Cheeky Pint - Ramp founder Eric Glyman on the many ways AI is changing corporate spending

Episode Date: February 17, 2026

Eric Glyman is the cofounder and CEO of Ramp, the finance automation platform that now powers over 2% of all corporate spend in the US. He sits down with John and co-host Alex Rampell to discuss how Ramp scaled to over $1 billion in revenue in just seven years, and why the future of fintech is "selling time, not money." They cover the "SaaS apocalypse" (and why lines of code are becoming a liability), how Ramp uses AI agents to review 100,000 expenses a day with 99% accuracy, and why their internal data suggests the US economy is much stronger than the Census Bureau reports.Timestamps(00:00:21) Ramp business today(00:04:27) The *correct* expense policy(00:11:07) Bill Pay(00:16:52) AI and software(00:32:23) Stablecoin-backed cards(00:33:06) Ramp data(00:36:25) How to cut your expenses(00:41:13) Ramp strategy(00:57:08) Capital One(01:06:34) Treasury

Eric Lyman is the co-founder and CEO of Ramp, the corporate card and finance automation platform. Founded in 2019, Ramp has taken the industry by storm. Oh, cheer. Oh, sure. Hey. Can you describe maybe a good framing, just the Ramp business today?

What's the biggest part of the business in terms of where you make money? What are the new growth lines? Any metrics you can share on the scale? But I think Alex and I have a million questions, but maybe you can start by just framing it up for us. Yeah, of course. So first, just the, The pace that this has come together has been pretty remarkable.

Seven years, yeah. You know, I think by the time we were, you know, six years in change, the company had passed over a billion a year in revenue. The largest portion of that is card. And so that might be a classic kind of interchange-based model. But behind it- People in their business, they have spend cards, everyone walking around, the company has a ramp card, and you're an interchange on those.

That's right. That's right. Next, you can think about bill payments and software. Software, it's a two-something year old business line, just about two years and some months. That's over a hundred million a year business line in and of itself, and that can be advanced functionality to maybe manage lots of entities to automate aspects of accounting, maybe aspects of procurement, bill payments. So this can be sending checks, wires, ACH, and that's predominantly afloat as well.

in some cases for an exchange transaction business. Treasury, you know, that's a product that is about a year old, several billion dollars of deposits. Some of that is checking-like products. Some of that is more of an investment and money ladder type product. And then the last, the other ones are procurement and then travel, which is a bit of an in-kind. And what's been so interesting is that if you break down and look towards maybe let's say contribution profit, gross profit of the business, a few years ago, it would have been, you know, 90 plus percent card. I think by the end of this year, you know, the second, third, fourth, fifth lines of business will comprise, you know, in aggregate, the majority of Ramp's business.

And so it's evolved into this platform by which if you're trying to operate your company, it's just a lot more efficient. You know, you spend less, I think people know, no ramp for, you know, we help the average company cut their expenses by about 5% per year. The thing that's been really fascinating is as people asserting to use these products in aggregate, not only they're not paying for five, six sets of point solutions, but they're also not wasting time. They're growing faster. I think that the average customer last year on ramp grew their revenue by, I think it was 16%, which compared to, in the United States, the average business. Yeah, I think it's 5% in the US. And so it's,

I think in some sense what we're trying to do is be not just a better platform, but a better, almost kind of digital brain for organizations to allocate resources and make sure spend is not wasted. So you start by selling, say, spend cards into a business. The CFO likes it, the employees like it, and then that gives you permission to go sell some of this other functionality. And so it's kind of a classic multiproduct cross-sell. Is it all this starting with spend cards, or do you now have kind of multiple front doors into the business? That's been the big story of the past year. You know, I think there was, you know, the last quarter thousands of businesses that came in just for bill payments.

There's accounting firms that, you know, are becoming into, they say, like, you know, we're a ramp shop here. If you want to work with us, you know, we'll bring in bill payments, treasury, just, you know, we use ramp to go power that. and they can manage 10, 100, 200 clients all through one platform. And we're excited. I mean, probably the fastest growing line of business is procurement, where there's single clients that are looking to kind of bring in and do full-scale purchase orders across, you know, whether it's single or, you know, a dozen plus entities all the way through.

And so that's been, I think, the really fun story of the past year. Do you have a view on what the right policy is, for employee spend within a business. I love the choice. You know, 37 signals or someone will say, companies are so lame, you just give everyone a credit card and trust people and it's fine. And then meanwhile, large companies are like,

well, this hotel is in a tier two city and therefore there's this dollar limit and it must be booked 14 days in advance. And so you see companies operate at really two ends of the spectrum in terms of how much flexibility they give people. What is correct for a company or does it just vary by size?

I love this question. And the interesting part, if you really kind of dig into ramps businesses, we have ways of back testing and actually understanding. Based on how strict your policy is, how things are running, does that have an impact on how much time your employees are, let's say, doing expenses, how quickly you're growing, and you can start to actually compare, based off of the operating hygiene of the company, what are in margins? what is like a pace of growth that occurs in the company. And I bring this back to what. So you can do a correlational study between expense policies and company growth. Yeah. And yeah.

And look, it's pretty interesting. I mean, the first, there's an aspect of in most companies, particularly really high growth companies, it tends to resemble something closer to the no rules, rules, netbook approach of we're going to trust but verify and shine a light on it. spend tends to be, you know, reasonably permissive. But then part of the breakthrough of the past year is you could basically take an expense policy. Let's say it's written, you know, in plain English, you know, if the flight is more than five hours, you can take business, if it's under things that would have been like horrible to go and, you know, have your managers go and verify

the stuff. Now you can run that through an LLM. I think that we're processing over 100,000 expenses a day that are being reviewed agentically. This is a very fast-growing subset of the business. So sorry, like you give the Ramb agent this company's expense policy, and then it applies it to the transactions that are coming through. Exactly. And so you can start to do things. Like I think about the episode you'd had with Susan Lee was, like, incredibly instructive

where, you know, she sort of says, like, it would feel so silly. And it's not a great use of my time in some sense to be a very expensive machine learning algorithm to do, to review expenses. but yet somehow a lot of people and companies are reduced to that, thanks to Sarbanes-Oxley and the rules around it. Now you can have an agent functionally that does that, that takes that aspect of the job. And so it has access to the full set of data that you, that you would, all the transaction-related metadata, the receipt data, the timing data, the policy data. It then can go in real-time review, you know, was this in or out, can have the full audit trail explaining its reasoning.

And today it's over 99% accurate, which turns out it's much more accurate. than people are. Yes. People don't know the expense policy and expenses are pretty automated. And I find this thing super interesting in part because I don't think it really should be anyone's job

to go and review people's expenses, but somehow, well, it's a no-one's JD. The law kind of requires everyone to waste an hour of their time every month if you're managing. And does the law allow for it to be reviewed identically and then just signed off by a human? It does.

It's like the goal of this is separation of duties. that you yourself are not reviewing your own expenses. Sure. Yeah, yeah, yeah. Of procedures that govern and actually are effective through the action of, okay, the rule says this, did you take some steps to do this? It can be a system that doesn't.

Yeah, you kind of self-certified. The funny thing is that, I mean, one way of doing this, actually, we used to do this, is why not just post your expense reports in the public eye, right? So, and the reason to do this is actually it could go wrong. You could say, I'm going to spend, you sit at the four seasons, I'm going to see it at the five seasons. You could go that direction. But what you want is you actually want a moral code. Yep.

Right? It's like if you were the owner of the business, it is your own money. Yes. So if you were staying at the five seasons, I've just made that hotel chain up, it's like you're stealing. You're stealing from yourself, why would you do that? So it's like the problem is that once you get to tens of thousands of people, how do you impose that moral code? And actually, like, the two like tent polls that you just mentioned, they're both bad. Yep.

Right? Because it's like if you have to stay at a crappy hotel and you're about to sign a $2 million contract, right? And you didn't get any sleep. It's the motel six and you take a two-hour taxi. It's like, all right, you save the company money. That's it. Like, that does not make sense. Stay at the four seasons. Yep. But you can't really embody that in like, if this, then that. Because what you want is you want this moral code. Like, that's what you want. And like, how do you actually instill that? And there's almost a behavioral psychology way, which is like, hey, we'll just show what people are spending. If you're at the top of the leaderboard, we might trust but verify and

verify a lot more, but that's the hard thing to do and actually preserve as the company goes from like the founder to the founder plus the founder's brother to like, you know, many, many more people. How do you keep that same, you know, as pre decor or, you know, kind of this informal code? I think it comes back to, what was the name of the movie? Like 12 Angry Men, yeah, I think it was, where, you know, you, as you're watching the film, you get some level of detail and someone seems very guilty. You know, it's a dead shutcase and as more evidence emerge, you realize actually this may be different, different, and you need more context in order to arrive at maybe a moral conclusion. Did it relate to closing a project? How does it relate to an outcome that maybe you'll see

emerge one month, two month after this? You stayed at the five seasons, close the deal that changed the company, whatever the example is. I would argue in favor of tools that, you'll see, have more context that do more jobs of work because it both not only can you do the narrow job better, but you can start to get at the answer of what actually is right for shareholders. Where should we be allocating capital? Because it's so interesting to your work because every company approaches this differently. Yeah. Like I'm on the board of WISE and, you know, Christo flies coach everywhere. Everybody flies, like that's just the policy. But, you know, it might be penny wise pound foolish. Not for me to say. But I also. I also.

really admire the corporate code. It's just like you actually, that is cultural. Yep. Like, it's kind of weird to say expenses are cultural, but they are. For sure. Yeah, it's shared, um, shared belief system. It's a shared belief system. It's like, what is the culture of the company? When you talked about your expansion to bill pay, it seems like bill payment has proven over the past 40 years, uniquely resistant to automation and modernization. If you look at how a typical business, you know, pays their rent or, you know, if you order a keg of Guinness, you know, you'll get a PDF now emailed to you by some person who has a relationship with you, and there'll be bank account details, which hopefully are correct, and you kind of send a payment

to those. And even like bill payment products, you know, you guys have a bunch of technology here, but it's like we scan the PDF in an automated way, or we ensure that the bank account details where it's typed or something, but it's kind of putting a little bit of lipstick on the pig of, you know, the whole system being super antiquated. Why is the system so antiquated when it comes to bill payment in particular? I mean, I think this is some of what Alex was bringing up. It's the constraints of programming things that, you know, in an if-this-then-that-kind of world are very heavy.

There's a lot of complexity. And when you think about kind of the nuance and algorithms that govern, you know, why do companies spend money under some circumstances, how hard it can be to record. You know, I wouldn't overlook, you know, let's say that you're a manufacturer and you're buying some asset which you're going to use for five years and it's kind of depreciate. It's a very different accounting treatment versus I'm buying like a pay-as-you-go SaaS-app. All the complexities around that that might govern whether or not you decide to spend. And then finally, once you get all this detail, like how do you review this and decide,

where to allocate your next marginal dollar is very complicated. But like many systems are in place upgraded, despite the fact that's pretty complex. So credit cards started with no real-time authorization system, which is crazy. And you just hope that they were good for it. Exactly. Yeah, yeah. Yeah, yeah, exactly. The machine with the pleasing sound.

It would be due great in the current ASMR environment. But then they added, like, you could call up and get an authorization. And then they obviously added to kind of the current systems we know where. Exactly, yeah, yeah, and then the modem. And so, kind of in place, credit cards were upgraded with much better capabilities. And similarly, if you look at kind of checks and how they work, even though we kind of think of checks as antiquated, it used to be the case that physical checks had to be flown all around the country to be, like, physically settled. And then there was the Check 21 Act in close of the year 2000, where they said a scan of a check is good enough.

And so they could be, you know, digitized by the banks and then shredded. And then there was the, you can take a foot of a check with your phone. And so we've managed to take this super old-timey check system. And despite the fact it's super old-timey in some ways, it has actually been meaningfully upgraded. And if you looked at the bill pay system from the outside, you would say, we should have DNS for companies. So rather than a company, like, sending you their bank account details, you should, like, look them up in some central clearinghouse. And that way you confirm that you're not being fished. And a lot of spearfishing kind of attacks work that way.

You reference this. So, like, there's actually an indifference point that you can graph. Like, if interest rates go up high enough, if I, if I, you know. I send you a check, right, which is like a paper mail check. Yes. And that takes five days. And hopefully the USPS goes on strike for two more weeks, right? So I've got the postmark.

I actually benefit. It's actually cheaper for me. You legally paid, right? It's crazy. No, it's crazy. So like this is the problem. Like credit cards, everybody, like, I'm in the store. I want the TV.

You want to sell me the TV. We both want this done right away. And in the knuckle crunching, you know, ASMR, you know, carbon copy days, they might not have been willing to sell that to me because they didn't know. if I was good for the money, they'd never seen me before. And the interesting thing is that, you know, AR and AP are almost an adversarial process. You mentioned this, right? It's like, what do you want to do as a controller?

Well, you want to pay as late as possible, and you want to collect as early as possible. And then you have this weird thing where, like, checks, like, it's not just an accident that they stick around for a long time. It's like there was a financial incentive for one party. So that's true on payment timing. I agree with that. But there are some things that are just a deadweight loss, like, the ability to fat finger a bank account?

You know, do you tell, like, no one benefits from that. Like, everyone has a horrible time. No, the Nigerian guy. There's some people who benefit. Let's think of everyone. I will posit that many networks have been upgraded in place, but somehow kind of the loose network of businesses paying each other via PDF invoices has proven very resistant to in-place upgrades.

Also, if you understand, I love your notion of, like, DNS for payments or for expenses. So, I don't know if you saw this, Google wanted to issue a 100-year bond? Yes. Yeah, yeah. So why is that interesting? So imagine that I am owed money by Google. I am one of the small businesses that you reference.

Their job is to pay me as late as possible. Yes. Right? They can borrow money for 100 years at like 3% or whatever it is, like cheaper than the U.S. government probably. T plus 100, yeah. I mean, it's a little more expensive than the U.S. government. But they are borrowing, like that's crazy.

I can borrow money at 20%. but why do I need to borrow money? Because Google's paying me late. Those jerks, right? So, like, I should be able to borrow money kind of at the rate at which Google is borrowing money because my AR is their AP. Yes.

But the problem is, unless you put all this together, you would just look at me and you're like, well, you're just a little schmuck. Like, I'm not going to, I'm going to charge you 18%. It's like, yeah, but it's Google. Yeah. They could borrow money at T plus, you know, whatever, you know, Lybrook, Sofer plus 100.

100%. that's not fair. But the only way to really solve that is with more data and actually entangling, not entangling, but just kind of connecting these things together. For sure. What's your vision for, once AI is doing a lot of software engineering, what does that look like in three or four years' time? Like, is the competitive equilibrium similar,

but just the expectations for the amount of software and functionality businesses are shipping is much higher? are software teams similar looking, different looking, again, you're doing a lot of AI engineering. What does the future hold? It's all blurry. It's totally crazy. Like, you know, there's, you know, designer shipping code marketing at Ramp reports into, you know, or CTO, Kareem, my co-founder, who's doing something like the best marketing I've ever experienced and seen.

We have customer support agents like shipping code to production too. I just think that the half-life of you see a problem to how long it takes for you to go fix it and do something about it is shrinking immensely. Or if you want to change a color of a button, you can just say, you know, at rampant spec, you know, can you change the color of this button? And it goes and spins it up and it does it within minutes, it verifies and validates it. And so I actually think in some sense, you know, kind of these classic barriers that software businesses had, are clearly going to a road, right? Yes, but, you know, this is the old joke of, it's much more fun to write code than read code,

which explains a lot of software engineer's behavior, and it becomes easy to change the button. Is that like another instance of it being more fun to write code than read code, where lines of code are a liability and not an asset, because, you know, they are something you have to reckon with? And so are companies at some level incurring some tech debt now, where they are adding a bunch of code, which will maybe be harder to reason with later,

or do you just get bailed out by the models getting better? It's really interesting. By the one of the other interesting kind of sub-conversations I'm hearing a lot, too, is when you think about where tech debt comes from, there's a set of conditions and trade-offs you make, you write things in a kind of a discrete and deterministic way. Under these circumstances, follow this code path. Under this circumstances, follow this other one.

In a world where there's LLMs and kind of the model, themselves are improving. I think it's entirely possible that the way that code is written is you say, here's what I'm solving for, you know, under these kind of conditions, here's what I want to occur, go write the code that drives this outcome. And maybe with the models such as they are today, can get it done in sort of a spaghetti code written fashion, but it kind of works, even though some kind of Rube Goldberg machine underneath the hood. But at these models get much smarter, you might write your code base in such a way where you say every year, rewrite the underlying code, but here's the outcome I can drive, and today you accomplish my outcome 90% of the time, 95, 98, 99, 100,

and do you just have kind of self-healing and writing code all the way through? And this notion of underlying code does goes away because we're writing things in this different manner. Obviously, there's real conditions in which that won't occur. Like if you're kind of writing code that needs to have four nine, of accuracy and uptime. Like, that's probably not the methods you're using. But, you know, if you're like a growth engineering team, that's probably what you're doing today

if you're kind of on the leading edge of the stuff. And so I find this stuff very fascinating. You know, and when I think about, like, the deeper implications of this stuff, like, I think that if you are completing a small amount of cognitive work, right, let's say you just are a, you know, expense app, You know, the thing, the spend has occurred.

You need to go get the, write it down somewhere and get someone's approval, and that's all the knowledge work that you're doing. That's like very few tokens in order to accomplish that, both to create the infrastructure in order to facilitate it. Like that probably evaporates. You know, I think anyone can probably custom write that kind of app. Whereas if you're doing much deeper kind of work, you know, such to underwrite a company, provide financing, automate areas. of accounting. Like, I think kind of the fitness function for companies becomes, can you actually do things in such a way where even if you could kind of spend tokens on it, it would take more tokens to create the thing or do that work than the system maybe that you've built to kind

of drive that outcome. So it's, I just think the rules of what it means to be a software company you're changing. I think network effects and what you're building is more important than ever. Like if you think about kind of the classic set of modes that are there, I think that this question of where are their moats in a world where, you know, I like Dario's way of putting this. If you have like a country of geniuses, you know, living somewhere in their writing code and they're incentivized to compete with you too.

You know, if you're not really kind of following what are the classic four moats and building towards that, like I think just life gets a lot harder. Yes, yes. I mean, do you of you, do you guys have a house for you on the new competitive equilibrium with a lot of AI engineering really working? Well, I think there are a couple things.

So, like, I think Mark talked about this a little while ago, but what is an EPD team, you know, engineering and product design team, product development team? So you'll normally have one product manager, maybe you have five to eight engineers and one designer, and now everybody has cursor or clawed code. So the designer's like, I don't need any of these bozos, right? The product manager is, I don't need any of those bozos.

And each of the engineers is, like, I don't need any of these bozos. It's like the start of the dark night. Yes, and they're all right. It really is the story. Exactly. And they're all right. It's like they're all wearing the Joker mask. Or the Joker mask is ClaudeCode or Cursor.

But the problem is because I was talking to one of my CEOs, this is a pretty scaled company, lots of revenue. And it's like they use all these tools. They're not more efficient. And it's like, why aren't you more efficient? And it's two things. Number one, it's like it's a real company. They have real customers.

They can't just like push things and hope for the best. But it's like you actually have a, you have an HR problem in that if you're building from scratch, granted, you have nothing, you have no tech dead, you don't really have to worry about customers, you don't have any, but you wouldn't have an eight-person EPD team. You would probably just have like each person, you'd have like, all right, we have eight different product managers

slash engineers slash whatever, like each one is a pod unto themselves. So that's one thing. I totally agree on the data modes where that has become more important. I'll tell you a story that you might like. So I met this company, V-Lex. It's a 25-year-old company. This guy, Alex, bought up every legal record in Spain, like probably going back to 1492, like, buys the, and here's the Ferdinand and Isabella, like, here's the document.

Like, I'm going to take a picture of that. I'll sell it to every law firm. And he built, like, it was like a $20 million a year of SaaS business, you know, bootstrapped for 25 years. And then I went to like $100 million in one year. Now, why is that? Because he used to sell this document or like, you know, he used to, sell a subscription to Kirkland, Ellis, and Latham Watkins and all these big law firms, and they would take, a paralegal would take that, they would turn it into like a document,

they'd charge the client $10,000, and, you know, chat GPT can't do that, like, Jen and I can't do that, but you know who can do that is VLEX. And now, so, another good example of this of, like, who has proprietary data? A lot of times the data is free. This is the really cool thing. Or, like, it's sitting, like, I wouldn't call your data free, but it's, it's, it's not, It's not like for-sale datasets. So do you know DomainTools.com is my favorite business? So DomainTools runs a crown job every day on every single internet website. They do a who is lookup.

So who is look up every single day. And made a historical record of that which none has. So if you want to see who owns stripe.com in 1999, like, well, it was free in 1999. So if you invented time machine, go run that Who is query in your terminal, but you can't do that. So you have to pay them. But all that data is free.

flight aware with ADSB data. So you have a lot of these weird businesses. And of course, this is not a new idea like FACC set, Bloomberg. Like you have aggregators of data, but that becomes so much more valuable. Totally. Because your 10,000 geniuses cannot do that. 100%. 100%. And like you always experience this of like you hire like someone extraordinarily talented, like top of the class at MIT. And you say like, all right, join like the, join the engineering team and go ship the code and they ship something kind of crazy. you know, on the first day, and it's sort of slow. And it's like, you know, you can have someone who is, like, intellectually, like an absolute

giant, but learning kind of how a company does things the way it does, learning the kind of the procedures and nuance of an organization, like, takes times. It's part of what makes working with interns or junior engineers, like, fun. I think their learning curve is obviously immensely steep. And I think that the speed at which, you know, with sufficient access to the data and the procedures of a company, they're going to get there very, very fast. but, you know, these moats are real, you know, anyone who's... Well, the other mode, I would argue, is the dark matter moat.

Yes. And what I mean is, like, you know, like the Milky Way, nobody could figure out why the mass is the mass, because it's like all the observed stars and planets and everything else. It's no. Actually, the vast majority of the matter or energy, because they're the same thing, is dark matter, dark energy. And what does that mean? Nobody the hell knows.

But it's just like we don't know it. And for products, it's like you built, like, if I go tell Claude, go clone ramp, right? Because this is the SaaSpocalypse that's happening right now. It's like, oh, of course. Well, I just went to the website, and now I have a website that looks like grab. No, no, no. There are like 9 million edge cases. Like the tech debt sounds bad because it's a pejorative debt bad.

But actually it's good because what you've done is you've uncovered every single problem that can go raw. Like the fact that, I mean, a great example, remember when the power went out in San Francisco a month and a half ago? So we have this amazing thing called Waymo. Waymo had not figured out this quarter case of what if the, power goes out. It was a thundering herd problem with the customer service or the human overrides. But just they had no idea. And it's like that's actually great that that happened. You need these problems to happen. For sure. And just because my background, I used to write shareware. Let's try before you buy software. Shareware was a big thing. That's a blast from the past.

So there's a blast from the past. So there's a website that's part of CNN. It might come back. It's a premium. But this is where I'm going with the story. And you'll like this. So download.com was the preeminent site for downloading shareware. It was a like, you know, CNET was one of the most popular properties in 1999, 2000. So all the top downloadable software products were there. Download.com sounds like a company that had a Super Bowl ad. They wouldn't. I bet they did, actually.

Probably had two. I'd be shocked. They probably had five, right between Pets.com and something else. But so Download.com had all the popular products. And then this site called Elance shows up. And Elance is now called Upwork. This connected you with work that you would want done by very smart people, basically in the developing world.

So I want a software product built. Here's everybody in Romania and Russia and India. I want translation. I want graphics. So what ended up happening is people would look at the download.com top list. Because before it was a very cottage industry of who wrote shareware. And it was very profitable. Like ID software, shareware company, McAfee, shareware company.

Actually, CyberSource started off processing payments for shareware companies. Ah, okay. That's how they got McAfee. That's funny. Very interesting history to this. So we talked about some other time. But basically what happened is people found Elance, like, oh, I could pay anybody $500 to clone anything on this list. Everything on this list makes tens of millions of dollars a year.

Let's go. And the cloning never worked, right? It functionally worked. Because if I say, I'm going to clone Eric, I might not know that you have a pancreas. Yep. Right? I'm sure you do. Right?

I might not know that you have two kidneys. So the problem is that the cloning just, it goes skin deep. And like, that's the embedded advantage of these companies. So do you then think the SaaSpocalypse is kind of irrational? I think it depends. I think some of it is very rational because if I want, if I have a feature that became a company, and I know this sounds like a very negative thing to say, but like I want to get paged if my server goes down.

It's a very, very logical reason to build a company called pager duty. That now has a lot of stuff around it. But I might just say like, hey, whenever my server is, like there are corner cases. There is the proverbial, the power goes out in San Francisco, do something differently. That's very, very different than like NetSuite, which is, I have a saying that I like, which is the best companies have hostages, not customers, at least in enterprise software. Not for you. Because you actually have IMPS.

But that, they're much, much harder to go rip that out. And a lot of it is kind of like the Goldilocks zone that you operate in, right? It's like if you're too expensive, of course I'm going to try to rip that thing out. If it's so cheap, then like I forgot nobody even used it. So you have to be in this Goldilocks zone. You have to have enough complexity. and ideally the front end is different than the back end. So, like, workday, I think, is, like, nobody's going to get rid of workday.

Yeah. And I actually credit David Ricardo with this. 1870, you know, comparative advantage. Like, sure, you could grow your own food, right? You could plumb your own plumbing. Yeah, yeah. But you're not going to do that. And somebody you could do your own HR system.

I think the one, maybe pitch for Stripe and others that I would say. say here is, I do think that that is right. And there is a lot of complexity in, you know, local tax law for payments and things that make work data and get extraordinary business. There was this, like, overarching macro question of like, how does work get done? And if you believe that, you know, works can get done through tokens, you know, and models, presumably, you know, probably doesn't go through payroll, probably goes through a credit card or check. to these types of companies. And so if kind of the share of, you know,

it's almost this sort of simple math. If you could like x-rayed the P&L of most companies, the majority of it classically, at least for asset-lis firms, is payroll. You're paying for people to do things. And SaaS is maybe a, you know, a small percentage of companies' income or companies' cost base. Does that suddenly that share grow to high single digits

low double digits, significant double digits. And does a share actually move where the payroll economy itself, even though maybe it grows, becomes less relevant? I think this is the really funny part of even as this has been going on, what do I know as a private company other than seeing our own payment data, but you start to see these companies beating their earnings in a way they never have before where the terminal value perhaps is falling out. but, you know, they're saying, you know, shareholders were re-accelerating.

We haven't seen this since 2021. We're going faster, and you're going to have multiple progressive quarters of this actually occurring for certain types of businesses. And so it's a really interesting, you know, time to what I very violently agree with. Your view is like, yeah, it depends. It depends. It depends. It's my brilliant comment.

It depends. Yeah. You mentioned. Me too. I have very hard marks of you. As you're hearing from Eric, Ramp is because, become the default way a lot of American companies manage spend. Stablecoins allowed that functionality to work in many countries all at once. With ramps stable coin-backed corporate cards,

businesses can fund a balance with stable coins, issue cards against those balances instantly, and allow employees to spend anywhere cards are accepted without the business having to think about stable coins all the time. Same card experience, same controls, just a much more global set of rails underneath. This is one of the many practical ways we're seeing businesses on Stripe use stable coins by launching card programs in many more countries and doing so in much less time than it would have taken otherwise. If you're thinking about using stable coins to expand, strike can help. You mentioned your spend data. What does the spend data that Ramsey's tell us about the economy? It is, I think it is stronger than many people understand in lots of ways. I mean, first, I'll,

go back to one of the things that perplexed maybe our team for a long time and, you know, our economists are on the team, you know, saw this data, even as recently as last year, where the Census Bureau would do this periodic surveys when they'd go out and ask, like, you know, how much is your business using AI to produce goods or services is very, you know, refined economic way of wording the questions? And, you know, they would come back with these pronouncements saying a single digit percent of businesses in the U.S. have adopted AI. We looked at our data, and we support over 55,000 businesses. We lean a little bit towards tech, but not heavily. It kind of resembles the distribution of businesses you would see in the

States. And, well, the majority of businesses have used AI. You know, you look at businesses, whether they're paying for. As in they subscribe to chat GP or entrapic or something like that. Exactly. Or maybe a business that is a true. through, you know, agentic cognition or a coach or something like that. This is kind of vertically, vertical application. And so one, there is this disconnect between kind of the use of tools, if you look at of how quickly businesses are adopting and responding to these new tools versus what maybe people report on.

Next, growth. I think it's been clear over the last few quarters is the US itself is re-accelerating. GDP growth has gone from, you know, maybe the one to two. you know, area to four to five, and you could argue how much of this is a little artificial with subsidies, but it's been pretty significant. But subsidized by what? Some of the, like the big, beautiful bill, as well as some of the tariffs. Yeah, yeah, and where that's been reallocated.

I think some people, I would argue on the whole, maybe unfairly said this. I think that there's more durable growth inside the businesses. But I would say overall business health is much stronger. And I think that the really interesting thing, and again, some of this is specific to the data that we see, but I think that businesses are generally getting more and more savvy about finding tools that help them be more efficient. And I think what skews our data is maybe the savings we drive for people. So as the way of explaining it is, like, people know the Ben Franklin would say this phrase of a penny saved is a penny earned. And this is this awesome aphorism. but average American business has an 8% profit margin.

And so mathematically speaking, penny saved is equivalent to 12 pennies of revenue earned. And so if you save businesses a lot, you end up with these outcomes of the average ramp basis materially outgrowing kind of the regular U.S. average. And we can clearly see this and demonstrate this for our own set of customers. I suspect these types of things are occurring at businesses adopting these new sets of technologies. would argue probably faster very clearly than what the US is, maybe the classic sources are seeing. So I think it's much healthier. When a business saves money on ramp, what happens?

Like the, you know, CFO comes in and says, oh, my God, we're, you know, spending way too much money exactly on confetti. We don't need this much confetti. Who is buying the confetti? Yeah, yeah, yeah. And we have huge stockpiles that we don't need. Like, what happens when a business saves 5%? Like, what are they actually cutting? Yeah, yeah.

So there's two pieces of it primarily. One is like these hard dollar cost savings. And then some of this is time. And I'll start with the time because it's the squishy one. But I think that it's in some cases like actually like much more important. Oh, sure. They save time under expense reconciliation. That makes sense.

Yeah, yeah. So they're no longer going through line by line and therefore there's, you know, one person who is freed up to go do something else. Yeah, yeah. And it's, I think kind of one of the classic biases that people forget is people chronically undervalue their own time. You know, is maybe a principal business. You know, everyone, you know, everyone has an hourly.

Within a business, human time is incredibly expensive. I think the lean companies got this right in eliminating the bottlenecks there. So, okay, that's one form. What else? That's one form. Next, all right, when you start to have these fine-tune kind of controls, this part has been, I think, probably the biggest lion sure of this. Let's go back to me, one of the earlier conversations of why do people use checks,

this horrible system and purchase orders. Well, one of the advantages of checks is unless you mail it to someone and you sign it, no money can leave your company. And whatever maybe person knows who's ever had a credit card and gone to a gym once and had a good New Year's resolution, but as you go a couple times, and you're like, God damn it, this gym is charging me. The difficulty of sending a check is a feature, not a bug. Yeah, exactly.

But part of what Ramp was the first to build. One-time use cards. Single-use cards, but also more than that, merchant blocking. So you can, whether it's on one card or 10,000 cards at once, building a kill switch to say, okay, we've signed this new deal with this merchant. We're only on Uber. We are no longer taking lists.

And anytime someone goes and tries to go on merchant A or B, you can do this. Or you sign a new contract and you say, I'm going to spend $10,000 only with Salesforce. And on the $10,000 and one dollar they try to charge you, it declines. and what gets to happen, you get to have a conversation with their sales team who really wants to make their budget. And if you look at this mathematically, for most companies that come over, a low end, maybe a very hygienic company that is more giving out few cards in the old world. You could durability cut their expense about 2% of year by doing this. Some of these very lazy, fair businesses are saving just 10% just through these companies. Next, you start ending up with these more fine-tuned controls where you can say, like, under these circumstances,

I want to go and have kind of charges that occur. Maybe you have an engineer state until 8 p.m. at night. You can go and, you know, buy a meal. But if you take an Uber on a Saturday, that should turn off. And so you have the cards. If it's like an Uber on a Saturday, auto decline. But you can text and say, actually, it's for work. You send back a yes, it turns on.

And so it's all these little tiny paper cuts that actually start to go into one. Next, it's vendor data. One of the unique assets of RAM is anytime you spend money, you upload a receipt. Maybe you upload an invoice or an MSA. This kind of takes us back to the pair of his days. We know across hundreds of millions of purchases every year, not just that you spent money at a software vendor, but what did you spend per seat? And so if you're a customer on ramp and you're about to go and pay this large bill on random SaaS vendor, we can show you in real time before you kind of send the funds. You are paying 20% more than the rest of the market.

you know, here's kind of the cost curve what others are paying, and actually by going and empowering your procurement team. Do you even have dated to do that? Because, like, my AWS bill is not like your AWS bill, and so... But don't you need to know how many instances we're running to know if this is a good deal or not? You can, but you can still kind of get down to the level of, is there a bulk of discount or not, and start to know, is there a negotiated aspect. There's other types of things where...

I'd argue maybe a lot of classic software as a service ends up in this way. It's like your pricing is really dependent on, you know, did you sign that deal on January 1st or on December 31st when the sales team really needs to hit the quota? And you can actually see down to the seat level, you know, you're paying $30 per seat. It's a great time to be signing a Salesforce contract. Exactly.

You know, and so you can actually get down to the seat level and say, okay, you're about to auto renew. The market price has actually moved for the set of service. And so it can be very, very useful to procurement teams to know where they compare with the market. And that was actually, yeah, that was my question. So if you remember Groupon, a much beleaguered Groupon, but Groupon started off as a site called the tipping point.com slash Groupon. Because originally it was like, hey, I don't like the fact that Starbucks uses paper cups. If I get 10,000 other people that donate a dollar will fly a plane in front of Howard Schultz's house, which also emits carbon, that's example.

But you only want, it's a collective action thing. That's right. So, and then down, because I met Andrew Mason and Brad Kewel when they were first starting this business. It was like eight people. It was tipping point. And downstairs there was a pizza restaurant or something. Like, oh, well, if we got like 50 people to agree to buy pizza, maybe they'll give us a lower price. Right.

The cause became discounts. Yes. But then the thing is, Groupon wasn't known for this, like, it has to tip because they always had the demand. So they never had to worry about it. Because before it's like, you've got supply, you've got. demand, right? So I guess my question for you is, can you be the arbiter of pricing? Can you, can you aggregate the demand? And the same way that, like, Costco, who shops at Costco? Every small restaurant shops at Costco, right? And Costco uses that collective bargaining power, if you will,

to say, hey, Coca-Cola, give us a very, very low price. They take very, very little of that. Because right now I'm using Ramp to buy stuff. Yes. But I would imagine that, like, if you could say, hey, I have $100 billion, I didn't know, it was that high, that's amazing. I have $100 billion of spend, I can hopefully direct it this way or that way. Please give me a 20% discount. Can you do that? Whereas that kind of like more further in the funnel of like the purchase process? There are this, this large swath of businesses that I've been fascinated by called these group purchasing organizations. A lot of these, you know this well, it came out of that in the healthcare world where it's a very small set of the end. Yeah, exactly supplier. But if you can go and aggregate

demand, you could say, okay, for these type of purchases, you're going to offer this procedure at this account for this type of equipment, you're going to give this level bulk kind of discount, and you've gone, and you've done that. And I think these are very popular now in the private equity world. When I look at ramp data today, there are dozens of, you know, more and more every year of merchants where, you know, there's, we are sending billions of dollars. You know, it is truly, it is the client's money. They are going where they're going. But we have a sense of actually, okay, where is this actually going? And can you go and say, you know, across the ramp buyer base.

Over the next 12 months, this is how many dollars will go towards you. Can we negotiate a discount? The other way, which maybe starts to, you know, sometimes these businesses veer closer to advertising but work. It's really interesting is we see the fastest growing businesses. What are the businesses that people are getting really excited and are adopting really quickly? And we might have a signal of these are actually good businesses and good tools. and actually most businesses should move towards that.

Could you go and actually start to say, hey, your renewal is coming up in 90 days? Have you considered this other business who has provided a 20% complimentary welcome lower price to you? And so there's multiple forms that can take place with a short version of it is I think, one, it's yes, I think you can offer a bulk discount, but two, you end up almost getting closer to,

you know, back to this other theme of like, can you start to go and maybe, you know, show businesses that directing their next marginal dollar will lead to, you know, this outcome. Well, it feels like there's even like a third thing, which is I would call it merchant-specific balance. So imagine that it's December 31st. I'm buying something at Whole Foods. And then I see an offer not donate a dollar to the, you know, whatever charity they're pushing. But it's like, Why don't you commit $2,000 of spend for $2,26 for $1,800? Yep. And the nice thing there is that they lock in that spend for me.

They actually collect it. I mean, I know there's a achievement law and all this complicated stuff, but the key thing is it's almost a risk management and a loyalty play for them at once. Because the problem is that they don't know how much salary to buy. They don't know how many. So it kind of goes back to the AARAP thing that we were talking about earlier. Yeah, yeah. Because the other thing is not just saying, hey, I'm in a group, I'm going to group bargain on behalf of all the different customers that I work with.

But it's an ancillary thing, which is you might want to just pre-commit your spend to a particular vendor. And that vendor would love to have that spend pre-committed, even if their Amazon and their cost of capital is very low. For sure. Because they know they don't have to worry when they're planning their budget for the next year that you're going to churn in month nine. And that seems like another, like the closest that you can get to that is gift cards. Yes. Strangely enough, which I'm sure you know well from your gift cards for business. Yeah, because it's like you go to Costco, this is actually a big business at Costco. You go to Costco, they sell gift cards. We were just talking about this. So they sell gift cards. You can buy $100 of Starbucks

gift cards for $80. Is Starbucks dumb? Like, why are they, like, they're worth $100? No, because they basically have in the ecosystem money that is going to be spent at Starbucks. And yeah, there's breakage and other stuff, but it's actually a quite, it's quite a valuable value proposition for the receiving merchant. Because they know that. that you're going to spend your money with them. But I want to go back to your previous idea, where McDonald's every five years or whatever does a big bake-off between Coke and Pepsi. And they always renew a Coke and they have a long-term. Maybe a movie theater chain is a better example where all the big chains, like they don't serve Coke and Pepsi. They only serve one,

and they do a big, a bake-off between the brands every five years. And you have lots of small businesses that are buying from Coke or buying from Pepsi. And so it feels like you just do a bake-off between them saying, ramp is going to have a preferred vendor. And you can't I'm obviously use a ramp card on either. It'll work, but we have preferred rates with Pepsi. Is that a thing REM should do? It's a really interesting question. Short is, I think, over the long duration of time,

I'm kind of a bit of a crazy person. I'm like, we should try everything. This is my actual answer. Plod code. Yeah, go, let's go. Let's be a building. Make money for Pepsi. Go negotiate. The cost of a phone call negotiation has never been lower.

But there's this almost philosophical question of, like, All right, where is the differentiation? What makes ramp different? But isn't that increasingly at the scale? It is. And I think that you're right in that, like, at the very beginning of the company, the answer was very easy of, like, look, our cost of capital is nowhere close to a bank's. The interchange that we could make is nowhere close to it.

We have all the disadvantages of scale. And kind of the only thing that we could do to compete with. these people was we could, you know, everything was slow at, you know, the bank that I worked at before. It was hard to ship things. We need to move fast. We need to kind of have this emphasis around velocity to ship product and just kind of blitzkrieg faster than maybe others could respond. What it's evolved into, and I think is today probably the largest point of differentiation at the meta level between ramp and maybe the financial service providers that we compete with is they sell money and we sell time.

They'll sell you a loan at a lower cost of capital, you know, rewards at wherever they said it. We will sell your expenses done. I'm sorry, you're naturally skeptical of this idea because it's selling money rather than selling time. I wouldn't say I'm naturally skeptical. I would say that... It's okay, we're not precious.

We've lots more ideas. No, no, it's good. There is this question of, you know, I think back to our roots, like, I don't know, like, how do you build a product that is 10 times better than other folks? And I think when you get really large, actually just a line drive is good and a 2x or a 3x is better kind of thing is actually good. But, you know, how do you find these set of things that other, your product offering is so different than what you can find elsewhere? And I think that we can conceivably, and I know this,

like you can negotiate with kind of like the large logistics companies, a deal with like a FedEx that would be than what most companies are paying, and I think that that's interesting. Then you have all the sub-levels of how to get people to know about the offer, to sign in to the offer, to deal with all these sub things. Or you could just go and spend that next marginal hour to go and say, like, let's just automate all of accounting

for these customers. Let's go and start doing financial work for these customers. No financial institution is able to compete on that kind of vector. And so I would say it in kind of the fullness of time, we want to do both. And I think that you want to see people the maximum amount of time, the maximum amount of money that you can. But I think part of what makes us so different in this kind of world that we operate in is we have this obsession of, like, you know, sources of drag of the things that slow down purchases that lead you to overspend versus other companies. But just to push on that, I feel like the differentiation for companies often has to change as time goes on.

because they start in one competitive equilibrium, and then as time goes on, they're in another competitive equilibrium, because it's dynamic. And it feels to me that Ramp got its start with very fast product velocity and having this great product experience. And as you grow up,

you can just build scale into the product and scale. The scale-derived product advantages, it's not just like we're big, but like Costco, you know, the advantage comes from the scale, and they really passed it out to the customer. And it feels like there could be a second stage to this rocket where you get going with faster product velocity, but then there's actually a pretty different set of product differentiations as you scale up. I think it's true.

I think it's well said. And there's this almost question of like in every line of business that we're building, where are we in the S-curve? You know, how far, you know, is this a product that is serving, you know, these tinklers, early adopters? Are we in the early majority? Are we in the late where we need to shift the business to kind of harvesting contribution, you know, optimize price, not quantity in it or, you know, towards the end. And the thing which is so shocking, and I think maybe as part of why I love this business, and I think even, too, I think about Stripe and many of the great businesses and payments

that have been built. I believe today ramp powers more than 2% of all corporate and small business cards. transactions the United States, which is amazing for a business that, you know, the product you couldn't even sign up for it six years ago. And yet, that's a really fancy way of saying 98% of spend is not on us. Unramed. You know, and let's say we, you know, we do it again. You know, we grew faster last year than we did the year before. You know, I feel very good about the way this year is starting off. And maybe it's closer to four. Ninety-six percent is still big. 92% is still big. It is so large. And by the way, there's more ways to buy things than

just cards. You know, you think about bill payments. And so I think that there is an aspect of, for most people, there's so much drudgery around. Like, I think people are doing artisanal expense reports. You know, it's fun to be like a hipster and spend an hour making coffee. But like, it's a little crazy that... This is the blue bottle of expense resorts. You know, but unfortunately, you're in concur and you're like, this spinning wheel. It's a pour over. expense report. We love it that way. Single origin.

You know, try it's the experience. But no, you're the espresso. Yeah. Much more efficient. That's right. But like, what I would say is like this aspect of time is most people have not experienced of like, you know, this, this thing you know, is just a fact of life or building a business. That's been hard.

Doesn't need to be hard. Doing your books doesn't need to be hard. And so I still think in some sense, and where we are on the S-curves of our business, I lean that way, but you're totally right when you're at this level where in the not-too-distant future, I mean, you're there processing trillions of dollars per year in economic activity,

and we aspire to be there in the not-too-distant future. Sounds like you'll be there pretty soon. We're working our hardest, but... Exponential growth is a hell of a thing. It's definitely giving me good things to think about and work towards. So I was thinking about, you know, when we met, when you were running Paribus. And it kind of feels like, you know,

one of the first or second or third order effects of AI is the marginal cost of arguing has gone down to zero. Yes. Right? No, I'm serious. It's just like, I mean, my wife got into an argument

with some company, and it's like she used chat GPT to argue with them. They used it to argue back with her. And it's like, I just saw the future. This is incredible. And like we won. Your agent will talk to my agent, yeah. But it's like, you think about this,

like from a chargeback or it's like, you know, Hey, this price went down. I remember, like, this is such a good idea. It's like the price went down. You have these breakage models that the card networks had. Yep. And Best Buy has to write you a check or Visa has to write you a check

because that TV fell by 20%. But, like, nobody does that. Yep. And now everybody's going to do that. 100%. Or it's like, you do a chargeback for $5. It's just not worth it. For sure.

It's like my, I thought it was Pepsi that I was buying at McDonald's. It was Coke. Chargeback, right? Nobody's going to dispute that. because the cost is too high, but now the cost goes to zero. Right. So I'm just got to care, like, what do you think, I mean, it's hard to, you know, picture five years from now what the actual full effects of this are.

But if you kind of think about that as the macro abstraction, it's like marginal cost of arguing goes to zero. What changes? I think to be really explicit, I think what's happening is the marginal cost of time of knowledge work. That is a much better abstraction. Is what's going down so rapidly. And I think about our customer base.

of our customers don't have a single software engineer, let alone a software engineer for their finance team. And if what we are very good at doing is selling functionally sets of work, maybe it's embedded in a financial operating platform, but expenses done, accounting done, some type of knowledge work done, and you can deliver that. That is immense high leverage value for these customers. If it, let's say it costs $5 before, they didn't do it. Now they can get $5 of value, but maybe the cost of, it's a software-type cost.

Maybe it's pennies of tokens to actually go and do that. That is a great business to be in because it's a very high customer value. We can capture just a small amount of that and build this business. And when you go back to kind of the original insight of RAMP, we entered into this industry where it was very profitable, but it was not only was it misaligned, but people were fighting over like basis points. You know, every last dollar that went into rewards could have meant like tens or hundreds of millions of dollars in profit for the business, you know, for them. But, you know, if you think about for a customer, let's say that in order to make one extra

basis point as a business, you would try to incent them to spend a hundred more dollars. For that customer, let's say they buy something, that gym membership they didn't need, or that subscription keeps going. They have lost $100. It's gone out the door and maybe they go to the gym, maybe they don't. But that is out of their bank account. And if you just try to say, I'm going to have a better rewards program, sure, maybe you can get that customer, you know, a dollar or $110 back or some amount. That pales in comparison to just helping them just like not spend that $100. Like cancel the subscription.

The economic leverage of that activity is much higher. You sold your last business, Paribus, to Capital One. Capital One is one of the... biggest founder-run financial firms that people in Silicon Valley don't talk about. What should we all be, and has been extraordinarily successful, what should we all be learning from Capital One in their success? And I actually just start, how did they? Like, what product really broke out from them?

Just what is Capital One success? I think there's a lot that makes them amazing as a company. Both the founders are excellent. Rich Fairbank, Nigel Morris. I think it's worth people reading up on their stories. It's founded in 90s, is that right? So not quite. Okay.

From a legal standpoint... I'm very woolly on my Capital One history. I think that legally the incorporation in some sense for Capital One financially, I think it was in 1994, but the actual start traces back to the 80s. Okay. At the time Rich and Nigel had met, they were consultants. And they had this insight that the business of credit cards was, well, it was lucrative, was not serving most of the country. The way you could kind of think about credit cards back then, you know Diders Club, maybe others have heard of it.

It was sort of, it was a way for, like, rich business people to get together and have lunch. And, like, they put the card down and, you know, the restaurant would pick up the tab and they could go and, pay the restaurant back later and they'd kind of navigated that. And kind of the simplification is if you had a very high credit score, you could get one of these cards with the benefits that it had. And if you didn't have a credit score that met that, you could have a debit card. And that was basically it.

It was like a very kind of linear cutoff. And what Rich and Nigel, the insight that they had had is there must be some curve. We should be able to test this. we give people cards that have above an 800 credit score or something like that then, but what about 790? There might be people there that can go and pay for this. If, and the way we could go and take on the cost of this, maybe we charge them a somewhat higher interest rate until they prove kind of their advocacy.

And if 790 works, go to 780. So it's kind of the BNPL of its day. There is a population who are, for whatever reason, just below the threshold where banks are giving them good access to credit where you can actually very profitably lend to them. This is right. Yeah. Exactly. And so they, in the 80s,

we're functionally pitching all these different banks to say, we should go on this exploration. We'll even run this for you. Let us go and run this. And they went door to door to door to door to door. And the banks didn't buy it.

They didn't buy it. And then finally, there was a bank in Virginia, Signate Bank that said, fine, we'll let you run it. You can come join. We'll give you this group and some resources to go build this.

So they built this as this division inside of it. It started to work. As this was going on, the computer revolution was taking off. It was sort of an unfortunate acronym, but they called it IBS. It's not, you know. Yeligible something something. Yeah, yeah. It's information-based strategy.

And they said we could use different pockets of data and run these, you know, before there was big data. There was this kind of data. We could go and test, you know, maybe this person has a balance of $8,000 at this bank. We could send them an offer at this interest rate or this kind of, you know, you don't need to pay back interest for six months or 12 months, and they could start to go and see the mathematical return against this. And this division started really working, and it got so profitable.

It became a problem for the business, and they convinced them to spin it out. And so in 1994, that is the founding, as people know, capital. one today, but it actually was, I think, almost a decade in building to actually go and do this. I think that there was a lot that they got really right. One, I think that they took a much more of a first principles view of the business, whereas others said this is a profitable product. I'm going to do it like the other person and use kind of scale and distribution advantages. They said, well, let's think about the product nature itself. There's different pop. Everyone's making money in interchange. Maybe there's lending could work and you could kind of have

different strategies for different types of populations. They did this so large where I think at one point they were the largest customer of the U.S. Postal Service. They would send out so many offers. I think until Amazon took them over. There was a period of time that they did this. So incredibly experimental. They kind of carved the path and showed how do you go from credit facilities to for fintech founders. Eventually, maybe you become a bank or buy a bank and carve that path. So there's some tactical lessons. I also think they've done a great job of building a great and durable brand. One of the things that Capital One has done very, very well, I think, has focused on, like, what is the consistent visual message, what is the aesthetic, and how do you stand out in this kind of busy and different world? And so there's a lot of pieces to what's made that company work.

And they've also remained focused, which a lot of banks haven't, right? I would say so. Well, I think that's, that is a rewrite of history. They were doing cell phone financing, healthcare financing. They were a part of this thing. They've come back to focus after wandering in the woods. They had some JV in America One, I think it was called, with like computer with Amazon. They were actually like the most experimental business ever in a lot of ways.

And I think it was Hibernia Bank in Louisiana. And this was after Hurricane Katrina. I think it was maybe during it or just after they were able to buy, and it was like, it was an existential question for them. And I think that many people worried about, you knew this, like, well, too, from the BMPL businesses where if you're kind of a lending-based business and it's fine when interest rates are low, but if there's a crisis and people don't want to lend to you, it can just break your business. And so they had these kind of like scares, and they said, we need a stable kind of cost base.

Eventually they bought a bank, which was in a lot of ways very good. they had kind of the deposits as this durable, stable, low cost of, or consistent capital base. But the flip side of buying it was they had to reconcile their culture of like crazy experimentation of trying everything to, we're a regulated bank now. We've got to be bank people. And it's more than just an attitude thing. Like if you are, you know, a nationally chartered bank. Yeah, it's real structures, yeah. You know, like, look, it's, it's, it's to the level of, let's say, the bank fails on, you know, Monday night. There is personnel. Those guys in windbreakers in your office, actually. And they've probably been working there for some time before, you know. And so it's, I think there was a change. In some sense, there is experimentation, I think, within certain constraints, would be how I would describe. the Capital One post buying a bank versus before would be my read of it. But when you look at them in the 90s and 2000s, it was like them and in some ways,

like named the high-flying tech company. They were right up there in terms of share price growth. And they started reachieving it, I think, in the late 2010s. But it's a fascinating company. I mean, I think the talent pool, so at a firm, our first really good risk person. But this is true for every fintech company. is just like, actually, this is kind of cool. Billy Alperano, our first year up, grew up to Capital One.

I played the piano. And my teacher was taught by somebody who was taught by somebody. There's actually a chart. You can look this up. Churny and Beethoven taught everybody who ever taught anybody. So like Lang Lang, Lang or Yu-Jow went, like pick any famous pianists today. Yes. They can always trace their lineage 100% of the time to Churney, Carl Churney, or Beethoven.

Yes. And Capital One is like the Chirney. Our head of risk, Shri's Serney Vos. He's amazing. Came from capital. We're the same boss 10 years apart, actually, in some sense. And all the heads of risk for all modern fintechs that came from Capital One.

Well, because it's one of these things where, like, you know that you don't want to just hire for Intercept. You want to hire for Slope. And this is the problem. It's like, you find, oh, here, not to pick on Bank of America or Chase or somebody, but it's like, all right, this person clearly knows how to do their job. The bank that they work in is worth a lot of money.

but like they don't necessarily have, how do I put this delicately, the slope. They won't know what that means because they don't know what slope means. But seriously, like the guy that we hired just so, he was very, very smart. And that was the key thing about Capital One is that like they didn't hire banking people. They just hired smart people. And it became known as the place where smart people went. And actually the fact that companies would poach people from Capital One actually added to the alert.

It's like, I want to work at McKinsey because at the end of McKinsey, I'm going to get a better job somewhere else. Capital One actually had, it did have that imprimatur. And I think part of it is it's the only founder-led institution. Last question, Eric. We're talking about banking here. You have a treasury product. In five years, where do businesses keep their money?

I mean, statistically mostly, you mentioned 2% on ramp. It's even higher today in traditional banks, like a Chase for Bank for America. There's also neo-banks, you know, the, I mean, kind of bank-like. entities like Mercury or Revute or Monsa or things like that, there are companies like Ramp where you started in spend cards but maybe moving more into Treasury. How do you think that shakes out as a market? So as a macro point, I think there is an incredible amount of money made by institutions who are enjoying the profit pool and sharing very little with their end customers. You know, if you think about the implications of like the federal overnight funds rate.

Yes. This is basically saying, hey, if you want to go and... It's insane that there's so little yield sharing in the current market. It's crazy. I think that the national average for businesses, right, these are sophisticated entities with personnel, they're supposed to be able to manage and put their funds in some place that's more high yield. And the national average, you know, on checking accounts is 0.07% in the U.S. And so I'm guessing you don't believe that Bank of America and J.P. Morgan and all these folks will wake up more altruistic one day. And so what is the competitive process by which you think we'll get there? I think that new businesses, whether they have their own charter or they work with banks too, that, you know, this is not a monopoly. Like they have competitors. Everyone has competitors. And it is a market that evolves. I think that that rate will go up, that the easier it is for people to, whether it's to, to create depository institutions,

create accounts at these institutions, or create stores of value, maybe even outside of these systems, maybe in a stable currency. And so I think that rate goes up. I think part of what's driven, the extremely rapid growth of Ramped Treasury is, it's just a vastly better deal for customers.

Like, why you know, maybe you keep three months of just walking around money in your checking account, but if you know the funds you're gonna receive what you're paying out, well, we can move funds on the day payroll is coming due into that account. And then every other day, make sure the funds are earning the highest rate possible. And so I think from a macro perspective, these things tend to go up in terms of the relative yield. I think there's another question of slack in the system. If you have more and more, money can think, right? If the dollars in your company have some,

some level of intelligence, right? Like there's, it's able to kind of, you know, determine when can it be spent under what circumstances. It's increasingly recorded in real time. And there's some reasoning around this, some ability to kind of opine of where should the next marginal dollar go. And you have systems that are able to think infinitely about these things, even at 3 a.m. in the morning when most of your team is asleep. Well, once you determine, like, maybe. Maybe you'll determine I should keep the funds in some level in like a 2% or a 4% yielding account. But I think more of those dollars will go in flight, actually to go spend to if you have a business

that makes an 8% profit margin a year, that's a lot higher than what you can earn in the overnight rate. And so in some sense, I think you have the dual effect. Smarter capital allocation. I think more dollars will be put to work. I think I agree with Alex's macro point of if you kind of understand counterparties, you understand more information. I think that one, the cost of financing should go down, and I think more dollars should be in the system. In some sense, it's actually a waste for everyone to have your dollars

just sitting in a bank account. Who does that benefit? But it goes back to your time point. It's like the reason why I got mad at Chase a while ago, and I still have a Chase account. And like, why is that? It's like, I have a life insurance policy. I don't remember the login for it. It's just too much work. This is a true story. Isn't this an issue if you die? Yeah. I mean, well, but they'll pay my wife. I just don't know how to log in and change bank account, right? So they'll send her a nice letter, I'm sure, some flowers. But, you know, why, actually, this is true story. I wrote a check for somebody's bar mitzvah. Mazeltov. Has not been deposited. Do I want to be the schmuck who has the bounce check?

Right? No, I don't. So it's like I have to be. This kid is keeping you at Chase. Yes. Well, great to see you. You too. Thanks. Thank you. Thanks for the Guinness. It was a great time.