Upstart Holdings, Inc. (NASDAQ:UPST) Q2 2024 Earnings Call Transcript

Upstart Holdings, Inc. (NASDAQ:UPST) Q2 2024 Earnings Call Transcript August 6, 2024

Operator: Good day everyone! And welcome to the Upstart Second Quarter 2024 Earnings Conference Call. Today’s conference is being recorded. At this time, I would like to turn the conference over to Cindy Moon, Lead Corporate and Securities Counsel. Please go ahead.

Cindy Moon: Good afternoon, and thank you for joining us on today’s conference call to discuss Upstart’s second quarter 2024 financial results. With us on today’s call are Dave Girouard, Upstart’s Chief Executive Officer; and Sanjay Datta, our Chief Financial Officer. Before we begin, I want to remind you that shortly after the market closed today, Upstart issued a press release announcing its second quarter 2024 financial results and published an Investor Relations presentation. Both are available on our Investor Relations website, ir.upstart.com. During the call, we will make forward-looking statements, such as guidance for the third quarter of 2024 and the second half of 2024 relating to our business and our plans to expand our platform in the future.

These statements are based on our current expectations and information available as of today and are subject to a variety of risks, uncertainties and assumptions. Actual results may differ materially as a result of various risk factors that have been described in our filings with the SEC. As a result, we caution you against placing undue reliance on these forward-looking statements. We assume no obligation to update any forward-looking statements as a result of new information or future events, except as required by law. In addition, during today’s call, unless otherwise stated, references to our results are provided as non-GAAP financial measure and are reconciled to our GAAP results, which can be found in the earnings release and supplemental tables.

To ensure that we can address as many analyst questions as possible during the call, we request that you please limit yourself to one initial question and one follow-up. Next week, on August 15th, Upstart will be participating in the Needham FinTech & Digital Transformation Conference. On September 12th, Upstart will participate in B. Riley’s Securities Consumer and TMT Conference. Now we’d like to turn it over to Dave Girouard, CEO of Upstart.

Dave Girouard : Good afternoon, everyone. I’m Dave Girouard, Co-Founder and CEO of Upstart. Thanks for joining us on our earnings call, covering our second-quarter 2024 results. I’ve said many times over the last couple of years that I’ve never lost an ounce of faith or optimism in the future of Upstart, and today, you can begin to see why. I’m proud and thankful for the incredible work done by Upstarters in the last 2 years to build a stronger and better company on so many dimensions. The numbers and guidance we released today demonstrate that we’re turning a corner. We’ve made real progress toward returning to sequential growth and EBITDA profitability and, I believe, toward resuming our role once again as the Fintech known for high growth and healthy margins.

We’ve also rebuilt our funding supply by locking in important long-term funding partnerships and significantly reducing the use of our balance sheet to fund loans. We expect this trend of reduced loan funding from our balance sheet will continue through the remainder of 2024. But this progress is not due to any dramatic improvements in macroeconomic factors or risk. Any such macro wins remain in our future. Rather, our progress is the result of the dedicated efforts of more than 1,200 Upstarters. The improvements that are evident in our business today are coming from inside the house: First, significant and even dramatic AI model wins; second, a revamped and revitalized funding supply; and third, increased operating efficiency. These wins and more are providing the foundation for the Upstart comeback story that I expect we’ll share with you in the quarters and years to come.

Today I’ll provide some insight to these major initiatives and how they’re building on the progress we’ve made in recent months. We continue to focus the majority of our efforts on our core personal loan product, where the opportunity for leadership in a fast-growing category is clear. Our product today is far superior to what we offered two years ago in all the dimensions that matter. Model accuracy, fraud detection, automation, funding resiliency, acquisition costs, and revenue optimization are leaps and bounds better than they were in 2022. Most importantly, I’m thrilled to share that we very recently launched one of the largest and most impactful improvements to our core credit pricing model in our history. In fact, with this launch, 18% of all accuracy gains in this model since our inception have been delivered by our ML team in the last 12 months.

To dive a bit further, Model 18, or M18 as we call it internally, is the first to incorporate APR as a feature, or as an input to the model. It’s, of course, common to think of APR as an output of a risk model at least indirectly, but we know empirically that the APR also affects the repayment risk of a loan. All else being equal, a higher APR will select for a riskier borrower, a notion known as adverse selection. Conversely, a lower APR will select for a less risky borrower. If you have a background in computer science or math, you quickly realize that having APR as both an input and output to the same model presents some challenges. Solving this problem requires running our risk models many times in parallel to arrive at the appropriate answer.

In fact, M18 generates approximately 1 million predictions for each applicant in order to converge to the correct APR, which is six times the number of predictions of the prior model. We believe the improvement in accuracy is well worth it. Additionally, I’m very happy to report that we expect M18 to substantially improve our funnel conversion rate. From a competitive standpoint, I believe that significant technical obstacles such as the one I’ve described here are themselves a clear sign of progress. We’re pushing the boundaries of computing and AI to build more accurate models, and we have seen few signs that peers in the lending space are far enough along the path of AI-based modeling to even encounter these technical challenges. We also reached another all-time high on automation of our core unsecured loan product, with 91% of loans in Q2 fully automated.

As a reminder, this means no documents, no phone calls, no waiting, and no human involvement whatsoever. Two years ago, this number was 73% and we weren’t sure reaching 90% was even possible. Driving automated approvals up, while keeping fraud to minimal levels is an obvious fit for AI, so we would expect Upstart to continue to lead on this front. And automation isn’t just a win for cost and efficiency it also provides the foundation of a fundamentally better product for the consumer. Ultimately our strategy is to offer the best rates and best process to all for every credit product that matters. This means continuing to expand our platform to auto loans, small-dollar relief loans, and home equity lines of credit, and we’re making great strides in each of these products.

In Q2, our auto team released new underwriting models for both our auto retail and refinance products as well as a new fraud model for auto retail. We’ve now seen multiple months of calibrated loan performance and are growing confident that our loans are performant and increasingly competitive in the market. In the interest of continuing to move our auto business to profitability, we increased the monthly fee we charge each dealership for the use of our software. Despite this, we believe we’re still quite inexpensive relative to competitive offerings. We’re also investing heavily in servicing and recovery for auto and saw a 33% improvement in roll rates and a 44% increase in recovery rates in the second quarter alone. And our small dollar “relief” product continues to grow rapidly, with 57% sequential growth in the number of loans in the second quarter.

Our intention with this product is to expand access to bank quality credit rather than to generate enormous profits. Nonetheless, I’m thrilled to say that in Q2, SDL became our second product to reach break-even economics. We also signed our first warehouse for SDL this past quarter. For the current quarter, we’ve identified opportunities to reduce the variable cost of these loans by more than 40% which would represent another incredible win and opportunity to increase approval rates further. Overall, this team continues to execute like pros and is helping Upstart expand its impact on the American consumer rapidly and responsibly. As of today, our Home Equity Line of Credit is available in 30 states, covering 51% of the U.S. population.

We exited Q2 with an instant approval rate for HELOC applicants of 42%, up from 36% in Q1. This means we’re able to instantly verify applicants’ income and identity without the need for tedious document uploads. Consistent with our experience in personal loans, instantly approved applicants convert almost twice as often as other applicants. With respect to credit performance of our HELOCs, things couldn’t be better. With more than 300 HELOCs originated, we have zero defaults to date. Finally, we’ve seen significant interest from Upstart’s bank and credit union partners in our HELOC product and hope to launch our first lending partnership before the end of the year. We continue to invest enormously in servicing and collections. To give you a sense of this, in the last two years we’ve tripled the number of Upstarters on our servicing product and engineering teams, and this investment is paying off.

We’ve made it radically easier for borrowers to make payments in whatever way works for them. We’ve implemented new channels for reaching borrowers who are delinquent. These efforts and more have helped drive delinquency rates down by 16% year-over-year and have helped reduce support costs per current loan by 30%. We’ve also now increased the number of borrowers enrolled in auto pay for 36 consecutive weeks. Much of our team’s efforts to-date have prepared our servicing infrastructure for the deployment of AI models that we believe will enable us to build a significantly differentiated loan-servicing capability. Two years ago, we told you that we would upgrade the funding supply on the Upstart platform. We aimed to move a significant portion of our funding from at-will monthly agreements to longer term committed partnerships.

Given the importance and complexity of these relationships, we cautioned that this would take some time. I’m pleased to share that we’ve now accomplished this goal. We ended Q2 with well over half of the institutional funding on our platform coming from committed capital and other co-investment partnerships. We began with the announcement of our first partnership with Castlelake 15 months ago. This partnership has since been renewed. We’ve since added significant partnerships with Ares and Centerbridge. Other institutional investors that have been with us for much longer have also returned to the platform. We continue to pursue additional opportunities to broaden and deepen our funding supply as Upstart returns to growth mode. We also said back then that we’d use our own balance sheet as a transitional bridge to this better state.

You can see from the numbers we released today that we’ve begun to reduce the use of our balance sheet to fund loans. We’re hopeful this will continue through the rest of the year, though I’d like to always reserve the option to use our balance sheet to do the right thing for our business. I’m also pleased to report that banks and credit unions continue to return to the Upstart platform. We’ve signed eight new lenders since Q1. Performance and lender demand on the platform are creating a competitive environment which is beginning to reduce prices for Upstart borrowers. In fact, lenders representing about half of the monthly available funding on Upstart from lenders have reduced their target returns recently as their liquidity has improved and their demand for loans has increased.

This is the first time in two years that we’ve seen loan prices drop on Upstart. For many reasons, transforming credit with AI is complex and challenging. Tackling the world’s most entrenched problems with AI is difficult and it doesn’t happen overnight. But to those who ultimately solve these problems, there comes a tremendous reward. Today we’re tackling problems that we weren’t even aware of a couple years ago. My perspective is that, top to bottom, we’ve gone through a significant reinvention of the company, both from a technology and business model perspective. We’re confident we’re on the right track and making rapid progress. And this is just beginning to show in our financials. Despite the fact that many trillions of dollars in credit are originated each year, our competition in AI is scarce.

In Generative AI, you have a significant number of well-funded and talented competitors, such as OpenAI, Google, Anthropic, and Meta, at the cutting edge of model building. In AI for lending, you have Upstart. Thanks. And now I’d like to turn it over to Sanjay, our Chief Financial Officer, to walk through our Q2, 2024 financial results and guidance. Sanjay.

Sanjay Datta : Thanks, Dave. Good afternoon to all. And thank you for joining us. A notable topic for us over the past few quarters has been the macro climate and its impact on both consumer spend and credit loss. The stimuli of 2020 and early 2021 left consumers flush with cash, and in retrospect, unleashed a two-year plus surge of consumption as consumers clung to new elevated spending habits well beyond the duration of the stimulus, and in our view, also beyond our collective means. These trends were, of course, exacerbated by punishing price inflation. This inflation, which also had its roots in the post-COVID monetary expansion, appears to have mostly run its course as we had anticipated for much of the past year. We now also see signs that the venerable American consumer is reluctantly waving the white flag, acting to moderate outlays and rebalance budgets.

Consumption of goods, both durable and non-durable, has actually been falling in real terms over the course of this year. Spending on services has continued to rise, but half this increase over the past year is attributable to skyrocketing healthcare expenditures. Many other subcategories of services consumption growth in our economy have also started to abate. To be unambiguous, we believe this is a welcome development for the American economy, which has been on an unsustainable tear over this broader period of time. One product of improving fiscal health is that we are seeing credit default trends finally turn a corner, having peaked in aggregate sometime earlier this year, and now inflecting back down towards prior lower levels. This dynamic is reflected in our declining upstart macro index, which has now unambiguously fallen for three consecutive months and has reached its lowest level since January of 2023.

This downward-traveling UMI is now a consistent pattern across all borrower segments that we can observe. While the more U.S. borrower continues their rehabilitation, we also note ongoing improvement in the funding markets, both on the institutional side as well as in the banking and credit union sectors. For the second consecutive quarter, we’ve increased the number of lenders who are active on our platform and have observed reductions in required rates of return. On the institutional side, we have now renewed all of our committed capital deals from last year and are currently in the process of adding new partners to the program in anticipation of future borrower growth. One such recent example is the new agreement we’ve completed with Centerbridge, a leading global alternative investment firm, by which they acquired $400 million of our personal loans.

We are seeing early signs of funding progress in some of our newer products as well. We have secured financing to continue scaling up our auto and small-dollar loan offerings and expect to complete our first forward-flow sale of HELOC loans in the coming days. These collective funding efforts have allowed us to reduce the overall size of our balance sheet and store up some dry powder in support of any future growth and new product development needs. With this macro environment as backdrop, here are some financial highlights from the second quarter of 2024. Revenue from fees was $131 million in Q2, down 9% from the prior year, as higher pricing for prime loans created downward pressure on origination volumes. Net interest income was negative $3 million an improvement both year-on-year and sequentially, as the larger than typical core loan balance sheet we were carrying until late in the quarter produced income which helped to offset excess loss in our R&D portfolio.

Taken together, net revenue for Q2 came in at $128 million, $3 million above our guidance, but down 6% year-on-year. The volume of loan transactions across our platform in Q2 was approximately 144,000 loans, up 31% from the prior year and up 21% sequentially, and representing over 89,000 new borrowers. Average loan size of $7,700 was down from $9,500 in the prior quarter, driven lower by continuing robust growth in small-dollar loans, as well as by pressure from higher pricing on prime loans, which tend to run larger than average. Our contribution margin, a non-GAAP metric which we define as revenue from fees, minus variable costs for borrower acquisition, verification, and servicing, as a percentage of revenue from fees, came in at 58% in Q2, flat sequentially and 2 percentage points above our guidance for the quarter.

We continue to benefit from very high levels of loan processing automation, with our 8th consecutive quarterly improvement in percentage of loans fully automated, resulting in a new high of 91%. Operating expenses were $183 million in Q2, down 6% sequentially from Q1, as the workforce restructuring underwent yielded lower payroll costs across all of our functions. These savings were somewhat offset by the impact that higher loan volumes and smaller loan sizes are having on our loan processing costs. Altogether, Q2 GAAP net loss was $54 million, and adjusted EBITDA was negative $9 million, both comfortably ahead of guidance, and encouraging proof points on our path back to profitability. Adjusted earnings per share was negative $0.17, based on a diluted weighted average share count of $88 million.

We ended the second quarter with loans on our balance sheet of $686 million before the consolidation of securitized loans, down from $924 million in the prior quarter. Of that balance, loans made for the purposes of R&D, principally auto loans, stood at $396 million. In addition to loans held directly, we have consolidated $135 million of loans from an ABS transaction completed in 2023, from which we retain a total net equity exposure of $21 million. We ended the quarter with $375 million of unrestricted cash on the balance sheet, and approximately $449 million in net loan equity at fair value. We have long maintained that once the macro environment ceases to be a headwind, we will have the opportunity to generate conversion growth through improvements to our models and acquisition campaigns.

With loss rates that have now collectively appeared to plateau, this is precisely what we are expecting for the duration of this year. Last quarter, this nascent trend gave us the foundation to provide guidance for the back half of the year, which was based on an assumption that our model gains would deliver their historical pace of growth. Our model launches since that time have, in fact, produced enough uplift to put us ahead of schedule. Note that despite our relative optimism on the macro climate as it relates to credit performance, our guidance for the rest of the year in no way relies on either further improvements to the macro environment, nor on falling interest rates. Either of those eventualities, should they occur, would likely show up as tailwinds to our forecast.

With that in mind, for Q3 of 2024, we are currently expecting total revenues of approximately $150 million, consisting of revenue from fees of $155 million, and net interest income of approximately negative $5 million, contribution margin of approximately 57%, net income of approximately negative $49 million, adjusted net income of approximately negative $14 million, adjusted EBITDA of approximately negative $5 million, and a diluted weighted average share count of approximately 90 million shares. For the second half of 2024, we expect revenue from fees of approximately $320 million and positive adjusted EBITDA in Q4. Overall, we would like to say that we feel good about how we’ve managed financially through this challenging period. We emerged with expanded margins and a reduced cost base underpinning the tangible progress we’ve made on the road back to profitability.

And successfully reimagining our funding model has created a more resilient capital base and a shrinking balance sheet. More importantly, we are optimistic about the strength and direction of the business as we look ahead. While we are wary of prematurely sounding the all clear, the macro no longer appears to be a direct impediment to our business. An improving macro climate is not contemplated in our forward numbers and is not something we need in order to thrive. But if and when that does materialize, it should be wind in our sails. I would like to conclude by acknowledging the entire Upstart team for persevering together through this long metaphorical winter and also to all of our departed teammates who have been a part of the cause even if they are no longer able to.

I’m looking forward to a time in the near future when we all will have to refasten our seat belts. With that, Dave and I are happy to open the call up to any questions. Operator.

Q&A Session

Operator: [Operator Instructions]. We’ll pause for just a moment to assemble the queue. We will take our first question from Mihir Bhatia with Bank of America. Please go ahead.

Mihir Bhatia : Hi. Thank you for taking my questions. I wanted to start by just asking if you could comment a little bit more about just the inter-quarter trends and what you saw in July. It sounds like you’re quite positive on the back half of the year and maybe if you could just comment a little bit on what you saw, both in terms of loan demand and also just credit performance as you went through the months in the quarter and to the extent you are willing to about July.

Sanjay Datta : Yeah, hey Mihir. Great to hear from you. So, you’re asking about credit trends and loan trends in July?

Mihir Bhatia : And through the quarter, month-by-month in the quarter, like, did loan demand accelerate? Did you see more demand in June than April?

Sanjay Datta : I see. I mean, at a high level, I guess to the extent you can hear optimism both in our guide and in our comments, it’s probably reflective of a quarter that obviously is leading into Q3 on a good footing and a positive trajectory, and to the extent that we are guiding Q3 on an upward trajectory, I would say that July is representative of that as well.

Mihir Bhatia : Okay. And then maybe just switching a little bit to the expense structure a little bit more. What I’m really trying to understand is the fixed versus variable cost of the model. So, as top line expands, what kind of impact will that have on profitability and how much should we expect to drop to the bottom line versus maybe you reinvest in growth or product expansion or additional growth? How should we be thinking about that equation? Thanks.

Sanjay Datta : Sure. Thanks Mihir. In rough terms, as the business expands, I would expect our contribution margins, which really capture our variable cost base, to shrink somewhat, mainly due to reductions in take rates. As the business becomes more profitable, we will probably invest more in volume and in lifetime value. I think the cost components of our contribution margin should be fairly consistent because we essentially attempt to originate up to the point of marginal cost breakeven. I don’t think those points will dramatically change as we scale. As for the fixed cost base, I think, well, the intention is that it will grow slower than the top line of this business, meaning we should achieve operating leverage as the business scales. So between those two, I think that scale should drop pretty efficiently to the bottom line as we rescale.

Mihir Bhatia : Okay. Thank you for taking my questions.

Sanjay Datta : Thank you, Mihir.

Operator: We will take our next question from Ramsey El-Assal with Barclays. Please go ahead.

Ramsey El-Assal : Hi. Thanks so much for taking my question. The conversion rate increased quarter-over-quarter and obviously a lot more year-over-year. I know you mentioned some pretty exciting model improvements. I guess, what should we expect on conversion rate for the next couple of quarters? Are your model improvements driving maybe further conversion rate improvements or should it plateau at a certain point? What should we be looking for?

Sanjay Datta : Hey Ramsey, great to hear from you. I would say that to the extent our guidance is indicating upward trajectory, almost all of that is coming from conversion gain, and the underlying model accuracy driving funnel improvement over time. I would say for the foreseeable future, that will be the growth model. There is potentially a rate at which those conversion rates plateau, but I don’t think we’re close to those rates at this time. So there’s still a lot of runway to improve those conversion rates and drive the growth of the top line.

Ramsey El-Assal : Okay, a follow-up from me. On the smaller dollar relief loans, can you talk about these loans in the context of being like an acquisition channel for larger, longer duration borrowers or loans? In other words, are you seeing any of these small dollar customers come back and apply for larger loans that you can now kind of underwrite sort of like a training wheels type of a scenario in terms of being a channel into your core business?

Dave Girouard : Hey Ramsey, this is Dave. I think that’s a pretty good description of how that product works and why we have it. It’s really to push deeper with small amounts of dollars at risk, to be able to approve somebody on a shorter term loan, is just an opportunity for the models to learn faster and go faster and to acquire customers that are then eligible for other Upstart products later. So it is doing a super nice job of pushing the boundaries of our models, both in terms of the automation as well as in the selection and pricing, so that’s gone extremely well. We have seen quite a bit of return for other loans, so that’s also proving well. As we said on the call, it’s become economically strong for us. It’s not a drain on us in any way. So it’s been just frankly all around a great win for us and we would expect it to continue to be.

Ramsey El-Assal : Great, thank you so much.

Dave Girouard : Thanks, Ramsey.

Operator: We will take our next question from Kyle Peterson with Needham. Please go ahead.

Kyle Peterson : Great. Good afternoon guys. Thanks for taking the questions. I wanted to start off on the size of the balance sheet. Here it was great to see some nice runoff there, especially on the core personal side. I guess how should we think about the pace of runoff over the next few quarters, especially now that you guys seem to continue to bolster your funding?

Sanjay Datta : Hey Kyle, great to hear from you. The answer to that question is a bit – about the outcome of how fast the borrower side of the platform is scaling up due to model improvements and how quickly we’re signing up new capital agreements. Obviously the intention continues to be delivering those borrowers and that yields to our lending partners and to the institutional markets. But there’s always going to be a bit of mismatch in timing. We may get a model win and not have the capital available or we may sign the capital up and the model win may come afterwards. And so I think in the give and take between those two sides of our platform, that’s where we’ve historically used our balance sheet to step in. So all that to say, I do believe that the medium term direction here will continue to be a reduction in our balance sheet, at least as far as core loans are concerned.

But there may be some timing mismatch along the way such that there may be some sort of swings up and down as we do that. So it’s a bit hard to really calculate a very accurate pacing, if you will, given the volatility of those two sides of the business.

Kyle Peterson : Okay, that’s helpful. And then I guess just to follow-up on expenses, particularly with the fixed cost base, I think you guys have said kind of in the past that in the fixed cost base you guys have today can support a lot more volume than you guys have been doing, call it in the past four to six quarters here. How much, if we do get a better environment for originations, I guess how much more volume can you guys support with the fixed cost structure that you guys have today? The contribution margin probably you guys gave was helpful earlier. Just trying to think about the fixed cost leverage.

Sanjay Datta : Well, I guess I’ll say that through the end of this year and with the growth plans we have, we feel pretty good at where our cost base is. If the business were to start to really take off beyond that, I think there’s some areas on the margin that we would like to reinforce, but nothing on the level of what we anticipate the growth of the business itself could be. So, I guess the main takeaway is there will be improving operating leverage as the top line grows.

Dave Girouard : Okay, that’s good, color. Thank you, nice quarter.

Dave Girouard : Thank you, Kyle.

Operator: We’ll take our next question from Peter Christiansen with Citigroup. Please go ahead.

Peter Christiansen: Good evening, Dave, Sanjay. Thanks for the question. I want to dig into your comment about some of the at-will supplies of funding coming back. Just wondering if you could give us a barometer where we are perhaps compared to maybe, I don’t know, ‘21 part of 2022 in terms of some of those levels or at least indication of funding level that we saw back then. Then I guess, well, back then we also had 40% of your funding volume was through the ABS market. Would you expect that to returning to the ABS market for issuance in the near future? Thank you.

Sanjay Datta : Hey Pete, thanks for the question. I would say that the recovery of what we think of as the at-will funding markets, writ large, that’s the world of credit funds and hedge funds that predominantly depend on ABS as a liquidity channel. It’s early days for the recovery. I don’t think we’re near the scale that we were at a couple of years ago. That’s of course reflective of the fact that the ABS markets are certainly not at the level of volume and liquidity that they were back then. But I do think that those markets are rapidly improving and we have plans to be back in the ABS market certainly before the end of the year. So, I think those things continue to be on a good trajectory.

Peter Christiansen: That’s good to hear. And I recognize that period is not a fair comparison with the unique era. But secondly, in terms of the co-investment, how should we think about that level progressing over the next, I don’t know, one or two quarters? Is that still, do you think, going to be a portion or tied to your funded principle?

Dave Girouard: Hey Pete, this is Dave. I think the co-investment partnerships are definitely key to our future. I mean, that’s what we’ve been working on for some time, to go from almost entirely at-will funding a couple of years ago to having longer term committed partnerships. So that is very important to us. We view, the at-will funding can be useful in a lot of ways, but over dependence on ABS, particularly when those markets can ebb and flow quite a bit, isn’t healthy for us. So as we said, we have well over half our funding at the end of Q2 in these longer term partnerships, and we think these are, we would like to maintain that percentage. So I think we’re where we want to be with more long-term committed capital, less reliance on ABS and that sort of structure. As we grow back, we would like to sort of keep things as they are now.

Peter Christiansen : That’s really helpful. Thank you both.

Dave Girouard: Thank you.

Operator: We will take our next question from James Faucette with Morgan Stanley. Please go ahead.

James Faucette : Thanks so much. I wanted to follow-up there on the committed capital. How should we be thinking about what that looks like in terms of a unit economics or accounting treatment in those partnerships versus kind of at-will generally?

Sanjay Datta : Yeah, hey James. In terms of unit economics, the loans that are being funded through that channel look very similar to the broader institutional loans. They differ from the lending partner channel. In that the risk aperture is a little broader and the returns are a little commensurately higher. But in terms of our unit economics, there’s really very little difference between that channel and maybe what you might think of as more of the at-will institutional channel. In terms of the accounting, like these deals I would say are still becoming more and more standardized or templatized as we do more of them. I think historically they’ve shown up in a couple of different places on our balance sheet. But increasingly we’re going to love to sort of standardize the structure of the deal, of the deals that we do. And we do pull the holistic view of it together on our investor earnings deck, which gives you a glimpse of the total exposure.

James Faucette : Got it. And then quickly, last quarter you alluded to the fact that you were seeing some, you had indexed more to prime than you historically had and given some of the prior actions you took. Just wondering if you can give us an update in terms of what you are seeing in prime versus subprime this quarter and what you anticipate going, getting back to more normalized mix?

Dave Girouard: Hey James, this is Dave.

James Faucette : Hi! How are you?

Dave Girouard: Good, thank you. Our mix has swung toward prime, and I think generally that we would see, as we regrow, we would like to be very balanced across the credit spectrum, and we think that’s best for our brand, it’s best for stability of the business, etcetera. So one thing we would anticipate in the coming quarters is a stronger position at the primer end over the credit spectrum than we’ve had traditionally, where we really have not had funding appropriate to compete in that part of the market, but we think that’s changing. So I think you’ll see us be more balanced in the future than we’ve been in the past with regard to the credit spectrum.

James Faucette : Good, that’s good to hear. Thank you.

Dave Girouard: Thanks James. We will take our next question from Dan Dolev with Mizuho. Please go ahead.

Dan Dolev : Hey you guys, thanks for taking my question. Great quarter, great results, very happy to see that. I want to know, what’s going to happen assuming interest rates cut. How much torque do you think there is in the business, that you can actually expand growth, expand loans, as the environment gets more easier for you to do that? That’s pretty much my only question. It’s like, what the – how much upside can we dream, to dream at this point? Thank you.

Sanjay Datta: Hey Dan, great to hear from you as always. Look, reducing rates, benchmark rates and market rates are unambiguously good for the business. They haven’t obviously been the main headwind to our business. Default rates have been much more punitive in how they’ve evolved over the last two years or so, but definitely having the benchmark rates go up from zero to 5%-ish has been a headwind as well. And if that reverses, it’ll be a – it would presumably be a tailwind. It’s a bit hard to quantify the exact nature of the tailwind as rates reduce and it obviously depends on how far back down they go. But each quarter point will result in lower financing costs for the institutional investors, and if that creates lower hurdle rates, those will result in lower rates to our borrowers. And I guess I’ll just say that I think each cut would be a noticeable benefit in terms of its impact on our conversion rates.

Dan Dolev : Got it. Well, definitely looks like you’re up-starting a new cycle, so congrats again.

Sanjay Datta: I appreciate it, Dan.

Dan Dolev : Thank you.

Operator: We will take our next question from Giuliano Bologna with Compass Point. Please go ahead.

Giuliano Bologna: Hello! Good afternoon, and congrats on the results and some of your funding announcements. One thing I’d be curious about digging into a little bit is your marketing expenses. It looks like you got some improvement in your marketing efficiencies this quarter. And in the past, what you’ve kind of said is that there were some challenges with some loans being priced about 36% that you couldn’t necessarily convert. And I’m curious, when you think about the improvement in your marketing efficiency this quarter, how much of it was driven by being able to approve or underwrite more loans under 36%. And I’m curious, kind of how that could evolve over the next few quarters and how that’s kind of factored into your outlook at this point.

Dave Girouard: Sure. So the marketing efficiency is a function of our funnel conversion, most generally. So when the funnel converts better, our marketing tends to get more efficient, etc. So that’s a dynamic that’s always in play. The 36% kind of rate cap on Upstart means that, as base rates go up and as risk goes up, more and more, fewer and fewer people are approved, and we’ve seen that in spades in the last couple of years. We went through a two-year period where rates almost constantly were going in an upward trajectory. And every time that happened, a bunch more people would not be approved, because effectively the rate in the system requires of them, it goes over 36%. So that’s a little bit unwinding going the other way now, which is a good thing.

Partially, or most of it actually is due to model accuracy in the newest versions of the models, who are able to sort of identify more people who fit under that envelope of 36%, and the result of that is that you see marketing efficiency improving. So that’s a dynamic we would expect to continue in the coming months and quarters.

Giuliano Bologna: Yeah, and maybe taking away at that point, I’m curious in a sense of where things are, in a sense of when we think about funnel conversions and kind of the improvement, where do you think we are? Have we kind of improved 10%, 20% of normalization or is there a lot more to go with 100 basis point or 200 basis point decrease in interest rates?

Dave Girouard: Hey Giuliano! I would think of this as just an ongoing journey. I think that model accuracy has systematically improved since the beginning of our company and each improvement has a commensurate improvement on our conversion rates. Those can obviously be temporary set back by the macro, but as the macro normalizes, so will our conversion rates. And the question to how much better they can get, is sort of the same answer to the question of how much more accurate can your models get at approving good borrowers and avoiding bad ones. And we’ve talked about the fact that we think we’ve really just kind of scratched the surface in terms of our model’s ability to improve explainability in credit default. And so we believe that the longer term roadmap for this company continues to be improving models and improving conversion rates over the years.

So we don’t think of it as sort of normalizing right now. We think we’re back on the journey of improving models and improving conversion rates, now that the macro is no longer a direct headwind.

Giuliano Bologna: Alright, maybe one very quick question. You’re obviously going on 50% or rolled off 50%, forward committed capital as kind of a percentage of your funding. I think in the past you’ve kind of referred to that as kind of where you’d want it to be closer to a higher end of the range. I’m curious, would you look to kind of overshoot that and then grow kind of the spot or uncommitted business to catch up with that? Is there kind of any structural limitation in the near term to what percentage of volume or funding you’d want to have come from forward committed capital sources at this point?

Dave Girouard: Yeah, I think that given that we are feeling increasingly optimistic about the roadmap of model improvements and the lack of macro headwind, I think it’s in our interest to put in some more capital deals in place now. And in your words, to try and overshoot a little bit in anticipation of that growth materializing over the coming quarters, just given that these deals are relatively heavily negotiated and they take some time to put in place. So I think we want to err on the side of having those partnerships in place, in anticipation of where we see the borrower side of the platform growing.

Giuliano Bologna: That’s very helpful. I appreciate it and I will jump back in the queue.

Dave Girouard: Thank you, Giuliano.

Operator: We will take our next question from Rob Wildhack with Autonomous Research. Please go ahead.

Rob Wildhack : Hey guys, a question on the outlook. Updated guidance suggests better trend on origination. You guys sound pretty positive overall. Could you maybe break down how much of the improved outlook is coming from maybe mechanically from lower interest rates versus a better model versus maybe better funding? How would you quantify each of those or any additional drivers into the better outlook?

Dave Girouard: Hey Rob, this is Dave. I think that there is no assumption of approving interest rates or a reduction and kind of macro risk built into that. So the guidance is based on really what we’re seeing based on improvements we’ve made internally. And maybe the way to think of that is better models means better conversion rate. The other important input is we have to, of course, have sufficient funding supply to keep up with that growth. But the gating item in terms of like what’s really gating where our guidance sits today, it really is just about economic funnel conversion. And it’s improved a lot really through model improvements primarily. And at this point we feel comfortable that we on the funding side can make things match well. So, that’s a long-winded way of saying it’s really through things we’ve done ourselves. It is not based on any assumptions about improvement in rates or risk in the environment.

Rob Wildhack : Okay, thanks. And then a question on the small dollar loans. I mean, could you give some color on how much the growth in small dollar loans may or may not have impacted the conversion rate quarter-over-quarter? And the same question going forward, as you grow in small dollar loans, does that drive the conversion rate a lot higher?

Sanjay Datta: Yeah, hey Rob. The STL product is having an impact on the overall conversion rates. I think it’s on the order of maybe 2% or 3% impact at the scale that it’s at. So it’s not insignificant, but it’s also relatively minor.

Rob Wildhack : Okay, thanks.

Sanjay Datta: Thank you, Rob.

Operator: We will take our next question from Simon Clinch with Redburn Atlantic. Please go ahead.

Simon Clinch : Hi everyone, thanks for taking my question. I was wondering if you could talk about what it takes or what factors you, or what levers you can pull and what macro tailwinds you might need to see the sort of gross inquiries that come into the upslot network before conversion. How do you drive that higher over time, because that is down quite materially from where it’s been in the past. And I’m just wondering if that was just overstated previously and whether there’s actual quite a lot of upside still in this coming cycle for that.

Sanjay Datta: Hey Simon, just with the top of the funnel inquiries, such as the visits to the site.

Simon Clinch : Yeah, before conversion, yeah.

Dave Girouard: I don’t – we’ve not published sort of traffic or conversion to the site. So that’s not something that we’ve discussed publicly or tried to track in that means. Is there something different you mean by that?

Simon Clinch : So I just take your volumes and then kind of back out from the conversion rates to what it was before you’ve converted and I’ll just use that as a means to sort of track approximately what the volumes would be.

Dave Girouard: Yeah, it’s not exactly the same thing, but it’s directionally correct. Generally speaking, a lot of times we are controlling that by how much we’re spending in various marketing channels and also just generally how competitive our rates are. So that’s part of it, whether we’re doing direct mail or some sort of digital acquisition or whether we’re kind of remarketing to our own customer base or through partner channels that are responsive and can vary how much traffic they send us based on the quality of our rates, etc. So that’s, those are things that are a function of the market in some sense, or how strong our product is, how much we’re actively marketing. So hope that fills in some of the blanks for you.

Simon Clinch : Okay, thanks. And maybe you could talk a bit more about the Model 18, M18. And just, I guess, can you give us a sense, for those of us who aren’t educated in machine learning and stuff like that, but just really how unique something like that is and ultimately how quickly a model like that really starts to have an impact on your business?

Dave Girouard: Well, we’re in a sort of never-ending quest to accurately price each and every loan offer that’s made on our system. And one of the things we’ve known, and I think most lenders of some sort know, is that the quality of the offer you make to the market, meaning the level of the APR, has an impact on who accepts it and therefore how that loan performs. So the APR, which is, most people would think of it as the output of the model, actually affects the performance of the loan. So this is something, again, most people would tell you they have an intuitive sense of, but mechanically answering it and having models that are sophisticated enough to handle that is very important, particularly in the modern world where consumers have lots of choices, they compare rates all over the place.

You know, this is something that even 10, 15 years ago, hardly existed. But today consumers have a lot of it, ways they can compare and find the best rates. So having a lot of savvy around that notion of adverse selection and positive selection is really important. And solving it from a technical perspective really comes down to trying to converge to the appropriate APR. And what that amounts to technically for us is running our risk models many, many times in parallel, in order to converge to the right number. It’s a significant challenge that we’ve gotten over and I think we’re just beginning to reap the benefits of it. The guidance that you are seeing for the second half of the year, a significant fraction of what you are seeing in terms of our optimism for the second half of the year, it comes directly through the improvements in that model, and also we see a lot of continued opportunity in that domain, in that area to improve the models.

And that’s what, again, that’s what we’re in business to do. It’s generally where all the advantages of Upstart are, is when we can build better risk models and we’re having some really good success in that area right now.

Simon Clinch : Great, that’s great color. Thank you.

Dave Girouard: Thanks Simon.

Operator: We will take our next question from Vincent Caintic with BTIG. Please go ahead.

Vincent Caintic : Hey, good afternoon. Thanks for taking my question. First, just wanted to follow-up on the funding partnership discussion. It’s good to see that the credit investor demand is increasing. Just if you could maybe talk about some of the discussions you are having. What are those credit investors focused on? What’s changed where you are now getting more signups? How is – if you can give a sense for how pricing has changed or improved and maybe how much of your annual origination volume is now covered by all these new signups? Thank you.

Sanjay Datta: Hey Vincent, welcome back. On the funding partnerships that we are engaging in, I mean, there’s sort of two general vectors. One is increasing comfort or confidence with credit trends in general and maybe sort of macro risk. And then second, we’re sort of being innovative in some of the financial structures that we’re coming up with and discussing with some of these partners and prospective partners. And it’s sort of a learning, I would say a learning curve for all of us, in terms of how to get these partnerships implemented and put in place and managed. And so a lot of the journey with a prospective partner is just about understanding the model and the structure and how it all works. And then the recognition that there’s definitely ways of creating win-win partnerships here for us as the issuer and for these counterparties who are interested in the yield.

And so, I wouldn’t say beyond that there’s been dramatic changes in preferences over rates, and sort of supply and demand dynamics. It’s mostly been just an ongoing education for all of us around how these structures work, and I think it’s going in a very good direction. In terms of capacity, as Dave said, we’re sort of a bit north of 50% of all the institutional money that’s going to fund the loans on our platform and the past quarter came from these types of arrangements. And we’ll aim to maintain that kind of coverage or that kind of capacity over the long-term and the medium-term. We’ll maybe overbuild a little bit in anticipation of some growth that may happen in the coming quarters.

Vincent Caintic : Okay, that’s great color. Thank you. And my second question, just if you could talk about the competitive environment for consumer financing. It seems like others in this environment might be pulling back when you hear about from the traditional banks on their earnings calls for talking about, some stress on the low end and the middle consumer. So it seems like a lot of competition is pulling back, but I just wanted to get that sense from you, what you are seeing with that competitive environment. Thank you.

Dave Girouard: Well, I think our position on the consumer, I like to think we’ve been ahead of the crowd a bit, in the sense that it was clear there was deterioration of credit at the sort of less affluent part last year, and then later last year into the more affluent part. But as Sanjay said in his remarks earlier, we’re seeing sort of uniform improvement now across the board. So we sort of feel like we’ve been kind of signaling this for some time, that we’re nearing the end of the cycle. And I think we just have clear indications that credit is actually in a normalization period, not in a deterioration period. Now, what others are seeing or saying and where their data is coming from, I obviously can’t speak to, but I think we feel pretty good about that.

With regard to, banks and lenders can either be a partner of ours or they can be a competitor of ours. But I know the ones that are partners of ours are tending to see increasing liquidity and have sort of swung to the place where they are needing more assets, they are needing more loans and we talked a bit about that. So they are coming in a little bit more competitively, lowering their return targets and really wanting to sort of swing the dial a little bit. So I don’t think there’s any sort of caution to the wind like environment, but I do think the sort of lack of liquidity that was really serious a year ago and probably carried on through the end of 2023 has really improved a lot. And for us, that means the lending partners, the banks and the credit unions have definitely returned and that’s been very helpful for us.

Vincent Caintic : Okay, great. That’s a very helpful color. Thank you.

Operator: We will take our next question from Reggie Smith with JP Morgan. Please go ahead.

Reggie Smith : Hey, good evening. Thanks for taking the question. I’ve got two quick ones. So I guess you guys called out model improvements and a better UMI, which is great to hear and see. My question is, how should we think about those two things in the context of the returns in your core investment portfolio? And I guess specifically I’m trying to figure out, I mean, should that manifest in better performance there? If not, like where do these gains and model efficiency accrue? Obviously consumers are getting approved for more loans, but how do we think about how that flows through to your business? And I’ve got a follow-up. Thank you.

Sanjay Datta: Yeah, hey Reggie. This is a great question. In general, model gains or model accuracy improvements such as the one that we highlighted, generally improve our ability to accurately separate risk. And that generally shows up mainly in our improved conversion funnel. So it would create business expansion. It wouldn’t necessarily improve the calibration of the model in how it assesses an average pool of loans. So it wouldn’t necessarily be expected to have a huge impact on the performance of the co-investment positions we have. The UMI, to the extent it continues to fall, would have a direct impact on the performance of loan pools such as the ones that our co-investment partnerships have invested in, because it essentially means that credit trends are improving in real time.

And as they do the performance of those loans, any loans that are outstanding would be expected to improve and potentially over perform, and that would result in higher returns to our investment positions. So I think that would have a pretty direct impact.

Reggie Smith : Right, understood. And then I guess to follow-up on the unit economics. I’m not sure how much you guys can share here. But curious, with some of these committed structures, I assume you are selling these loans maybe at a slight discount to fall or maybe part of – where are you in that? Where are you in terms of that? And is the thinking that over time you could get to a place where you do sell a better premium default or is kind of part the aspirational goal there? Or am I completely off and maybe selling them at a gain right now? I’m not sure.

Sanjay Datta: Yeah, the committed partnerships we are in, as with all of the at-will capital, the traffic and the institutional markets, all of those loans are trafficked at par, and I think that’s our goal. We’re not necessarily looking to create a business model from gain from sale. I think our goal is to traffic loans at par that are correctly priced to the borrowers. And to the extent we’re co-invested, we’ll participate in the yield. That would be…

Reggie Smith : Understood. One-last-one. [Multiple Speakers] Okay, if I could sneak one last question, I want to give you guys flowers for returning to EBITDA positivity in the fourth quarter. Was curious how you are thinking about stock compensation expense longer term. I noticed that it’s been up and it’s well above where it was when you guys were much more profitable. So just curious, like, what’s your thinking there? Thank you.

Sanjay Datta: Well, we happy to take our flowers for the return to profitability. I appreciate that. How we’re thinking about stock compensation, I don’t think it’s dramatically different than how we thought of it in the past. As a tech company that’s headquartered in the Valley, it’s important to us for our employees to have a stake in the mission and the outcomes of the business, and I think we’re at a pretty comfortable balance between cash compensation and equity compensation, depending on role and level. So I don’t necessarily see a dramatic departure from how we’ve managed it to-date.

Operator: We will take our next question from Arvind Ramnani with Piper Sandler. Please go ahead.

Arvind Ramnani: Thanks for taking my question. I want to ask, on this call and in the prior calls, you’ll have talked about some of the big investments you have made in improving your model and capabilities. And as we get into a better kind of operating environment or lending environment, not that you have a better model. I mean, how do you expect the business to perform in a more conducive environment, just given the backdrop of a better model, a better offering?

Dave Girouard: Well, I think, as I kind of said in my remarks, I think we’ve gone through a pretty significant transformation of the business over the last couple of years, both from a technology perspective and from a business model perspective. On the technology side, we feel much, much better at the quality of the models, how quickly they can react to changes in the environment, the amount of separation we’re getting. So, it’s the normal trajectory of an AI model where it’s getting more and more data, more and more variables. We’re putting more sophisticated software in as we talked about Model 18. So, higher degrees of automation, as we talked, we have a record high on that front. So, the technology side has just really improved a lot and just made us more efficient.

And I think, on the business model side, one of the things we clearly identified is we needed to have funding structure that had permanence to it, so that when we grow, and even if there’s bumps in the road along the way, which there inevitably will be, we can grow through them. And that’s kind of what we’ve done on the business model side, has really changed the nature of funding from completely at-will to dedicated partnerships, and we have some skin in the game in these partnerships as co-investors, which we think given our role and our aims in the market, is a structure if that makes sense. So, of course, in the good times when rates are dropping and the consumer’s getting financially healthier, that’s all very easy, and we’re hopeful that’s what we’re headed into.

But of course, the test is when the market is not so easy, but that’s what we’re designing for. We’re designing for a future with less volatility and more ability to thrive through whatever economic climate we find ourselves in.

Arvind Ramnani: Yeah, that’s really helpful. And I know, like I mean, I’m willing to give you the benefit of doubt that our models are better, but I wanted to ask, have they been validated by some client feedback, some banking partner feedback? What is your sort of comfort level in saying that, ‘hey, we have a better model,’ right? I mean, are you looking at internal data and coming to a conclusion, or are you getting that from external validation? What really gives you sort of comfort that you have proof that you have a better model?

Dave Girouard: Yeah, I mean, there’s very, very well-understood statistical techniques to actually describe and quantify accuracy of a model, and there are several different ones, and we use generally all of them. So it’s not hard for us to assess ourselves whether our model is getting more accurate or not relative to prior versions of our model. So that’s not – it’s not hypothetical in any sense. It’s something very straightforward in terms of building more accuracy into a model. Certainly, every lending partner and credit investor on our platform sees all the data that is coming out in terms of all month-by-month performance data, etc. They have their own means of evaluating whether they think the credit’s performing well or not, or what have you, but they are not looking at the software if you will, trying to assess our model, but they care about the results, of course.

But there’s no – I don’t think there’s any reason to question that we can accurately identify the level of improvement and accuracy that we see in each subsequent version of our model. It’s kind of the nature of the system to do so.

Arvind Ramnani: All right, yeah. That’s really helpful. Thank you very much. And I’m looking forward to circling up with you soon.

Dave Girouard: Thanks Arvind.

A – Sanjay Datta: Thanks Arvind.

Operator: There are no further questions at this time. Mr. Girouard, I will turn the conference back to you for any additional or closing remarks, sir.

Dave Girouard : Alrighty, thanks to everybody for joining us today. As we discussed, the actions we’ve taken over the last few years are beginning to pay off, and we believe we’re well set up for the remainder 2024 and into next year. So hope you all enjoy the rest of your summer. We look forward to speaking with you all in the fall.

Operator: This concludes today’s call. Thank you for your participation. You may now disconnect.