Stephen C. Daffron talked with The San Francisco Experience in June about the significance of data transparency and interconnected data, and how the modern investor is shaping the demand curve.
The San Francisco Experience podcast brought to you by Jim Herlihy, independent commentary from a Silicon Valley perspective for a global audience, featuring newsmakers, thought leaders, and authors. Season 27, episode 8. BetaNXT: A private equity success story. Talking with chairman and CEO Stephen Daffron. Our guest today joins us from his office in New York. BetaNXT is a premiere provider of technology, data, and operations and services to a client base encompassing 50 million investors, 37 million daily transactions, and 70,000 investment advisors. BetaNXT provides end-to-end solutions across the investment lifecycle. Steve Daffron is also co-founder and industry partner at Motive Partners, a specialist private equity firm that invests in financial technology companies. Motive Partners acquired BetaNXT and related assets for $1.1 billion about two years ago. He also once served as president of Dun and Bradstreet. Hi Steve, and welcome to the show.
Thank you. Glad to be here. Thank you for having me.
My pleasure. Steve, let's take a moment and look back on your career. After graduating from West Point you served in the U.S. Army as an officer. You went on to Yale, where you earned multiple graduate degrees, culminated in a PhD. Your experience in the financial technology industry, in fact, spanned private equity, hedge funds and investment banking, and included time with Renaissance Technology. You were CEO of IDC. You were also with Goldman Sachs and Morgan Stanley. In fact, you were the Global Head of Operations and Technology at Morgan Stanley. And then in 2016, you joined Motive Partners as a co-founder. Tell us about Motive Partners investment strategy and the BetaNXT investment opportunity.
Jim, it's a pretty interesting story that goes back a ways. So, let's kind of start at the end. Eight years ago, two partners I met for lunch at Balthazar, in the village, which has the best steak tartare in New York. And these two partners are people that I've known for 20-plus years, and we've all built and run companies successfully over the course of our careers. And we’re having lunch, talking about what's coming next. We’d all just sold companies that we'd been running for other private equity firms, and we decided at this lunch, rather than running companies for other private equity firms, that we would use our money, pool our assets, and create our own private equity fund. And we decided, and then later that year created Motive Partners with the idea that we could be a different kind of private equity firm, that we would invest in things that we knew about. We would be not just the public we fund that, understand the financial underpinnings, but actually having written the code, made the payroll, built the teams, and we would do that, and we did it. We started it and we closed the first fund at $485,000,000 and we're now in the second fund of about $2.5 billion, with the idea being that you can be an investor while being an operator and being an innovator at the same time. That three-part model is what sets us apart. And that has been the key to our success, and the reason other investors want to invest with us – because we invest in things that we understand about where we have an edge. It was that edge that led us to BetaNXT, because one of the things we did when we created Motive Partners was start essentially a research facility.
I'm a lapsed academic. In my previous life I was a professor at West Point. And one of the things you do there is you learn to dive into the data and understand how the pieces fit together. And one of the things we found, especially in the wealth management space, is that the data structures didn't work very well, but there were things there that were obviously malfunctioning. And we looked in the places in the marketplace where we could acquire, carve out parts that weren't malfunction, that weren't functioning as well as they could, and see if we could fix them, which is that's how BetaNXT came into existence, as we found a really interesting positive market image but with older technology, a firm based in Milwaukee called Beta, we bought with that a firm called Maxit which did cost basis data and tax data. And then paired that with another firm called Mediant, which did client communications data; proxy prospectus data. Put those together and we created something that matched a demand curve coming from the primarily from the self-clearing broker dealer community, but also from the fully disclosed brokerage community, saying, we want this to work better. And pulling this together and having quite deep experience running data and tech operations and putting, frankly, some capital into it from Motive Partners and from our partner Clearlake, who invested alongside us. It created an explicit opportunity to better serve the broker dealer community through better technology solutions, more cost effective and more efficient workflows, and most of all, better client experiences, because that's what was driving it. Fast forward to today, BetaNXT powers the future of connected wealth. If you look across the US market right now, that software, the operations, the “data as a service” is essentially with all the major self-clearing broker dealers in the US.
That means that's 70,000 advisors. If you have advisors who you're asking to help you understand how to manage your portfolio, you're probably using our data, our technology, that those advisors, of course, are giving the best advice they can based on the data that's available. So we work it with those three core business solutions, united by a data architecture that allows us to have securities processing, custody operations, end-to-end tax reporting, digital investor communications and shareholder engagement all in one data architecture. I'm really, you can tell it my voice, I'm kind of a data nerd because if the if the data works top to bottom, things work. Sometimes we refer to this as connected wealth. Connected wealth in the wealth management space requires connected data because those institutions like LPL, like Wells Fargo, like Stifel – they need to be able to handle the data in a way that drives your costs down, increase your efficiency so they can support those advisors in the way those advisors more and more want to be, which is in near real time.
There was a time when my father or your father might have been willing to get a monthly report on his mutual funds and that was sufficient. That time is long gone. Now, connected wealth can't exist without connected data, which is near real time. It integrates all the information necessary for the clients’ wealth to be managed by that advisor in a joined-up solution with near real time delivery. And you can tell this is something I think about a lot.
I can tell. You mentioned three customers there, three clients of BetaNXT: Wells Fargo, Stifel, LPL. Huge presence in the marketplace. The fact that you have 50 million clients, 37 million transactions a day, BetaNXT must be, if not the largest, one of the largest players in that market space. Who are your competitors?
Well, in the self-clearing part of the broker dealer space, we are the largest. But in the larger addressable market, where you have fully disclosed, the competitor is probably Broadridge, it’s the biggest competitor out there. And it's different market share for different components. For example, Broadridge has a lot more of the institutional business than BetaNXT does, while BetaNXT focuses on the retail wealth managers and some of the institutional business, but more of that's being done by Broadridge.
Now you mentioned that in our fathers’ day or grandfathers’ days, they would have been very happy with a monthly statement of their mutual funds position. But increasingly today, individual investors are a lot more informed, much better informed for a whole host of reasons, but much better informed and therefore more demanding in terms of the kind of information that they're seeking out. Of course, AI – artificial intelligence – I'm sitting here in San Francisco. We have 16 of the largest artificial intelligence companies in the world located here. We're a center of innovation. How are you going about integrating AI into your overall offering? Because I would imagine of your 50 million clients and of the of the 70,000 financial advisors, they must be coming to you and wanting to know what you're doing with AI. And to the extent that Motive Partners has been the principal owner of BetaNXT for the last two years, it must be high in your agenda. Tell us about AI and how AI might be adopted by BetaNXT going forward, or is it already being integrated?
Well, the answer is yes and yes, but I want to answer you from a slightly more academic perspective, because AI is a solution, is a part of the supply curve. Let's go back for the moment to the demand curve. The demand curve… you know, our fathers, our grandfathers timing would have been a monthly report. Now the timing, think of not a “you and me”, but think of our kids, that my daughter is going to be having, she represents the demand curve. And in fact, there's a great paper came out from the World Economic Forum in August of ‘23 that talks about the future of retail investing and talks about what's happening to the investors.
And first, there's a huge amount of money moving from my generation to my daughter's generation. And as that money moves, that expectation of investing and how the investments will happen, changes too, that client demand curve, those end investors’ needs, that's different than it used to be. It requires a level of interaction, requires a level of precision, requires a level of timeliness that wasn't there before. So, what happened in this great wealth transfer between the investor generations is it requires us to deliver faster, more efficient, more transparent…sometimes referred to this as hyper personalization. So, when my daughter – again I'm back bringing this down to the individual – when my daughter picks up her phone and wants to be able to do something in her investment portfolio, she doesn't want to wait for it. She wants to be able to see that now. So, that's where we need to get the data to be curated to a point where that can happen.
Now, AI, and I've spoken about that at some length, artificial intelligence is wonderful, and we've been using and working with it now literally for years. And we continue to incorporate it into what we're offering. But we're doing so very carefully because artificial intelligence is only as good as the data, you're using to train those models, which means if you don't have highly curated, highly structured data that works front to back, you're going to get hallucinations. You’re going to get hallucinogenic egg on your face. Because you'll be coming up with things that just simply don't make sense. So, we work through the data structures. We're very closely tied to one of our great partners, a firm called Snowflake. We work on this to make sure that we can do a data architecture from top to bottom. I'm going to give you an easy example. Think of something that happens all the time: a stock split, and sometimes that's referred to as a corporate action. Now that sounds like just a simple thing, but that means that that issuer who decides to do a stock split has to take that data, and think of what that means in terms of the issuer, and all the millions of portfolios that have that in it, that has to get from the issuer all the way into the security master of those firms, all the way up through their trade blotter, to the advisor in a way that that advisor can understand.
Once again, you're using data structures that are clear – which means oftentimes we're using copilots or tools to help make sure it's clear at the advisor level, that advisor portal interacting with those institutions to make sure those advisor portals are clear – to the investor, “Here, Steve Daffron’s daughter, here are your choices: you can take cash, you can take security, you can take combination. Here's what we recommend because…” the investor makes a decision and then it has to come all the way back down. Now if we did this in the data architecture that we to see how many times the data broke between the time the issuer set it, and the time the investor saw it, and then back when to make the decision all the way back down to that investors account in the portfolio, because that has to include things like how does the stock split affect my cost basis for my portfolio? How does it affect my tax exposure. All of those data elements have to be cohesive and coherent. Otherwise, the data breaks and what you've got is bad answers. And you can't have the AI that works without that, unless the data makes sense.
Well, speaking of the stock split, I'm thinking of Nvidia last week where we had a ten for one stock split. It went from whatever it was: $1200 to $120. Of course, it's back up to about $140 now, which would be like $1,400 pre-split. But to your point, I mean, that was a ten for one split. And you know, you've just very skillfully walked us through step-by-step.
If it works. But it you're if your advisor can't do that with you then he or she isn't getting the data they need to do their job. And the enterprises that we work with serving – and candidly, they ask us to. This is not just us at the supply curve into this. This is the demand curve, this is Barry Sommers at Wells Fargo saying, “This is what my advisors need. You need to figure out how to deliver it.” So that's why we're creating this kind of connected data that supports connected wealth. In order for those advisors of Wells Fargo to be able to give their clients the best possible advice, they have to have connected data that connects all the way from the issuer to the advisor. And we have to able to say to them, “Trust us, that data will be whole.” Then we can bring tools to bear to make it effective.
You know, you talk about connected data and we've come so far from the masses of raw data that we were all familiar with not that long ago. But today we as investors or as financial advisors, we need to present a connected picture to our clients or to ourselves in order to make investment decisions.
Correct. Absolutely right and you said it well. In fact, when something doesn't look right, you know it. The true challenge is creating data that's trusted. It requires a lot of work, which frankly, that's what BetaNXT does, to bring all that historical data necessary to have a curated data set, that allows us to use effective tools like the more effective AI tools. Otherwise, you have breakage, otherwise you have a lack of trust. Another great paper that came out in the World Economic Forum talks about the future of advice and talks about what investors wanted. And the first thing they wanted: they wanted to have advice that they could trust. And the only way to trust the advice to have connected data that supports that connected wealth advice.
You know, you have 70,000 financial advisors on your platform. And let me play devil's advocate here. Of course, we've seen explosive growth in the field of ETFs. And you know some would argue that if your whole portfolio consists of ETFs, what do you need a financial advisor for. Now you have 70,000 financial advisors on your platform. And obviously there aren't a lot of investors who are about to let their financial advisors go in favor of ETFs. Talk to me about those trends, ETFs, digitization, those trends. How does BetaNXT, with all of the innovation that's coming down the road in the financial markets, how do you stay ahead of that curve and what's on the horizon. What's coming up next year or the year after?
Well, first, what's on the horizon and what they're asking for, what the demand curve... I keep going back to that same phrase. What is the demand curve say? The demand curve doesn't say I'm satisfied with all ETFs. The demand curve doesn't say just because I have digitized data, I don't need advice. And okay, well, and you'll understand the theme here. When I talk to our clients, Dan Arnold at LPL or Ron Kruszewski at Stifel, and I ask them what they care about, what do they want? They have a well-defined list of things they want to do, and they want more and better control over the data flows into their companies. They want fewer one-off solutions, more coherent solutions.
I'll give an example. There are still people who are buying and selling mutual funds. And mutual fund sub-accounting is an entirely separate set of processing flows that you have to be able to incorporate. Now, that's not something that BetaNXT originally did, because it was not a part of our original DNA, but because our clients said we want that mutual fund sub-account processing to be done in the same context, the same data architecture, the same coherent architecture that you do everything else in, we went and did it for them. We went and found the best thing in the market and got that for them. Why? Because that's what they need to do to have their advisors and their investors to be satisfied. And that’s going to happen across the board. There'll be more and more people who want to say, “I want to do alternative investments. And I wanted to have my alternative investments be seen in my portfolio modeling, be seen in my tax reporting, be seen in my returns.” We are working with another firm called CAIS. “And oh, by the way, this is another thing we didn't tell you about.” They don't want to have to do a correction. How many times have you had your broker dealer tell you, “Oh, by the way, that 1099 you sent you? Need to send again, because we didn't have quite all the data there.” Now, that's not something we should accept anymore. We can run 1099s now literally every day.
We have your data up to date in new real time. We can do 1099 every day. Your cost basis data which is foundational to what you're doing with your portfolio. That's the data updated constantly in near real time. Now that's what our advisors are asking for. That's what the advisors and that's what our clients are asking for, so that's what we're doing. We're essentially being driven by what the new wave of investors are asking their advisors and what those advisors are asking their enterprises like Wells Fargo and Stiefel and LPL, and we are the ones who help them do that. And we're really proud of the fact that when those enterprises see a change in the marketplace, like, for example, the registered investment advisors, that's where a lot of growth is happening in that space. And they needed to attract those registered investment advisors. They come to us to help them see how they can show those registered investment advisors how to have a coherent, connected data to connected wealth.
Very impressive. Now you describe yourself as a lapsed academic. And before we came on the air you mentioned that you're not that lapsed, that you're still you're still active as a professor. Give us a flavor of the current role that you play in academia.
A few years ago, one of my friends at Yale asked me, because we invest in financial technology. And she and he, two friends of mine, were talking to at the Yale School of Management, at the Yale School of Economics, how to engage with the economics of how to think about financial technology investing. And so we put together a series of case studies that says, when you go look at financial technology companies, what are you looking for, or the underlying data that makes them worthwhile? Why are they worth 20 times their EBITDA, or why they're not worth 20 times their EBITDA? What are the things you have to do when you invest? And this is again back to Motive Partners, our foundation. We tend to go and find places where you invest, where you know how to bring the capital to bear on how to make the multiples jump when you put the capital in the right place and taking that kind of practical knowledge of academia is what we try to do. And it's been it's been fun. Candidly, it's a lot more work than is sounds like.
Well Steve, in the remaining few minutes of the podcast, what are the opportunities for investors today in your industry, in the financial tech industry. Because I think you've given us a great, a great perspective today, from a private equity perspective why Motive Partners invested in BetaNXT. Can you share with our listeners some investment opportunities that might be out there that that our listeners might be looking at in the financial tech industry?
Okay. Well, I'll give you three dimensions. The first one is finding data companies, companies that actually understand where the data is moving. Because the data, it's almost as though it's an organism. It's growing and evolving in a way that allows the transparency to get better and better and better, by any companies – and I'll mention my friends at Snowflake – by any companies who are actually enabling that is a way to go into the space, because you're looking at people who are creating tools. Remember the old phrase about the people who got rich in the gold rush were the people who sold picks and shovels. Well, the picks and shovels these days are companies who actually understand how to create transparency and connected data front to back.
And there are a plethora of those out there, and that's both in the public companies like Snowflake that I just mentioned, but also private companies, private companies like CAIS, which does this for alternative investments. Private companies like InvestCloud, north of us in the stack where they are building the transparent client portals. Those are places where the data transparency creates value. Value for the clients they are servicing, but frankly value for the investors. Global Shares has been one of our greatest investments because it was an investment that was key towards helping people understand how to get data transparent on employee stock shares. A little company in Cork, Ireland that we invested in for a few years. It's now been purchased by Morgan Stanley and it's doing great for large numbers of Morgan Stanley clients. Why was that a good investment? Because it created data transparency on a part of the marketplace when the transparency didn't exist. That's the place to look for companies [to invest in].
And Steve, what new initiatives are you working on. Obviously very creative mind…you're a hands-on operator. What other initiatives are you working on there at Motive Partners and BetaNXT?
AI, you mentioned before is probably where I spend most of my creative juices these days, and it's not the AI that's…I'm a believer in making the plumbing work. AI that’s glitzy and shiny, it's not my shtick. My shtick is finding AI that makes the plumbing work better. One of the biggest heartaches that we're not solving in the BetaNXT, but that I want to figure out how to address is the onboarding. The client acquisition and onboarding is one of the greatest pains that the advisors, whether they're in the wealth manager space or the banking space. And that's something I think, with the right kind of intellectual horsepower we could solve, where it doesn't take you three days to get a client on board, it doesn't take you a week to get a loan approved. It doesn't take you a month to be able to get your portfolio approved through KYC. We should be able to do this in a matter of seconds if the data structures are curated to a point where we can bring these AI tools to bear, which I think we can. And frankly, that's one of the things we're working on. It's still at the point where we're doing the math, it's quite a ways from where I’m going to say I have a good solution but the math is starting to make sense to me now.
Well, Steve, when you come up with that solution, I think the entire private banking, investment management, wealth management industry will be knocking on your door to adopt those new technologies because I for one, I was in the wealth management business and the KYC process was always a – when you say 2 or 3 days, my goodness, it was we were lucky if it was that short – but, I'll again, my own experience with onboarding, I would agree with you, onboarding of new clients, very difficult, very cumbersome. And at the end of the day, we actually lost clients as a result of that. But I've given us a flavor of what to expect, and some new initiatives that you'll be working on. We'd love to have you come back and spend more time talking about that. And how can our listeners follow up with your company and with you.
BetaNXT.com…we're on the web. Reach out to us and we'll be happy to reach out to you and tell you about what we're working on, what's coming next.
Fantastic. And apart from the website, any other social media that you're active with: X, LinkedIn, that sort of thing?
All of the above. Laura Barger is our Head of Communications and Marketing. She's our social media queen, and she makes sure that we're accessible in all of those.
Well, Steve, I want to thank you very much for taking the time today away from BetaNXT and Motive Partners to share with us the strategy that you've put in place to make BetaNXT an even larger, more efficient player. And to anticipate the more demanding investment needs of today's wealth management clients. Again, Steve Daffron, thank you for joining us today.
Thank you, Jim. Enjoyed it.
And for our listeners, today's episode is number 535. Listen to us on Apple Podcasts, Spotify, Pandora; 18 platforms with listeners in 60 countries. Feedspot is recognized us as a top 25 California news podcast, ranking number 12. You can obtain a transcript of today's show on Apple Podcast. This has been the San Francisco Experience podcast with Jim Herlihy coming to you from San Francisco.
Source: The San Francisco Experience Podcast