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Max Levchin - Building Affirm, PayPal, and Why He Only Starts Network Businesses
00:55:03
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- [00:00]
A
The only kind of businesses I like to start anyway are networks. And once you have a product market fit, if it so happens that the product is a network, it becomes to at least some degree, self reinforcing. My career in computer science is sort of a constant attempt to lean back into math. The goal of a firm is this nuanced approach where credit is good. I firmly believe that access to credit is really, really important. Permanent debt is terrible. If you're running the kind of company where you're just absolutely sure that there's nothing left, like you've reached the end of the Internet, there's nothing to build, you probably should look for someone else to run the company. Not to delve too deep into the satoshi conspiracy theories. It's probably more likely a group than one person.
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B
What did you learn working with Elon Musk? How about Peter Thiel? Welcome to Fintech Leaders. I'm Miguel Armaza and over the last six years I've recorded nearly 400 conversations with the top leaders in fintech. I also co founded Gilgamesh ventures, a fintech VC where we've backed almost 50 companies around the world. In this show we extract how the best builders and investors in fintech think what they've learned and and how you can apply some of these lessons to your own work. If you enjoyed this conversation, I invite you to leave a review on Apple, Spotify or YouTube. I sat down with Max Levchin, co founder and CEO of Affirm. Without a doubt, Max is one of the living legends of tech and fintech. He co founded PayPal along with Peter Thiel and Elon Musk, invented anti fraud and cryptographic technology that is widely used and is still foundational to this day and has spent the last 14 years building a firm into one of the largest publicly traded fintechs in the world with a mission to replace credit cards with more transparent lending. He is one of the most thoughtful and brilliant founders I've ever spoken spoken with. Hope you enjoyed this conversation with Max Levchin as much as I did. First of all, thank you for for joining us on Fintech Leaders and thanks for hosting us in wonderful Affirm headquarters in sf. So your grandmother was an astrophysicist.
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A
Yep.
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B
And your mother a physicist.
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A
And my grandfather and my uncle. I have a lot of physicists.
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B
It runs in the family.
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A
I'm sure there's not entirely uncorrelated, but yes, physics is definitely a thing in in a family.
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B
That's probably what fueled your love for math. Mathematics, yes.
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A
Although the same grandmother spent a lot of time dissuading me from majoring in math because there is no Nobel Prize in mathematics. She told me over and over again. She was actually as, as we should not speak with that accent. To me, that was a entirely artistic license. She spoke to me in Russian, so I probably wouldn't need to replicate that here. But it is true that there's no Nobel Prize in math. The legend has it it's because Nobel's daughter married a mathematician and he didn't approve the marriage. I don't actually know if that's true or not, but that was also a lore. My grandmother told me sounds like a
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B
father in law thing to do.
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A
But I majored in computer science in part because I really wanted to do math and math was definitely frowned upon. And my grandmother was very pro physics, tolerant of computer science, not super excited about math as a major.
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B
On the accent, I've always wondered. I've heard you speak both in person in the past, but also watched your interviews. You came to us at age 16. But if I was to prompt a Voice LLM today to give me an American accent, I think you would come up. I know that you learned English by watching TV shows like Diff'rent Strokes, watching the news. I myself learned a lot through listening to music and kind of following the lyrics. But I still have an accent. How did you lose, more importantly, to lose your gain such a clear accent?
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A
Definitely a very conscious effort. And so I don't know if I have any profound techniques to impart. I was a reasonably well trained musician by the time I came to the US and I played clarinet since the age of six or so. And if you are a woodwind player in particular, you really have a good sense of control of your embouchure, which is fancy word for musculature of the lips. And you presumably have enough of a musical ear to be able to say, wait a second, that's not quite right, I need to work on that vowel or that phoneme. And so I think it was just a combination of having the predisposition towards constantly refining a sound and knowing what it takes to refine. So it's funny enough, the same grandmother was completely fluent English. She wrote many papers that she didn't have to translate. She wrote them in English. And her own English accent was horrible. Like it really sounded like a Russian villain from a Hollywood movie. And I remember when I was a kid, she would show me these really thick books that she had on a shelf that that's what she learned. So she'd Never had English instructions. She'd just learned from books. And to learn the accent, she had these books that showed sort of cross section of a human face with, like, the placement of the tongue. She's like, you need to do that diphthong. You have to do the diphthong. Right. Except in her case, it actually sounded like diphthong, like something totally not like the word diphthong sounds like. And so I remember thinking, you can only go so far without direct imitation. So, but anyway, I definitely worked on the accent very hard, and I'm still, amusingly enough, slightly self conscious of the accent. My high school buddies that I still keep in touch with that heard me fresh off the boat sometimes mock me or troll me by telling, oh, that accent, it's coming back. And immediately tense up and try to figure out where did I screw up? Like, what did I say? So it's definitely no longer conscious modification of the speech, but I'm definitely conscious of the fact that I used to have one and I have to maintain the perfect accent. And reason for it was actually pretty simple. I realized as soon as I got to my high school in Chicago that there were kids who spoke like the locals and speak the ones who didn't. The ones who didn't just didn't get the same treatment. Like it or not, I have to blend in.
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B
Yeah. It's just a reality that you noticed. Yeah, yeah. So, Max, I want to talk a little bit about your beginnings in cryptography, because that's actually what fueled your initial company, which became PayPal, of course, after a few years. But cryptography has come a long way since the mid to late 90s. Right. And I know you're very involved with this. You actually speaking of the Nobel Prize, you launched your own prize. Right. The Left Chin Prize for real world cryptography. Maybe Tell us a little about the price. And then I want to ask you a couple of questions about what's going on in that space.
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A
Sure. Actually goes right back to the grandma conversation. So years ago, when she sort of hammered into my head that there's no Nobel Prize in mathematics, I sort of said, well, surely some Nobel like character must have introduced a thing to highlight successful mathematicians. And there's of course, the Fields Medal, which is a great way of being distinguished as a, or being recognized as an important contributor to the field of mathematics. And cryptography is in fact, kind of is actually a really, really interesting kind of tangential related tidbit. But my career in computer science is a sort of a constant attempt to lean back into Math, which every time touches this incredible vaguely accidental luck. So when I was in college, all I wanted to do was math and I was majoring in computer science. So I ended up just kind of leaning into number theory, which is discrete mathematics. Part that is really useful for three things in practice. Cryptography, which was my first love. Computer graphics, which is another sort of big part of my life for a while, and machine learning and now deep learning, of course. And so I keep on bumping into this one part of math that I just sort of fell in love with in college and it keeps on having these amazing commercial applications and so sort of a fun, fun factoid before the web, before payments, before PayPal. The natural progression of a number theory specialist. So college degree in computer science with some number theory inclinations would have been to work for AT&T or go work for the NSA. But I was not yet a citizen, so the NSA wouldn't have me back to the leftchin price. So I think it's 10 years ago now I realized that there's not a cryptography specific equivalent to the fields and asked. By then I'd sort of acquired a bunch of friends in the field of cryptography that some of them were actually very helpful to me in the early days of PayPal. Friends that I met along the way and sort of had this dinner where I said there should be something to recognize people that really push our field forward. And I'm an occasional participant and a little bit of a tourist these days because I keep on starting companies, but I love the field. I feel like there's an opportunity to recognize contribution to practical, valuable inventions and ideas in cryptography. Why hasn't there been one? And they sort of went around the room in this dinner and no one stepped forward and so why not? Maybe it should be me. I did not initially plan to name it after myself, but as prizes go, you sort of set up the funds and hand it off to some sort of independent body to judge and award every year. So I have nothing to do with neither denominations nor the final decisions. But the committee that runs the prize had a free hand in naming it and so they chose to name it after me, which is for a time was embarrassing. And now I sort of feel grateful for their recognition of my recognition.
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B
And it was interesting to me that initially I thought, oh, this is a great way to uncover new research that's going on in the field. But it's not just that because it's not always. Yeah. So the latest, I guess recipients, they've been added in the field for half a century.
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A
That's true. In fact, they just announced another set of winners and that includes some folks that had their fingerprints on the field going back to roughly when I was born, sort of exactly half a century. It's terrifying, but it's not always the case. For example, one of the earliest recipients was Moxie Marlinspike and the team behind Signal, which is actually probably more in tune with what the prize is about because that's a great example of real world. Everyone, I'm sure you're on signal. I certainly use Signal because it's a beautifully engineered open source system that is verifiably secure. So if you want an encrypted message that you're quite sure no one's reading, that's probably the best choice. So the fact that the committee that awards these recognized them, was very much to my liking and that's sometimes the case and other times they sort of say, wait a second, no one's ever really formally recognized with a prize like this. Someone like Diffie and Hellman, who are the progenitors of much of the public key cryptography that we're using today on
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B
the topic of encryption. So Google rock the world, at least for the mainstream. A couple weeks ago I believe they announced that they believe that their quantum computer could actually break the RSA24.8 standard with much less compute power than initially anticipated. What are your thoughts? Obviously not just for a firm, but I guess this is a problem for the whole world.
- [12:47]
A
It's not really a problem we've been living with. We being the practitioners and people who are just interested in the field for 20 years now with a full understanding that quantum computing is coming. It's a matter of when, not if. It is a fundamental promise of quantum computing that you will have the ability to brute force or quasi brute force. These schemes that power the likes RSA and several other cryptographic primitives. We have plenty of post quantum quantum resistant, post quantum crypto algorithms. So I don't think there's plenty of teams that I think are scrambling to say wait a second, we thought this is coming ten years from now. We were caught asleep with a switch. But most sort of well managed systems are long at least planned for a five thoughtful transition to a post quantum future. Post quantum cryptographic future. So I think the world that was rocked is more of a newspaper headline. Less serious system design.
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B
That's good to hear.
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A
Your money's safe.
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B
I heard you say that in the 90s you actually attended quite a few cryptopunks Events, happy hours. And that you really suspect that whoever was Satoshi, either a person or a group, they definitely attended some of those events.
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A
That's my theory.
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B
Any thoughts on who could this be?
- [14:18]
A
You know, for a long time I thought Adam Beck was in fact satoshi. I've met Dr. Beck. He swears it's not him. I have no reason not to believe him. I therefore revise my views to one level of indirection. That is to say, I think he knows who it is, but it's probably not him. That's as far as I can go.
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B
I've read a theory that says it's Jack Dorsey.
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A
It is less likely Jack Dorsey in my mind than Adam Beck. Even after Adam says that it's not him. But it's also perhaps because when I was hanging around cypherpunks, I did not meet Jack Dorsey. I met him later. So in my mind that person's already. I've already intersected with them, whoever they are. It's also not to sort of delve too deep into this Satoshi conspiracy theories. It's probably more likely a group than one person. It just feels more like a work of a couple of really thoughtful people. Because hashcash and stuff that Adam Pegg put together quite publicly without being pseudonymous is a foundation of what's gone into the original Bitcoin paper. And so it feels like a collaboration, not just one man's genius.
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B
Yeah, I think that makes sense as well. Staying a little bit on the 90s
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A
before we talk about affirmative, it's fun to remise.
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B
What did you learn working with Elon Musk?
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A
Probably fill out a full interview at some point. He has an incredible sense of conviction about just about everything he says and does, which he is probably the first person to tell you he's not 100% right about. So there's sort of a typical truism in leadership and found a leadership in particular where you sort of decision now is better than wrong, decision now is better than indecision and right decision later. I think he takes it to the absolute extreme where you're often wrong, never in doubt. And that is a superpower of his where he will train his aim on a problem, see a solution declared to be so, tell the troops to march forward. It's probably better than 50 50. Right. But it doesn't matter. He doesn't mind being wrong and he will just retry and retry and retry again. And I think that's a certainly something especially for someone with a kind of a proto scientific Background mind is a very difficult thing to get behind. Like a 25 years ago, 30 years ago in the 90s, I would have said that's a crazy thing to do. Like, let me lean back, think it through, plan out the game, I'll be right, then I'll move. Watching someone who is willing to make the move would seemingly bear thought because there's many moves, perhaps infinite opportunities for refinement later is a good counterweight to that approach. And sort of. I'm not sure where I am these days on sort of shoot first, apologize later versus lean back, think it all through. But I'd certainly picked up quite a lot of the gotta decide sort of attitude.
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B
How about Peter Thiel? What did you learn working with Peter Thiel?
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A
Elon and Peter actually share that sort of decisiveness as a superpower thing. Between the two of them, they're quite similar. Peter has another thing which, I mean, Ilon and I didn't work together that long, so I haven't seen him in the sort of full gamut of leadership skills. Peter has one that is truly unique. He becomes so genuinely excited for the work you're doing. Like, you can't fake it. Like, he will become not just a willing participant or a supporter. Like, he can be giddy with excitement. He, when he sees you do great work and that motivates people like, you will not believe. When he sort of leans into a professional relationship and becomes a supporter, you sort of feel like you have to do your best work. Like, this guy is so invested in what I'm doing. He may be more invested than I am. Like, I can't let him down. And so if he is the CEO of a company you're running, it's an incredible leadership skill because everyone around him knows that he is so invested in what we're doing together. In your work specifically, your work is really important to him right now. So that. That's a great skill and a great sort of a. I'm not sure it's a skill versus an innate behavior of his, but it's always motivated me to do my best work at PayPal.
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B
Reminds me a little bit of some of my best MBA professors.
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A
They.
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B
They were not only good because of how they taught in their subject, but because everyone brought their A game to their classes. So as a student, I really enjoyed not just what the professor was doing, but what he was making everyone bring. Right, Great. So talking a bit about kind of fast forwarding a little bit to your affirmed days, I guess this is a subject you've talked about in the past, but I think it'd be good to we hear it. And that's the concept of no late fees. Right. Which is essentially you are saying, hey, if I make a poor underwriting decision, I have to live with it and I'll take the hit. There's no other way to monetize this. Do you think this is one of the most important decisions that you made for a firm?
- [19:52]
A
I think so. It obviously goes beyond no late fees. And no late fees is kind of the easiest one to explained because everybody has such a visceral, oh, I hate late fees. It's so annoying. And we didn't stop there. We don't compound interest. So it's always simple interest loan. We pre price interest. So if you're going to be charged interest, you know, upfront how many dollars it'll cost and it can go up from there. We don't do deferred interest, which is where we agree that it's zero for now. But if some condition is met, it flips becomes not zero. And so we sort of eliminated all of these things. And they were all invented by the industry for two reasons. The typical reason explained as well, you know when you need a carrot and a stick, so a carrot is, I'll tell you, I'll give you a nice rate, maybe I'll give you even a very low interest rate. But if you are late or if you're, you know, you're not following my exact schedule, you need a, you know, need a way to slap your wrist. And so that's when the late fees come in. It's not actually the real reason. The truth is a little bit darker and I can very quickly prove that it is in fact the case that none of these are effective mechanisms. So the, the, there's kind of three groups of people that are late or flip into this deferred interest scheme, et cetera. Some of them are just sloppy and they miss a day because they didn't set the reminder because the calendar changed, because their phone was off or whatever it is, they get slapped a late fee. Oh, I hate late fees. But they're too honest to say, you know what, I'm not paying. In fact, they know it'll cost them more be problematic if they don't pay. So they just sort of eat it and like, all right, fine, I'll pay you and I'll pay your late fee and I hate you and maybe I'll never use you again. And that's like 95 plus percent of people who are late Another group of people, much smaller people who had never intended to pay, and you can charge them a trillion percent late fees, they will still not pay you anything. So the sort of story you tell yourself about, well, late fee will slap your wrist like there's no wrist to slap. They've long left the building like they don't care. And then the smallest group, but very real, are good people that mean to pay. They're not sloppy, they just had something change in their life and they cannot. And that group is actually, they're on their back like they fell down. And by charging them lead fees, you're telling them like, yeah, I'm going to kick you while you're down. And they're the ones who are definitely going to remember and they're going to say, you know what, I'm not using you again. I sent you a sob letter that was true. I had an illness or I had a death in a family, or I lost my job, whatever it is, and I asked for a hardship excuse or a delay and you wouldn't grant me one because you wanted a late fee, like, screw you. But those two last groups, neither one can pay, so there's no late fees there. With the latter you have to wait and then give them a chance. With the former, there's nothing you can do because they don't care. The 95% plus of that of the total late fee content or revolving content on these complex interest schemes, they're just sloppy. The best thing for them and for yourself you can do is say, hey, I think you missed a payment. Let me remind you, let me remind you again. Vast majority of these people say, oh my God, I'm so sorry. So what's the late fee? Because they're so conditioned by the industry to expect it. And the answer is a firm doesn't charge any. And that is the brand making moment that we hoped for, which worked beautifully. People now know that we will not kick them when they're down or certainly when they were asleep with a switch briefly. So that's sort of the why the whole idea of, well, you need a characteristic like that's all sort of industry telling stories primarily to itself. I think at this point no one remembers this analysis, but it is certainly true. The darker, truer reason is inside the fine print that explains all these fee schedules. Typically on the back of your credit card statement is the business model of majority of the issuers where they derive something like half of their profits from late fees, deferred interest, all that junk. And so when we started the company had multiple reasons why we didn't want to do this one. We wanted to build a brand, and we wanted our story to be, hey, you can rely on us not to take advantage of you when you were sloppy or when you actually had something bad happen. Just as importantly, we wanted to attract the brightest minds. And a typical conversation you have with somebody who is in machine learning or data science, really good computer scientist who works on Wall Street. So what made you go join a hedge fund and say, well, I really love financial mathematics, like the bond math, like sort of complicated compounding curves, the sort of really interesting distributions you get out of it. I love that stuff. And I didn't want to work in banking because, like, I don't want to explain myself at cocktail parties. Like, I make money by charging late fees. Like, yuck. Like, I'd rather go to a hedge fund and squeeze the last penny out of the market for efficiency purposes. Which is also kind of a conversation at a cocktail party. But at least you know, you're not riding the back of someone at the same party who is currently experiencing a late fee. And so I thought, you know, what if we could steal some of these best minds by telling them, you could work in finance, you could build these really complex models, and yet you could hold your head up high and never worry about having to explain yourself. Like, oh, I make money by charging a lot of late fees. And so that worked beautifully. Like our original team with some of the brightest people I've met already, by then, having been in the industry for 20 years, there's some really, really great people, and many of them are still here. The third one, kind of the most important reason is we thought from the very beginning that our advantage would be underwriting. And nothing makes you better at a thing than constraints. So if you look at any bank, anytime they talk about increasing delinquencies, the CFO of that bank, typically on a public call, will say something like, well, delinquencies are rising a little bit, but it's okay, because the late fee income will rise with them. And so we'll sort that out. It's okay. Like, delinquencies rising, fine. Late fee will rise accordingly. And at the time and to this day, I believe that that's basically shorthand for we can be sloppy. We don't have to be that good at underwriting, because if we screw it up over here, we'll just make it up on the late fees. It's all good. And we really want it to be the very best at underwriting. So we will charge nothing above what we said we would, because then whatever happens to delinquencies will not get an offsetting income anywhere else, which will make us scramble and improve the underwriting functions. And that's exactly what happened. Our underwriting is second to none. And we've never had the, oh, don't worry about it, we'll make it up on delinquencies as the fee income rises. And so I'm not sure at the time I knew all of these would actually play out as I had expected them to, but they did. And more often than not in my career as an entrepreneur. Make some assumptions and if one out of three works out, you're great. And this was sort of three for three. So that's the full story of why and why we're so committed to it.
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B
As with everything in human nature, incentives matter, right? And so those incentives really force you to have underwriting models that are second to none. How have you adjusted, if at all those models with LLM technology? Is there maybe some unstructured data that wasn't being taken into account that now you can. I'd love to hear from you.
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A
Totally. It's actually sometimes difficult for me to explain as well as I'd like, because for majority of the world, it seems that the ChatGPT moments or the introduction of LLM into the CS vernacular was like this binary thing where neural networks were written off, scrapped, peep of history, and suddenly they were back. And the LMS were a shining example of how neural networks actually make a difference and would be amazing. And if you're in the industry, and I don't think it's unique to us, but we were certainly very much in it for a long time. It's always been a continuum. You look for new modeling technique, you ask yourself what academic papers have been shown to pick up any incremental alpha. Where can you find another technique, another idea? And so long before, I mean, not long before chatgpt moments, but certainly around the same time, we were all reading the same papers asking ourselves, what can we learn from these new applications of neural networks? And so we're now deploying models that were built with the full appreciation for just how powerful the attention mechanism is. And the attention is all you need. The paper that came out in sort of 1718 timeframe really shone the light at a very simple architectural idea that allows you, with great computational expense, incidentally, but allows you to model these fantastically complex systems that have no need for inherent labeling. And we've sort of taken that and ran with it and have all sorts of really interesting ideas that we try to keep close to our best for a little while before the industry catches up. But we have sort of whole new family of models that we've been deploying very successfully in fraud fighting in particular. But also there's applications in credit, of course. But long before that we'd sort of asked the question, can you find incremental information value simply by outsourcing feature finding to LLM models? And that's been the case, well understood by the industry at this point. But I think we were there either first or close to first. And so we've been sort of on this journey of whatever the latest hotness in machine learning research is. We want to be the first ones to try it, we want to run it against what we have today and make sure that we're staying ahead of the train and have been very successful at it.
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B
Yeah, I mean some of these tools were being already used internally at big companies. I think externally there was a period where you could only access GPT3 through Dungeons and Dragons I believe it was. But it was mostly like you said, industry insiders, nerds that really understood this. How would the impact of not a language based model, but more like a math based model, kind of like what Vlad Teneff is building with Harmonic AI? How would that affect underwriting?
- [30:32]
A
Probably an important question to answer. Underwriting specific. As you look at these attention powered models, how can you take data that looks more like a table, essentially a relational database style data set? Can you use LLMs to model that? And the answer is you can. It's a little bit different than what you see in the in chatbots, but it rhymes. And that's an active area of research. There's certainly a couple of companies that we've seen that are doing some really interesting work. We're not even a little bit satisfied with what we know and we think we have something better than most people have. But that's sort of the more applicable thing in our world. Certainly the work being done in codifying math with essentially it is a language model and they're trying to formalize proofs. And so formal proofs is a thing that's been around for quite a while. It's actually one of the very last Vestiges of Act 1 of neural networks when I was in college. So this is full 30 years ago, but I remember learning about formal proofs and sort of looking at some basic neural networks trying to do formal proofs a long, long time ago. And so There's a bit of a rebirth, that whole genre going on right now with Harmonix and a couple of other people who are doing something really interesting there. I think that's a little bit different from underwriting. You're not looking at giant data sets trying to find the next event, but it is undoubtedly applicable. Like, we will see discoveries. The most interesting thing that's going to come out of these formal proofing attempts, assuming they're successful, you will find new reaches of math that have not been proven yet or maybe have not been thought of yet. There's plenty of math that exists, and lots of people believe it to be true, but it just hasn't been proven because proofs are fairly binary. It either works or it doesn't. And as we sort of delve into those, we'll find some math that once we know is provably true, we'll utilize in all kinds of ways, including underwriting.
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B
Credit card debt at a national level in the US is about 1.5 trillion.
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A
Just under.
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B
Just under 1.5 trillion. I think half of it revolves.
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A
Yep, Right.
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B
One of your goals is to actually fight the credit card industry. Do you feel like you're succeeding? Do you feel like the tide is turning?
- [33:00]
A
Not actually fighting the industry as sort of a David and Goliath as it sounds, not exactly the goal. The goal is, in fact, to fight revolving. I think revolving debt for consumers is just a profoundly bad idea. It is very hard. Speaking back to math, we are not neural networks. Actually, we are neural networks. What am I talking about? We're neural networks, but we're just not very good at computing exponential functions and revolving on a progressively larger amount. If you're in debt for $5,000 now and you paid off a little and you spend a little and it's back to $5,000, and then the interest compounds again, and you look at your balance and next thing you know, it's $10,000. And you really can't quite figure out what happened. And what happened is people are very bad at estimating exponential curves. And so as profitable as it is for the industry, I think it's just an unhealthy way for people to lead their financial lives. And so our goal at a firm has always been to provide an alternative that gives them access to credit, that offers them a product that doesn't confuse them, and in fact, is easy to estimate. When you look at a firm loan information, say, Oh, I borrowed $1,000 and I signed up for another 50 of interest, and I am halfway done. I know that I owe $525 and that number cannot change and I have six more months to go or 12 months ago, whatever it is. But that number is not increasing in some convoluted way that I really have a hard time estimating. And so that's what we're attacking. It's inevitably a complicated, more complicated story to tell than any of us prefer easy sort of bookends is to say, well you know what, borrowing is just bad. You should not borrow money. That's just a bad idea. It's too hard, too complicated. Bad, bad, bad. It is not like I imagine you went to college having borrowed a bunch of money. I certainly went to college having borrowed a bunch of money. What are the better decisions I made? I wouldn't be here here, wouldn't know what I know today if I didn't graduate University of Illinois. And I was more than happy to borrow to do that and pay it off in due time. I think that is true for a lot of purchases that really matter. And a firm is for transactions that matter. It's for when it matters. You should use something that you really understand. And a firm is that alternative, the other alternative to ah, too hard, just use credit cards. You know, forget thinking sweat, swipe and then figure it out. And that's how we end up with a trillion plus of national credit card revolving debt. And people are struggling and sometimes get into very, very bad financial situations. And so the goal of a firm is this nuanced approach where credit is good. Like I firmly believe that access to credit is really, really important. Permanent debt is terrible. And so what we're trying to navigate is this product that gives anyone who needs it an can't afford it, in fact excellent access to credit without the burden of getting into debt that they can't explain, can't work out of that. That's the full answer. I've struggled for the last 15 years to explain in one sense how to talk about it in simpler terms. But unfortunately it's a complicated topic which so makes it easier to defend our leadership position because something that this subtle, you have to be very good at math to compete with us. And we're pretty good at it.
- [36:17]
B
And this philosophy is reflected in how you've structured the affirm card. Yes, right. Which I believe is your fastest growing product. Maybe share a bit of that structure.
- [36:29]
A
Sure. It's actually that is the simplest I've come up with over the years. So it's a debit card, it connects to your bank account or we can offer you an account if you don't have one or don't feel like connecting one. And when you swipe, just settles against that account, it's a debit transaction. Unless you tell us upfront, hey, the next one, that's an important considered purchase, I would like to turn that into a loan. We'll underwrite you and tell you, okay, this loan is either interest free or maybe has some interest. Agree to the terms, you agree and then your next swipe becomes an affirmed loan. So it's basically affirm on a piece of plastic that knows how to handle cash transactions, debit transactions, but also differentiates considered purchases and turns them into affirm loans. And the big bet was will people actually go through the conscious process of saying that's a loan and that's not a loan. And we're all trained to believe that, just swipe and go and sort it all out later. But it turns out that that's not the case. We have millions of people transacting every day very thoughtfully deciding between that one. I don't want to wait, want to pay it off, want to move on, forget about it. You know, it's a cup of coffee, $50 t shirt, those are all pay now move on 500 couch, $1,000 computer. Those are obviously better off as pay over time, a little bit easier on the cash flow. Those take a little bit of few clicks in the app, but they, they are rewarded with peace of mind and the knowledge that when they commit to a 12 month loan, 12 months from now they'll be done.
- [38:08]
B
And I think as an outsider, I think the direction of travel for a firm is clear. You, you want to, you're going beyond bnpl, you're, you're going in the direction of a full financial institution. And in fact you recently applied for your bank charter, which makes a lot of sense, but maybe guide us through your decisioning to apply to a bank charter right now.
- [38:36]
A
So it said for a long time that we don't need a bank charter to do what we do. And we have many excellent bank partnerships. So we operate today as a bank partner issuer. So we have several banks that we collaborate with where we're subject to their policies, their regulatory oversight, we have to explain ourselves to their regulators through them and so on. But there would be two reasons giving us a purpose to apply for bank charter. One, we'd get sophisticated enough where we would want our own regulatory relationships, where we would want to speak to our regulators directly and who, who knows if our charter is granted. But we had reached that Point where we can see in some future, fairly distant future, I imagine, still years away, we would want to have a highly direct conversation with our regulators. Just as we get larger and we're still growing. Last I looked, we were growing 4x e commerce and 5x overall credit card spend or something along those. Don't quote me on these numbers too precisely. But the point is we are taking share from both point of sale, share wallet and also taking share from other financial instruments, for example credit cards, debit cards, et cetera. And so given our growth and kind of the consistency of the growth and the number of years we've been doing, it's reasonable to expect that we'll continue growing for quite some time and gain share at some point. Having a direct relationship with your regulators goes from a nice to have to requirement. And that's a first, first sort of brick in that wall. The other side is I said it before, I'll say it again. There will be a day when we want to offer a feature or a collection of features or a new product that requires you to be a bank. And we've successfully avoided that need because we have not delved into products that only banks can offer in this country. But that's not necessarily a true forever. And so. So if and when we're granted the charter, we can expand our interests into features that require charter.
- [40:43]
B
Can you also share a bit about the power of the network that a firm has built, similar I guess to amex as a very powerful network. How does this come into play as part of your overall strategy?
- [40:57]
A
Yeah, I'm on record saying that the only kind of businesses I like to start anyway, our networks. And once you have a product market fit, which is just always a difficult thing, if it so happens that the product is a network, it becomes to at least some degree self reinforcing. Where the more in our case merchants we bring onto the network we connect using a firm API, the more consumers see our logo, the more consumers say, oh, they are accepted everywhere. I really loved that couch I bought with a firm. Now I can buy a TV with a firm. So our merchant penetration fuels consumer usage with no incremental marketing. Someone who likes the product, someone who appreciates the no late fee stance, et cetera, will spot our logo in more merchants and say oh, that's great. Like I love these guys. They're better than whatever I used before, so I'll use them here too. So. So it's essentially a self perpetuating flywheel. And as more consumers use the product, more merchants become Aware of the fact that this is kind of no longer optional. So Amex is a very good analogy because if you sort of look back even 15 years ago, Amex had this reputation, not wrongly, that it's a nice to have logo. So Visa, MasterCard required Amex, you know, they have a lot of tourists, they have a lot of sort of high income folks that would only transact with their platinum Amexes. Sure, you want to put their logo on your door too, but it's not a requirement. Amex has successfully transitioned from this sort of a exclusive club into there are many people now, it's a very large group and they're growing faster than some of the other players. You kind of don't want to be left behind, you want to offer their logo. So from, sorry, it's not accepted here at this point, any gas station there'll be an Amex logo on the pump. And that is entirely because they successfully got to critical mass of merchants who had then got enough usage from consumers. The word spreads naturally. Well, you should add the Amex logo because you know, boy, I added them and I got 15% more transaction, 20% more transactions. The same exact is true for any successful payments network. You have to break through the critical mass of consumers demanding the logo. But once you get there, it becomes self reinforcing where more consumers means more merchants take notice, more merchants take notice, more merchants sign up, more merchants sign up, more consumers take notice, goes around, makes sense.
- [43:26]
B
And you get to the consumer not just via a direct relationship, but you have all these massive partnerships. Shopify being probably the main one.
- [43:39]
A
Of course.
- [43:40]
B
Yeah.
- [43:40]
A
And these are in the modern world merchants are aggregates and Shopify in my biased opinion obviously is the best platform for merchants to use for everything from managing their inventory to their storefront online to their ad campaigns into fully integrated, vertically integrated engine for online sales. It was very important for us to become the preferred partner there so that our logo would be in front of millions of merchants and hundreds of millions of consumers that shop with those merchants. And so that's certainly given us a nice growth boost. But we've since partnered with many more platforms.
- [44:23]
B
Max, thinking a little bit about the future. About a month ago Citrini Research made big headlines. What did they get wrong?
- [44:32]
A
I think they this is not unique to them. I think the temptation to shrug off the difficulty of some of the non technical accomplishments in these companies is a lot. The example they used was in their imaginary future. There are now thousands of successful doordash competitors because it's so Easy to replicate the app. DoorDash app is not the important reason behind DoorDash's success. It's the fact that they painstakingly built up that same flywheel where they got enough restaurants and enough grocery stores and enough places where they're accepted to actually integrate their connection to their network. And so when I open up the DoorDash app, I'm not generally speaking looking, is it accepted? Do I need to get some other app? Like the notion of a fragmented ecosystem of restaurant specific apps or grocery store specific apps is like on its face obviously silly. Like you want to go to a single concentrated source. And like DoorDash primarily worries about Uber Eats, they are not worried about someone saying, well, I have the best app that I cloned from DoorDash because it'll take years, just like DoorDash to get into enough restaurants to matter. So I think that's a good example of kind of what they got wrong and kind of almost to a silly degree. Some of their ideas were certainly easy to believe and relatively powerful, but I think glossing over like, well, they just distribute it somehow. Don't worry about it. Software is all that matters. Software all that mattered. The world would look a little bit different. Like, you know, SaaS would have been a different industry.
- [46:16]
B
Speaking of predictions that you like to challenge, another one is the number of engineers is going to go down. And also us humans work, professional workers, we're going to have a three day work week working three hours a day or something like that. Sounds like you completely disagree with that as well.
- [46:37]
A
Yes, I think that's completely ridiculous. I think there are people who probably hate their jobs and they sort of can't wait to get to a three hour work week or, you know, but I think that's like not even a little bit correlated to advances in AI. It's just like human nature is some people love what they do and some people hate what they do. In some ways, the sort of the corporate level version of this debate or individual one is very similar. Like when we plan. So we're on a quarterly planning cycle at first and every quarter we make this long list of things we really, really want to build. And it's mostly a recycle of last quarter's list that we didn't get to. And then with great degree of debate, we draw a red line through it and everything below the red line is kicked down to the next quarter because we only have so many engineers who are, by the way, all are using AI all the time. If you look at the Pull requests that are AI assisted versus not assisted. That number, starting three months ago, started dominating by AI assisted. At this point, it's basically all AI assisted. And some people use it in ways where they essentially puppeteer AI through English and then read code. And in some cases, people love the autocomplete. We're fairly agnostic as to how we want these tools used here, but we definitely want the productivity boost. In my mind, all that's done is it pushed the red line down so more can be done this quarter instead of kick down the line to the next. And it's very easy to measure. We prioritize or sort these lines in our project list by expected return on investment. So we have some dollars we're willing to spend on engineers. We want a certain revenue set of dollars to come out. And if the math works, then that's coming this quarter and some things will take longer. And so we know how to prioritize that. And you can fairly easily factor token spend into that. And that's what everybody's doing now. And these tokens can become quite significant part of your cost. So you have to start asking yourself, like, what's the most optimal way of using it? What's the best roi? So all the same things we know how to run a successful engineering team with before CodeGen tools is applicable today. But in all the cases, the world in which we say, cool, our list is 1,000 items and we normally can fit about 200 in at the same price. We can do 300 and get more revenue faster. Nah, we should cut the engineering team and get 100 in. It just seems completely counterintuitive. And so if you're running the kind of company where you're just absolutely sure that there's nothing left, like you've reached the end of the Internet, there's nothing to build. Like, you probably should look for someone else to run the company. Like, it's sort of. We're fully out of ideas. We want to work four hours a week just seems like a very. I mean, maybe that's like the, you know, 2200 or 2300 future where we've built everything, we have reached the end of useful ideas or AI. So smart is just building everything without any human help. And maybe it's three years, not 30 or 300, but right now we're in this Cambrian explosion where I. I was literally making coffee this morning, looked at my espresso machine and thought, I wonder if I can use one of these CodeGen tools to get into the barely digital guts of my espresso machine and modify something I didn't like. Oh yeah, I'm gonna. Before I head off to work, I'm gonna ask my favorite agent to poke it around both online and inside the machine, See what I can do. And the number of ideas you can make real and the cost of the barrier to entry to start the project is essentially zero. Like that's the exciting part of AI. Sort of the doom scenario of there's nothing to build implies that everything you see around you is satisfactory, which is just not the case.
- [50:27]
B
It's also human nature. Right. You want to pursue more things. Yeah, exactly. All right, before I let you go, Max, you have said that you spend 99% of your time with a firm. How about the 1%? Other than your family, of course. What other interests do you have?
- [50:46]
A
Very serious about coffee, very serious about road cycling. I still write a lot of code and my personal excitement around this agentic programming is the barrier to start a new programming project is now just knowing how to phrase what it is you're trying to do versus committing a weekend long project to learn a new programming language or a new form framework or new approach. And so that. That's the most exciting thing about favorite
- [51:10]
B
coffee making technique for me. It's French press.
- [51:13]
A
Espresso. Espresso.
- [51:15]
B
All right. You have talked about watching and re watching Seven Samurai and you recommend that to entrepreneurs often.
- [51:25]
A
Why is that? I think it's one of the most entertaining and sort of artistically beautiful master classes on leadership. Like the short version of the plot is a bunch of unorganized villagers get attacked by these terrible bandits. They hire a very small team of professional soldiers led by a veteran to defend them. But what actually happens is the soldier, the character's name is Kambe, builds a team and an army, but it's really a team of not just the samurai, but the villagers organizes them into an army to beat the bandits. And it's a beautifully shot. It's a 1953 movie, all black and white, sort of very stark. But it's an amazing story and it's a great story of how to lead people who do not believe they can win.
- [52:17]
B
I'll check it out on my fly back to New York.
- [52:19]
A
Should definitely. I've seen it 113 times.
- [52:22]
B
Oh my God. It's a.
- [52:24]
A
It's a favorite.
- [52:25]
B
Lastly, what did you strongly believe when you started a firm that you no longer believe today?
- [52:33]
A
When we started, I thought the primary reason for choosing to try a firm would be affordability, where people would say I don't have access to credit or I don't like the cost of credit that I have. I'm going to rationally choose this new product that at the time would never have heard of. It seems like it's fair and interesting and it'll be affordable. The reality turned out to be all that. But the flywheel of the brand where people actually remember the treatment they receive from us, they'll know late fees, the total transparency, the no compounding, like all the stuff that we talked about turned out to be much more important. I always thought of it as an internal advantage where I would recruit the best team. I would be able to hold my head up high and say, we don't charge late fees. You know, we are the good guys in lending. But I never really expected it to be a thing that our audiences or our user base would say, these guys are good guys. It's credit. Like, you need access to credit and then you forget who gave it to you. Not so. It turns out that people actually remember and they really take to our brand with a great degree of love. I think the best thing. So I'm always wearing my logo, which part of it is just sort of. You run the company, you got to wear the colors. But I also do it because whenever I'm outside the office, there's always someone who stops you on the street or especially at the airports. And like, do you work for a firm? Like, yes. Like, I love your company. I challenge any lender, any bank, any lender, any financial services provider to have that degree of consumer love. It's super gratifying and I don't think I expected it, but I'm certainly extremely happy with what I got.
- [54:16]
B
Well, Max, thank you for spending this time with us. But probably more importantly, thank you for all your contributions to our industry and for inspiring multiple generations of builders.
- [54:29]
A
Keep deleting me, but thank you, thank
- [54:32]
B
you, thanks for tuning in and I hope you enjoyed this great episode with the legend Max Levchin. If you want more interviews, make sure to subscribe, follow and leave a review on Apple, Spotify, YouTube, or whenever you listen to podcasts. It helps and means a lot. And if you have any suggestions or thoughts about the show, just drop me a line on LinkedIn. See you next time.