00:25:26 · Jenny Johnson
[00:25:26] S1: Well, first of all, you're buying these at multiples, so you're assuming a good growth. If you don't get growth, you're really in trouble, because believe me, they're pretty good multiples, especially in the private markets. Although, I have to say, because we were really early, we got them at very good prices. I would argue that Lexington, we definitely paid full price at the time, but we hit the absolute sweet spot for secondary PE, which meant that they actually grew faster than even our models. So that ended up being a really tremendous deal for us. But at the time, it was certainly fully priced for the size of assets that they were. You know, I think that what is lost on some people is that the mechanism of paying somebody in the private markets with carry, and carry is embedded and doesn't get paid for years, you have an unbelievably good natural retention that you don't have in traditional when you buy a traditional asset manager. You don't have a natural retention where they have multiple years waiting to get paid out for investments they made five years earlier or ten years earlier. To answer the question, in most cases, we did cash, maybe cash with debt. And then in the case of the Putnam deal, we actually did a bunch of Franklin stock. They wanted Franklin stock. The Great West Life had realized this trend of needing to be a big scale manager in order to get on these platforms. They could see the consolidation. And the problem was, Putnam had great performance, but they were just subscale. And so, you know, I think we've taken the equity team or the total assets there from 136,000,000,000 to over $220,000,000,000 And it's really because we're able to bring this high performing team onto platforms that they just were too subscale to get on those platforms. And so we did most of that deal. They were looking to diversify. They wanted to hold stock in an asset management company. They were looking to diversify how to do that. Instead of having just Putnam, they wanted to own a broader asset manager. So we did that with stock.
00:27:33 · Molly O'Shea
[00:27:33] S0: How good is AI at real professional work? Mercor AI Productivity Index, or APEX, tracks it with every major Frontier model release. Bill with partners like Harvey and Cognition. See where the frontier actually stands at mercor.com/apex. Today's episode is sponsored by VCX by Fundrise, the public ticker for private tech, allowing investors of all sizes to invest in venture capital. Learn more at getvcx.com. Public is a multi asset investing platform where you can automate your investing with AI agents. Create your own custom agent with a simple prompt. Agents can monitor markets, execute trading strategies, and manage your cash across stocks, bonds, options, crypto, and more. Want to buy at market close and sell the next day is open? Just tell your agent. Automate your investing at public.com. Founders scale faster on Deel. Set up payroll for any country in minutes. Hire anyone, anywhere. Get visas handled fast and get back to building. Visit deal.com/sorcery. That's deel.com/sorcery. Let's talk about the modernization of asset management. One of these, I think, key part was Lexington. I don't know if you remember, but I certainly remember when the markets were down and I was working at a VC fund and no one had a DPI and we were all trying to make ourselves feel better. Lexington had swooped in and bought up like 10% of our portfolio and gave liquidity to our LPs, which was fantastic. They did a good job, and I'm sure they're happy about it. Another part of that is tokenization. We haven't talked about tokenization yet. I know you've talked about this a bunch. So what did you see with tokenization? Again, having run technology and operations, I think I
00:29:20 · Jenny Johnson
[00:29:20] S1: had an advantage in the seat on understanding why blockchain was so important, and I genuinely believe it will replace the rails in financial services. It'll be slow because it forces the change of a bunch of business models and the toll takers who take a fee on a transaction. But it basically does three things really well. It has a source of truth, and anybody who runs a back office or tech department understands we're still running well, we're not, but a lot of big financial services firms still run mainframes, which means you have batch processing at night, which means your data is not updated until sometime in the middle of the night. With blockchain, it's immediate. And so there's a huge cost in firms to reconcile data between systems, and then you have to go reconcile the transaction with your counterparty. That all goes away with blockchain. There's just one source of truth updated immediately that everybody goes to. The second thing, it has the ability to program these smart contracts. So whatever terms you and I agree, if this threshold meets you have to pay me collateral, or this one I have to pay you collateral, all of that gets programmed in. Whereas pre blockchain, that is sitting in a document somewhere, or you have to go and try to build it into the transaction, but it's really hard to do. So it tends to be in a document somebody is following, and they'll say, Oh, let me go collect collateral you owe to me. That goes away. It immediately is paid. And the third thing is the ability to make a payment. So, I looked at that and said, Well, this is a no brainer. This is what we do in this business in the back office, and so this is hugely efficient. And when we came out with the, first tokenized natively on chain tokenized money market fund that the SEC approved, they had us parallel process on our old transfer agency system, our old shareholder record keeping system, and our blockchain system. And a couple of things. We were still one of the few firms, I think there were only two of us, still running the old system in house. And so we were able to look at the parallel processing, and we were astonished by how much more cost effective it was to run it on chain.
00:31:22 · Jenny Johnson
And we looked at that, like if you open one of our traditional money market funds, need $500 to open an account, because anything below that, the other shareholders are subsidizing your servicing fees. Whereas we did it on the blockchain system, you can open an account for $20 We probably can go down to $5 because it's just that much more efficient to run. So we look at it and think that the financial innovation that's going to happen is going to be really interesting and significant. One is you're going to have 20 fourseven trading. It's going to be atomic settlement. And you're going to have a lot of innovation that's going to happen because of the ability to program. And now add AI to that. You can build your logic of a trading pattern in there. And so we're big fans. Our tokenized money market fund, to give you an idea, it calculates interest every second. If you're a hedge fund and you use it as collateral and you hold it for four hours, twenty two minutes and thirty two seconds, we'll pay you that interest. Your cash that you earn that day is paid in your account at the end of the day. On a traditional money market fund, it's accrued all month, but you can't get to that cash until the end of the month. If you're a corporate treasurer, that's kind of significant. The ability to access that cash or even an investor, like a portfolio manager, and you're using that as senior cash and as the cash comes in, you can actually move it and use it in a portfolio. So it just gives you a little glimpse of the innovation that's going to come because of tokenization.
00:32:49 · Molly O'Shea
[00:32:49] S0: You embraced this super early, and really embraced it. I know you're also embracing AI and AI agents. You have over 1,000 AI agents for 800 plus investment professionals. Are there any areas where you're looking for AI to create more efficiencies internally? Where are the pain points for you?
00:33:08 · Jenny Johnson
[00:33:08] S1: I bucket AI in a few places. First of all, on the investment side, real win is making us better investors. Right? So analysts more efficient, so they're not spending as much time on admin, so they're actually spending time talking to companies, doing more research, maybe even covering more companies. And so it is all about improving investment performance. Any cost savings there is insignificant to the benefit of just improving investment performance. With respect to distribution, it is actually about growth. So we had a partnership with Microsoft that they were excited to do. They actually gave us free resources because it was such a sophisticated challenge and solution from a technical standpoint. Simple problem, right? What your issue in sales? I want to meet the right clients and have the right conversations. That's essentially what you're trying to achieve. But it's actually a really difficult technical solution because it requires you to have multiple AI agents that talk to each other and are coordinating with each other. And then it requires you to go out and get a bunch of different systems to pull in data. So you might need your product system. You might want a system that shows you a holding of, say, a financial advisor. So that firm may give us a feed on that. So I'll look at what the holdings are. I'll view our products. I might go to social media just to make sure that I can talk to that client about whatever's important to them so I'm updated on it. I'm going to go to some of the rating agencies on there, the Morningstar and others, to understand as part of the products what are the best opportunities. And so Microsoft was excited about it. What we've seen in the early results is 23% uplift in number of clients that one of our market leaders is visiting and an 11% uptake or increase in sales. So we think that's just going to get better and better. So that's distribution. Now where's the cost savings part? The cost savings part comes in the back office. It doesn't actually mean you have that much less people. I think you just do more. And in the case of technology, what's exciting is you have AI writing the code. I've never talked to a CIO who runs a technology department that doesn't say, Yeah, we got all the projects the business wanted done this year. It's all about prioritization.