Upstart Holdings, Inc. Common stock Bank of America SMID Cap Virtual Conference

Yeah. Really short tagline would be AI for consumer lending. We operate a marketplace business where consumers can go and shop for offers of credit. We do personal loans, auto loans, HELOCs. Really, over time, we will offer the entire suite of consumer credit products. Our real strategy from the beginning has been to say, "Hey, there is a whole bunch of transformative technology innovation happening around how we use models to make better predictions and understand patterns and data." But that innovation has largely not made its way into consumer lending, which is arguably the most important place for it to go. Because if you think about the history of consumer lending, this is the world's oldest industry. Almost everybody borrows at some point in time.

Actually, surprisingly, a large number of people, depending on your exact metric of preference, something like 50% or more of people in the U.S. we think are underserved in how they access credit. Either it costs too much, they can't get approved, it takes too long, and it is all fundamentally because the ability of the models and the lending companies to understand their risk is too limited. So what we have done over time is we have built models that can both better understand the risk, which we call better risk separation, and automate away a bunch of the process. As a result, we are able to radically reduce the cost and complexity of credit for everyday Americans who are looking to borrow, and that is just about everybody.

Yeah. It is exactly those two things I said. One, this is an industry that is relevant to almost everybody. The addressable market here is enormous. It is almost laughably large if you try to do any kind of math against it. At the same time, usually industries that are that big are really saturated, really well addressed, all the sort of innovations have already gotten plugged in, and that is just not the case in the consumer lending world, which I think for various reasons historically has tended to move slowly in adopting new technologies. We really have been, for a number of years here, the first, and we think we have quite a large lead in taking a lot of the innovation happening in AI and applying it to this space.

We think it is one of the best possible applications there is for AI to do good and serve the consumer. I think you put those things together, disruptive technology transformation against a huge market that has not really fully ingested that disruption, and I think naturally you are going to get a business that has the ability to compound for a very long time.

Yeah. Yeah. Obviously, Dave and I worked together in close partnership for a long time.

We started this business, as you said, 14 years ago. The thing about this business is that it surprised us in how long it took to build. At first, I think when we started, we thought, "Oh, we will just do this, and within a few years, everybody is going to be chasing us on this same race of applying AI to credit, realizing how large the opportunity is." I think we have just been consistently surprised how slowly that has taken to happen.

I think it's actually for a lot of the reasons that it took us so long to build the sort of first, what we call the first leg of the race, which has a lot to do with the fact that consumer credit, maybe credit in general, but certainly consumer credit, obviously it's highly regulated. It's an industry that has a lot of entrenched ways of doing things. If you think about what does it take if you're going to say, "Hey, we have this completely new way of understanding credit risk," what do you need to do to actually make that a market reality and do that at scale? Well, it turns out you need a whole bunch of different kinds of very old institutions to buy in, right?