 Hey everyone, it's theCUBE, the leader in live tech coverage covering day one of Smith Lake Summit 2023 from Caesar's Forum in Las Vegas. Lisa Martin with Dave Vellante. Dave, we've had some great conversations so far as we always do. We're going to be talking about data trends in the financial services industry next. Always an interesting industry to break down. Yeah, because financial service companies are tech companies. They've always been very data driven. They lead the trend. So I'm excited for this. Yeah, we're going to hear some trends. We've got one of our alumni back with us, Rinesh Patel, global head of financial services at Smith Lake. Ainsley Simmons joins as well, the president at Pershing X. It's great to have you both on the program. Thank you. Thank you for having us. First question is the same one to both of you. Rinesh, we'll start with you and then Ainsley will go to you. When you're looking at the financial services industry as a whole, how are customers currently leveraging data? And what are some of the challenges with data that are coming to you to help solve? Rinesh? It's a great question. Ainsley was speaking about this earlier on today. I think if you take a typical asset manager, bank or insurer today, they've incrementally added technologies over time as and when the problem has arisen. So today you have a lot of systems that make up a typical landscape in those institutions. A lot of interdependency between those systems, but minimum interoperability. These systems don't speak to each other. So what you're doing is spending a lot of time, cost and money, literally pushing and pulling data in and out of systems to support the requirements of customers and their customers. And I think that's creating a lot of friction. It means that you're unable to support your customers as effective as you would like. That's really creating a lot of contention in the industry right now. Ainsley, you're saying similar things? Yeah, very similar. So my business is in the wealth management business, so advisors serving clients. And what we're talking about this lack of interoperability is a real problem for advisors as well. So they have data in somewhere between eight to 12 applications that are locked in those applications. So when you phone and you ask a question, they really don't know the last thing you did or the last thing they were working on. And that is really frustrating for individual investors. And it really puts advisors back on their heels trying to answer their questions. So this is a huge problem, and we're going to get to woe, but talk about your role inside of BNY as a startup. Was it to solve this specific problem? It was. So PershingX is the startup. It's the division within BNY Mellon that was started just over a year and a half ago. I was the first employee. And we started this FinTech in the bank to solve this problem because we have clients. Bank of New York Mellon has a business called Pershing. It's a custodian, eight or 900 advisory firm clients in the U.S., and they kept talking about this problem where nothing connects. They have these eight to 12 different applications to do their work, and it's gotten so bad. The industry's given it a name. It's called the swivel chair. Right, and so I liken it to the security business. When you look at the taxonomy of the security landscape, Opti does this great chart. It'll make your eyes bleed. And I think your business is very similar. You've got dozens and dozens, maybe it's even hundreds of applications and different services, and they're all bespoke individual items that now you guys, so I'm interested in how you attacked that problem because you had this mess on the table. We do. And it's got to be more than just calling Snowflake, but I know that's part of it. Well, that was definitely part of it. Calling Snowflake was a really big, important decision we made about a year ago. But what we're building, what we've built, I have to stop saying building because we've actually launched it. What we have built is the industry's first operating system for wealth management technology. So just like an operating system on your phone where you can search across applications, you get alerts across applications, and it helps pass information from application to application, we've built that for the advisor desktop. So we have native applications, so you can use our trading, you can use our financial planning, but we also connect to third party applications on the operating system. And the magic behind that operating system is a consolidated interoperable data layer. Therefore, Snowflake was absolutely one of our first phone calls because we knew to have a really great operating system. We needed an unencumbered data architecture and cloud-based data platform. And the power of what A&Z is talking about, the client data enriched with third party data, leveraging a data experience like data sharing, enables that interoperability that doesn't exist today, gives those customers deeper differentiating, timely insights. So that's the real value that PershingX is going to bring to the market and customers. So, okay, so who are the users? Is it really the wealth managers? It's the advisor. Now, very interestingly, so we came into this thing, we're going to build an advisor operating system desktop. I had an advisory council of 25 firms guiding us along the way. And my second meeting with them, they said, would you please add an investor site to this? Because if you have this really great interconnected platform with this really great data layer, boy, we would sure love to give that to our end clients, our investors. So we're now working on that and we're going to be debuting that sometime next year. Why Snowflake? Why was that, you talked about how integral of a component it is to the success of what you've built, but why? Yeah, I think two big reasons. One, this common shared vision of interoperability was really important. And when I was doing our research, we were doing our research, looking for firms that thought that way, Snowflake rose to the top. The second thing is we were led by our clients. So we have many billion-dollar-plus wealth advisory firms on the Persian custody platform. And they already were looking at Snowflake, dewing POCs, some of them are shared clients already. So they were walking us down the road to making this decision because I think they saw the same thing, a firm that could scale, that had a robust financial services vertical that knew the industry. Those were all really important factors. So what's the business model? For Wove, or I'm sure you know the business model for Snowflake. No, for Person X. Yeah, so Wove is going to be software SaaS for our applications and our operating system and our data. And then we also offer investment products, models, portfolio construction, individual investment securities, ETFs, mutual funds. Those will be on assets under management, basis points on assets under management. So two different ways to monetize. So the strategies to consolidate all these bespoke tools. Correct. And who do you sell to? So we sell to advisory firms. Sometimes they're large and they have many, many individual advisory firms underneath them, aggregators, that's been a big trend in the industry. Sometimes it's just a really successful advisory firm that was started by someone in the family and has passed on three generations and manages a lot of wealth. So full spectrum? Full spectrum. Small, medium, and large. Absolutely, yeah. But if, go ahead, please. Oh, thank you, Dave. If my advisor has access to this, do I as well as an investor? Well, that's what I was just saying. You're about, we're going to be looking at the same. But we're going to be adding that. That's why you're like. Because what you just said is why they want it so badly. They want to make sure that everyone's looking at the same data. And there's never that awful feeling where a client's like, well, wait, my number is different than the number, you know, as an advisor I see on my system, which happens all the time today. Well, then that allows you to do your own what ifs. When that's an assumption changes. But I mean, think about how many, typically you sit down with your financial advisor or maybe twice a year, but typically most people are once a year. Think about how many things change in a year. Kid transfers college, people have a child. I mean, so many assumptions change, but you have that one snapshot. So now you could make this self-serve. It can be so dynamic, which is really the vision here, is that your financial life becomes incredibly dynamic because you still want the advice from a trusted advisor. You still want someone to be guiding you, but you also want to trust and verify and make sure you know what's going on yourself. And we're seeing that is absolutely a trend. And all data sources, right? I mean, so it's not because typically you don't have all your assets in one place. You've got real estate, you've got 401K maybe somewhere else, you got your crypto. Right, and well, and that's part of those snowflake value prop is being able to tap into the ecosystem and leverage. So, talk about the marketplace. That's the value. We take the client data, we enrich that with the data coming from the third parties from the marketplace. And that allows us to be able to provide those advisors deeper differentiating timely insights to make those informed decisions in a very complex condition. Do you have competition? Yeah, sure we do. Yeah, there's many firms that market themselves as advisory platforms. The issue is they've had to get there through acquisition. So they've bought 12, 14, 18 little pieces of software. When you acquire companies at that pace, it's very difficult to go back and build that interoperability. It's very difficult. I'm sure they're working on it, but it's very difficult. What's different about us is we have started with that as a design principle. Ground up, ground up. Ground up, and it is our North Star in all of our decisions. So every time we're thinking about something, we're thinking, does this connect? Not just, is this a great feature? Did it start inside the bank and then you spun it out or was it? No, we're still inside the bank. So it is a startup. It's funded by the Bank of New York Bank. But maybe, let me rephrase, in terms of the initial value prop. Idea? Yeah, was it sort of dog-fooding and then like AWS and hey, actually we can sell this to the world or was it, hey, this would be a good idea to solve? Problem solved. Well, it's a little bit of both because the bank has Pershing, which is a clearing and custody platform. That's part of the solution. So part of what a customer needs is already there. But what it came from was years of hearing what else they wanted and what they wished to be true. And then realizing, oh my goodness, that could be a new line of business. So you sell it as an integrated package or not necessarily? You can buy it on a standalone basis. You don't have to custody with Pershing. But if you do custody with Pershing, yeah, we'll give you a discount. Pershing on Pershing. Yeah, if you're buying both, we'll make it attractive for you. What's in the name, Pershing X? Oh, that was really just because we didn't know what the platform was going to be. And we wanted to make it clear that it was not based Pershing, but it was something new. And it kind of just stuck. But the platform's name is Wove. That's how we're going to market. Because again, as I said, we will have customers that don't custody with Pershing. So that custody at other custodians. So we didn't want to carry the Pershing name into the market. You know, I know it's a little ahead of the game because you talked about investors having access. You envision that you will ultimately be able to interact with Wove through a natural language interface. Well boy, oh boy. We discussed this earlier on today. So if you think about the evolution that we're going through right now of data and large language models, AI, I think we're already on the cusp of exposing effectively natural language questions and answers using Snowflake as a capability. So if you're an advisor, you're able to type in into the application, ask a question and get those insights back in a language that's more custom to you. That certainly is the journey that we discussed earlier on today. Yeah, and even some of the features that were debuted this morning, like the ability to parse documents and find data out of those documents and then store them in the database. This is still a very paper centric business, not because the companies want it but because the regulators do. And so a lot of that technology coming out of, you know what Snowflake has been working on this year will be immediately applicable to us, which is again why we're so excited that we can sort of stay on and ahead of these trends as we're building out the platform. So that document, the applica- Aplica. Aplica capabilities, that's going to be great to parse that data, connect structured data, unstructured data, with again the client data, provide that insights back. Yeah, that's big in financial services, back office, insurance. Exactly. Okay, so how far away are we? Are we months, years, decades away from, I know it's not decades, from that natural language interaction. I think we're already there. I think if you think about the data that Snowflake has, the data our customers have, how they want to expose not just the data now but the intelligence to their customers to drive better decisions. I think the technology that exists now, the large language models, the generative AI, the capabilities that we're building on top to really make value from that investment data customers have done, we're already there. Yeah, I think in financial services, the hoop that we get to jump through, that other industries don't have to is again regulatory, security, Bank of New York Mellon manages about a quarter of global wealth. So we have to be very careful with our clients' information. So again, one of the reasons we wanted to work with Snowflake is the investment that's being made in the safety and security of the platform because that really matters to us. And so we'll jump through those hoops together, we'll figure out when the right time, but it is absolutely not years. That's good. Yeah, it is absolutely good. It is good. Rinesh, customers in the financial services sector at Snowflake account for about a quarter of Snowflake's revenue. The story that we're learning from Ainsley about CricingX and WoV, how similar is that to other customers in financial services? Are they leading edge? I think it's pretty consistent. I think the picture across wealth management firms, asset management banks, it's pretty much consistent. It's a series of myriad effectively of inorganic and organic investment decisions over time that's led to that lack of interoperability. And I think that's what we're unpicking through the financial services data cloud. Bringing a fragmented ecosystem, which historically was connected through the physical movement of data, now leveraging capabilities like data sharing, where they're no longer physically moving their problems across to the counterparties. They're now more interoperable, they're now reaping the benefits of that interaction. Interoperability, don't underestimate it. Don't underestimate it. No, Ainsley, Rinesh, great to have you guys on the program. Thank you for sharing the story of CricingX, why you launched the company, the catalyst, how Snowflake is powering that, and what it's going to enable folks to do now and in the near future. We appreciate your insights and your time. Thank you. Thank you, thank you so much. Our pleasure. For our guest and for Dave Vellante, I'm Lisa Martin. After a short break, come back to theCUBE, Snowflake Premier Technology Partner, SQL DBM is going to be here with customer PSL group. They're going to talk about the partnership, they're going to talk about what's in it for customers, and how the collaboration is crucial to the size of data platforms. We also want to remind you, you can find all of our Snowflake sessions as well as all CUBE events at theCUBE.net. You're watching theCUBE, the leader in live tech coverage.