Upstart Holdings, Inc. (UPST) Earnings Call Transcript & Summary

Welcome in, everyone. I'm Henry @HenryInvests on X, formerly Twitter. I've been posting about Upstart for about 2 years now. And today, I'm really excited and honored to be joined by Upstart CFO, Sanjay Datta, who is here to answer the questions of retail investors. Sanjay, thanks for being here. And congrats on a really nice quarter.

Thank you, and thanks for making the time. Always excited to chat with folks who have questions. So we're looking forward to it.

Yes. Real quick before I get into some of my questions for those who are listening live. This is a live Q&A. So you can ask questions in the chat and we'll periodically glance at them. And there's some time at the end, that's allocated for those questions. So make sure if you're thinking of them to post them in the chat.

I kind of just want to start with the reaction from the market. Obviously, quite favorable to your results on Tuesday. What are some of the accomplishments Upstart achieved? And maybe what are you most proud of this quarter?

Well, that's a good question. I mean, maybe I'll just answer that question in a bit of the grandeur sense. I mean, we've sort of been through a bit of a 2-year nuclear winter. It's been a tough slog and I think throughout that, our teams have shown a lot of perseverance. We've had have a lot of grit. I feel like it's maybe not super well appreciated, at least in the media that at least for the mainstream American borrower, what we've been through since essentially the stimulus ended for credit has been on par with the '08 financial crisis. And a lot of folks -- it doesn't seem like it should be the case because the GDP has been strong and employment has been good, but that's what we've been working through. And it's been tough but the teams have shown a lot of grit, improved our business in very meaningful ways. I think we'll emerge from this with more resilient funding supply, better servicing capabilities. I think our risk models have only gotten better and more predictive. And a lot of that hasn't seen the light of day. And I think when the macro clouds received a little bit, I think a lot of goodness will see the light of day. But in the meantime, I'm just really proud of the teams for just kind of keeping their heads down and keep working on the business, trying to make it better, knowing that at some point, the environment will turn in a lot of this -- a lot of the good work they've been doing well sort of will manifest.

A lot of the analysts on the conference call are really focused on your financials and not a lot of them asked about AI and models. So I kind of want to start there. A lot of your improvements that you're seeing are coming from increased accuracy in your models. Dave Girouard said your models were leaps and bounds better than they were in 2022 in terms of model accuracy, fraud prevention and automation. What's kind of your message to skeptics of that who've become increasingly vocal this past week who just don't really believe that you're able to do what you claim you can't?

Yes. There's no shortage of skepticism out there. And I think some of it is very reasonable. Some of it is not. I mean, there's basically two flavors of skepticism. One is like, oh, the credit markets are fine. They work great. They don't need to be improved. And I think that's just mathematically disprovable, right? Like a good risk model should keep out bad borrowers and include good borrowers, and it's very, I think, easy to demonstrate that both of those things are not happening. So the folks who have skepticism around the opportunity to improve the credit markets, I think that don't have, in my opinion, a lot of fact base to back that up. I think there's reasonable skepticism to say, hey, does this Upstart AI even work? Like is this the thing to improve the credit markets? And I -- the reason that's, I think, in my mind, a reasonable skepticism is because I do think that lending has a long history of charlatans who have claimed to have better mousetraps and a lot of times they don't. And so I think it's a reasonable question to ask. When -- if you sort of rewind back to the earlier years when we were out talking about machine models and AI before it became a buzzword as it now is, I think there was skepticism around the technology people are like, well, what is this, fancy model you have. And now I think there is not as much skepticism around the technology just because of all the things that have happened in AI over the last year. So I don't think there's as much skepticism that there is this new technology that can do some pretty magical things. The skepticism remains about us and do we have the capabilities to build those kinds of models. And honestly, to that, like -- at the end of the day, we're going to do our talking on the court, right, we're going to -- we're going to -- if we're right about what we are convicted and we're going to be successful and build a big business and you're going to see growth in profits, at least over the medium term and I think time will tell. We're pretty convicted in our position. So I don't know I guess the short answer is not going to waste a lot of time trying to argue whether we have the capabilities to build these machine models or not. We think we see them in action. We have the data points internally. We've tried to expose them externally. The rest will just play out as it does.

Yes. I think a lot of people give Upstart credit for certainly being able to separate risk better, maybe you're like the lower end of the credit spectrum. I'm curious and a lot of other people are curious. If we were to take like a FICO score range of 450 to 850 is Upstart's value proposition really near the 450 level? Or is it pretty consistent throughout in terms of finding hidden prime or people that are being underserved?

That's a great question. I guess I would say that our models now have pretty extensive training data, let's call it, 600 and above. So we've done a lot of lending down to 600. We're always trying to push that frontier lower but I think that's the point that we've gotten to where we feel we have a very robust training data set. And in that range, call it, 600-and-up, I think our accuracy across that range is roughly uniform. But the importance of the risk model grows as you become riskier, right? So the riskier the borrower or the borrower group, the more defaulters there are to avoid by having better models and therefore, the more value you can create. So it's not that our models are better at the riskier part of the spectrum but it's that the exercise we're performing is more valuable. And that's why we tend to disproportionately compete well in areas where risk is higher.

Yes, for sure. I mean, this quarter alone, default rates were down basically across all groups, which I think was a surprise to most of the market and it does show that your models are working. Maybe just one last question on models. You guys said that your competition in AI is scarce. I'm curious where you think your competitive advantage really comes from. Was it being first to market? Is it your algorithm, your data -- like the data that you have, maybe it's Upstart's, maybe a little bit of both. I mean I'm just curious where you think that advantage lies?

Yes. It's a great question. I mean I do believe, over time, we will have the proof points to demonstrate that this is just a fundamentally better way of decisioning credit. And so a lot of people will come down this path. I think it will be clear that the rewards are big. We have an important advantage in the head start that we have. And that's something that's actually quite specific to machine learning and how it works. And the way to think about that is we've been gathering for the last 10 years now a lot of alternative data and lending against it. And the history of whether people repay you or not, it's called the training data. And so for example, we've probably lent to many people who went to Concordia University, and we know what the -- who have studied economics. And we understand now how to price that as a risk factor because we've done the lending. And if tomorrow, someone wanted to kind of come down this path, it wouldn't be enough for them to just start collecting where you went to school and what you studied because they don't know what impact that has on your propensity to repay them. And so in order to develop that same training data set, they're going to have to put a lot of money at risk and lend. And you will generally start with a V0 of your model and it won't be very good because there's no training history, and you're going to put money at risk. And you just have to then wait to see who pays you back and who doesn't over years. So there's no real shortcuts around the fact that you need significant amounts of training data and repayment history collected against the characteristics that you think are interesting in order to sort of develop the predictive power. And yes, like as of today, I think there's -- on one hand and maybe even less than that, you can count the number of people who are trying to apply these machine models to the space of credit, in particular. Even if there's a lot more that start throwing money at this problem in the future, we're going to have a 10-year head start on the training data that there's no real easy way to shortcut. So that's a big -- I wouldn't call it a moat because at the end of the day, anyone can throw money at this and do it. But it is a head start in the sense that it takes time to replicate.

Well, as your models get more accurate, you're driving conversion gain against an unfavorable macro backdrop, which is pretty impressive. The market is generally expecting a 77% chance that we see 100 basis points or more of rate cuts this year. I know that's not something Upstart thinks about. But in the previous earnings report, you had said that for every 100 basis point reduction in rates, you'd expect Upstart's conversion rate to increase 12% to 15%. In Q2, the conversion rate was 15%. Are you kind of implying that would go up to 30%? Or did you mean something else by that?

No. So that's heuristic -- yes, so rough heuristic is a 100 basis point improvement in APRs essentially. Probably around a 15% conversion gain but that's a 15 relative percent -- percentage points. So the 15% conversion rate would go to like...

17%?

Yes, something like that.

Got it. Okay. Because I believe -- I think your conversion rate as a public company topped out maybe just under 25%. Where do you view that dynamic going forward? Is that something you think you can achieve again? Or like, I guess, in the long term, where do you think conversion rates could realistically go?

It's a good question. I mean more -- on a more basic level, the room for the models to improve their predictive power is enormous. Like we're still just scratching the surface of being able to explain the error in credit decisioning. So there's a lot of room for models to become a lot better. And in a first instance, as you get a more accurate model, you will improve the conversion rate. But at some point, something else happens, which is if your conversion rates get too high, it generally means that suddenly you're not doing enough marketing, right? Like my conversion rates were 40%, it would mean that I'm leaving a lot of profitable loans on the table. And what I should do is start spending more on advertising to get on the average, less converting customers into the -- onto the platform. So it will bring down the conversion rate but it will create revenues and profits at the margin. So even though the models are getting more accurate, at some point, it doesn't keep manifesting as conversion gain, it starts just manifesting as more volume and more profitable marketing spend. So I don't know the exact place where it should plateau. But I think some place, probably between where we were and 30% is -- I couldn't imagine it were much higher than 30% without us reacting by trying to then reach more people that would then bring down the conversion rate on average.

Awesome. Thanks for the color. I want to touch a little bit now on the future of Upstart, which is obviously pretty exciting and then we'll go ahead and get into some questions from the audience. So just once again, a reminder to make sure to submit your questions now. In Q2, Auto and HELOC had pretty good performance. I think HELOC had no defaults to date. Auto saw a 44% improvement in recovery rates in Q2 alone. So it's clear that these models are working. They also were growing nice in terms of volume and small dollar loans are growing really fast. My question is, when can investors expect these new products to sort of have like a meaningful impact on the top line for Upstart?

It's a good question. Yes, I think we've got a couple of bets that we're incubating, I think, in hindsight, certainly with Auto, we picked a really challenging time to try and get that up and running sort of right at the point where our business started to really come under stress. We had Auto coming out of the gates. And so it's definitely taken longer to get that up and running than we wanted. But I guess at a high level, the small dollar product is something that's -- it's working so well that I can imagine it starting to be meaningful financially this year potentially. . Auto and HELOC, I would say, we have optimism that those will be meaningful contributors in 2025. There's a lot of execution between now and then to make that happen but I don't see any reason why we shouldn't aspire to that.

With those new products coming in, you guys obviously are more diverse in what you're offering. So if there were to be another turbulent time in the macro economy similar to what Upstart just went through. Do you guys kind of think that your company would be a little less cyclical with more products and maybe models that are smarter and have learned from this downturn? Like do you kind of see -- how do you view cyclicality in the future?

Yes. That's a good question. We've been thinking a lot about that one, obviously. I think there's two answers to that. The first answer is we can definitely reduce the volatility in our business model. I mean if you think about it, the inception of Upstart was really -- we're lending, first of all, within credit, we're lending the riskiest product, which is an unsecured term loan. That's generally at the bottom of anyone's [indiscernible]. And we're lending it to, I think, maybe amongst the riskiest consumers, like by design, that is our mission. We have a business model that, again, by design in order to be cash efficient, is very heavily transaction sort of transactional like on the transaction we make of our economics. And we've been doing it with a funding model that was largely at Will capital. So for all of those reasons, we have about as max volatile business, as you can imagine. I think all of those things will evolve. So we are getting into more secured types of products that have less sort of immediate volatility to the macro. I think you'll see us expand our aperture across the borrower base and maybe sort of start to compete again with some primary borrower segments as well and they will be a little bit -- or at least will be more diversified across the borrower base. I think you'll see us pursue different type of funding or different type of business models that are transactional, things like servicing revenue, right? Our servicing revenue has been very stable or much more stable over the past 2 years. And I think some of these newer products will have much more of the economics as ratable servicing revenue rather than onetime transaction revenue. And then, of course, we've spent a lot of time discussing and working on how we create a more resilient funding model while still not being the balance sheet and owner of the capital, and I think we've made good strides there. So for a lot of reasons, I think we can sort of derisk the sharp volatility of the business model that we have today. But the second answer to your question is, at the end of the day, we're still applying technology to a very -- to credit, right? Credit is the underlying truth of credit is that it's a volatile thing. And so I think that will always be a part of the journey. I don't think we can eliminate the risk altogether. And one thing you said, which is important to say, like, our models have gotten a lot better and continue to get better at the exercise of what we call risk separation. And what that means essentially is, imagine you and I both have the exact same credit score and traditional metrics. But we probably have a different actual creditworthiness. And so can our model, look at you and look at me and say, actually, Henry is much more likely to pay you back, and Sanjay is going to be a bit of a dead beat. Even though they look the same. Like that's -- it's the assessment of the individual. Our models in no way are able to predict the macro. If we could, we could get into a different business and make a lot of money. I think we can say that we've gotten a lot better at reacting to the macro. So the next time something happens, we'll know it hopefully sooner than anyone and reacts more precisely than anyone. But whatever happens next is going to look very different than a pandemic. It's going to look very different than a dot-com bubble or a subprime mortgage crisis. So machine models are not good tools for trying to anticipate macro things. And for that reason, there's always a fundamental macro sort of volatility that I think we will work to subdue but never eliminate.

Yes. I mean, while we're on the topic of macro, it feels like these past 2 weeks, the only thing everybody has been talking about is this looming recession for the United States, which may or may not happen. And of course, not in the business of making predictions. But if there was to be a recession in the United States, how would that impact Upstart?

That's a good question. And it's frankly been the question of the week. Because we're once again -- we have been for a while and continue to be very contrary in our views on the macro. And so it's -- let me just maybe -- I think we do have some strong views on what's currently going on in the macro. Maybe let me explain that. And then I'll answer your question, which is how would this impact you? So our rough story arc on the macro goes something like this. Like if you sort of rewind to COVID. And of course, in the wake of COVID, there was lockdown, there is a lot of people leaving the workforce unemployment spiked and the government essentially flooded the economy with money in a very significant way. Like, within 1.5 years, they increased the money supply by almost 40% in this country. That's like a massive influx of liquidity and for a good reason, I think nobody knew where the world was going. And what happened in 2021 is essentially that as people came out of lockdown, and they found themselves quite flush with liquidity, they started spending. They started consuming on a level that they -- that well beyond what we were doing pre-COVID. So they went on a spending spree. And the second thing is they sort of only gradually trickled back to work, and it's because they have -- they are flush with cash and the government was putting a lot of the bill. And in 2022, basically, two things happened that were interesting. The first one is the government stopped sending stimulus by the end of 2021. But nobody stopped spending as if they were getting the stimulus, like the consumption kept surging. And of course, in the media, all of the headlines were like, oh, the American economies unstoppable and it's great. And of course, at the time and this is when we started to sort of come out in our earnings calls and we said we're a bit on an island. And we're like, hey, this isn't so good. Consumers are spending money they don't have. It's -- they're spending -- they don't have the income to back it up. The savings rates are getting bled down. Everyone's sort of razor thin, and we're starting to see people not repaying our loans. And everyone that we were talking to in the market sort of said, oh, this must be a problem that's just you guys because the economy is great. Why would there be defaults. So we sort of stood out as being contrarian and not pleased with the economy back then. And then the second thing that happened is -- of the set -- of the crowd that was 55 years and older that we're working. And then when everyone went into lock down, 2 million of the 55-plus year olds never went back to the workforce, okay? They just like -- they sort of like stayed retired or something. And it contributed to what has been a historically tight labor market. So if you know like for the last couple of years, it's been hard to find people to fill jobs like restaurants looking for servers and folks looking for help have just not been able to find it because there's just not been enough bodies for the work. So that's the sort of -- that was the state of the world for a while. And of course, we were sitting around going on. How long does this -- could this possibly last, right? Because now at some point, you can't spend money you don't have, which is what consumers were doing. And we said like, well, this can't go on forever. So at some point, this will normalize. And then the answer turned out to be -- it went on for longer than we could have dreamed. It essentially went on for 2 years, okay. So that's been the state of the world. And that in a nutshell has been, if you just want to like really simplify what the problem statement for our business has been. It's been that. It's been consumers have gone on a 2-year surge of spending with money they don't have and they've basically -- a lot of them have gone upside down and defaults of skyrocketed. And you could sort of see that in the macro index we published. So fast forward to 2024 and what are we seeing now? Well, towards the light, we are finally seeing those trends reverse. So one thing that's happening is consumers are finally starting to get their budgets back in balance. And you can see this in every headline. It's like, "Oh, the fast food industry is reducing their prices because people are just refusing to buy -- to eat out anymore. And target is reducing their prices because people -- and then the travel industry, like Airbnb said, all people are not traveling like these. So every headline you see is about consumers reducing their spend. And of course, the media now is like, "Oh, my God, the GDP is going to contract. We're going to have -- this is a technical definition of a recession. It's when consumption slows and GDP contracts and there's a lot of gloom about that. And of course, we're sitting here like we're ecstatic. We're like we're happy because we have essentially had a GDP growth that was not sustainable and was not supported by the income that was being earned. So on that front, we're like, yes, we're happy and we seem strange. And the second thing that's happening that's related is that the 55-year-old plus the 2 million of them that never came back to the workforce still haven't come back to the workforce. But the 25- to 54-year-old set is streaming back into the workforce. And they're now looking for work at record rates, right? The labor force participation in that segment is as high as it's ever been since the world war, which is good. It means people are like trying to get their finances back in shape and they're looking for work. But of course, when people stream into the labor force, what happens, it grows the denominator of employment and it increases unemployment. So the reason unemployment has gone up in the last few months, and this is easy to look at it in the Fed data. It's not because the economy is shedding jobs. It's because more people are now looking for work that weren't before. So we love that. So once again, on our earnings call, we did strike an optimistic tone. And because we're seeing all of this backed up in our credit data, like people are starting to pay their loans back again. People's personal fiscal shape is getting better and we celebrated that a little bit. And of course, the #1 question was, you guys seem out of step with all the headlines. And that's the reason why. So to answer your question, what would a recession, how would that impact your business? There's a couple of answers. If by that, you mean reducing consumption and contracting GDP, right now, we'll take that all day long, right? We think that it's been unsustainably high, reducing consumption will improve our credit -- will improve our credit repayment trends. If you mean by recession that unemployment is going up,and it's going up because people are flooding back into the labor force. Again, we're happy. We'll take that because it means people are -- and the good news for those job seekers is that the labor market is still historically tight, like -- there is currently 8 million open jobs in our economy. There's 8 million help wanted signs. And there's only 7 million people in the entire country looking for work. And the fact of having more jobs than people to do them, is a very recent and historic thing, like it has not happened this millennium since the turn of the millennium. So there is work and if people are looking for it, they'll eventually find it, it means the unemployment is fictional. Now, if there is a recession, that's severe enough to cause actual job loss, that will impact us for sure. That's something that I think we don't think is a high probability of happening, but if it does, like for example if unemployment went from 4% to 7% as a scenario. The way to interpret that is, okay, that means 3% of the country just lost their job. You could roughly assume that 3% of our borrower base would representationally lose their job and default on their loans for us. Okay? So what that means or rough cumulative loss rates across our platform on the order of 20%. So 20% would go to 23%, okay? So there'd be a 15% relative increase in our default rates. You can imagine that as like if you follow the Upstart Macro Index, that would be the UMI rising by 15 points, from 1.5 to 1.65. So it would have an impact for sure. And it wouldn't be nearly as large as what we've lived through. We've gone from like 0.6 to 1.6 but it would have that sort of flavor of impact. And I think it would take a fairly severe contraction to start causing actual job loss. But if it does happen, that's the sort of rough math.

Really appreciate the color there, very in depth. A lot of people are going to appreciate that. So thank you. We're getting close to time here. So I'll do two quick questions from the chat, and then I'll close it out with one of my own. Some people want to know about the buyback program that is still in place. They want to know a little bit about the framework there. Can you give any update on that?

Stock product. Yes. I mean, I guess the rough framework we have for capital use goes something like this. We could use excess capital, of course, to repurchase stock. We could use it to retire our convertible debt, which has been trading at a healthy discount or we could increasingly use it in these capital co-investment deals. The economics of which are $1 invested would roughly, we would expect $1 invested in those deals to roughly return a private equity style ROE, so something in the mid-to-high teens. And it would unlock roughly $19 more of third-party funding on which we're clipping a 10% take rate or something like that. So the economics are pretty compelling of that investment and it keeps it in the system. So we've been actively contemplating all three of those. I would say until very recently, we've been cash conscious. We wanted to conserve cash and keep it in the system. Now that the business is feeling a little more expensive, now that the macro environment seems to, as we said on the call, stop being a direct impediment. I think maybe we'll think a little more expansively about capital use but that's the rough framework that we're pretty much discussing on a weekly and monthly basis. And by the way, if I know -- I'm happy to go over a little bit if there's a lot of questions out there.

Okay. No problem. I appreciate that. Somebody else is asking Upstart stopped reporting you just went to 100 plus for banks and credit union partners, which some people didn't like that you were consuming that. Is there any rationale behind that or maybe an updated partner count on where you guys stand today?

Yes. I mean two things there. One, the pace at which we're adding partners definitely slowed during this period of time where everyone has been worried about credit performance. But I guess, more importantly, at some point, it stops being the point, right? Like at some point, like going from 100 to 120 doesn't add much. It then becomes more about the capital that we're decisioning. So I just -- I don't know that I don't know that continuing to report that we've added 10 or 15 banks is really meaningful once we're at this scale. Like it was very meaningful when we went from 30 to 40. But going from 150 to 160 or 170, I think like we've stopped tracking it ourselves because now it's how they're spending, how they're competing for borrowers, what rates they're setting, how efficient their capital is. So it becomes more about looking at the dollars than the partners, I guess, is the short answer.

Yes, absolutely. When people ask me what I think on that, I pretty much give them the same answer.

You're frozen or I'm frozen, Henry.

Are you able to hear me?

Okay. I think you froze for a little bit. I was like or I, missing was you. Anyway I missed the last little 10 seconds the way you said but...

Okay. Yes. Anyway, I guess, just on the topic of partners, if you were to get like an influx for a bunch of new partners who wanted to maybe onboard to the Upstart network, is that process really scalable quickly? Or are there lags and how that can happen?

Partners on the funding side, like banks and investors.

Yes.

There's -- I mean, I think it's easier for an institutional buyer to get up and running because they're just essentially purchasing assets. It's a little bit of a longer process for a bank to get up and running because when they are using our technology, they are the lender of record, and so they have to worry about regulatory stuff like fair lending. So there's a lot of committees in the bank, they have many committees and they have to worry about regulatory agencies and such. So it's a larger leap for a bank to get up and running. But yes, I mean, I guess the more general answer to your question is there's a borrower side of our ecosystem, which is our ability to approve borrowers through better models and there's a funding side. And scaling all of that up simultaneously is a challenge, right? Sometimes you get a big model win and you have a lot of new borrowers, you can approve and you need to scramble it at the funding and sometimes you sign a new big funding deal and you need a way to put the money to work and you have to go and try and figure out how to get the borrowers through the marketing channels. So the scale-up of our business is not boring. It's a bit of a pendulum. And when it's growing very quickly, there's a lot of work to try and coordinate all that stuff, but we've done it before.

Awesome. And then last question I have for you and I think it will be a good one to sign off on. A lot of Upstart retail investor base is going to be watching this Upstarters are probably going to be watching this a lot of us have really a strong conviction in the underlying mission of solving affordable credit. What's kind of your message to them?

Oh, goodness. I mean, similarly, similar to what I said with the workforce and how they've persevered. I mean I guess the message would simply be one of gratitude. Thank you for your support. Thank you for persevering with us. I know we're -- we're not a stock for the fan of heart, I think. And I think it's because we're trying to do something that's legitimately difficult. We're trying to take this new technology, which is emerging in real time and we're trying to apply it to an industry that's both heavily regulated and very volatile, which is credit. And look, there's been a lot of twists and turns along the way. And I think there will continue to be, I don't think this will be an easy path. But I think, a, will hopefully never be boring. And b, we are as convicted as ever that at the end of that road, there is -- there will be huge rewards for everyone for whoever successfully sort of transitions the credit industry over to more sophisticated to underwriting models. And so we're very grateful for people who are seeing past the near-term ways and who feel convicted in the mission that we feel convicted in and who are sticking with us through what I can only imagine, and I know personally because, obviously, I'm a shareholder in the company as well. It's sometimes hard to -- every quarter I got to get on and sometimes good and sometimes it's not. And it's -- the mission helps us keep our eye on the medium to long-term price, but that's not to say that the turns can be painful sometimes. So I guess a lot of gratitude from all of us at Upstart for those of you who are following the story, whether you're a believer or a skeptic, frankly, we're looking forward to the dialogue over time. And we think it's going to get to a great place and we hope you follow us there.

Thank you for your time today, Sanjay. And to everybody at Upstart, thank you. It's not common that companies connect with the retail investor base. So we certainly appreciate it. And we're all cheering you on to see what you bring in the coming quarters in the coming years.

Well, thank you, Henry. You made it happen. You're very persistent in your outreach and I think it's great. I'll be happy to talk to you about maybe doing it again soon to. So we get the next set of questions. The story will certainly evolve and so will the environment and sold the competition. And so as that happens, maybe we can get back on and check back in.

Absolutely. Sounds good. Thank you again.

Happy Friday to everyone.