Franklin Templeton CEO on SpaceX, Anthropic, Circular Deals & the State of the Market
- Jenny Johnson’s constructive market view rests on earnings and cash flow, alongside caution on leverage and sticky inflation. She thinks roughly 70% of companies beat earnings projections and sees markets broadening beyond hyperscalers. The 2% productivity reading, she argues, reflects earlier technologies; meaningful AI contributions to earnings still lie ahead because adoption requires organized data and “change management.”
- Johnson favors shorter-term AI financing and would personally avoid longer-term data-center financing tied to today’s technology. Extrapolating current chip and energy requirements for 20 or 30 years overlooks the innovation that demand encourages. Today’s borrowers have substantial earnings, but circular financing and unclear revenue recognition require scrutiny: “Know your stuff as you’re making those investments.”
- Franklin Templeton’s SpaceX and Anthropic positions came through late-stage investing intended to recover the old IPO return opportunity. Companies staying private longer meant portfolio managers were missing their “IPO kickers.” Johnson says mutual funds or ETFs can hold up to 15% illiquid assets, but suggests 6%, 7% or 8% to leave room for market movements.
- Johnson is enthusiastic about SpaceX’s innovation, citing Starlink’s usefulness and Musk’s work in space and robotics. She says colonizing Mars is quite possible, while emphasizing “a lot of key-man risk with Elon.” She does not directly endorse Musk’s separate claim that SpaceX will become the most profitable company on Earth.
- Client consolidation underpins the 17 acquisitions in six years cited by O’Shea. The $4.5 billion Legg Mason deal balanced wealth and institutional channels at 50/50; Johnson estimates Canvas grew from about $2.5 billion to $30 billion in roughly four years. She acknowledges Lexington was “fully priced,” but secondary private-equity growth exceeded their models.
- Tokenization’s clearest benefit in Johnson’s account is lower servicing costs and faster access to earned cash. Franklin’s traditional money-market fund requires $500 to open an account; its blockchain version opens at $20 and probably could reach $5. Second-by-second interest calculation and daily cash payments illustrate why she believes blockchain “will replace the rails in financial services.”
- AI agents are already producing an early sales result, while their eventual contribution to model-provider revenue remains uncertain. A Microsoft-supported deployment delivered 23% more client visits and 11% higher sales in early results. Johnson says firms will need to consider agent frequency and whether some queries can use free models; O’Shea describes governance that routes requests between models and cites companies shifting to 99% open-weight or open-source usage.
1. Earnings are holding up before AI lifts productivity
- Johnson separates “noise” around AI, circular financing and revenue recognition from the broader economy. Inflation is “probably pretty sticky” and rates probably stay higher; today’s level is unusual against the last 25 years, less so historically. Leveraged businesses face pressure, while the US consumer remains strong. She thinks “something like 70%” of companies beat earnings projections and sees markets broadening beyond hyperscalers.
- Her geopolitical example is the $20,000 drone that can bring a tanker to a halt, make insurance hard to obtain and effectively stop oil moving through the Strait of Hormuz. More oil is getting through than expected, but she sees no quick resolution in the Middle East or Russia–Ukraine. US–China relations look more constructive, though she says each country is heading in its own direction and there are lines neither will cross. The US needs China for rare earths; China needs US consumers for its manufactured goods.
- AI is her “biggest growth lever,” but Johnson attributes the current 2% productivity reading to earlier digitization and cloud adoption. Running technology taught her that the challenges are data quality and organization—not the system integration people often assume—and “change management,” because “people don’t like change.” Meaningful AI contributions to earnings will take time; that remaining opportunity supports her optimism.
- Her jobs argument reaches back to a 1997 BusinessWeek cover predicting the internet would eliminate brokers: advisers now provide broader financial planning. Efficiency comes first, then employee creativity. Wearing basic Ray-Ban Meta glasses golfing, she wondered why they could not find her ball; her programmer son is working on an app. “We find new things that we can’t imagine initially.”
2. Long-term AI financing bets on today’s technology
- O’Shea’s challenge, citing Ken Griffin, is whether chip supply, demand and obsolescence undermine the buildout. Johnson recalls a Gartner curve—she is unsure of its exact name—of excitement, disillusionment and recovery: “So the question is where are we on that curve?” She sees “a frothiness in some areas,” yet distinguishes today’s large, cash-generating borrowers from internet-bubble businesses without revenue.
- Her financing preference is shorter term; she personally would avoid longer-term data-center financing. Extrapolating today’s chip and energy requirements for 20 or 30 years assumes insufficient innovation precisely when demand encourages breakthroughs. She thinks Griffin is “probably right on that piece of it.” Revenue recognition also leaves company comparisons unclear: “Know your stuff as you’re making those investments.” That supports her preference for active management.
3. Longer paths to IPO drove SpaceX and Anthropic exposure
- Companies staying private longer deprived portfolio managers of their “IPO kickers,” Johnson explains, prompting late-stage investments including SpaceX and Anthropic. She says mutual funds or ETFs can hold up to 15% illiquid assets but might run at 6%, 7% or 8% to avoid a market-driven breach. Client interest subsequently prompted a venture group that can invest alongside traditional portfolio managers.
- O’Shea asks whether SpaceX’s Starlink, launch economics and AI positioning support Musk’s extraordinary profitability claim. Johnson does not directly assess that forecast; she first cautions against fashionable labels, noting that Franklin Resources owed its name to the 1970s appeal of gold and “resources.” Her instruction is “stick to your knitting and say what you are.” Her concrete customer endorsement is Starlink, “a game changer” for internet access at her Montana property.
- Johnson credits Musk with challenging the system around space investment and driving cost efficiency. She says his Mars ambition may not arrive on schedule, but “he often delivers.” She sees colonizing Mars as quite possible and points to robotics as part of that vision, while emphasizing “a lot of key-man risk with Elon.” Her closing choice of Musk as the closest modern Benjamin Franklin carries the qualification that there is “no perfect match.”
- Johnson traces the pooled-fund idea to giving ordinary investors access to equity-market returns through expert advice, reasonable prices and diversification. Her father took over the Franklin Funds subsidiary with $2.5 million in AUM and $10,000 in revenue in 1955; it took until 1983 or 1984 to reach $1 billion. She sees a parallel in private markets and wants access to be fairer, while recognizing these are “absolutely illiquid vehicles.”
4. Acquisitions buy distribution as clients consolidate managers
- The $4.5 billion Legg Mason acquisition, which O’Shea says doubled AUM, filled core fixed-income and private-market gaps, including through Clarion Partners. Franklin’s 75% wealth/25% institutional channel mix met Legg Mason’s inverse, producing a 50/50 balance. The deal was announced five days after Johnson became CEO, after a year of work; COVID lockdowns followed three weeks later. She held to the strategic case despite falling markets. Selecting the “best athletes” across teams moved online, and the deal closed 60 days early.
- O’Shea cites 17 acquisitions in six years; Johnson says the logic is capability and distribution as clients choose fewer managers. Infrastructure is the capability she says remains incomplete. O’Shaughnessy Asset Management’s Canvas platform added tax-efficient separately managed accounts and technology usable over active strategies. She estimates Canvas went from about $2.5 billion at acquisition to $30 billion roughly four years later.
- Lexington Partners and Clarion Partners have more than doubled since acquisition. Johnson recalls Benefit Street Partners at roughly $26 billion when purchased; private credit now totals just under $100 billion, including subsequent acquisitions. Private credit contains distinct segments requiring origination capabilities. The latest asset-backed team acquisition filled a gap where clients were interested and spreads looked attractive.
- Deals usually used cash, sometimes with debt; part of the Putnam deal was paid with Franklin stock because Great-West Life wanted broader asset-manager exposure. Johnson estimates Putnam grew from roughly $136 billion to over $220 billion as Franklin opened previously inaccessible platforms. Lexington was “fully priced,” but growth in secondary private equity beat models. Private-market carry creates natural retention through payouts years later, while Franklin’s wealth distribution helps acquired teams reach a different buyer.
5. Tokenization changes servicing costs and cash access
- Johnson believes blockchain “will replace the rails in financial services,” slowly because it changes business models and transaction-fee economics. Three functions support her claim: one immediately updated source of truth reduces reconciliation; smart contracts embed agreed terms; and the system makes payments. Her example is collateral owed under terms sitting in a document: programming those terms into the transaction makes payment immediate.
- Franklin’s SEC-approved, natively on-chain tokenized money-market fund initially ran alongside its legacy shareholder-recordkeeping system, allowing a direct cost comparison. Traditional accounts need $500 to avoid other shareholders subsidizing servicing; the blockchain version opens at $20 and probably could reach $5. Johnson expects 24/7 trading, atomic settlement and innovation from programmable transactions, potentially combined with AI.
- Interest is calculated every second: a hedge fund posting the fund as collateral for 4 hours, 22 minutes and 32 seconds earns interest for that holding period. Cash is paid daily, versus monthly access in a traditional money-market fund. For corporate treasurers and portfolio managers, the benefit is access to earned cash they can redeploy.
6. AI agents lift sales while governance could temper model revenue
- O’Shea cites more than 1,000 agents for 800-plus investment professionals. Johnson separates the objectives: better research and performance in investing, growth in distribution, and efficiency in operations. Investment-side cost savings are “insignificant” beside better performance. Coding assistance can clear more projects from the backlog; greater capacity need not mean materially fewer people. “I think you just do more.”
- A Microsoft partnership built coordinating agents combining adviser holdings, product data, ratings and client context to help salespeople “meet the right clients and have the right conversations.” Microsoft supplied free resources because of the technical challenge. Early results showed a market leader visiting 23% more clients and an 11% increase in sales.
- The revenue uncertainty emerges after experimentation: Johnson says firms will need to ask whether agents need to run, how frequently, and whether some queries can be handled by free models. O’Shea describes a governance layer that could route requests to a top or free model, then cites emerging companies that were overloaded after 14 trillion tokens before shifting to 99% open-weight or open-source models. She suggests frontier models may still be used for biosciences and other frontier projects.
Full transcript
1. Where is the market really headed?
Jenny Johnson, welcome to Sorcery.
Thanks for having me. It’s great to be here.
Well, thanks for having me in your super fancy, gorgeous New York City office.
We’re very excited. You’re in the Heritage Room, which is all about our history.
I know you guys like Benjamin Franklin, huh?
We do kind of like him. He was a stud. He was a pretty cool guy.
Yeah. I’m going to ask you a question about him later. But before we begin, I just want to give a nod to Franklin Templeton. You guys have been around for multiple generations. Your grandfather started in 1947, and you went from managing $2.5 million in AUM to $1.8 trillion in AUM, which is crazy. There’s a huge growth story behind it, and your story in particular: You started in the mailroom, and now you’re the CEO. I want to talk through all of that, but before we get to it, where are we in the state of the market? We have people saying we’re in a hidden bear market. There’s also all this talk about AI premiums and the big deals that are happening, and IPOs are getting pushed back. How do you consider all of this?
I think you have to break down a couple of things. Look, there’s a ton of noise in the AI and hyperscaler space. There’s noise around circular financing. There’s noise around how they’re doing revenue recognition, right? Let’s put that aside for a second.
You look at the economy, and I think inflation’s probably pretty sticky and rates are probably going to stay higher. But the current rate level is not unusual from a historical standpoint. It’s unusual for the last 25 years, but in history it’s not that unusual. You’re young, so you don’t remember the days when mortgages were much more expensive, and things still functioned. The rate environment is definitely higher, so if you built your business model around it or have a lot of leverage, that’s a concern. But if you’re a good cash-flowing company, the consumer is still very strong, particularly in the U.S.
Productivity is up; it’s at 2%. I don’t think any of that productivity story has anything to do with AI. It’s all technologies that have been around for a couple of decades: digitization, cloud services, all of those things. It takes a long time for new technology to be adopted in an organization. I always say, I ran technology at Franklin Templeton, and I tell people your 2 biggest challenges in technology are not what people will tell you. They’ll say it’s integration of systems. It’s actually the quality of your data and getting it organized. The second thing is change management, because people don’t like change. They don’t want to adopt new things. It’s a lot of effort on their side.
The AI we have today is going to take a while before you really see it being meaningful to companies’ earnings. That’s the upside I think we’re going to see happen. Back to the market: If you look outside the hyperscalers, you do see some broadening of markets, and you still see strong earnings. I think something like 70% of companies beat their projected earnings, so we’re still seeing good tailwinds around that.
Now, what are the headwinds? Obviously, it looks like it’s going to be tough for this war in the Middle East to end anytime soon. A $20,000 drone can essentially bring a tanker to a halt. If that happens, it’s hard to get insurance, and it effectively stops the oil getting through the Strait of Hormuz. Having said that, there’s actually a lot more getting through than I think people thought would happen. As I said, the economies—particularly in the U.S.—have been pretty well adjusted to oil at this price. But that’s probably going to stay there for a while, and frankly, I don’t see a quick resolution in Russia and Ukraine either.
2. Why AI is the biggest growth lever
We have to look at these as almost business as usual. I think the U.S. and China are much more constructive than we’ve been in the past. But having said that, I think it’s kind of a friendly-type thing. There are areas where you’re just not going to cross the line. China’s going to head in its direction; the U.S. is going to head in our direction. But we need each other, and we need them for rare earths. They need our economy and consumers to sell the things they manufacture. We’ll figure out ways to work well together.
What are the growth levers that you’re watching?
I think the biggest growth lever is AI. It is such a massive disruptor. Having said that, I’m a student of history, and I tend to be more optimistic about what this means. Every major new technology that comes in, if you go back and look in history, brings predictions of the demise of all the jobs. In 1997, the cover of BusinessWeek said the internet was going to eliminate the broker. Today, a financial adviser does more for their clients than ever. They’re no longer just an investment adviser. They’re a true financial planner, leveraging the internet and these tools to provide more services.
A lot of jobs that you couldn’t imagine will come about. What happens is that you make what you do today more efficient. But once you get it into employees’ hands, they start to think creatively. There are going to be a lot of things that we never imagined we would need or do. I was using Meta glasses recently, right? So I was—
Did you have the Kylie ones?
Are those the ones with the screen?
I don’t know.
Oh, yeah. No, you were saying the design ones. I got the basic Ray-Ban Meta ones, whatever. But I was on the golf course and I was like, “Why can’t these Meta glasses find my golf ball?” So I said to my son, “Hey, because he’s a programmer, could you make it?” He’s working on an app to do that right now. Did I ever know or think about it? And, by the way, it would leverage the iPhone, but you couldn’t have your iPhone; you need to have the Meta glasses. So suddenly, I’ve already come up with 3 other programs that I told my son he should go write.
We find new things that we can’t imagine initially. I’m not negative, but there is going to be this transition that we all have to be careful about. I do think there’s massive, massive upside, and that’s probably the biggest tailwind. Everybody talks about AI, but there’s a ton of other innovation going on. What’s happening in biosciences—
Oh, it’s major.
Major. The pipeline of new drugs, the customization of medicines, material sciences—there are a ton of things being done there, and a lot of innovation. They’re now talking about 4D printing, where it actually moves into place when it gets in the right position. Those are all big tailwinds that are the bull case.
3. Are we in an AI bubble?
Ken Griffin was just on stage at the Citadel Securities Conference, and of course they asked him about the AI bubble. One of the biggest points he made about this was that we just don’t know what’s going to happen with supply and demand, especially with chips. We’re making all these chips now. When are they going to expire? When is that going to falter? How do you make sense of this? I’m very curious because I’ve heard that you’re a student of history and you love history. We’ve been saying we’re in a bubble for 2 or 3 years now. When are we actually in the bubble? Have we been in the bubble the whole time? How do you make sense of bubbles as you see them throughout all these cycles?
When I was running the technology group, there was something Gartner had called the, uh, exuberance curve or something. I can’t remember exactly. It happens over and over: New technology, this is the greatest thing ever, it’s going to be the greatest thing. It goes all the way up. It’s so great, it’s so great. Boom. And everybody’s disillusioned by it. It’s terrible. And then it comes back up to where it sort of should be.
So the question is: Where are we on that curve?
It certainly feels like there is frothiness in some areas. Personally, if you’re betting on the need for energy based on today’s technology—both in manufacturing chips and in the production of energy—you’re assuming that for the next 20 or 30 years it doesn’t change dramatically.
But that's pretty unusual. When you get a demand, people innovate and you find tremendous advances. My instinct is, if I were to finance, I still would like the financing on the shorter term because these are still big, cash-flowing companies. These are not internet-bubble companies that didn’t have revenue. These companies have significant earnings, so they’re going to be able to pay their debt.
Would I go longer term on the financing for things like data centers or other things? I personally wouldn’t, because I think you’re betting on today’s technology and that we won’t innovate quickly. We see what’s happening with AI: it’s solving math problems that we’ve never been able to solve in history. I think you have to be a little careful on that, and I think Ken’s probably right on that piece of it.
On the other hand, we’ve talked a little bit about the accounting side. It’s a little unclear with some of these revenues, and how is it apples to oranges when you compare companies? You have to be really careful and know your stuff as you’re making those investments. That’s why I’m a big fan of active management.
Having said that, you probably leveraged AI while preparing for this podcast. I know when I’m preparing for something, I literally have a conversation back and forth, which opens up new thoughts for me. That would be difficult. Usually, I then hand it to my team of experts and say, “Validate these things,” because you can’t necessarily just take it for what it is, but it can lead you to how you think about stuff.
I think we all get a sense of how incredible this tool is and the opportunity with it, but it will take time. When it happens in companies and sectors, the leaders could leave others behind in those sectors.
4. How Franklin Templeton got into SpaceX and Anthropic
I think that’s how quickly this stuff is moving. Whatever metric you want to use for revenue, what we’re seeing from Anthropic and OpenAI is unseating a lot of incumbents and people you’d think would be winning in this day and age. Now their IPOs are getting delayed, and who knows why. Maybe it’s because they say things they don’t mean, or maybe they do mean them and we should listen.
I thought this was really interesting. I told you I did a lot of prep going into this. I listened to a lot of your interviews on podcasts and on the news, all over the place. There was one really interesting one that opened up this other realm of Franklin Templeton that I didn’t really know about, but kind of knew, right? It was when you were talking about the upcoming SpaceX IPO back in July or whenever it was, and how Franklin Templeton got into late-stage investments. Do you want to tell that story? I think it’s a good encapsulation of how Franklin Templeton runs.
Yeah. We’re headquartered in Silicon Valley, so we have a growth equity team there. As we all know, companies are waiting much longer to go public. Some of the portfolio managers said, “Boy, these IPO kickers we used to get that were a kicker to our performance—we’re not getting those. We should do some late-stage venture, because late-stage venture is what underwriting at the IPO level used to be.”
A mutual fund or an ETF can hold up to 15% illiquid assets. You don’t tend to run it at 15%, because you’d have a breach if the market moves, but you could do 6%, 7%, 8%. We started to invest in late-stage venture deals, and then some clients saw the deals we were in and said, “Hey, could you set up a fund?” We now have a venture group, and they’ll often invest alongside the venture fund with traditional portfolio managers who want exposure to late-stage venture.
So, I found out you guys had exposure to SpaceX.
We did. We did Anthropic. I mean, a bunch of them. Yes, exactly. If you’re there and you have connections with the entrepreneurs and the venture community—and you’re headquartered there—you’ve got to remember, your kids tend to go to school with these people. They’re in the neighborhood. They’re community people, and you get to know them. That allows you to have access to those deals.
5. The SpaceX question every investor is asking
SpaceX is a particularly interesting name because they came to the markets sooner than anyone else, and they have quite a diversified strategy. More often than not, they’re trying to label themselves as an AI company. We were talking about this earlier: the makeup of that revenue, whether it’s getting these data center contracts right before the IPO, the Starlink angle, getting to the consumer side of things, and then the launch costs that will bring down the economics of everything else.
For a company like SpaceX, what are you trying to watch out for? Do you think this one will become—I think Elon tweeted it will become the most profitable company on Earth by an order of magnitude.
There’s a lot in there. Let me first address one thing. Maybe we should look at history: everybody renames their business based on AI or dot-com. We just changed our parent company name from Franklin Resources to Franklin Templeton. I asked my dad, “Why were we ever called Franklin Resources?” He said, “Oh boy, in the 1970s, you couldn’t sell it. The stock market was terrible. You couldn’t sell anything, but you could do gold investing because there was high inflation. If you had ‘resources’ next to your name, that helped you in the stock market.” So there you go. It’s a trend people follow all the time. What I always say is, stick to your knitting and say what you are.
Having said that, I’ve used Starlink. I have a place in Montana, and it was a game changer for me because I could never get good high-speed internet. The portable Starlink is amazing, and everybody I’ve talked to who uses Starlink is a huge fan.
If you read Walter Isaacson’s book on Elon, you’d recognize how much he has changed space investment and travel, and really fought the system that was sort of gumming itself up. It’s all about innovation and cost efficiency. I honestly believe it, and Elon seems so focused on getting to Mars. He makes these statements and we all say, “Oh, that’s ridiculous.” Maybe he doesn’t get there right on time, but he often delivers.
Like flying cars.
Exactly. Although I saw a very funny flying car company that said, “Welcome to the race,” or whatever. The work he’s doing in robotics is amazing, all of which is needed for his vision to colonize Mars. I think it’s quite possible. Your only risk there is you have a lot of key-man risk with Elon. We all have to hope he stays healthy and can continue to innovate.
6. Closing a $4.5B deal in the middle of COVID
He’s a man of misery.
7. The strategy behind 17 acquisitions in 6 years
So I want to shift a little over to more of your career and coming into the CEO seat. You came into the CEO seat and immediately were leading one of the firm’s largest deals. This was the Legg Mason deal for $4.5 billion, and this also doubled your AUM. Walk me through that process, why you had the conviction, and the reasoning behind it. Then I definitely want to talk through your acquisition strategy, because I heard and saw that you guys have done 17 acquisitions in the last 6 years.
On the Legg Mason deal, there were parts of the market that we just knew we needed to fill out, and Legg Mason filled those things out. One, they had the largest category in core fixed income, and they had a huge franchise with core fixed income. We wanted to get bigger in private markets. We bought a private credit manager, and they had Clarion Partners, which is an outstanding real estate manager.
That got us into private markets. At the time, Franklin was 75% retail wealth channel and 25% institutional, and Legg Mason was exactly the opposite. We suddenly became 50% institutional clients and 50% wealth clients. That just balances out your business better.
For all those reasons, it made a ton of sense. The challenge was that the deal was announced 5 days after I became CEO. We’d obviously been working on it for a year. The problem was, 3 weeks later, everything was locked down with COVID, and of course the market tanked.
It was really interesting because it never occurred to me to think, “Oh, that’s too bad. We got this deal and locked it in.” Some of the articles said, “Oh, poor Franklin. They can’t get out of it.” If you’re getting into a deal because it’s a good strategic fit, you’re going to roll through those ups and downs. We knew it was an important strategic fit, and frankly, asset managers in down markets don’t tend to transact because they’re a great cash-flowing business and people know they’ll bounce right back with the market. So, we were really happy to do it regardless, but it meant there was much greater complexity in trying to close the deal.
When you do a deal, part of it is figuring out your talent. You’re going to have to reduce some roles because there’s a lot of overlap in corporate services, finance, HR, and legal. You’re trying to pick the best athletes and put together the best team. I think a big mistake acquirers make is assuming that their team is the best team. You really want to decide that you can pick the best athletes across the board.
Suddenly, we weren’t really able to travel and meet people, so you had to do everything over video. Fortunately for us, because we’re so global, we’d already adopted an environment where people were often on video in meetings. Now that’s standard, but back then people were really skeptical and didn’t really believe in it. It was already part of how we operated.
We ended up closing the deal 60 days early, which was kind of amazing at the time. I don’t think we ever lost faith that it was the right deal for us, and it turned out to be an amazing deal for us.
Of the 17 acquisitions you’ve done in the last 6 years, what are the themes? What are the reasons? I know you’re on this growth trajectory and all that. So, maybe talk through that, and then the higher-level goal.
Sure. First and foremost, it was about making sure we had the capabilities we needed to compete. A big trend in the industry is that clients are saying they want to work with fewer managers. A manager has to have a broader breadth of capability to be one of those fewer managers and offer more things. That’s where scale is really important. As I mentioned, we had categories we wanted to fill in.
The other acquisitions were about either product capability—and the only thing I’d say we don’t feel like we completely have today is infrastructure—or enhancing distribution. Otherwise, we’re probably the broadest asset manager in terms of breadth of capability. Maybe it was a technology tool, like Canvas at O’Shaughnessy Asset Management. They had a quant shop, but what was really interesting to us was the direct-indexing technology platform they’d created. It allows separately managed accounts to be tax-efficient, and because it was such excellent technology, we can now use it as an overlay on active strategies, which is pretty new.
I’d call that both a capability and a distribution opportunity, because there are clients who want separately managed accounts. They don’t want an ETF or a mutual fund. They want it in an SMA. That’s an example of that distribution capability. We bought a couple of wealth managers to bolt onto Fiduciary Trust, our wealth manager.
Lexington Partners brought us additional capabilities in the private markets, including secondary private equity. We’ve bought, I think, 3 bolt-on transactions for our private credit manager to ensure we have global scale, global reach, and capability. The crazy thing happening in private credit is that everybody talks about it like it’s one big asset class. But if you talk about fixed income, you’d say, “I’ve got high yield, mortgage-backed, asset-backed, investment grade.” Private credit is the same. You have to have those capabilities, which means you have to be able to originate.
Our most recent announcement was buying a team that does asset-backed lending. That was an area with pretty good spreads and a lot of client interest, and we just didn’t have the origination capability until we acquired them. Molly O'Shea
8. How Canvas grew from $2.5B to $30B
How do they grow once you acquire them? You mentioned OSAM and Patrick O’Shaughnessy as the manager. What happened with that after you acquired it?
The Canvas application was about $2.5 billion when we acquired them, and it’s now $30 billion. I think that’s probably 4 years later.
Wow.
That one’s done very well. Lexington has more than doubled since we acquired them. Clarion Partners, the real estate manager, has more than doubled.
We bought Benefit Street Partners when they were at $26 billion. We bought a couple of other firms, too, and now we have just under $100 billion in private credit. They’ve been successful. A lot of people are skeptical about traditional asset managers’ ability to have a cultural fit with private markets folks. There are obviously very different compensation structures and things, but that has actually worked really well for us, and our expertise in the wealth channel
As these guys are looking to expand into that wealth channel has been really helpful because that’s a very different sale from an institutional sale.
9. What makes an acquisition worth the multiple
Are most of these deals all cash? How do you structure them? If they’re getting enormous benefits after the transaction and growing four times or even more, how do you incentivize that?
First of all, you’re buying these at multiples, so you’re assuming good growth. If you don’t get growth, you’re really in trouble because 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’d argue that we definitely paid full price for Lexington at the time, but we hit the absolute sweet spot for secondary private equity, which meant they actually grew faster than even our models. That ended up being a tremendous deal for us, but at the time it was certainly fully priced for the size of the assets they had.
I think what’s 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—gives you unbelievably good natural retention that you don’t have in traditional asset management. When you buy a traditional asset manager, you don’t have natural retention where they’re waiting multiple years to get paid out for investments they made 5 or 10 years earlier.
In most cases, we paid cash, maybe with debt. In the case of the Putnam deal, we actually did a bunch of it with Franklin stock. Great-West Life had realized this trend of needing a manager with big scale to get onto these platforms. They could see the consolidation, and the problem was Putnam had great performance but was just subscale. I think we’ve taken the total assets there from about $136 billion to over $220 billion. We’ve been able to bring this high-performing team onto platforms they were just too subscale to get onto.
They were looking to diversify. They wanted to hold stock in an asset management company, and they wanted to diversify that way. Instead of having just Putnam, they wanted to own a broader asset manager. So, we did that with stock.
10. Why blockchain will rebuild finance
Let’s talk about the modernization of asset management. I think one 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. We were all trying to make ourselves feel better. Lexington had swooped in and bought up about 10% of our portfolio, which gave liquidity to our LPs. That was fantastic. They did a good job, and I’m sure they were happy about it.
Another part of that is tokenization. We haven’t talked about tokenization yet, and 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 had an advantage in the seat in understanding why blockchain was so important.
I genuinely believe it will replace the rails in financial services. It’ll be slow because it forces a change to a bunch of business models and to the toll takers who take a fee on a transaction. But it basically does 3 things really well.
It has a source of truth. Anybody who runs a back office or tech department understands that a lot of big financial services firms still run mainframes, which means batch processing at night. Your data isn’t updated until sometime in the middle of the night. With blockchain, it’s immediate. There’s a huge cost for firms to reconcile data between systems, and then you have to 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 is the ability to program smart contracts. Whatever terms you and I agree to—if this threshold is met, you have to pay me collateral, or if this one is met, I have to pay you collateral—all of that gets programmed in. Before blockchain, that was sitting in a document somewhere, or you had to try to build it into the transaction, which was really hard to do. So it tended to be in a document somebody was following, and they’d say, “Oh, let me go collect the collateral you owe me.” That goes away. It’s paid immediately.
The third thing is the ability to make a payment. I looked at that and said, “Well, this is a no-brainer. This is what we do in this business in the back office.” It’s hugely efficient. When we came out with the first natively on-chain tokenized money market fund that the SEC approved, they had us parallel-process it on our old transfer agency system, our old shareholder recordkeeping system, and our blockchain system.
A couple of things: we were still one of the few firms—I think there were only 2—running the old system in-house. We were able to look at the parallel processing, and we were astonished by how much more cost-effective it was to run on-chain. If you open one of our traditional money market funds, you need $500 to open an account, because below that, the other shareholders are subsidizing your servicing fees. On the blockchain system, you can open an account for $20. We probably can go down to $5 because it’s that much more efficient to run.
We think the financial innovation that’s going to happen will be really interesting and significant. One thing is 24/7 trading. It’s going to be atomic settlement, and there’ll be a lot of innovation because of the ability to program—and now add AI to that, so you can build your trading-pattern logic in there. We’re big fans.
Our tokenized money market fund calculates interest every second. If you’re a hedge fund and you use it as collateral and hold it for 4 hours, 22 minutes, and 32 seconds, we’ll pay you that interest. The cash you earn that day is paid into your account at the end of the day. With 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 significant. You can access that cash, or, as an investor or portfolio manager, use it as cash and move it into a portfolio as the cash comes in. That gives you a little glimpse of the innovation that’s going to come because of tokenization.
11. Will companies stop paying for top AI models?
I mean, 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?
I bucket AI into a few places. First of all, on the investment side, the real win is making us better investors. We want to make analysts more efficient, so they’re not spending as much time on admin and are spending time talking to companies, doing more research, and maybe even covering more companies. It’s all about improving investment performance. Any cost savings there are insignificant compared with the benefit of improving investment performance.
With respect to distribution, it’s actually about growth. 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. The problem is simple: What’s 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 a really difficult technical solution because it requires multiple AI agents that talk to each other and coordinate with each other. Then you need to pull in data from a bunch of different systems.
You might need your product system. You might want a system that shows you the holdings of a financial advisor, so you know what that firm holds. I’ll look at the holdings and our products. I might go to social media to make sure I can talk to that client about whatever’s important to them. I’ll go to some of the rating agencies, like Morningstar and others, to understand the best opportunities among our products.
Microsoft was excited about it, and what we’ve seen in the early results is a 23% uplift in the number of clients that one of our market leaders is visiting and an 11% increase in sales. We think that’s just going to get better and better.
Where does the cost savings come from? It comes in the back office. It doesn’t necessarily mean you have that many fewer people. I think you just do more. In technology, what’s exciting is having AI write the code. I’ve never talked to a CIO who runs a technology department who doesn’t say, “Yeah, we got all the projects the business wanted done this year.” It’s all about prioritization. If you can get more through the pipeline, that’s amazing. You’re not trying to save money; you’re trying to get more things through the pipeline. That’s how we bucket our approach to AI.
And then back to the initial question: What do you think about all these hyperscalers and their revenue models?
I think there are a couple of things we haven’t yet seen. Number one, the first thing you do is give your employees the AI tool and say, “Go run, go do these things, write agents.” That’s all good. Then, over time, it starts to cost you money. So now you ask, “What do all these agents need to run, and do they need to run as frequently as you set them up to run?” That governance and discipline—we don’t know what impact it ultimately has on these hyperscalers.
The second thing is that there are probably a whole bunch of queries an employee needs to do using AI that could be handled by free models.
Right, and so that governance layer of evaluating the request and saying, “You know what? This is a request we’re going to pay for the top model. This is one we’re just going to send to the free model”—all of those things will ultimately affect what the revenue looks like for these hyperscalers.
I’m seeing that in a lot of our conversations with these emerging companies. They’d rely on the frontier models, and then they’d have 14 trillion tokens and be overloaded. They’ve shifted their model, and now they’re totally efficient and running 99% on these open-weight, open-source models. So I think that’s probably going to make a big difference. But maybe we continue to use these frontier models for biosciences and for actual frontier projects.
12. Franklin Templeton’s 70-year climb
I know at the beginning I wanted to tie this back to a multigenerational nod to—I was going to say Benjamin Franklin Templeton, but Franklin Templeton. Your grandfather was sort of the first—
Since BEN is our stock, you can say that: Ben Franklin Templeton. Hashtag—well, it’s not hashtag, it’s cashtag, right? Your ticker is BEN on the New York Stock Exchange. We love that. I’d love to go through a little bit of the history of the firm, up to today.
My grandfather actually had a brokerage business, and he was a huge fan of Ben Franklin. He decided to create a subsidiary, so he decided to name it after Ben Franklin, and it was Franklin Funds.
My father served some time in the military. He came out when he was 24 or 25 years old. His older brother took over the brokerage business, and he said, “You know, I really want to do my own thing.” He talked to my grandfather and said, “I’d like to take over this subsidiary.” It had $2.5 million in assets under management and $10,000 in revenue.
He said, “You know, I was making $200 to $300 a month.” He said, “That wasn’t a bad salary for a new—” He kind of looked at himself, even though he’d done 4 years in the Army. “But that wasn’t a bad salary coming out.”
That was 1955. I was in college. I think it was probably 1983 or 1984 when I attended our first billion-dollar party. It took that long to get to $1 billion.
We acquired a company in California. That’s why we moved out to California.
I think Franklin was about $60 million in AUM in 1973, and the company we acquired was maybe $120 million or something like that. Then the market tanked the next year, and I think we eked out a $5,000 profit for the entire year, in 1973 or 1974. But it was still a good business, and you just kept at it.
I actually think a lot about why my grandfather set up the business. At the time, the average person couldn’t get access to the excess returns of the equity markets. The idea was: Why don’t we pool people’s money? We’ll give them expert advice, make it available at a reasonable price, and they’ll get diversification they could never get on their own. That was the concept.
I do think we’re at a similar point with the private markets now. Companies are waiting so much longer, and a lot of the debt goes into private credit. We’ve got to make sure it’s fair and democratized for people to get access, while recognizing these are absolutely illiquid vehicles. They can get an excess return because of the illiquidity.
13. Who is the modern day Ben Franklin?
We’ve been seeing that with publicly listed closed-end funds and all of that kind of thing. As we wrap up, I have one final question. This is the hardest question I’ll ask you today. Are you ready?
Yeah, I’m ready.
Who is the modern-day Benjamin Franklin?
I have to say—and this is because I once asked my team to do something, since everybody thinks our logo looks so old. I was like, “Oh, are you kidding me? Ben Franklin was a rock star.” You have to understand, this guy was not only an inventor, a politician, and a philanthropist, but he was also so amazing and really well-liked. The ladies loved him in France, that kind of thing.
I said, “So we should do something like, ‘Who would Ben Franklin be today?’” I have to say the person who comes closest is Elon Musk. People say, “Oh, but Elon isn’t as much of a philanthropist,” or “Elon isn’t this or that.” There’s no perfect match. A lot of times, a person is shaped a little by their time, but I don’t think there’s anyone who’s had a more significant impact on the technological advances that have brought us to where we are today than Elon.
He did say he’s going to give one SpaceX share to all the children in America.
I love that.
Which is like, there you go. See, he’s getting that. Ben Franklin probably had to make his money, too, before he was actually able to do the philanthropy side. So I’m going with Elon.
Great answer. All right. Well, Jenny Johnson, thank you so much. I really appreciate it.
No, thank you. It’s great.
So much fun.