You're listening to leaders in lending from Upstart, a podcast dedicated to helping consumer lenders grow their programs and improve their product offerings. Each week, hear decision makers in the finance industry offer insights into the future of the lending industry, best practices around digital transformation, and more. Let's get into the show.
Welcome to Leaders in Lending. I'm your host, Jeff Keltner. This week, we're going to re-air one of our previous episodes from 2022. In fact, our most popular episode this year, which is my conversation with Upstart Founder and CEO, Dave Gerard.
Dave and I dive into the problems he saw in the financial space that caused him to leave Google and found Upstart. Why really the big bet of Upstart is the belief that AI is going to transform the entire AI lending experience and really the entire industry and what that looks like where it's headed.
We dive a little bit into where Upstart's come, where we started how we got here, but I think equally importantly, what the future holds and why the big bet I think really is still on the possibility of AI completely transforming the entire lending ecosystem. I think we believe that it now as much as we ever have and so this conversation retains all of its relevance.
Dave, thank for joining us on the podcast today. I appreciate your making the time.
Dave,感谢您今天加入我们的播客。我很感激您抽出时间。
Great to be here, Jeff.
非常高兴在这里,Jeff。
This will be an interesting one for me because you and I know each other pretty well versus many of my guests that I don't know as well. But I really wanted to start the conversation with your life pre-upstart and like, walk me a little bit through how you ended up in, it feels like at two interesting places, at interesting transition points and cloud computing at Google back in the early 2000s and then in Fintech right now, you kind of find good points in the wave to ride them.
Yeah, I mean, I guess to go back to the beginning a little bit, I mean, I grew up outside of Boston in a suburb. Born in the 60s, grew up in the 70s and 80s. So I'm a lot older than most of the founders until a convales for sure. But my parents for like first in their families to go to college, they have that sort of, you know, move to the suburbs is the greatest thing you can do and get a job and work your way, etc.
So like the whole motion of entrepreneurism, if that's a word, wasn't really honestly in my vocabulary or family or DNA whatsoever. It was really about just sort of that more traditional path of a career and, you know, went to a great college and ended up coming out to California in the early to mid 90s and of course landed in technology.
And I've been here ever since 28ish years out here. So I quickly gravitated. I mean, I studied computer science, computer engineering in college. I wasn't destined to be a programmer for my life. But I was certainly kind of enamored with the potential for technology and so, you know, that's what got me out to Silicon Valley. I had a stinted apple like way back when, you know, another startup that wasn't my startup, but you know, had some startup experience and then landed, you know, quite a few years now in 2004 at Google.
And that was a little fortuitous. It wasn't yet public. So nobody quite knew what to make of Google, you know, until they saw the numbers, and they knew what to make of it. It's hard to think back to when Google was an unknown quantity of like, is this a good call to join or not? But that's what it felt like back then.
Yeah, I remember like driving there to go to an interview and thinking, wow, these people work for Google. I'd never met someone who works for Google because it was quite small and it was just this really search engine that was getting to be famous, but still wasn't really clear, you know, what exactly was going on in those buildings. And so anyway, I was very fortunate to have landed there just at the right place at the right time and spent eight years there building what is now called Google Cloud.
You know, didn't call that then, but it was the cloud applications like Gmail and Google docs, etc. As you know, well. And so that was kind of like a nice pioneering thing with some of the challenges being that Google had this crazy runaway business, advertising business, that in some sense, as you know, so we always had to compete with in terms of resources and attention and hard to be the little brother, little sister to one of the greatest financial innovations in the history of mankind, which would be the Google advertising system.
Yeah, that is maybe the greatest business innovation in history, just the way that thing prints and continues earnings call. It seemed to continue to go well.
哦,可能这是历史上最伟大的商业创新,就是那个东西打印并持续进行收益电话。它似乎一直都很顺利。
Yeah, it just doesn't even stop.
是啊,它根本停不下来。
So now, tell me about the decision to leave because I remember, I mean, I left and I used to tell the joke that my mother-in-law, you hired me into Google, you hired me out and she thanked you for one of the two because it was kind of like the place you believed, right? It was the thing we wanted over on the upstart.
But, you know, and I remember when I left, you had already started upstart, you had some, you know, sense of where you're going and that felt like maybe a crazy decision, but you were you were leaving, you know, maybe the greatest place in the world to work as people like to point out to me with like nothing but an idea and some hope that somebody would give you some money. That seems like a huge leap, what got you to the point of saying this is something I want to go do?
Yeah, you know, I had been there for eight years. The apps business had grown into, you know, about a billion dollar revenue run rate and all the way along, as I said, it was kind of a secondary, frankly, business for Google. And I always thought once you get to 100 million, once you get to 200 million, once you get to a billion, you know, it's kind of all of a sudden be the center of the universe there. And of course, it was just you just keep it up with the advertising business. So anyway, it was a great success. I mean, it's actually heartwarming to me that it's so big today and they're carrying it for it's more than a 20 billion dollar run rate business.
And so it's really, it would have been very saddening if they had just sort of written that off after I left. So in any case, you know, having been there eight years, I kind of always wondered, you know, it went really well for me there. But was it, was it me or was it Google, you know, could anyone have walked in there to those doors in March 2004 sat down and just started turning knobs and built a great business because Google just had such core strength. So part of it was, you know, I wanted to prove it to myself. Part of it was, look, I was there for eight years. I could stuck around for another eight, but, you know, is this the last cool thing I'm going to do with my life? I'm going to take a shot at something different. And I'm not sure I ever imagined I could leave Google and do something cooler better than what I had done there. But that's, you know, I fortunately, I had made some money. So I had the financial freedom to do it. And my wife was behind it. So, you know, when you're in Silicon Valley for 20 some odd years, at some point you decide you want to be a founder and you want to try that. And I do recommend you don't wait until you're 45 years old to do that, generally speaking. But that's, that's what I did.
Well, if that's your advice for me, I'm running out of time. Well, you're pretty much a founder here. So close. So tell me about the initial, like, what was the problem? I feel like most founders more than falling in love with the product that they have or an idea, it's like, it's a problem in the world that is the thing that drives them to say, hey, this is the thing I've got to fix. Right. What was that problem as you saw it when you were sitting at Google and you said, hey, this is the thing I'm going to go and as my shot is a founder to take a shot at doing this, like, this is what I want to go try and fix.
Yeah. You know, I'm not a purist to say like the only way to be a founder is to have an idea that you're obsessed with and fixed and you can't, you know, there's a lot of people that say, this is the only way to do it. That's the only way to do it. I guess for me, like, I got the idea of starting a company would be cool and ideas were coming night and day to think about it. I just, I just got an open mind to look for things that could be interesting companies for a period of time. You know, I literally started thinking about the notion I had a really nice Canon SLR camera. I really hated how I had to like take it home and connect it to my computer to get the photos out. And I was like, maybe I could have like a SD storage that was actually a Bluetooth sort of device. It could stick it instantly on my phone. I literally wrote this down in like a Gmail draft and said, you know, so think about a Bluetooth, you know, SD card for a, for a nice camera. And, and then the next thing after I wrote it is like letting people borrow from their future income. And it was just randomly through some serious conversations where it just kind of became clear that young people are kind of potential rich in cash poor. And that sort of potential rich in cash poor situation made them sort of make decisions that ultimately weren't awesome for them. We're not awesome for the economy. And so it really was just fascination with access to capital and access to credit how it worked. And you know, it didn't immediately lead to what upstart has become, but that was really this thread I started to pull way back then.
Interesting. And how did you go from, you know, young people with potential, you know, I like that phrase more potential than access to credit is an interesting concept. But how do you go from that to unsecured lending? I mean, that's like, you know, there's a lot of things you could do that almost feels like student lending in some way is the thing that you're going to say, how do I like enable people to pursue their dreams education seems like the thing or, you know, certificate programs of boot camps or in that kind of space.
And you ended up over a series of times on like unsecured consumer debt, which is just not the obvious place. Talk to me about how you got there.
你最终陷入了一连串的消费贷款问题,这并不是显而易见的地方。告诉我你是如何走到那里的。
Yeah, you know, I think when you started a company, you had this thing drawn up on the whiteboard that you're fascinated with and you love. And in our case, it was what became to be known as income share agreements. It was similar to alone, except you could, you would essentially pay back as a fractional what you earn instead of a by a defined interest rate. And so it was this very novel concept.
I mean, it had been kicked around sort of in the University of Chicago School of Economics kind of thing for a long time. But we were, I think the first company to really make a go of it as a platform. And but the reality, of course, is, you know, that whiteboard meets the cold reality of the world. And it's the outcome is not always pretty.
And effectively, we chased this kind of business model for about a year, bit more than a year. And, you know, kept trying to turn the knobs and see what we could do to make it work. But ultimately, it wasn't kind of scale. It wasn't going to be a successful company. We didn't have them much cash left. And so we, you know, toward the end of 2013, decided to move toward a much, a product that existed in large scale, which is a consumer loan.
The real insight that ended up making it a success was, you know, Paul, my co-founder had built a model to predict what somebody was likely to earn over their career. That was the price and income share, right? You have to figure out like, yeah, what they can make on that thing. So we had a model that would predict, you know, given everything it knew about you, what you're likely to earn over the next decade or so.
Well, we sent over a very short period of time, Paul transformed that into a model that said, what's the likelihood they're going to pay back this alone? And so it's sort of like asking different questions of a model. And load behold, starting in 2014, we had what became a very unique credit origination model that used data, both traditional data and data that, you know, traditional engines weren't using.
It's very simple simplistic back in the time, but I'll just say that the day we sort of pulled the lever and moved from income shares to loans, it started accelerating very, very quickly. So suddenly, we don't done that. Creating a bespoke market from scratch is no small task. It's no small task to step into a giant, heavily competed industry like lending, but in the end for us, it was obviously the better, the better step.
Yeah. I remember most about that, that those months was how risky the decision felt in advance and how obvious it felt on retrospect. I mean, you turn it on, you watch it, you go, how did we ever think this was a, was a questionable call, but it did not feel obvious at the time that we were the first call. I mean, it's hard to like do us something. Even if it's not working, I mean, you put so much into it, it, it, it always felt like maybe the next turn around the corner, it was going to start working.
So it is hard to work away and, you know, the, the chapter of the upstart book that we will omit is the one where we did hedge and we did look for a period of time. I'm sure you recall to actually having both of these products in parallel, just, just to sort of have a loan if you want a loan or an income share, if you want to do an income share. And I'm that sort of thing, which we invested in for a few months, we shut off in about a week because it became clear what everybody wanted and it wasn't the income share agreement.
No, it became obvious. And it's a little bit about like the unsecure like you could have, we could have asked Paul to kind of predict student loan repayments, other things. We kind of set it on unsecured consumer debt in the kind of smaller range and student loans, shorter duration of three or five years versus a student loan, which is often 10 or 15.
Talk to me about the parts of that market that make that a more compelling place to start from your point of view or why you didn't go somewhere else.
跟我谈谈那个市场的哪些方面让你觉得更有吸引力,从你的角度出发或者为什么你没有选择其他地方开始。
Yeah, I think it's really a question of what as a non bank, a technology company, you know, what can you play, what can you prove? And secured loans, whether those are cars or homes or what have you, it's just a lot to those, a lot to prove credit cards. The funding structure of a credit card is fairly sophisticated.
You know, an unsecured personal loan, first of all, obviously the fintechs were largely creating the category, the lending clubs and prospers at the time were kind of essentially had been creating this category out of almost out of thin air. So it was clearly doable, even if you had, even if you were selling loans to hedge funds at fairly high returns, if you hadn't a strong enough edge in your model, you could get started. So in some sense, it was doable. And that's probably the first thing.
But the second thing also is it's really kind of the purist form of credit, right? You're just underwriting an individual, there's no collateral. And in some sense, it's process wise, the easiest and it's model wise, the hardest. So that was a good fit for us because we had real modeling advantages we believe and I think we're proven to be true. But we of course, the idea of trying to like, I'll suddenly build a mortgage origination product out of scratch, certainly felt beyond us at that time.
Yeah, it's really interesting to think about where your strengths make the biggest difference in the market and focusing on that, which felt like the right decision for the company at the time. So we've used the word model a bunch and I mean, I'm sorry, it's maybe at the forefront of what we term AI lending and applying AI was AI or machine learning always kind of central to the thesis and central to how you were thinking about what would differentiate the company because it's very much center of what we do today. But I'm curious if that was always in your mind, the thing that was going to be the differentiator or the focus.
Well, you know, in the early days, we certainly didn't use those words. We definitely thought more data in better math, right? So and they kind of go together, the more data you have, the more you need more sophisticated math to make any sense of it. But we really, you know, we always like in the beginning, it was Monte Carlo simulations and a few other things that were probably better than what's out there, but not dramatically and we started with two or three dozen variables assembled together to create the first version of the model. So I definitely think we saw the road ahead. We knew what we were ahead. I don't think we would have been so bold to call it AI in those days. Probably would have been a stretch of the term, but you know, over time, certainly as the amount of data in the sophistication of the models grew, it became obvious that that's what it really is.
It's using AI and or machine learning to sort of predict the future to make credit decisions and in a bunch of other things as well. And but again, I think we knew the path we didn't quite have the vernacular nor do I think it would have made sense back then. Yeah, the initial models were not sophisticated enough to probably earn the time term AI. That's right. I think they are now.
I'd like to explore a little bit too, then, how the usage of AI evolved because there's both the sophistication of the initial model, the kind of income prediction turned into some version of can you repay. And then there's all other sorts of parts of the lending process to which upstart is now applying AI.
So talk a little bit about the journey of like, how do we think of AI in the process and how do we go from the one problem who deserves access to credit? How do we think about likelihood to repay to applying that more broadly to the problem of getting a consumer alone?
Yeah, when you think about lending and the lifecycle of lending, there are risks all along the path, you know, all the way from the very beginning. If you're going to spend some money to send direct mail to a bunch of people, you're risking that no one's going to respond to that thing and you just do some money down the toilet. Obviously, writing the core of it is the decision about who you lend to. And there's a lot more. But in the very beginning, the only thing we really tried to do was say, will this person default or not? What's the likelihood for this product that they're applying for? So it was a very binary sort of thing.
What's the percent likelihood of default? That's simple. And there was a lot of room for improvement just in that. And so that's where we got started. But over time, of course, you start to look through the whole process and you say, wow, all along this path, there's ways to be better modeling and better predicting the future de-risking the process. So for example, the credit decision itself is not just important whether or not they default. It actually really matters when. Someone who defaults in the 10th month of alone is very different from someone who defaults in the 3rd month of alone.
And so over time, probably over a period of years, turned a model with a sort of binary prediction into one that literally predicts the likelihood of default and or prepayment for that matter each month of alone. And that switch, which we flipped, I think in 2018, something like that, was the single biggest upgrade to our model we've done.
Now, of course, in online lending, there's a lot of risk involved, a lot of potential fraud, a lot of misrepresentation of credentials. So we also began to apply what we do to the problem of verification. Where essentially you wanted to do is make the borrower do as little work as possible, but verify everything you can.
In the early days, we just had a hard rule. We were trying to build that credit decision model. So we just verified every input to the 10th degree. And it's the hand. Was that by hand? We were talking to everybody, looking at everything. Yeah, it was just really, but the average applicant would probably upload four-ish, five-ish documents, and it'd be reviewed, there'd be phone calls, there'd be everything. And over time, we began to build more automated ways to do it.
And we also began to build models too. If you knew four things about somebody, what was the likelihood the fifth thing was true or not true? So we began to apply machine learning to that part of the equation. And if you fast forward to today, vast majority, more than two-thirds of our loans, there's no human involved on any side. There's no documents to upload. There's no human involved. And that's a true degree of sophistication.
We've been able to get to over time. Yeah, I think that's fascinating to see both the increase in sophistication and the core problem that you started with. And then they're like, hey, there's lots of other problems. We could take this concept and apply to and improve the process. That's kind of how I guess growth works in a business.
Talk to me now about the, you made this decision somewhere down the path. We started with a going a bank partner route where all the loans were really originated by a bank and not by even apply for charter or state licenses and become a lender the way some fintechs have pursued.
And then later on, the decision to partner with more than one bank to make this kind of a technology that you were making available to banks, to crush it to banks, and credit unions and other lenders. But why that decision? Why the path of working with existing financial institutions versus the kind of disruptor? We're going to throw out the banks, the bank is the old way. We don't need them. I think a lot of fintechs take that approach. This is very different.
I'm curious why you thought of that as the right approach for upstart. So in the first few years, I think we just wanted to make a product that worked. We weren't in position to go work with 200 banks or 500 banks. We really just wanted to prove we could build a better product.
And we worked with one single bank in those days to make it work. I think we reached a point in the history where it felt to us that this notion of being a brand with a hidden bank behind it and selling loans to hedge funds or whomever or maybe through to securitizations was ultimately the best business model. So we saw fork in the road where either you become a chartered bank of one type or another.
You take deposits and also that improves your cost of funding. It improves your liquidity, etc. is a lot of great reasons to do that. Or you just say we're not a bank. We really want to be a technology company and partner with banks. And you know, it's a lot of us being like you and I are ex-cougal people.
Becoming a bank didn't feel natural to us. It just felt like look, we're building great technology here. I don't know if we have the DNA of being a bank ourselves. But there's a lot of banks out there and I don't think it makes sense for most of them trying to replicate the kind of things we're doing here.
So I think we took what ended up being a unique path. I don't think others in our peer group or industries really decided this path. But for us it made a lot of sense. And it kind of made all of a sudden we can't just work with one bank. We have to work lots of banks. And that opened up a whole bunch of new sets of capabilities and functionality we needed. But I think several years later now it's been proven to be a great path for us.
Yeah. The interesting part of that path to me is that it introduces a number of people producing oversight or looking at what you're doing and wanting to do diligence. And particularly with the utilization of AI in an environment where that is from a regulatory point of view, not as well understood how to think about how regulations apply.
How do you think about working with your partners to make sure, hey, what you're doing in this space, it's kind of on the cutting edge. It may be where legislation or regulation has kind of thought about how to engage. How do you work with them to get them comfortable and feel like you're supporting those partners through that journey? And in some ways it's easier not to have them onboard everybody going, hey, absolutely, what do you think about this over here? And when the guy from the CFPB said something, so it comes with a downside.
I'm curious how you think about engaging with those partners to make sure they're comfortable and supportive of what we're doing. Yeah, I think very early on we knew that banks are heavily regulated and conservative by nature and they should be.
So working with them, building a product that banks would adopt really meant kind of seeing the world from their position and providing the types of controls and visibility and data that meant they could do this responsibly. They could do this with their own policy, with their own risk appetite, with their own business objectives and ways that they just had a lot of degrees of control.
This is an upstart originating loans for you. It's a tool set that allows you to originate loans better than you could yourself. And also in the company is both a consumer-facing company but also really enterprise company selling the most sophisticated technologies into one of the largest and most important industries that we have in the US.
And so pulling those both off is no small thing. Also it became obvious this is not a do things wrong and apologize later move faster and break things type of industry.
所以完成这两件事情并不是易事。此外,很明显这并不是一个以后再道歉、先快速行动再打破规矩的行业。
So we began to engage with regulators really from the inception of the company to say, hey, we think what we're trying to do is going to be very good for the American consumer. It's actually going to be very good for lenders.
And so I think literally back in 2012 before we even got started, we marched up and met with a CFPB and kind of open book showed them what we're doing. And then you know, over time as we started to look to working with banks, took some of it similar approach with FDIC, the OCC, the Federal Reserve, et cetera.
And I think perhaps little nightively, you know, Silicon Valley company just saying, hey, here's what we're going to do. We're kind of open in the commoto to you. What do you think? But I think it's paid off and you know, it's never perfect.
I view it as an area that we will need to invest in along with our bank partners for a long time because it is cutting edge technology. There's a lot of suspicion about AI and what it could do and could it introduce bias? Is it explainable? All these myriad of issues. So we have needed to proactively work with regulators both directly in and with our bank and credit union partners because it's a whole new area of technology and you just can't expect the world to just embrace it overnight.
It's going to take a lot of proof points that this is a good thing. It's helpful to banks. One of the most important things is it's going to allow more banks to be competitive, right? That's our belief is you're going to have success of more banks, regional banks, community banks. And the largest of banks, despite the onslaught of technology and fintechs and everything else going on out there.
But you know, it's a journey and it's a journey will never be done with. But those are what I would say are the two big pillars that we had to sort of take on when we made this move, which one is having a product that works for banks gives them degrees of control they want. And number two, of course, is sort of a constant effort to work with regulators.
Yeah, it's a fascinating space to be in very different than the pure SaaS space. That's a little simpler. The challenges are, I don't know, they make strong companies I think in the end.
One of the other interesting decisions that upstart made that I think is very different than many fintechs in the space was to focus almost exclusively on a single product for what feels like an extraordinarily long period of time compared to many who are coming out there with I'm going to have all the products, lots of stuff and two or three years, why that focus on one product and then obviously auto lending is kind of phase two and there's more stuff coming down the pipe.
So I'm curious why the focus on keeping really, really focused on a singular product for that long and then what made this the moment to say, hey, it's time to go and really start putting a lot of bets in different areas.
You know, a little bit I would say the DNA of the company and the founders, you know, a lot of Silicon Valley is extremely good at raising a lot of money. I mean, you have a lot of money, you become very good at spending a lot of money, usually means you hire a lot of people and a lot of people, you're just actually going to want to put a lot of products out there and it all sounds good and you're kind of hoping it works out sometimes it does.
But I think we were a little more wanting to really prove we had something, we wanted the product to work for banks, for consumers, we wanted the unit economics to work and we just didn't really see a place to sort of replicate what we were doing until we really had the confidence of working and that took quite a few years and I think we will have, you know, we're hopeful that this will prove to be the right path in the long haul.
We're now moving pretty quickly into auto lending on the platform and to us for a variety of reasons that was a logical next step. But it took us years to get started and now we're finally really beginning to see progress on that front. So we will go broader, but we really felt the base had to be exceptionally strong. We're going to do more work to do auto, more work to do a small business product, more work to do a mortgage product. Eventually, they all require a lot of work, but the stronger the base is the more proven it is, the more confident you can feel with dealing with the differences between these products, which are not small.
Yeah, I think it's, it was really, it's so interesting that you focus on really getting to positive unit economics, like a business that works before you expand because so often the startups they don't do that. And so often I think in Fintechs, they're focused on solving the business problems. The next product will just like it'll fix all of our unit and I'll just get fixed. And we just have two more things to put out the door. It's like the change man, right? We volume, we make it up in volume, but anyway, sometimes I can't make up losses with more losses.
Exactly. So I think those are just, and those are really the key focus areas now for new products. Is it kind of auto, small business, mortgage? What do you find as a unifying thread for how you see upstart improving outcome?
Or like adding value in those spaces? Because it's easy to go to a bunch of places and I think many institutions feel like their goal of having those products is to have them. So when they have a customer they have all the things a customer might want are available. And I feel like upstart's eat us is a little more like we're going to go into a space. If we think we can make it better in some meaningful way, if we can add value to the consumer, the bank, but improve the outcomes, how do you see the thread between those as far as like how the how you know upstart adds value to the ecosystem in those spaces?
Yeah, I think that the sort of common thread is we look for inefficiencies in the existing market, existing products. And in ways that mean that consumers aren't being particularly well served and maybe banks aren't doing as well as they could in a category. If there's no inefficiency, then you're just going toe to toe and there's no margins and there's just no win in it. You know, you just kind of, it's just a fight, a zero sum fight for market share. And we're not necessarily interested in that. We're looking for fairly transformative opportunities to make the product way better from both parties construct.
And, you know, so auto, for example, clearly, I would also say we're trying to be increasingly meaningful both to the consumer and to our lending partners.
Meaning personal lending, you know, it's a fairly new product. We think it's incredibly useful. I like to call it the duct tape of credit. Consumers love it. Banks love it less, but they're warming up. But it's a useful product. But of course, it's not the centerpiece. It's hard to say everybody in the country needs a personal loan.
But most people do need auto loans. Most people eventually, if they want to be homeowners, need mortgages, most small businesses need to tap credit. So we look for very large categories that really, in our view, underserved, not really great solutions or offerings from the borrower perspective or from the lender perspective.
And you know, I guess it's a little Amazon like, I mean, Amazon always says like, your margins are opportunity. And it's inefficiency, right, where there's just a room where better models, more sophisticated, a elimination of friction can lead to better outcomes for all parties involved. And that's what I think is the real opportunity.
If we talk about auto lending, for example, you know, we're getting involved now we're in a business where there are consumers involved. There are lenders, banks and lenders involved. There are card dealerships involved. So you also have yet another party in this thing. But in our view, the market works so poorly today that there's a chance to build product that leads to better outcomes for all three of those parties simultaneously.
And that's actually, in our view, ultimately what you want to achieve. You're not here to like put them out of business or them out of business. You hear to really do something that can be a win all around. And I think we have that opportunity. Yeah, that's the thing that I always come back to for the business is kind of that core insight that like many more Americans are credit worthy than we understand to be so. And if you can close that gap, then there's wins in that for everybody.
The consumer can win. The lender can make more money, lower losses. The dealer can serve more consumers. So that that core insight really has a lot of legs. Yeah one of the, you know, main message I really feel like we need to deliver better to the market is, you know, credit score, FICO was invented in 1989.
And it clearly was a very novel notion, sort of a universal number you could look up, not for everybody, but for increasing fraction of Americans to have a basis by which you could decide if you could make a loan or not. And of course, before that, God only knows you had people sitting across the desk from each other asking questions and more problems than you can count in that process. So it was an advancement. But, frankly, if you look between 1989 or 90 and today, have we really made strides forward in terms of inclusiveness, in terms of access to credit on affordable terms?
I'm not really sure that we have. I don't think the world looks much different in terms of who can get a loan at what price. So we really feel this sort of use of technology, AI machine learning, applied to this very large segment, which is such a big part of our economy, is long overdue.
I mean, it's wonderful cloud computing and AI have all sort of come to the forefront in the last decade. And it's unlocking this thing. But the real bright future we see is where the vast majority of people have access to affordable credit on reasonable terms in the blink of an eye, not through a elongated process or painful process, but when you need it.
Because as someone who grew up as a product of really high quality access to credit, I'm almost like a testament for when it works well. I grew up in a family with effectively no net worth. I was able to go to a great college and finance that. I went to a great grad school and finance that, moved to the west coast, bought my first car, bought my first home, found my way to Google, found my found it upstart.
And all along the way, if I did not have access to affordable credit, there's just none of it would have happened. So I'm sort of an example of when the system works well. And I'm very grateful for that. But there's just many, many millions of people who never would have had the chances I had. And that's what we're here to fix.
How do you think about it upstart as the company grows, keeping people's focus on that? I mean, I feel like all of financial services when I talk to people and banks and credit unions have an obvious kind of affinity to helping consumers, saying, hey, we want to watch the George Bailey.
It's a wonderful life. We're going out and using credit to enable. And then you read the stories. In other words, one about some of the credit card banks where for so many people in the institution, it becomes a game and they're like optimizing outstanding balances and like revolving credit because that's where the money comes from and you're turning knobs and you lose side of like what you're in it for and you kind of start making choices that aren't as good for the consumer because they're a little bit better for the business.
How do you think about driving the organization as it grows and grows very rapidly to maintain that focus on kind of the true north being? How do we help people have more access to credit and not turn the knob to optimize gross profit margin or something like that?
Yeah, I mean, let's say first of all, you have to start with alignment, meaning what you hope is success of your business, growth of your business is well aligned with this mission you theoretically are pursuing. If there's misalignment there, it's really hard.
So just take, I mean, I don't want to pick on any particular social media companies, but if a social media company's goal is to keep you using the product as much as you can, ultimately, you have misalignment between what the consumer wants and what you need as a business and that misalignment is really hard to address because I don't think any of us believe being on our phones all day long is a good thing.
I'm not frankly sure if the metaverse in immersing ourselves further in a fake world instead of the real one is a good thing. But from our point of view, I think we have really good alignment when we grow, when we enter new categories, when we bring more banks and lending partners on board, when we serve more consumers, it's generally because we're giving them better than they had available elsewhere.
So that alignment is fun, it's really hard to change. I mean, if we didn't have it, we wouldn't have it. We fortunately do. So that's a good starting point. From there, I would say, being a mission-oriented company means not having to say your mission-oriented company, you should just feel it.
And everything you do, everything you talk about naturally is about how do we improve the product for the consumer? How do we make it easier and better for lenders to serve the consumer? And it becomes obvious like why you're doing this. So at Google, Jonathan Rosenberg always said, repetition doesn't spoil the prayer. He didn't make that up, of course.
But as a leader in a company like this, you just have to day in, day out, keep reinforcing why we're doing what we're doing, challenging anything that seems to run in the face of it in the wrong direction.
And we kind of know our success is the world's success in a way that we feel inherently. So that alignment and then just that constantly reinforcement of where we're going and how we make decisions, how it drives what we do, sort of keeps you on the right path.
Yeah, I think that's an interesting point that it's not about, mission's not about talking about the mission, mission's about how you ask questions in the product and the business and the day-to-day execution, and does it align with what you want or not? Ultimately, you could put the make every company's got these mission statements on the wall and you, it doesn't feel that way when I'm here.
And that's a row of capturing things and words because they become roundable and repeatable. So I'm not against mission statements and not against value statements. We have those in those things.
Yeah, but ultimately they don't certainly don't make the company, they don't make them more real than what is already real in the company. And I think we live it every day. We have three founders that have been here since day one and that really helps us stay true to the mission. Agreed.
And one last area I want to delve into is a clearly AI transforming the consumer finance, probably the business finance and lending space is something, you know, UC coming.
What are the other interesting trends you see in Fintech or finance in general, with just kind of like the BNPL, the embedded payments? There's all sorts of like stuff going on, crypto. There are other areas you're going, hey, this is the thing I think is really got some legs. What do you focus on over the next couple of years?
Yeah, I think, you know, I certainly am a student of crypto and I think it could be one of the most overwhelming changes that any of us will experience in our lives. It's paying more goes and it's a little unclear.
I mean, I think, you know, I love to watch what Square now called Block is doing because, you know, they're really building an incredible ecosystem, both of consumers, meeting they have a huge consumer presence, but also merchants.
And so if there's anybody that was going to flip a bit and suddenly you're using Bitcoin to pay for something instead of a Visa, MasterCard rails, it would probably be, you know, Square or again, now called Block. But so I think that area of technology is, I mean, there's a lot of other things that are good and helpful, important that I think are just making business more efficient, making things easier for consumers.
如果有人突然决定使用比特币而不是 Visa 或 MasterCard 这样的支付方式,那么最有可能的就是 Square 或现在叫做 Block 的公司了。我认为这个技术领域有很多其他的好东西,它们能够帮助企业变得更有效率,也让消费者更加方便。
But when I think of something truly, potentially transformative, certainly it's sort of Web 3 and what could go on there. And it's certainly an area that we are going to be involved in over time. And I think at the right time, we want to make sure our partners have a foot in this as well because if it is that transformative, if you are a financial institution of any type, it's going to be a part of your future. And I think we can be an ally for our partners out there to make sure that they're on the right side of things. If and when, as crypto plays out, so to speak.
当我考虑到某些真正、具有潜力的变革时,肯定与 Web 3 有关,它可以在那里发挥作用。这肯定是我们未来要参与的领域。在合适的时候,我们希望确保我们的合作伙伴也涉足其中,因为如果它真的是如此变革性的话,如果您是任何类型的金融机构,它将成为您未来的一部分。我认为我们可以成为我们的合作伙伴的盟友,确保他们站在正确的一边。待加密货币等待成熟,我们就可以说所谓。
Yeah, I've certainly, I think students are good word. I don't feel like I'm an expert, but there's too much interesting stuff. And the amount of talent pouring into that space really seems to indicate that that doesn't typically happen unless there's something that's going to happen.
Yeah, you may still be a little unclear on the value prop of crypto. And I certainly question it in certain areas, but as you say, yeah, when the technology, when the, when the talent sort of moves so quickly in one direction, it's almost inevitable. I mean, that something very big is going to come of that. There's not really a history of technical talent wholesale moving towards something so quickly where it didn't become, you know, enormous fairly soon. So I think it's inevitable. I think there'll be a lot of flame outs, of course. Not everything's going to work. Not every coin is going to work. And some of the propositions I find a little dubious, but I think there's going to be some very, very big transformative wins. And we certainly want to be a part of that. Absolutely.
So, Dave, was there anything else? I got my kind of closing three questions that I asked everybody that I've got for you. Was there anything else you thought we should cover? Did I say this is more like a performance review when I asked this question about there, but I asked it to use a little bit of it. Like, was there anything else you felt like we ought to cover or topics you wanted to talk about that I didn't ask about?
I guess maybe I would just ask back to you, Jeff. When did you know you made a good decision to come to Upstart? That's a hard question. I would just say, you know, there's the question of like, did you make a good financial decision? Like, was giving up some salary for equity? Was that a smile? It's a question like, did I think I'd made a good call and did I convince my mother-in-law I'd made a good call? The second one probably took a while longer.
But to me, the amount I learned coming in day one, and this is for anybody listening, like joining a startup, I was a what, fourth or fifth person in the door, depending on whether you get Amazon or I on the podcast to talk about it. I get the microphone, so I get it. But, you know, just the amount you learned and that experience is incredible. And I, I mean, I joined you at Google in 2006, so right at the beginning of the cloud wave, but it is a whole different thing. Google, the Google business card got you so many meetings that you couldn't have gotten. And it just kind of like, it's like playing the game on the easy level. And I think it's a hard game, but you're not on the hard level. And doing it on your own is a whole different level. And I, that learning was invaluable.
So I knew I made a good choice from the very beginning, from that point of view. And then, you know, I think, I think one of the other points that you can talk to this is that you never, the success people see from the outside at any startup or new venture, it can look like, oh my God, you guys just killed it. And there were points along the way until very recently where you went, man, maybe, maybe we're not going to get there. It never feels nearly as certain from the inside as it looks from the outside.
And so I think from that point of view, it's been a, it truly is a roller coaster. I think people who haven't been through the real company starting experience don't appreciate how on the edge it can feel for how long, even when the outside world is. I'm like, I just raised a ton of money. You're looking so successful going on. Man, I think even in the best years of the company, if you looked at them day by day, each day would look like a struggle. It would look like work. They only tend to look really nice in retrospect when you're past something and you see the aggregate of what you've achieved. And hopefully it's a good thing.
But it's an experience I would never give up. It's not for everybody, for sure. And I think even if you're not going to be in a startup, not going to do a startup, there's things you can take away into your own job. And being a leader of innovation, being the person that's going to stick their neck out a little bit and push things forward.
To me, it's always about that. It's just how do you make steps forward? How do you move a little beyond your comfort zone and say, I have this idea, this vision of where things are going for my company. And I'm going to really do something new and different to get there. And you don't have to do a startup. It's not, again, not for everybody. And so many of them don't work out. So it's not giving everybody should do that.
But I think there's something almost anybody can learn from how startups work and what makes them special. Yeah. And I guess that when I get asked for my career advice and ask you for your soon, one of the things I always tell people is like, I've always looked for jobs where I felt a little bit like, I can't quite believe that I'm qualified for the thing and that you offered it to me. But I feel like maybe I could figure it out. And that's always felt like the place where you're to your point where you're learning, where you're going, hey, I'm, there's something here for me to learn and contribute to. But if it feels comfortable, it's probably not, maybe I could tell that. So right? Challenges like riding a horse.
If you're comfortable while you're doing it, you're probably not doing it right. And last time I love Thomas. But like, I think that's always the way I viewed it. And Ubstard has been that in spades, right? From day one, you kind of went, I don't quite know how I'm doing or how I'm supposed to do it or what it's supposed to be. But like, I think with a little bit of hard work and a little bit of luck, we can figure it out and make it for point A to point B.
So let me start on these kind of three closing questions for you. Number one, what's the most valuable leadership lesson you've learned during the course of starting and growing Ubstard? It's been, it's been quite the journey from, you know, your wife and kids in a t-shirt to say congrats for leaving Google and nobody's with you, but we are to, you know, go over 1,000, I think 1,500 people in the company now and an IPO.
But like, what's the most valuable kind of leadership lessons you've learned along that journey? You know, I think maybe the first starting point is kind of self-awareness of who you are, why you're in it, what you think you're good at and what you're not good at. So a real dose of self-awareness to start with because in building a company, you need first and foremost to surround yourself with people that make sense. I mean, you can share the mission with them, but hopefully they bring a lot of skills and capabilities that you don't have in your complimentary.
And because ultimately, you know, we've been up and down and all around as you know, I mean, we usually could have failed and been out of business many years ago, but we, we saw our way through it. And then I think we got to this point several years in where even when the worst thing hit us in the face, we really didn't flinch. We had huge confidence that this team could work its way if you think. So you know, that self-awareness, I think, leads to having a team that if you do the right in terms of recruiting and you can get the right people in the boat leads to a strength of team.
And ultimately, that's the key to success. It is the strength of the team itself. It's not choosing the right product or the right market. I mean, over time, you have to make good decisions and execute well. And the right team will help you do that more often than not. But if that team, a core team that I think is ultimately the predictor of your success, I mean, I can happily say, as you know, so much of our leadership team has been together, either from the very beginning or for many years, we have very little turnover. And it just kind of means when the next crazy thing in the road happens, like COVID, for example, you know, you're just in a place where you can navigate and execute, do things well, feel comfortable that this team is going to navigate these, these turbulent waters, whatever they might be. And if you can just get yourself to that position, everything feels much better.
I almost feel like it inverts it a little bit. The challenge becomes the opportunity to go, hey, if it's hard for us, just imagine everybody else who doesn't have this group of people in the room to tackle it, like you kind of, I feel like at least for that team, we almost like it and go, I know it's going to suck, but it's probably good for us competitively because we feel like we can weather that storm better than most and we'll make better decisions because of the quality of people.
All right, that's what would be interesting. I usually ask bankers, like, what's the best piece of consumer banking or consumer lending advice you get in there? They're often come back to me 20 years ago when I was going through training and you've come into the space a little more recently in your career than all the way back to what's the best advice you've gotten about entering the consumer lending or the consumer banking space?
I think, you know, ultimately it was the advice early on from some legal folks we knew, even before Alicina joined, to say like, you should meet the regulators. You should take that path because it was sort of a, there's many people who look at value who I think would have said, you know, run under the radar as long as you can and then eventually you'll talk to them. But we sort of took the counter advice to go and really be, as I said, open Camano early on, perhaps naively in certain ways, but I think the trusted and gendered over time, not purely.
I mean, they're still plenty that don't know us. We, it's a very wide array of regulators and attorney generals and lawmakers and advocacy groups. We can't win them all over once, but I think having that, like, we have nothing to hide attitude. We will share what we're doing with anybody. We're proud of it. We're dedicating our careers to, you know, improving access to credit for people. So, so I think when you have that, you know, go back to it is, is, is yeah, if you're confident and proud of what you're doing in the case of what we're doing, we're closely with the regulators because they matter a lot.
I was, I was certainly fascinating advice and I certainly was given the counter advice often, like, what do you crazy people do on talking to regulators? And I think it's paid off in spades.
All right, last question for you, Dave. What's one bold prediction about the future? So I mean, I guess usually I got to bring a guest back on to see if they were right or right. Yeah, I get to see you more frequently. So we'll get a check in on this one more. No, no, no, no sort of context for that. Just a bold prediction about why I had another Brady super bowl, which I guess whoever said that is because losing their bet because that's not happening now. But you know, any, any, you can keep it in the banking space. You can put it in the metaverse wherever you want.
Yeah, I think we're going to start to see a lot of new banks being formed. I mean, I think the grounds, you know, we went many decades without really bank formation almost at all. And suddenly we're seeing some, some fintech pushing through and there's some charter, OCC Charters and myelcy stuff happening. And I think that can only, you know, go in the direction of more. And if there's, if there's people that come together to create these, these businesses and pursue charters, I just don't see how I think it's good.
By the way, I mean, I think naturally any, any market should be able to have new competitors and incumbents and it's been emerging a banks going on for a long time. But I think we're going to start to see some real new competitors in the industry. And I think in a helpful way, in a way that's going to be good for the industry overall. It's really going to change things and drive change. But so I think we'll see a lot more vibrant industry looking forward than I think we've probably seen in recent times. More partners for Upstar. Let's hope. Let's hope.
Upstar partners with banks and credit unions to help grow their consumer loan portfolios and deliver a modern, all digital lending experience. As the average consumer becomes more digitally savvy, it only makes sense that their bank does too. Upstar's AI lending platform uses sophisticated machine learning models to more accurately identify risk and approve more applicants than traditional credit models, with fraud rates mere zero.
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