Invest Like the Best with Patrick O'Shaughnessy
00:25:30 · Gabe Stengel, Patrick O'Shaughnessy
[00:25:30] S1: We are a classic enterprise software business. We price per seat right now because our buyers are used to pricing per seat. They think of us in a similar category to Bloomberg, to FactSet, to Capital IQ, to PitchBook. And so we have to build a very human business. Every time you sign a deal, it requires an AE and a solutions architect or the sales engineer going in and shaking a lot of hands, explaining how it works, explaining how to integrate it. You can't sign one deal where the usage just rises a 100 fold. I look at how hard it was for Anthropic to sell to us very easy and the amount that we pay them has risen exponentially without a human loop because it's a token consumption model. There's a lot of industries where riding the coattails of token consumption isn't gonna work for enterprise sales and we're one of those. And so it's actually pretty interesting because we have to build a go to market machine five times faster than most enterprise sales organizations ever have to build. And so I do think there's the category that's just typical enterprise sales, but using AI models as a tailwind to build a 100 times better products. And then there are the token brokers, the token consumption businesses where you're selling in the parts of enterprise where they're used to buying usage based tools. Cursor, factory, cloud code and others. And so you can go much further commercially with fewer people. [00:26:45] S3: What's your prediction for how or if that will change in finance?
00:26:45 · Patrick O'Shaughnessy, Gabe Stengel
[00:26:45] S3: What's your prediction for how or if that will change in finance? [00:26:48] S1: I think that every business needs to go through two different pricing revolutions. You need to move to some sort of usage based and then you need to move to some sort of outcome based. For me, if I can figure out a way to skip the token base, skip the usage base, simplify it for my users and just wait until I can say, hey Patrick, what if I just charge you for every good investment idea I give you? Or what if I charge you for the quarterly report you send to LPs that I can do perfectly? Or what if I charge you for every sim that you create as a banker? I would much rather get there than have to figure out some random way of trying to assign dollars per token that is something that we're not gonna quite agree on because you're gonna spend a $100,000 on tokens and say well did I get a $100,000 of value and I don't really know. But you know what the value is to you of a good investment idea because you can actually see how much money did I earn. Or you know what the value to you is if you can produce a sim if you're a bank because you know what you charge these firms to actually sell the business. [00:27:47] S3: Presumably, you can't change your seat price on the fly dynamically at least with the same customer. So how do you deal with the problem of like, in some ways, misalignment with the customer for your business where if you do a great job and they use the thing way more, which costs you a lot of money, they become a worse customer?
00:27:47 · Patrick O'Shaughnessy, Gabe Stengel
[00:27:47] S3: Presumably, you can't change your seat price on the fly dynamically at least with the same customer. So how do you deal with the problem of like, in some ways, misalignment with the customer for your business where if you do a great job and they use the thing way more, which costs you a lot of money, they become a worse customer? [00:28:05] S1: The reality is is we are 1% of the way into our product roadmap. 99% of the innovation for capital markets is in front of us. And so what matters is that we're a good partner. We're a good steward of their AI strategy, and they wanna work with us in the future. [00:28:18] S3: It's so interesting to think about the shape of this in the future. You said you're 1% penetrated into the road map. Give us a sense of where you think this is all going from your product perspective, not industry wide. If you have that much of the road map ahead of you still, describe that to us.
00:28:34 · Gabe Stengel
[00:28:34] S1: Think about the percentage of all capital markets workflows, investment workflows, investment banking, jobs that are still completely human rate limited and done by human intermediaries. It's kinda similar to other parts of financial services where fifteen years ago, twenty years ago, every mortgage that someone got, you went in, you spoke to a banker at a local branch, It felt like a very human decision. I'm buying a house, I'm taking out a loan, this is important, I need to speak to someone. No one ever thought that you wouldn't want a human in the loop for that. Now 40 to 50% of mortgages are just delivered online by platforms like Rocket Mortgage. I think there's going to be a huge amount of innovation in how companies transact, how companies raise capital, how companies raise debt. I think it'll be easier than it's ever been in ten or twenty years for someone who's a business owner or someone who works at a company to go online and click a button and try to raise capital the way that someone can go on to Robinhood and click a button and buy an equity. I think it'll take five minutes for KKR to figure out can I sell this portfolio company to another sponsor, not five months? Think I you're gonna be able to price assets in an order of magnitude less time. And as a result, markets are gonna be more transparent, more liquid, more efficient, and there's gonna be a whole bunch more activity.
00:29:49 · Patrick O'Shaughnessy
[00:29:49] S3: I'm gonna focus on the specific future of Yes. Automated risk pricing for lack of a better simple term. We're three years from now and everything you just said is true where I can raise single digit millions of dollars of better equity kind of like filling out an online form and the thing can just price the risk for me and give me an offer. It's like open door for like every year or something. What do you need to build that you don't already have to enable that sort of capital market future?
00:30:15 · Gabe Stengel
[00:30:15] S1: It's actually a very similar strategy to Bloomberg strategy. Bloomberg strategy was... I'm gonna omit a lot of details here but offer a little bit of data to get in the door, build all the analytics and workflows on top that someone would need and then provide the exchange and the communication platform where you can actually transact in a bunch of asset classes that before it was pretty opaque. Bloomberg Messenger. For us, it's use a little bit of AI to get in the door, build out the full workflows, go from copilot chatbot to full autopilot tool so I can make sure that I'm a 100% accurate on your IC memo or on the DDQs that you're doing. And then provide the communication channel between counterparties so that if I have agents that can autopilot do the work, I can actually transact for you. And the difference between what I need to build in Bloomberg Messenger is I don't need to build the communication channel for humans to transact. I need to build the communication channel for the agents to transact across these businesses, across these investment firms. And so if you think about what is the actual infrastructure that needs to get built, I mean think about what is the system that would allow a large private equity firm to feel comfortable having an agent negotiate a deal on its behalf. Correspond with all the third party consultants in the transaction, the people doing the q of e, the legal advisors and so on. And then actually run an auction process where you have a bunch of sponsors providing bids. There's a huge amount of software to be built out. And I think sometimes we talk about that as looking like an exchange for a lot of these asset classes that are not standardized.