial services and products Right, you've seen a piece of that in the open banking world Right, but we've not seen that in the capital markets world, I think, as we find programmable assets actually managed on ledgers Right, that could happen, but that's when it's a slow progression. Some of these entities have to rejig themselves, reinvent themselves, I would say or add new services. We have seen traditional asset custodians adding support for digital assets and tokenized products, actually for custody and asset servicing Right, because that needs change to their platforms and services, operations, etc. Right, it's a new kind of actually supporting the same financial product in a new form, right, and that I think would be the change.

Actually, it won't replace them, but it'll actually make them change and add new services. If they don't add, somebody else will come in and add those services.

Matt Nelson: I'm interested to see how it gets, how this technology gets adopted because, to Prakash's point, the value proposition, the benefits could be significant Right there, its legacy technology that sits at the center of the industry and though it works, there's a huge efficiency gain potential.

As Prakash said, there's also a lot of plumbing that sits in our industry. That's old plumbing that's been there for a very long time and it's difficult to unwind that plumbing and to replace it. So it'll be interesting to see how the industry really pursues adoption of that. Certainly, something like T plus one, as we know, is coming to at least North American and Mexican markets next May and Europe's starting to take a very solid, strong look at it now for some time down the road. So, as an accelerated settlement cycle moves and maybe at some point we'll start talking about T plus zero or same day in some level, there's a lot that's got to change there, not just time zones that's a whole separate thing but just the internal processes, the batch processing, the back and forth data that goes on in the industry today. That's got to accelerate. So could distributed ledger could this emerging technologies help make that happen? Probably so. It'll be interesting to see how it gets adopted.

Jim Jockle: And also the security issues around that legacy plumbing as well. So obviously cyber is on top of everybody's mind. So I think the safety that TFI and the blockchain can bring and shore up some of the cyber risks as well what is definitely going to be critical going forward, given the sophistication of hackers. But I wanted to jump back for a second to the AI and machine learning part of the survey, and 71% of respondents said AI is significantly changing the way they work. And now the survey was conducted about a year ago. If you had a crystal ball, how do you think this number has either grown or shrunk since that?

Matt Nelson: I would say it's probably increased. I think I'd feel pretty confident saying that it's increased To your point. You're using it every day. I'm not yet.

I work in a strategy type role, so could I see it potentially replacing the creation of strategic plans and things down the road? Yeah, so maybe I'm just avoiding accepting future, I don't know. But yeah, I mean, I think that at this point we've really started to understand the use cases for AI, and they vary obviously significantly. Whether it's improving customer support, customer interactions most of us are doing that. I can go on my banks app and I'm asked a question and I'm pretty sure it's AI All the way through to operational support. So I know RPA isn't really part of this. That's kind of a separate technology. But using AI machine learning to automate things like trade reconciliations, trade break resolution that's certainly been going on and that's hugely impacted operations.

Again, I have more of a buy side focus myself, so we're starting to see it get adopted in the front office investment decision making, asset allocation, portfolio construction. There's a handful of AI powered ETFs on the market. No, the jury's out on whether those are outperforming humans or other processes that are in place, yet I think we see that coming so you can look across support front office, middle office, back office and you see applications today and people that are using them. Then you go into supporting legal and the different support functions. Again you see the support. So long answer to your question. Yeah, I absolutely expect that that number will have increased from 71%.

Jim Jockle: Obviously it's newer technologies, but have you seen any AI ML solutions delivering measurable ROI at this point and if yes, maybe you can tell us a little bit of some of those use cases?

Matt Nelson: You know this is a little bit more difficult. Again, I think that some of the applications like client interactions, operations that have been in place for longer yeah, I mean you can definitely. I don't know the numbers, but you can expect that whether you're able to reallocate headcount or reduce systems that are in place today, there's absolutely going to be measurable ROI benefit for those. As I was talking about sort of the, the buy side front office, I don't know yet. I'm not sure whether it's delivering ROI. If you think you know, in our terms that would be alpha lower costs. I'm not sure that it's there yet.

I think you know scanning those AI powered ETFs, it's kind of spotty. You know some that are doing better than just an S&P 500 ETF, some that are doing worse. So I think it's still a lot of learning in the decision-making or security selection process and I don't think the fees are lower from what I've just kind of done. Seen through a cursory check, I think you're about on par with actively managed equity products. So that may be a little further out until we start to see some real measurable ROI. But I think definitely the client service, client support, operational applications yeah, and percussion is better than I do more about the use and code development. I'm guessing that that's really showing some benefits as well.

Prakash Neelakantan: I think, yeah, I would see the, given the timeline, see where that chat GPT started, and then the JNAI platforms being available for integration into enterprises, then the guardrails being put in actually to make sure that it's used correctly Enterprise is protecting their own IP and data.

Actually that all of this has taken time. So I would say it'll take some more time for large scale use in specific use cases for us to kind of truly measure any improvements in productivity. There were many reports, right Since Matt mentioned software development. We are a fintech and so software development is very much part of everything every day, things that we do as a large part of the organization, and we expect productivity improvements using all the tools available today the JNAI tools that support actually code, pilot and equal and stuff actually that support there are studies which say that a 30, 40% productivity improvement. But I think we'll have to put it in practice, in daily practice, and then actually measure actually whether it's impacted productivity and we expect surely some productivity gains in all of these tools, right, not truly quantifiable yet, I would say.

Jim Jockle: Two other quick questions for you Data analysis and visualization. Right, so the study showed it was a priority of new investment. Do you feel this is still true and how do you think it's going to look on the survey this year?

Matt Nelson: Yeah, I think that the analytics visualization angle in the context of a digital transformation is still hugely important, so I think that it will continue to be a high priority.

Who knows how the numbers shake out, but most firms at this point, most larger firms, certainly mid-sized and larger firms are a product of M&A activity over many years.

Certainly, banks have evolved that way and increasing asset managers, the M&A activity and the buy side over the last call five to 10 years has been significant as well, so that as a result, we see firms with multiple order management systems, multiple accounting systems, multiple performance and attribution systems, valuations all these systems that have just kind of been stitched together and with the advances in data management technology and the visualization layered on top, we're now really able to not only kind of harvest the data and the insights from that data better by giving our users, whether they're front office, middle office, investment, whoever they may be the ability to combine internal, external data sets, data sets from different order management or portfolio management systems and again really be able to manipulate that data, create the types of visualizations and tools that allow them to get the most of the value out of the data and then to be able to deliver that data out to their clients in a much better, more holistic way.

So you know, I think that's just kind of a small lens into the buy side. Banks, obviously, are magnified in terms of the number of systems that they've got, so I think that it will continue to be a huge priority. And just within the buy side, it was 94% of firms that were planning to increase their investment in data analysis and visualization. So I think that that remains a huge priority. It's just. It makes sense. It enables us to extract so much more value out of the data and support our clients much better than we ever have before.

Jim Jockle: So we've made it to the final question of the podcast. I'm going to ask both of you. We call this the trend drop. It's like a desert island question. So what to you, is the technology everyone who works in the capital market should be tracking, and why and why In Prakash? I'll start with you.

Prakash Neelakantan: This is a tough question actually. We talked about existing technologies. Ai and AI will evolve. So I would say one or two things actually, not just one thing, that I would watch for. I would continue to track, actually, the path towards what we call AGI, the truly independent AI, fully automated general AI. So the path towards intelligent agents, truly intelligent agents, assistance, which can actually sit side by side with everybody and work with them on tasks for you, where the agent can plan and do tasks, not just look for information or digest and synthesize information. That would be the path actually. So that would be something I would continue to track for.

Actually, if it happens, that's a complete changer. If AI can actually plan and execute as independent agents, that's a game changer for lots of things Compute power, actually, and what we are doing today with computing. So the second part that I would watch for actually is, I think, whether can we go beyond today's keyboard based interactions Actually, which are predominant for almost every transactions that we do, to completely voice and video, gesture based communication, etc. Whether you want to call it metaverse or whatever it is actually. I would still continue to track that because that actually can increase the bandwidth of interaction between agents as well as systems, as well as actually participant humans in any kind of interactions. So those would be two things that I would track.

Jim Jockle: It's interesting you bring up the metaverse. There's an AR ETF on NASDAQ now. I think it launched in the last year and a half. But anyway, back to the desert island. Question, matt. What are your thoughts?

Matt Nelson: Yeah, it's an interesting one. I mean Prakash certainly knows a lot about the detail, more than I do. I mean, I think that for me I'd say AI would be the obvious answer, not understanding the level of the autonomous that he was talking about. And also, when you get that far down the intelligence, the real scary sort of intelligence, I guess I worry about our ability to put the right guardrails on it within the industry even alone. I know the SEC has been starting to talk about this, but it's clearly so new and so complex that there's very few people that truly understand it. So anyways, I'll stay away from that. And Prakash's answer there was really interesting. I think that for me over the next few years hopefully I wouldn't last that long on the desert island I'd be rescued within a year or two. So I'll just think in sort of a shorter term.

I do think that the whole visualization and the advances also in sort of desktop technology. We have an order management system, for example at Broadridge, a buy-side order management system. There's some really fascinating stuff that's going on now with solutions that are enabling us to bring that to the desktop in almost a super lightweight, like a browser on the desktop, but with the performance and the flexibility that you would expect out of more of a locally installed software application. So I think what we're able to do as vendors and as certainly within institutions using the same type of technology, to really kind of rethink the way that users interact with technology on the desktop, mobile, is pretty exciting right now and again, with that data work that's been done, the visualization and this kind of new usability paradigm that we've got now, I think it's a really interesting time in the way we interact with software. Yes, just within financial services, but more broadly, I hope to see advances on my desktop in the way that I'm interacting with tools and systems. I think it'll be an interesting time.

Prakash Neelakantan: So what I mentioned, actually two things. They were more generic right. It could impact any kind of business, not specifically capital markets, see the other technology we discussed, actually, which is blockchain and DLT. We've always been talking about use of DLT and kind of permissioned consortium models, actually, right, the other side is happening on the crypto and the crypto has taken a dip right now, but one of the things it's kind of constructing is actually decentralized models of everything, right, including decentralized financial products. That is something, actually, that I would track very closely. If there is regulated models, controllable models of DeFi that can get constructed over a period of the next few years, right, that actually can truly disrupt capital markets, right. So what it needs more work to be done right, what is being done today is lots of experiments, I would say early stages. If it can truly evolve to its original thesis, then that's something worthwhile tracking and it could potentially impact what we do in capital markets.

Jim Jockle: Well, matt and Prakash, I want to thank you so much for this conversation. The time just flew by and I think we could probably talk for a lot longer, but I mean incredible stuff and thank you. I appreciate you, gentlemen, sharing your thoughts and we look forward to the next iteration of the survey.

Matt Nelson: Thank you, Jim it was a pleasure.

Prakash Neelakantan: Thanks so much, Jim. We appreciate it.

Jim Jockle: And this week we don't have a preview of the next episode because this is the last episode of the first season of Trading Tomorrow navigating trends in capital markets. We're so grateful to you, our listeners, for joining us every week on this journey. We will release season two right in the beginning of 2024. In the meantime, you can find us wherever you listen to your podcasts. Remember to like, follow and comment. Thank you.