Motley Fool Money - What’s On Your Balance Sheet?

Episode Date: June 19, 2022

Upstart Holdings is a lending platform, powered by artificial intelligence. Shares are down more than 70% year-to-date. It’s down, but not out. CEO Dave Girouard joined Motley Fool CEO Tom Gardner t...o discuss: - How Upstart is using its balance sheet now - Growth opportunities in auto lending - One stock idea (that’s not his own company) Stocks mentioned: UPST, AMZN, AAPL, ZM, GOOG, GOOGL Host: Tom Gardner Guest: Dave Girouard Producer: Ricky Mulvey Engineer: Dan Boyd, Adam Landfair Learn more about your ad choices. Visit megaphone.fm/adchoices

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Starting point is 00:00:00 Hi everyone, I'm Charlie Cox. Join us on Disney Plus as we talk with the cast and crew of Marvel Television's Daredevil Born Again. What haven't you gotten to do as Daredevil? Being the Avengers. Charlie and Vincent came to play. I get emotional when I think about it. One of the great finale of any episode we've ever done. We are going to play Truth or Daredevil.
Starting point is 00:00:18 What? Oh boy. Fantastic. You guys go hard. Daredevil Born Again official podcast Tuesdays and stream Season 2 of Marvel Television's Daredevil Born Again on Disney Plus. I'll say even whatever is on our balance sheet, it's a fraction of what a lot of other fintechs have. We are not a balance sheet company, do not intend to become one. And maybe we just need to be a little more disciplined and have technology that's a little better at price discovery.
Starting point is 00:00:44 I mean, I think that's what we're getting toward. I'm Chris Hill, and that's Dave Gerard, the CEO of Upstart Holdings, a lending platform that uses AI to determine creditworthiness instead of the traditional credit score. The company ran into hot water when some investors were less than pleased to find loans on its balance sheet, and year-to-date, shares of Upstart are down more than 70%. Gerard joined Motley Fool CEO Tom Gardner to break down how Upstart is using its balance sheet, growth opportunities moving forward, and one stock idea outside of his own company. Now I want to talk specifically about Upstart, the business, and then really get to today's environment in the latter part of the conversation.
Starting point is 00:01:35 But right now, as you look at your company, what do you see as the top few competitive advantages? Yeah, I mean, we're going after a very hard problem that I think very few others are even concerned about or attempting to deal with. And that is access to credit. And, you know, the simplest way I can describe it is, you know, in our view, 80 to 90 percent of Americans are fundamentally creditworthy. given the right product at a reasonable price, they will pay back that loan, whatever form that is. But really, only about half of Americans are recognized as such. So there's just an enormous difference between the reality of the risk in the world in how these very archaic systems we have to measure it work.
Starting point is 00:02:21 And that is a, now people might just say, that's the world, you know, that's how it is. Some people got good credit scores and some don't. But there's a better reality out there. I'm a technology optimist. I've grown up in the technology world. I've seen the way it can transform industries and worlds in just unimaginable ways. Yet somehow are we supposed to believe that this notion of having more accurate credit and making credit more readily available than more people at better prices is impossible to solve? So that's the heart of what we're focused on in that building the application of artificial intelligence to credit to us,
Starting point is 00:03:02 is an obvious join, right? AI is clearly a technology that has amazing potential in so many dimensions. And credit is a risk-based problem that is vast in scope. So if you can be the company that really leads the charge in terms of applying AI to this enormous giant industry, the potential there's awesome. It does come down to execution.
Starting point is 00:03:25 There's a lot of pieces and parts of the problems to solve. But the addressable market or the chance have to do it is so vast. And honestly, we are not like Uber and Lyft elbowing each other or, you know, we don't have others that are really in our face, if you want to say, trying to do the same thing. Most are just happy to build a digital bank or some other type of payments company, all great businesses, other businesses, but there's really very few looking to innovate on this very specific problem of how do you make credit work better and more efficiently and through the application of very sophisticated models. And that's a place we feel, particularly in the U.S.
Starting point is 00:04:06 market, really in a class by ourselves. Perhaps you just answered this, but what would you say to somebody who said, Upstart has created something that would be a useful application inside of a larger bank, but I don't see it as a standalone company. Yeah, I mean, I think that's probably an inside-out way to look at it. I mean, banks, any particular bank solves a problem for a particular set of customers and a certain set of products. The technology that we're developing, we think, is utility far beyond any single bank and what they would want to do. So, you know, there's a good reason to be a bank. A lot of some fintechs are deciding to become banks. You have your own balance sheet. You have deposits and you lend against them. And it's a known thing. And if you're a new
Starting point is 00:04:49 age, 22 digital bank, you have some advantages. And so that's all good. But in our view, the most impactful thing you could do is to insert this technology into as the highest fraction of credit originations of all flavors going on in the United States and eventually the world. You could never do that as a bank. You could be a great bank, but the impact in the scale that you can build at, if you are a tool that every bank, every credit union, every lender can use, I believe it's a much more scalable, much more impactful, much more impactful model. And one that is, you as a guy that came from Google, a bunch of folks came from Google and companies like that, that's the appealing opportunity we're excited about.
Starting point is 00:05:32 What did you just learn in deciding not to take loans on the balance sheet as a market clearing mechanism? I guess in a way, I was wondering or thinking that maybe it was almost like putting your personal lending business back in R&D because the regime, the environment change so substantially that the model needed to kind of catch up to the new reality. But you'll see, and I'm sure you have seen or your investor relations team has seen, littered around the internet comments saying, well, they said they were a tech company, but they're a bank, they're a subprime lender now. They're taking the, they're taking the, they're taking the, they're taking the lending risk, and it's just beginning, because if this environment worsens, then do that even
Starting point is 00:06:10 more. And obviously now you've, you've changed course on that. So, so you talk about the importance or significance of upstart not becoming a bank. And there are people who believe that you just took a step in that direction. So correct that thinking or explain your rationale today. Yeah. I mean, we've always grown up as a balance sheet company, not intending to build loans on our balance sheet to generate net interest income, which is, again, a perfectly good business, but not our business. As we've said before, our business is in effect a marketplace. If you wanted to say the technology is one thing, the business model is a different thing. The business model is largely a marketplace with consumers on one side, banks and lenders and investors on the other side.
Starting point is 00:06:56 And what we have said and continue to say is we will take things in our balance sheet to test and try out new things. It's really a form of R&D. But ultimately beyond that, we want to be a market maker. Now, like in any market, you can have surpluses on the supplier demand side. The pendulum swings back and forth in any kind of marketplace business. The truth is on the funding side, it's just more. brittle and it's not as getting price discovery, making supply meet demand, which is, of course, the kind of objective of any marketplace. It's not as fluid as we would like. Some of the things
Starting point is 00:07:29 we can fix and some of them may just be endemic to the nature of banks and lending and capital markets, investors. They react emotionally sometimes more than just to numbers. But in any case, the bottom line is, yeah, we move, I would say 85-ish percent of the time we've been in this business. we had been borrower constrained, meaning sort of unlimited sources of lenders or funding and always just borrower constrained in terms of where we could economically bring borrowers under the platform. The other 15% we found a place where there's overwhelming consumer demand and there's not enough lending capacity out there, which is where we've, you know, been.
Starting point is 00:08:07 And in March, we kind of made that, that switch happened pretty quickly for a whole a whole bunch of reasons that are largely about, unfortunately, war and inflation and things of that nature. But in any case, yeah, I mean, we were caught a little offside. We weren't as good and aren't yet as good at getting price discovery happening, meaning prices move up until supply meets demand. That's maybe the economics 101 thing that needs to happen. So that's our intention going forward.
Starting point is 00:08:34 I'll say even whatever is on our balance sheet, it's, you know, a fraction of what a lot of other fintechs have. We are not a balance sheet company. do not intend to become one. And maybe we just need to be a little more discipline and have technology that's a little better at price discovery. And I think that's what we're getting toward.
Starting point is 00:08:52 Just to understand the thinking that went behind that, was that to fill in a gap in the marketplace for defensive reasons or for revenue-generating reasons? What would be, what ticked you towards making that decision? It's just continuity. you know, you sort of have a, the pipes are running. The bar is applying. They're being matched to lenders. The lenders are selling some of the loans, keeping some of the loans. So yeah, I mean, it's just sometimes like in March 2020 to go back a couple years, there was just, you know,
Starting point is 00:09:26 an insane upset of the Apple card in the course of a few weeks. This wasn't quite like that. But, but, you know, you just have that when the economy changes really quickly. And, you know, we have to make decisions really, really fast on such things. And generally speaking, like I said, that's not our goal. We don't, interest income is not of interest to us. We really aim to be the marketplace and the partner to these banks and credit unions. And I think, you know, we're going to get closer and closer there. But that's, you know, the important thing to say is we have mechanisms to make sure supply meets demand. We are not, every loan that is approved on our platform, it is known what bank is originating it. And if that bank is not going to hold it
Starting point is 00:10:07 themselves, then what investor will have it after the fact. So, There's never a case where there's loans sitting around and we are left with them, quote, unquote, but it was decision really to keep the pipeline moving and not to sort of defer it. And we have a lot of tools to make sure supply meets demand. We're going to get better at that to make sure we're good with that in the future. You talked about growing a company over long periods of time as a risk mitigation exercise. Which do you feel is the bigger risk to upstart if you can compare these two? Would you say the bigger risk is that your data advantage of 10 years is not as great as you had hoped because other people,
Starting point is 00:10:40 people came along leapfrog, there were different sources of data. It wasn't as big elite as he thought you had on the last 10 years. That's one or two, that the 10 years of data you have is in a low interest rate environment. And the models, your fear about the adaptability of the model when conditions worsened, when credit markets stall. So if you compare those two, which one do you think is a greater long-term risk? I mean, honestly, I don't fear either of them because I don't think there's any evidence of either. We don't see others building models similar to ours.
Starting point is 00:11:13 The best thing we can do is try to observe how other models work. And they all, in terms of consumer lending, they all tend to be so highly correlated to a credit score that it's really hard to see anything beyond that going on. So maybe around the edges, but we just don't see it. So it's hard for me to worry that suddenly our advantage out there is lessening. I just don't see that. On the second thing, I mean, conceptually, you could worry that your model, the environment is going to change that your model suddenly becomes useless if you want.
Starting point is 00:11:46 I mean, for us, it's almost implausible to imagine that because, again, it's how it's doing relative to a traditional credit score. And that's not a tough fight for us, just to be frank. Like the amount of risk separation, if you just look, we put actually a slide about this in our investor deck, if you just split all of our loans by credit score and then you split all of the same loans by the upstart, essentially risk tier. what you see is a dramatic separation in the wrist tiers, a very smooth, from tier one up to tier eight, like a very smooth increase in loss rates as you would like across these risk tiers.
Starting point is 00:12:22 So the tiers are working incredibly well, whereas FICO, it's only lightly correlated. It's useful a little bit, but it's actually not that well correlated. And so, but anyway, I don't want to sound like we don't have things to worry about, Tom. Every business does and we do. I feel like if I could just nominate a number three, we have to execute. There's a lot of things that can go wrong in any particular business, and certainly in ours. And for us, it's execution, you know, to grab the opportunity to prove this isn't about unsecured personal lending.
Starting point is 00:12:54 It's also about auto lending. It's also about small business lending and mortgage lending. So to prove more categories, to win over more lenders to the platform, those are the things I worry about is really how do we take those next steps to really prove this is going to be the business that we believe it's going to be in a few years. Well, let's go to the other categories. Let's move to auto lending now. And enlighten us, teach us all the differences between personal lending and auto lending, the size of the market, the competitive dynamics in those markets, the potential margins,
Starting point is 00:13:26 and the amount of market share that you think is available to upstart in the two different categories, those two to start. Yeah. So, you know, personal lending, depending how you measure it, it's, you know, maybe 100, 100, 150 billion a year in originations, we believe our platform is potentially a market share leader in the U.S. in that category and has become so over the last few years. But, you know, that's, that's, it's not a mainstream credit product, meaning most banks don't really offer personal loans at scale. It's a bit of an, it's historically an esoteric product just because it wasn't very economic for a bank to like make a $10,000 loan.
Starting point is 00:14:02 They just weren't going to make enough, you know, interest on that to make it worth the effort of doing. FinTechs have really almost created that category in the last decade. We've really built a very strong position there and continue to build on that. Auto is very different, of course. It's a very well-established category. It is probably scale-wise, maybe seven, eight times larger. Maybe it's a 700 billion a year in origin, maybe 800 billion a year in origination. So much, much larger, much more mainstream to the financial services world, to the banking world. And, and, And it's a secured loan. So it's a fundamentally different product where unsecured personal is really like you're betting on the person, you're underwriting the person. In an auto loan, much like a mortgage,
Starting point is 00:14:45 there's a person, but there's also an asset behind it. And that means it's a collateralized loan. There's something you can recover. Generally speaking, it makes the loan notionally less risky because you can recover a higher fraction if the person chooses not to pay. Getting that right and how that works. Also, the payment waterfall is different. Generally speaking, somebody is more likely to not pay a personal loan where the sort of quid pro quo is they might, their credit score might get hit or a car loan, their car might get repossessed. And so generally speaking, it's always believed that a car loan is higher up the payment waterfall for the consumer. So that's how they differ. From our point of view, they're still very sophisticated modeling in
Starting point is 00:15:26 both. There's a lot of process involved in a car loan that's not involved in a personal loan. If it's a refinance, which is the first product we got in, you have to deal with. paying off the prior lender, establishing, you know, the new creditor on the lien, on the title for the car. So there's some logistical stuff that can make it, what I would call historically a zero billion dollar market, meaning like, yeah, who wouldn't want, if it took 10 minutes, who wouldn't want to refinance the car loan to save a couple hundred bucks a month? But if I have to go through trudging to the DMV and God knows what,
Starting point is 00:16:01 and notarization and all that, maybe I just won't bother. And I think that's where the industry's been to date. So we've been building a process that feels more like the unsecured personal products. It's all automated. It can be done really quickly. I think even the bigger opportunity for us in auto is at the car dealership itself when people are buying cars. Historically, one of the, let's just say, worst experiences ever invented in the United States
Starting point is 00:16:24 of America is what most people experience when they go to buy a car. And it's just a circumstantial thing that's built over time. but we bought a company a year or so ago now, Prodigy, that is really the software going into car dealerships to help them create a more pleasing process for all, a more efficient car buying process. And we're just now testing upstart loans in that process. And that's an enormous opportunity because that's where the bulk of auto lending happens, the vast majority. And it's really inefficient, both in terms of process and in terms of pricing. So it sort of pulls on both of the ropes that make our business. business go. And we're seeing extremely promising early results. So our view generally is,
Starting point is 00:17:08 if we were betting on this, in a few years, you'd see auto surpass our personal loan business just by the potential, the inefficiency and what we think is a very good position. We have, we feel pretty confidently the fastest growing auto retail software that's in the industry. There's a whole bunch of providers of trying to make software that helps car dealers sell more efficiently, but ours is clearly growing faster than others. What do you expect the margins to look like in auto lending versus personal lending? Margins to us, we think won't be very different, very similar. Generally speaking, more of the revenue will likely happen over the term of the loan as opposed to up front. So you can view that either as a good or bad thing. But we think the margins
Starting point is 00:17:54 and the sort of take and all that won't be all that different. I think the level of inefficiency and opportunity, pretty similar. But I do think the nature of that product isn't a large upfront fee or anything like that. So it'll tend to be a bit more recognized over the term of loan, which, you know, for the point of just kind of stability, if you will, is not necessarily a bad thing. We're kind of going to take a step back for everyone to just get their footing about AI and to have you explain taking the auto loan on your balance sheet as an R&D maneuver to train the AI. So to make sure the system works so that now lenders can come into the platform and feel confident that the data you're presenting is valid. So could you just explain that process and how somebody just coming
Starting point is 00:18:40 into it for the first time might say, what? Wait, all these loans are on their balance sheet. This isn't a riskless organization. They're having to shoulder all of these loans. And it's in the hundreds of millions of dollars. Walk us through the process of how that works. So just to give an example, so we have a small business loan product coming out later this year. We've talked about it a bit. It's on the near-term horizon. And, you know, for the rest of this year, we'll probably hope to really get this thing tested and out there and trying it, maybe a couple tens of millions of dollars of loans, which in the grand scheme of lending is not a lot. Now, we can't go to one of our bank partners and say, hey, we got this thing,
Starting point is 00:19:18 it's ready to go. You want to get the first small business loan and upstart? Because that just doesn't make sense for them. They have a lot of responsibility, and they're vetting on something. We just never allow for that. So when we're bringing a new product to market, or maybe something very different in an existing product, we want to have the capacity to test it ourselves and get through the first version, the second version, maybe the third version of the model. And usually the curves is such that you can iterate quite quickly if you have enough volume. So that's what we've been doing in auto, is really funding most of it and testing it. Now for the refi product, which has been in the market for a while. We're now transitioning that where banks and credit unions are becoming the lenders
Starting point is 00:20:00 for that, and we're sort of getting it off our balance sheet. That's how it's supposed to work. We do it for, it kind of depends on the product. It might be for six months or nine months or something like that, maybe a year. And then at that point, you know, lenders have enough confidence in the product that they can step in and take it and be happy with it. And it can pass all their tests, if you will. And in small business now, we're going to start that process for that product soon enough. And we'll go through the same thing, six, nine months, who knows exactly? And that capital on our balance sheet, it's an incredibly valuable use of it, because it is R&D. I don't know how you would build an AI model where the bank assumes all the risk
Starting point is 00:20:41 of the learning of getting this thing right and figuring it out. That's not, you know, a reasonable position for a bank to take, and it's not a reasonable ask for us to make. So we don't do that. We say, look, we're going to build the first version that's ourselves. We're going to test the pipes, we're going to refine the model. And when you're comfortable, you come on board and it'll be be ready for you. Sorry to go back to this. I promise it'll be the last time I ask about taking the personal lending business back on the balance sheet. But is it fair to say that that was happening because essentially you needed to put it back in R&D to show the banks that this model does work in the new regime? I think that would be a decorative description of it. In reality,
Starting point is 00:21:19 I think it was just a mismatch of supply demand that happened in a very short period. of time. And we just opted not to turn off some of the pipes as quickly as we could have, which would have been a different choice. So really, it was just sometimes you don't know if something is momentary and it's going to clear itself up in a few days or whether there's something deeper going on in the economy or whatever. So no, I mean, I'd like to say, I can't say that was a form of R&D. I mean, we were pretty transparent that that's what happened is suddenly the markets did turn. And our price discovery process isn't fast enough to get prices where supply meets demand. And when we had that dis-equilibrium, if you will, we took
Starting point is 00:21:59 some of them on to our balance sheet. And yeah, we do not intend to do that. It's not our business. And we're going to get better at the tools to have price discovery happen faster. I mean, one of the very encouraging things we're seeing is we have a lot of pricing power. I mean, we have moved prices up a lot. We've kind of said this earlier because, you know, core interest rates have moved up, Fed rates moved up, probably the two-year trip. Treasury is really the sort of mark that matters the most to us. And the two-year treasury is up a couple hundred basis points since the fall, as well as the risk in the environment, that also pushes rates up. Yet still consumer demand is super strong. And that just kind of shows we have,
Starting point is 00:22:38 I think, real pricing power, which is good. But it means we're not as good as we want to be at getting price discovery happening. We live in interesting times. Certainly a comparable would be to go back around 20 years and see what happened to the valuation. of a lot of technology and growth companies. With hindsight, say that their prices got well ahead of their value, but then the best among them delivered some of the greatest returns in American market history after that because the actual revolution was real. It was tangible, even though there were a bunch of joke companies that should never have even
Starting point is 00:23:09 existed, let alone come public. There were actually some obviously an amazing companies, and every company would like to compare itself to Amazon and the public markets, of course. But in that, I think, 2001 shareholder letter, Jeff Bezos, I think the word ouch was right there in the beginning. You know, our stock is down 90%. And Bezos, in talking about it, some interviews I've seen after the fact, said, you know, it was funny because internally, a lot of things were going exactly the direction that we wanted them to go. But maybe a collection of valuation reset, big new changes in the environment, and trouble communicating what we were achieving and going for all kind of hit us a week. once. But when I was looking at the internal numbers, I was actually very pleased by what was
Starting point is 00:23:51 happening, but our stock was down 90% at the time. So, I mean, without putting you in a position where you have to compare yourself to Amazon, given that, I mean, compare and contrast, the feeling that you have right now inside of Upstart, what you're seeing develop at the company, versus the absolute invalidation of any prior valuation above $150 a share all, you know, in a six-month period slamming you. So the external validation is getting knocked down and the internal experience, how different is that for you? I mean, it's not as stark as it might feel to the outsiders. You might think, oh, we're just like demotivated or just crushed by this. And I don't think there's a lot of that. I mean, I wouldn't say nobody looks at the stock price. That would be silly.
Starting point is 00:24:37 But honestly, like, we're pretty focused on the mission on what we're accomplishing internally. I think a good lesson for one of your members. If they really want to understand us, forget all the noise, forget the stock price at any point in time. Go to the beginning, at least as our public journey. Read the S1. Read how we describe what we do, why we do it, how we do it. Because we put a lot of energy in our S1 going way back then to describe how this AI works. It's not just noise.
Starting point is 00:25:07 There's some deep science there, and we actually got super dispositive of it in the S1. then go read our first earnings report or a second earnings report or third. And just take all the market noise out of that. And judge for yourself, is this real? Are these people legitimate? Did they do what they said they were going to do? And if you do that, whatever conclusion you come to, you can come to. But I think you have some sense have to ignore the fact that the stock, which started at $20,
Starting point is 00:25:34 by the way, when we went public, ran up to close to 400, came all the way back to wherever it's sitting today, $45. bucks. But again, that's that's the market. That's the noise. Read the details of what we've done and who we are. And I think you have a better chance to get to the truth than just reading kind of speculative ideas about what we're good at or not good at it. We said this. And we're not perfect. We'll make mistakes. Any decent company trying to be transformative and trying to do really hard things is going to make mistakes. And we're in that list. But we're also in a very strong place, a very strong position to launch these new products from a really well capitalized.
Starting point is 00:26:14 I mean, we're a company, just by the way, Tom, as a private company, we raised a total of $160 million, which frankly a fraction of most fintechs. And when we went public, I think we had in the range of 90 million of that still on our balance sheet. So like, we've just been that kind of company since day one. That's never changed. And I think if you want to be a long-term investor, you've got to get to the heart of company, who they are, who the people are, how they do what they do, and then place your bets.
Starting point is 00:26:43 This is probably my least favorite question to ask one of those rash statements that floats around, maybe not floats around, that spirals around. And I want to give you an opportunity to explain how the process works on executive selling of shares, right? Because these stories, your stock now has about a 30% short interest. And therefore, I don't want to be conspiratorial in my thinking, but therefore there are a group of people because short shorting is a short-term transaction that have a short-term incentive to swirl some rumor out there in the marketplace. So could you talk about your ownership stake, shares that you've sold in the last year, how that works, and what it says about your commitment or lack of commitment to upstart?
Starting point is 00:27:25 Let me give proper context to it. We were eight years as a private company and now year and a half, eight and a half as a private, year and a half as a public. In the eight and a half years as a private, nobody, no insider sold a single share. In fact, there were at least a couple junctures where nobody wanted to fund our business, honestly, and a couple of times where I put, what amounted to pretty significant parts of my personal worth, my family's worth, into the business to get it to the next step. And nobody sold anything, not me, not our board, not, not any of the executives. The only selling that's gone on since we became public from executives have been through 10B-5-1 plans, you know, structured selling plans where they're set up in advance
Starting point is 00:28:09 and you have no choice. My plan was set up over a year ago, May 2021, to sell what amounts to a single-digit fraction of what I own based on price triggers, et cetera. Those things always are. And that's it. I have no ability to change that. Can you legally stop them or not? I don't know, but they were set based on what the world looked like and what Upstart looked like in May 2021. And that's it. That's the long and the short of it. So I own the vast majority of shares I've ever had, ever had in Upstart, and I expect to have them for a very long time. Last question, which is probably a one you wouldn't expect me to ask to close, but if you could, in a very generalized way, provide investment advice to investors in high growth, technology,
Starting point is 00:28:55 enterprising companies, given what you've seen previously at Google, watching what happened in 2000, 2001, 2002, 2008, 2010, and a different sudden drops. But this is obviously a substantial one when you have the NASDAQ fall more than 25%. That's maybe a once out of every 10-year outcome or experience for the NASDAQ. So what advice do you have for us as investors in companies like your, is not specifically upstart, but just if you're investing in companies that are spending on R&D in trying to explore the future and their stocks have gotten rocked 30%, 50%, 70% or more. What advice would you have for anyone who's thinking about their portfolio now and seeing a lot of red?
Starting point is 00:29:35 Yeah, I mean, obviously, you don't want to act in fear. I'm one who has not historically done a lot of singular stock picking. I do it occasionally, but I usually will not do a lot of that myself. But occasionally I just have conviction. And I have conviction through experience and seeing a product. And I'll just give you an example. I put a big chunk of money recently. The first time I bought a single-ish stock in a long time into Zoom.
Starting point is 00:30:00 And I was like, I know that business. We were trying to build products like that at Google. I know how hard it is. That company executed incredibly well when suddenly their business just went through the roof in early 2020. And I have just so much respect for what they've done. And I know how hard the problem is to solve. I mean, how many times is like doing video like this been just a nightmare. in the past. And I just, despite the fact that Microsoft's coming after them, Google's coming after them,
Starting point is 00:30:27 whoever else. So to me, it is, you know, you can do index investing or whatever you want, but you want to have some conviction somewhere. And I don't know if I got Zoom at its lowest or whatever. And, you know, timing the market is just not a useful exercise, I think. But find an area where you have conviction. You've seen when the team can do. You have enough personal experience to know it. It's not just something somebody mentioned to you. And that's how I think about it. Honestly, I've invested in Apple in 2001 because I thought the iPod was a pretty damn awesome concept. And I thought, wow, Steve Jobs can create a number one position.
Starting point is 00:31:06 I had left Apple a few years before that. And I was fairly disgusted with the company when I left it. And I thought, if he can do that with an iPod, what else is he going to do over the time? And that one worked out pretty well. As always, people on the program may have interest in the stocks they talk about. The Motley Fool may have formal recommendations for or against, so don't buy ourselves stocks be solely on what you hear. I'm Chris Hill.
Starting point is 00:31:30 Thanks for listening. The market is closed on Monday for the Juneteenth holiday, so we'll see you on Tuesday.

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