Stephen C. Daffron and Craig Iskowitz discuss integration between BetaNXT and other Motive companies, about competition and cooperation between competitors, and, of course, AI.
I’m excited to introduce my next guest. It is Stephen Daffron, Chairman and Chief Executive Officer of BetaNXT. Stephen, thanks for being here.
Thank you. I’m glad to be here.
Where are you calling in from?
I’m calling in from our offices at 55 Broadway in Lower Manhattan.
That’s a great place. I’m in New Jersey. We’re experiencing the same crappy March weather — rain. But we’ll have to deal with it.
I can’t wait for spring.
They tell me it’s around the corner, but I don’t trust them on that. They haven’t been delivering on any of their promises recently. But yes, spring is coming, I’m sure. But before spring gets here, let’s jump into our conversation about BetaNXT. I’m interested in hearing more about the company and our audience as well. Can you please give us a 30-second elevator pitch to start us off about BetaNXT?
Okay. BetaNXT is a SaaS software-as-a-service, DaaS data-as-a-service, and OPaaS operations-as-a-service that provides connected data and operational solutions to the industry — the industry is the wealth management industry, both the retail end and the institutional end — that helps those enterprises support their advisors and support their investors across the entire United States.
There are about 50 million Americans every day who, when they want to wake up in the morning and log on and see how their portfolio is doing, are using BetaNXT software, BetaNXT data, and BetaNXT operational support. That’s what we do.
And it’s all in the background.
Yes. We make all our enterprise clients — Wells Fargo, Stifel, LPL — we make them look good by making sure that all the data that should be connected stays connected and that all the operational processes and technology that need to work do work from front to back and side to side.
When we were prepping for this call, we were talking a bit about Motive Partners, which is now the owner of BetaNXT, along with a number of other companies. I thought the strategy was interesting, which we wanted to get into. Could you talk a little bit about the strategy behind Motive acquiring BetaNXT and some of its other companies?
Sure. Motive Partners was started by three partners. All of us have run public companies in this space for years. For example, I was head of technology, operations, and data for John Mack at Morgan Stanley for many years. Others had also run companies for private equity firms like Warburg Pincus and General Atlantic. But for the three of us — this was in January 2016, so we’re just passing our eighth anniversary — we got together and said: “We’ve sold our last companies. What are we going to do next?” We could run other companies for other private equity firms, but we decided to create our own private equity firm. The three of us put our money in, and soon enough, we had other investors who would invest with us, with the idea being that we’d invest in things that we knew about and that we felt we had an edge in.
We studied the financial technology marketplace and looked at where things didn’t work as well as we thought they could. One of them was, in fact, the wealth management space. We looked at it from top to bottom. We found the places, if you were doing a heat map, where the friction was causing heat — the investor wasn’t talking to the advisor, the advisor wasn’t able to get past the trade blotter to the clearing, and the clearing itself wasn’t clicking with the books and records — and the places where that wasn’t working as well that we felt we knew something about, and we’ve invested. And one of those places, pretty early on, we decided was the BetaNXT space, which has all the pieces that go all the way from order management.
You need to know what the client is doing, from the onboarding of clients and the onboarding of their advisors to the clearance, the settlement, the processing, and the client communications. We bought a company called Maxit, which allows us to do cost basis. And of course, with cost basis, you ought to do tax reporting. Those all get tied together into a big, responsive, connected data set that allows those enterprises to solve their advisors’ and clients’ problems. BetaNXT is one big piece of that puzzle, but we also connect other parts of the ecosystem. The idea is to make the parts of the companies we invest in work well together for the end client because that’s what we’re supposed to do — make their lives better.
The other companies you own include Wilshire, Finantix, CAIS — of course, BetaNXT — InvestCloud, and the APL division of Fiserv that was merged with InvestCloud. What kind of benefit do you see from having all these companies under the same umbrella?
Getting them to be part of — the Japanese term is ‘keiretsu’. You’re doing this so that you’re getting these companies to work together effectively. They’re not necessarily owned by each other. We don’t own 100% of all those companies, and we’re not forcing them to work together. We’re creating structures that optimize the relationships between those companies to serve the client.
The client is also changing because that client now doesn’t look like it did 10 years ago. And that’s going to change even more dramatically. As the massive amount of wealth moves from my generation to my children’s generation to my grandchildren’s generation, you’re seeing the investor herself change. First, it’s going to be more male to more female. It’s getting from older to younger. It’s getting more geographically and ethnically diverse. That investor has different expectations. This keiretsu is meant to solve the expectations and challenges that that investor is asking for.
I’ll give you an easy example. One of the most basic things that we’re supposed to do for a client is explain what happens when a security does something, like a stock split. An issuer decides they’re going to do a stock split. Think of what that means to the investor. That means that the issuer’s choice to split that stock has to go up the chain and be pumped up to the advisor. The advisor has to explain to the investor and say, “Here are your choices.” She has to make a choice — ”Yes, I’m going to take the stock split” or “No, I’m going to take the cash” — and then that has to flow down past the trade blotter, through clearance, through settlement, back to the books and records, and then it has to be reflected in her portfolio.
Do you know how many times and how hard that is? Many of the firms are trying to reconcile the data from that investor to the books and records dozens of times. And every time they try to reconcile the data, they’re slowing it up. She isn’t getting the response that she wants to get, which is: “I made the choice. I want to see how it affects my portfolio. I want to see what it does to my cost basis. Therefore, I want to see what it does to my taxes. And I want all that data to be connected.”
Back to BetaNXT, we’re kind of the core engine of this. We power that connected wealth by making sure all those data service interfaces connect. We give her what she’s looking for, which is near real-time data, a broad scope of products, and accuracy and security. That’s why we tie these companies together. This is not “thou shall.” This is what we think is the optimal answer. And we’re agnostic — we don’t just connect with companies that Motive Partners owns. If Envestnet, which is another company that services some of the same clients, needs to connect to those clients, we’ll work to connect to them. We’ll make the APIs work for that client. We go back to serving that end client, that advisor, which is where the rubber meets the road.
We’re going to serve 70,000, give or take, advisors around the US — 50 million investors, 70,000+ advisors. If we do this effectively, we’re helping those people do the right thing for the right reasons — to send their kids to school, to pay their mortgages, to manage their portfolios. Sorry, I get long-winded on these things. I apologize.
That’s the beauty of a podcast, Stephen. You can do that. That’s the whole point. We don’t want sound bites. We want to dive in a bit.
One of the interesting aspects of keiretsu and linking companies is making the sum greater than the individuals without having to merge with one company. I’m looking at the wealth management parts of Motive’s holdings, for example, with the APL platform, which I saw they’re rebranding. They’re going back to the APL brand, which I think is a smart move. Do you see either integrations or areas where you can be complementary to each other?
Yes. The most straightforward one is the one I just talked about. If you have products that have sleeve data in their portfolio construction, that have data that they’re using to model their portfolios with, and that data needs to be shared as a part of the clearance and settlement process, then having that be built in a way that has the same joins — the same connective tissue, if you will — as we’re using for the clearance and settlement that’s required by DTCC, that’s required by the SEC, if we do that coherently between APL and BetaNXT, you, A) dramatically reduce the time it takes to do that processing and B) reduce the cost of the enterprise.
Charlie Scharf at Wells Fargo will tell you upfront that one of his most important partners is BetaNXT. Why? Because we do everything with his data. We curate the data for Wells Fargo, LPL, and Sifel. We do that in a way that allows us to connect what’s going on in APL with what’s going on in the clearance and settlement with what’s going on in the books and records. It’s the advantage of that enterprise but it’s also the advantage of that advisor because that advisor plays swivel chair roulette.
I’ve seen a McKinsey study that said advisors were spending up to 70% of their time doing things other than talking to their clients and giving advice. They were swiveling the chair to move from one part of their dataset to another part to another part to be able to give the client the advice they needed. This idea is to move the data structures to a point where we can look at them in one way and see a coherent whole so that that investor gets to make the right choices in the right timeframe and it costs the enterprise less.
That’s the name of the game — grow your business and keep your costs flat while you scale your business. Wells Fargo is a great example. Wells Fargo is a big BetaNXT client. They drive all their custody behind the scenes — the intel inside their custody business. And APL drives their wealth management platform across the business. I know they re-signed a big contract with them. Do you see any specific ways that both of these firms together, linking them in some way, can provide more value than the value they provide separately if they’re both owned by separate companies?
Let’s add one more company to make the case, just to show how it works across the board. And that company is CAIS. CAIS is a reservoir of alternative investment data. For all the asset managers who have alternative investments, CAIS brings them together and curates alternative investment data in a way that can be plumbed through BetaNXT. The security master at BetaNXT can take the data from CAIS and plumb it through BetaNXT all the way up to the advisor because we already have those connections all the way up to the advisor.
The advisor then gets to offer that alternative product, which he didn’t have before, from CAIS via BetaNXT to that investor. That investor then gets to say, “I’m going to put this in my portfolio.” The portfolio modeling is being done by APL using that same data set, that same data configuration, so that the investor and advisor can see it and it flows back down through BetaNXT to the books and records.
It sounds so logical. Of course everybody should do this, except for the entire time, and I’ve been doing this for 30+ years, no one’s been able to accomplish that. That isn’t a smooth, easily working, reliable process. Instead, what we have had, and in many cases, many platforms still have, is a series of hash marks. “We’ll stop it here. We’ll throw this data away here. We’ll try to read records down below and over the way.” Meanwhile, the investor isn’t getting what she asked for.
It’s not easy. We spend a lot of time here at Ezra Group helping broker-dealers with these kinds of problems. We always appreciate when there are companies in the background, like BetaNXT or InvestCloud APL, that can provide that kind of data, that kind of consistency, and that kind of scale, which is not common. People don’t realize the scale of a Wells Fargo or the wirehouses. And there are only a handful or even less, of technology providers that can support millions of accounts on their platform.
Again, Charlie Scharf from Wells Fargo, but I also just had a conversation with Tony Miller at Janney in Philadelphia a couple of weeks ago. He was saying he recognizes that the way things have always been does not get us where they need to be. We, the fintech companies, have to recognize that we have to work together. He, the client, is saying to us: You don’t get to do things your own way; you have to work together.
We’re going to T+1. T+1 is a crucible that forces a lot of the companies that haven’t been in this mode before to get into it. Why? Because they can’t do it by themselves. If you’re not prepared to work with everyone else in the ecosystem and you think you can be a part of solving a major broker-dealer T+1 issue and you’re not a part of the ecosystem, you’re fooling yourself, and frankly, you’re endangering our industry. What’s that famous Ben Franklin quote? “We must all hang together or we shall certainly hang separately.” We have to do that. We have to work together.
One of the things that BetaNXT does — we did this last year at the SIFMA Operations conference and we’re going to do it again this year — is recognize the fact that while we are a private equity-held company that has to make money (we are in fact trying to make money for our investors), we’re also part of the larger industry. And we all succeed better when we succeed together.
Frank, the CEO at DTCC, will tell you that that’s the reason for DTCC’s existence. I was there when we created DTCC and the modern characterization of what you could do for equities and then fixed income and government securities. That came from the idea that companies could not do this by themselves. Goldman Sachs, Morgan Stanley, and JP Morgan, as powerful as those institutions are, are not powerful enough to make this industry operate just themselves. They have to cooperate.
We refer to that as ‘coopetition’. Everybody’s a partner and everyone’s a competitor in some ways. And you mentioned a couple of firms. You mentioned Envestnet, which you work with, and APL, which is now part of InvestCloud and Motive. Those two companies are very fierce competitors who are broker-dealer platform wealth businesses, but they also have to cooperate because they share some clients’ [inaudible] technology, which is behind the scenes people don’t realize. There are still some things going on at the back end. Everyone needs to work together because, as you mentioned, we often share clients, especially the larger ones. At a Wells Fargo-sized company, they have hundreds of vendors.
And the idea here should be that we’re doing this because there is a net good in it. You go through the effort of making these things work. It’d be easier just to be working on your own little silo and doing your own little thing, but you’re not serving the client when you do that. If the client has to force us to work together, we’re forcing the client into a role they shouldn’t be having to play.
That is true. All boats rise when the clients are successful. We’re all going to make money when the clients are successful. There are successful fintech startups, such as Altruist, that were reselling custody and then built their own custody platforms, even though the BetaNXT platform was out there. They could have adopted that and run with it. Do you see that as a trend that’s a long-term headwind for BetaNXT? Or is this just a one-off [inaudible]?
I know Altruist. They’re still our client. Think of what Altruist has done and what almost any self-clearing firm is doing — they’re looking at the demand curve and they’re seeing the pieces that they’re better off building themselves versus buying or leasing from someone else. Altruist still uses BetaNXT’s client communications piece. They’re still using a lot of the cost basis work that we provide for them. They just happen to have a fairly narrowly defined, well-defined, for a specific set of clients that were not being particularly well-served by the rest of the industry that Altruist designed their custody platform to do.
Candidly, a lot of their clients, as they grow and become more complex, won’t stay Altruist clients. They’ll go on to a bigger or better platform, or Altruist will have to grow its platform to more scale to be able to handle that. But it goes back to the same point: Understanding the demand of the clients you’re trying to serve and then bringing it together.
I’ll give you another example. BetaNXT didn’t do mutual fund sub-accounting. It’s a very straightforward process, but it had never been built into the BetaNXT repertoire. When we bought BetaNXT, we said to do this; we listened to the clients. The client, in this particular case, Wells Fargo, says: “We’re having to deal with mutual fund subaccounting separately, and they’re using all the data that exists inside BetaNXT. Why don’t you do it for us?”
We could have built that inside. But instead of building it inside BetaNXT, we simply went out and found the best available third-party provider, in this case, a company called Envision out in California, and built a partnership with them so that we could connect what they were doing, which was the best in class, to what BetaNXT was doing in terms of structured data architecture and servicing Wells Fargo in a way that was completely transparent to them.
As far as Wells Fargo was concerned, it was all BetaNXT because we did all the work to make sure that the data structures that Envision was using matched the data structures that Wells Fargo was having BetaNXT. We figure out what serves the client best. If Altruist wants to come to us and say, “We changed our mind; we want you to do our fixed income processing because it’s not part of our platform,” we’d make that work.
No, Altruist is not a headwind; it’s the smart guys who are listening to their clients, building what they can build in-house, and working to outsource the things they don’t want to build in-house. It makes perfect sense. And it’s the way the rest of the market is going to go as well. I can see the whole trust platform happening in the same way as well because there are a lot of clients in the marketplace who are saying: “We don’t like the fact that all of our P&I accounting is being done over there and all of our normal processing works on here and we can’t show them together to the client.” I anticipate that’s going to happen as well.
Now you open a big can of worms that we get involved in a lot when it comes to trust accounting and agency accounting. And more and more companies have all of those. They’ve got a corporate IRA, they’ve got a trust business, they’ve got a bank, and they’ve got to figure that out. Up until now, it’s always been the case where you try to keep as many accounts as you can off the trust platform because it was more expensive. We came into many companies where they had everything on the trust platform because it was simpler, but they were wasting a lot of money — millions of dollars — because the account fees were eating them up and we had to move those accounts over to the agency platform, then build customs integration between them so they could then see that. Building out some capability where… At BetaNXT, do you see that with your keiretsu — linking these companies — they could provide a one-stop-shop, a single pane of glass across trust and agency accounting?
That’s one of the things we’re working on now. In some of the research we’re doing now, we’re looking at the data structures that underlie P&I accounting and what you have to do there. The data structures and the OCC regulatory structures require those things to be done differently. Can we translate those into ways that will make these data structures work together? We’re working on the order is the answer. There have been companies that have tried this before — SEI, most famously. I think we can do this. I think it just takes some new thinking in terms of how to frame what the client wants to see. Here’s what the client doesn’t want to see: “I can’t explain that to you because that’s not in my bailiwick.” The client wants to see that we understand his or her portfolio across all of its component pieces. That’s what they’re expecting us to do.
They have high expectations that aren’t always met, which is one of the reasons why they need consultants. There is so much going on and there isn’t enough cooperation. And everybody wants their application or their platform to be the single pane of glass. That’s when you start getting into the fighting between these back-end platforms that don’t want to share data and don’t want to provide the best capabilities for their clients. That’s where we often come in. But if you can build something like that, I could see people beating a path to your door.
We’re a little bit academic in the sense that we somehow step away from the cold face long enough to look at the bigger picture and figure out what, from a data science perspective, needs to happen here. At Motive Partners, we have something called Motive Create, which is a set of people who have been the best mathematicians, the best computer scientists, and the best data scientists we have. We pull them offline from our portfolio company sometimes and sometimes we recruit them directly from academia or other firms and from Google, which has been our greatest stomping ground. We bring them together, and we pose this kind of problem to them.
We say: “We’re not asking you to make a profit, we’re asking you to go figure out this problem.” We give them a chance to go away, think about it, and come back with a solution that has broad ramifications. Those solutions can then become the foundation for how we do trust accounting, for example, and how we can rationalize the reporting that we’re doing for agency accounting and the reporting we’re doing for trust accounting in a way that makes sense for the client. And of course, the new tool in that space is AI. We’re working that order pretty hard.
When I first went into this, I was skeptical. What I have gleaned so far from this, though, is that AI can be a magnificent set of tools to help us solve this problem. This problem is the disparate sets of data that the client needs access to and that we need to bring together to be able to do something as straightforward as a corporate action without reconciliation or trust accounting in a way that the client can explain the overall effect on the portfolio. The only way I trust AI to do that is if we can have a controlled, highly curated set of data that we control the training of the large language models on. Your AI is only as good as the data you’re training those models with. If you don’t control that data and structure it in a way that you’re sure about, you’ll wind up with hallucinogenic egg on your face in a big way.
Sure. With corporate actions and trust data, you see uses for AI. Do you see any other areas that you interact with where AI could be valuable?
A huge one is client reporting. Again, back to that idea of eliminating the swivel chair. In many cases, it’s not that the data doesn’t exist or that the data is not compatible; it’s that we don’t bring the data together in the right places in the workflow. AI can help you find those places to bring the data together at the right time. Something as straightforward as when a client service person picks up the phone and talks to an enterprise about what’s happening in the clearance of the severance process. To know how that works and to have that client service person be prompted to say, “The data that you need to see is in this space at this timeframe and it will bring it together to you here.”
That kind of streamlining is something AI does beautifully well. We have a hard time as human beings doing it ourselves because we’re not in all those places at the same time. AI can help us do that and — going back to the same point — in a highly controlled, curated dataset. Would I want to do that if that large language model was being exposed to the web and all the vagaries of the web? No, I wouldn’t. I would only do that if I had certainty. That’s the number one thing we have to do as we employ AI to make sure we stay in control of where that data is coming from, how it’s being curated, and who has access to it so that you don’t wind up creating more problems than you solve.
Amen! And on that note, Stephen, we are running out of time. Where can our audience find out more information about BetaNXT?
BetaNXT.com on the web is the way to go.
All right. Stephen, thanks so much. I really appreciate it. I know you’re super busy. Thanks for being here.
Goodbye. Good talking to you, Craig. I look forward to doing it again.
Source: WealthTech Today
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