LendingPoint Revenue & Funding (2024)

[00:00] Hey, folks. My guest today is Tom Burnside. He is leading lendingpoint.com, an AI driven credit tech lending platform. He sees the company as a way to do well and do good simultaneously by protecting, nourishing, and growing each consumer's financial future. He does this with over twenty five years of experience and a wealth of industry knowledge prior to lendingpoint. He's an accomplished credit and financial services leader and trusted data scientist. Tom leads the rest of the team [00:24] in serving their borrowers, their originating financial institutions, their merchants, and other service providers while delivering predictable returns to their capital market providers. Tom, you ready to take us to the top? [00:35] >> We are. [00:35] All right. [00:36] So what gave you this idea? Think back in '20 Was it 2013, the start date? [00:41] >> Well, was 2014, the end of twenty fourteen, really started funding in 2015. What gave us an opportunity is what we were looking at was at a marketplace that was serving some of the credit bands well, really kind of the assets that other banks otherwise would buy. What we saw was an opportunity for kind of the more challenged credits to start there, understand that, do it really well through AI, and then continue to broaden our funnel. And [01:06] >> so today, fund all credit bands from five fifty all the way up to eight fifty. But we started in that really that six sixty and under space just so we could try to understand them, give them a reasonable price and reasonable product and tell their story in a way that nobody else was telling it. [01:23] So these are folks, if you're listening and you're doing $50,000 a year in annual revenue and you want to take out a, what, a $5,000 loan, Tom, something like that, that can check out your offer. [01:32] >> Yeah, $5,000 now that that market goes all the way up to $50,000 So as we've got better on the marketing and the better on the understanding of the customer, we've been able to expand the offers. [01:43] Did you, sorry, what did you start with though? What was your initial sort of target offer size in 2014? [01:47] >> It was about 5,000. It was about 5,000, very beginning, start at 5,000. [01:50] So that was your sort of thesis. And then it scaled from there. Guess take me back to one of those early deals. So I'm a consumer, you said a credit score above what? [02:00] >> So typically in the early days, that credit score would be around 620, 625, maybe in that area. [02:06] Then what might that offer look like? [02:08] >> Well, was either somebody that was likely, had light credit footprint, they were just getting established and nobody could really kind of put all the other kind of API and data information together to be able to tell their story. So there's a lot of other things that you would look at outside of just credit. You might look at phone bills, you might look at rent history, you might look at some other things to tell the story of [02:26] >> their willingness to pay, right? Or their ability to pay. And so those are the things we really focused on. We focused on, I mean, of the problems you always have is fraud and we focused a lot on KYC, know your customer. And we were able to get a very predictive outcome on those predictor scores. This was typically somebody that was either on the way back up, had gone through a dip or just had a very light [02:47] >> credit footprint. [02:49] And today, even back then in your pro formas when you're building in sort of a charge off or a losses or bad debt expense, is this 2%, 3%, four percent? What do you build in as a buffer? [03:00] >> Well, really what you're doing is the AI models have done an amazing job of predicting risk. And so the way that the AI models work today is it predicts risk, puts you in a category, and then tells me, okay, basically here's what the risks are going to be. But then pricing is the next kind of optimization tool that we use. And we have about five different buckets of credit grades or risk, right? And we now are [03:24] >> up to 400 different pricing points with inside of those grids. So we are getting really, really good at giving you the right product at the right time at the right place with the right terms and conditions that you can understand how affordable it is for you to finish a project or resolve some consolidation of bills or whatever it is that you need to do. [03:45] Oh, what's going on there, YouTube? Good to see you guys. Now imagine this, you love watching these interviews with SaaS founders, but imagine if we took all of the valuation data out from over 2,807 interviews I've done manually saves you a lot of time. Well, we've done this. We've built it into the beautiful interface inside of Founderpath. Check this out. I'll show you how you can access this in a second. But you log in, you connect [04:08] your Stripe account, you see your valuation real time. You can see what it changed over the past eighty eight days and even set goals for valuation this year. Now the secret evaluation is there's many different ways to value a SaaS business. So the reason you're gonna see three or four different valuations inside of your Founderpath dashboard, this is all free by the way, is because depending on who's doing the buying of your SaaS company, you're gonna [04:33] get a different valuation. A VC is gonna pay a different valuation. Private equity firm is different. If you're gonna do a minority sale, that's different. And if you sell the whole business, that's a different valuation. You can see all those when I hover over here. Right? So the teal is what a VC would pay. Yellow is what private equity And red is if you sold the whole thing outright. Now what's cool about this is this is [04:54] not built off random data. Again, you guys hear these interviews on YouTube. All these datas are built from real time valuation data points founder share with us on the show. So traction 1,200,000 seed round 3.7 raise. They sold 22% of their business. Go in here and filter by the event. Maybe you only wanna see companies that have sold the whole business. Well, here are a bunch that have been acquired the valuation and the multiple. Maybe you're [05:20] going out right now and you're raising your seed round. We'll go in here and look at all this recent seed deals that went down, what they raised, what valuation they raised at and what percent that they sold. There's never been a larger dataset of SaaS valuations than what you can get now inside of Founderpath. And we're thrilled to bring it to you. All right, we're gonna go back to the YouTube video here in a second, but [05:42] if you wanna check this tool out, if you wanna jump in and sign up, you can check it out for free to get your valuation at this link. This link, founderpath.com/products/valuations. Or if you go to founderpath.com and hover over products, click on get your valuation here, and go ahead and sign up to give it a whirl. Again, all that valuation data live right inside the platform. I hope to see you there. Alright. Let's jump back into [06:08] the interview. So let's go stay in 2014 before because you've had a lot of growth. Let's stay in 2014 though for another minute or two. I take I'm one of your first customers. I have a 650 score, 700. I go ahead and take 5 ks. What am I gonna pay you back over what term total? So is it 5,500 over six months or what's the term look like? [06:26] >> Yeah. Typically, the average price back the days was about 22 to 23 percent [06:33] >> weighted average coupon if you think about it in that particular way. And it was typically over three to four years is what we were doing. [06:42] Well, that's a long payback period. That's a long time to payback. [06:45] >> Oh, absolutely. Yeah. Even back then, the models were doing a really good job of predicting somebody. Typically, what happens in this this is why we saw the opportunity. In this particular area, you saw a lot of very, very short transactions, six, eight, twelve months. And we saw an opportunity to give somebody something that was very affordable. And so we didn't want to go below twenty four months and we were able to get those out as long [07:05] >> as forty eight months, even back in the day by telling, by taking the AI information and doing a better job of telling a story, and therefore giving them something that was affordable. Because one of the problems is if you're paying back $5,000 over twelve months, it's a very expensive payment. When you start to elongate that out, it becomes very affordable and you give them the opportunity to get back on their feet and be able to pay [07:27] >> back. And now, most of those customers have come back to renew with us or come back to take another loan with us. We now have about 30% of the base is in a renewal status with us because we made it affordable, they were able to pay it back and they're able to take more money. [07:41] Mhmm. Just to be clear, if I take that 5 k from you in 2014, I pay it back worth three to four years. My total interest on that 5 k over four years is 1,200. [07:50] >> Right? That's 23% ish or is it 20% No. Per [07:53] >> That's roughly. That's roughly about 23 over that period of time. [07:56] I see. See. Interesting. Okay. [07:59] >> Yeah. So it wasn't based on typically what you see in this market is a discount rate, or you see a percentage. That's not what we did. We actually use an interest rate and if we were charging 23%, it's 23% a year based on the outstanding balance, which averages out to about 20, you know, 23 to 30% over the life of the of the of three years. [08:20] Mhmm. Okay. Got it. So I mean, I mean, can we basically say that that's effectively an 8% APR or interest rate? [08:28] >> No, you would want to think about it as an interest rate as a 23% interest rate, right? So it's not really a discount. It's just a simple interest rate, like you pay for a car or a house or anything else that you do. If you take some of these discount rates, they could be upwards over 100% interest. And so we think that we're given the best deals in the marketplace hands down. [08:48] Yeah, and I would agree with that based off comps I know, but talking about the pure interest rate makes you seem really bad be because mean, it makes anyone seem bad because the numbers are scary. But because you give people such a long like, get I totally get this. You give people a long time to pay back. It it it makes it sound a little bit better. But the reason I'm asking these questions is you were [09:07] able to secure to lend, you have to secure money to lend, right? You secured $100,000,000 basically on day one, I believe. How did you do Well, [09:16] >> I mean, some of this was based on track record. So we were able to get better pricing on the facilities that we that we borrow from for ourselves to be able to make that money available to our customer. So we were able to get some pretty good rates back in the day. That rates those rates have come down a lot, right, over the last few years. [09:32] But, Tom, come on. [09:33] What was what was what was good back in the day? [09:35] >> What was good back in the day? We we started off at around a 10% cost of funds on our own. [09:40] That's not quite a lot of were there warrants involved? [09:43] >> There wasn't there was a few warrants in there. Like, we I think we gave up 1% in the first year to get a to get some of the good deals. [09:49] That's that's not bad. [09:50] >> Not too bad. Not too bad. We didn't feel too bad about it. But the good news, the customer is able to get, you know, because we were able to save money, we were able to push that forward to the customer. [09:59] No, that's great. I mean, that's exactly why you wanna be able negotiate obviously that low cost capital. Now was your credit box really tight? Right? Did they really restrict you what states you could lend to, scores above six fifty or above, or did you have enough flexibility to actually deploy that capital? [10:14] >> Yeah, we had enough flexibility. I mean, obviously being in this market for quite a while, what we did is we really used more of our own equity. So our advance rates were a little bit lower, our box was wider, so we could test more. So we were able to go right out the market and test it in the best of ways. We did most of it on own balance sheet to start with, just so we could [10:33] >> prove the concept and the model worked. [10:35] So Tom, to be clear, you raised equity on day one and you were using that capital to test? [10:40] >> To test the market. [10:41] How much on day one? Do you remember? [10:43] >> Well, yeah. So the the what's interesting, the group of team the team we have here raised about $220,000,000 of friends and family. Just really no outside rounds, but friends and family, we raised that over, you know, over about probably four or five different tranches that we re raised it, but we didn't really consider them A rounds, B rounds. They were friends and family coming to the table. We had other deals that we had done together that [11:06] >> worked out well, and so it was relatively easy to raise that. Our first institutional raise didn't actually happen until 2020. [11:13] Well, that's why I'm asking. So that 02/20, like that capital you started on your balance sheet on day one, was that like a prom note on the operating company or was it actual equity that your friends and family, they put money in for equity in the business? [11:24] >> A little combination of both. Some of it just pure equity, some of it was more mezzanine type structure. So a little combination of both, but it allowed us to use that money to leverage to be able to get us access to capital, be able to test our models and make sure that our models were as predictive as we were hoping they were going to be. They became that over a short period of time and therefore then [11:51] >> the cost of capital continues to go down as your performance of models are better. It's magic that way, right? [11:57] There's a lot of fintech entrepreneurs listening to this interview, and they're all wondering how much loan tape and vintage history do they have to build to drive their costs from 121% warrants down to 8% to bring in a bank on top of the credit fund or whatever to drive the blended down. What did you back then have to grow your loan tape to get significant savings below that 10% cost of capital on your first 100,000,000? [12:18] >> That's a great question. I think there's a couple of things. The weighted average life of an asset, even though you write it for twenty four or thirty six months, people end up paying it off in eighteen months or they paid off in sixteen months. So within about a year, a year and a half, you have a pretty good idea of how the curves are going to work because most of your losses are really front ended in [12:41] >> the first six months, you'll see about 60% of your losses on a vintage analysis curve. So it's relatively easy. Once you get past six months, they can kind of predict the rest of your curve. So a year into it, you've got a couple of turns of products. But it really wasn't until we got over, call it $100,000,000 of transactions until they said, look, you got enough scale, enough predictability, and a couple turns of the product that [13:06] >> we feel comfortable in giving you better pricing and better advance rates. [13:10] Okay, this makes sense. And let me A couple of things I wanna pull out here because it's great for consumers listening. First off, you don't charge prepayment penalties, which is great, right? You let people pay off early if they want. [13:19] >> That's right. [13:20] Yep. A very flexible capital product. That's fantastic. No hidden fees. Talk to me about scale that first year. So just total amount of loans done in 2014, do you remember? [13:29] >> Yeah, it was about $15,000,000 It wasn't a lot. It wasn't a lot. [13:34] But it felt like a lot back then, though. [13:36] >> It sure did. And we learned a lot. [13:39] I was gonna say, I mean, we can sort of calculate. Right? If you had 15 out, you gave us 23% minus 10%. That's a 100 what is that? You know, 13 points of spread. Right? That's nice. It's a good business. So you go, okay. We're onto something. What's next? [13:51] >> Well, then you have these little things called losses, right? So you have the cost of capital, but you also have losses, your second largest component. So it a lean year, but it was a great year of learning, a great year of understanding how their credit models were going to perform and what we needed to augment them to get the losses in line with where we were hoping them to be. [14:13] I love this. Okay, so that's a great This guy, this is year one, just heard it. Year one, now let's go fast forward, Tom. 2018, How much total capital raised over the prior four, sorry, lent over the prior four years? [14:25] >> So I mean, got, what's interesting about it is we hit about $360,000,000 or so. So things were starting to grow. [14:33] $360,000,000 in loans in 2018? [14:35] >> Yeah, the capacity is starting to grow now, we're starting to get in a great place. The models are performing well, we have a couple of different lines of credit now at this point, all of them have been upsized. So now we have access to roughly, think I at that particular point about $350 to $400,000,000 of capacity at that particular point in time. Life is getting better, cost of funds are coming down by a couple of points. [14:58] >> So those spreads are widening, which is always good, it helps pay bills. [15:03] Mhmm. So I mean, we're talking like you get down to 7% in 2018, 6%, something like that? [15:07] >> It was about 8%. It was about 8% at that point. Right? And it wasn't until you really cross over a $500,000,000 of originations a year until pricing really starts to come of real scale. [15:17] When did you hit that? [15:19] >> We hit that in 2019. [15:21] Okay. [15:21] >> And that's happening Yes. In New York [15:25] Wow. Okay. That's fantastic. I mean, of the problems a lot of folks have when they do these deals is they think they wanna go raise a big warehouse facility. The problem is you end up with unused fees if you can't attract customers and deploy it quickly. It sounds like you just told me in 2018, you had 400,000,000 in capacity, but you did $360,000,000. That's very good optimization in terms of actually utilizing what you took down on [15:46] the facility size. How did you plan that so well? [15:49] >> Well, the nice thing about growth is our models have really led, our AI models from a marketing perspective have really led who we go after and how big that TAM is or that total addressable market. So we knew basically based on our efforts what we needed to do to grow the next $10,000,000 next $20,000,000 a month. And so what you're really trying now to do is line up capital, the capital that you need to backstop that [16:17] >> advance rate and grow and continue to grow the business. And so that was all kind of coming together at that particular point and really limiting factor was capital. It's just how much capital do you have on the books. That was really more of your limiting factor, more so than the capacity of the lines. [16:34] Yeah, very cool. And then fast forward to date, obviously, we're the middle of twenty twenty two, but what was 2021 total loans, new loans done that year? [16:40] >> 2021, I mean, very was interesting year. We grew 144% year over year, '20 to '21. [16:47] What number? [16:48] >> Capital deployed? [16:49] Yeah, [16:50] >> I'm sorry. [16:52] What number grew by that amount? [16:54] >> The capital deployed The or the [16:56] >> funding levels. The We'll talk about revenue here in just a second, the funding levels themselves. So we went from roughly about, we went to $2,100,000,000 in 2021, which is a huge growth. We slowed down a little bit during COVID in 2020, but then we had just significant, of closed a little under 1,000,000,000, then went to 2,100,000,000. So we had significant growth kind of year over year. You know, this year, we're already starting out about 800 and [17:28] >> about almost $900,000,000 just [17:30] for You've already done 900,000,000 in q one? [17:32] >> Yes. [17:33] Incredible. Yeah. [17:34] >> It's it's it's growing quickly now. [17:36] That's incredible. Okay. I didn't bring it up, but you did. Talk to me about revenue. [17:41] >> So from a revenue perspective, I think there's probably two pieces here. In 2021, we were at about $330,000,000. [17:48] Mhmm. That's a run rate. Net interest margin, or is that before you pay out your cost of capital? [17:55] >> This is basically this is our this is our net revenue. Right? [17:58] After you pay back your warehouse providers all that? [18:01] >> That's right. [18:01] Wow. 350, you said? [18:03] >> $333,300,000. So approximately $330,000,000 and will be around 600,000,000 this year. [18:08] That's incredible. And what's [18:10] your first million dollar year? Do you remember? Was that 2015? [18:14] >> Yeah. It was 2015. [18:15] Yeah. You got there pretty quick because I'm doing the spread on 15,000,000 out, right? With 13 points of spread, you get there quick. Yep. Interesting. Most most businesses like this have trouble scaling for for two reasons. They have to fight yield compression. Right? Because more money will plow into the market. Right? If it's a known known asset class. Right? The second is your Google ad expense goes up, right? You have to have CAC arbitrage somehow. So [18:38] how have you fought both of these headwinds on both sides keep scaling so fast? [18:43] >> Well, look, I think the question has always been in the FinTech space. Is it scalable? Is it predictive? And is it sustainable? Can you grow it? Can you continue to grow it at appropriate rates? And I think we've answered those questions. I think, first of all, the biggest challenge you have is you have to be able to optimize your cost to acquire a customer. And that really comes through your ability to renew a customer. I mean, [19:09] >> have an 86 net promoter score. We work really hard on our customer to make sure that our customer is having a great experience because if they have a great experience, they come back. They see you as kind of that trusted advisor. So I mean, right now, about 25 to 30% of our base runs in renewals, just renewals alone. These are customers just coming And [19:28] how many by the way? So how right now, if you look at your loan type, how many customers have at least a dollar out with you? [19:33] >> We're a little over 300, right at 300. 300,000? And we've serviced about four fifty in total. [19:41] Wow, so that's a very high renewal rate actually, right? I'd expect that number to be way higher if people weren't coming back, but it's actually not a big number of people. [19:48] >> That's right. And the average transaction today is about 11,000, right? So it's moved from the five thousand days to about 11,000 today. [19:57] And you still like it's still sort of three to the average deal, three to four year payback, 23% ish? [20:03] >> Well, we bought a point of sale company and so things moved, changed a little bit when we bought the point of sale. When we bought the point of sale company, we were able to move to seven and ten year paper for home improvement. So we're in the home improvement space and point of sale as well as medical. And in those spaces, you tend to go a little longer in turn. On a direct to consumer type of [20:22] >> product, it's typically still around five years to the typical duration. [20:29] So, is really interesting. I talked to lot of SaaS founders that have built like a really interesting marketplace that maybe connects, I'm gonna make this up, a lumber provider of two by fours with construction workers. And there's a massive audience on both sides and they sit in the middle. And what they're doing now is sort of factoring the paper, right, on thirty day things. Correct me if I'm wrong, you effectively understand how exciting this is. You [20:51] might go buy that thing and you already know the finance side of the business. So, you'll sit in middle and just start doing that in the construction space. [20:58] >> That's right. Interesting. Yeah, mean, for an example, if you some look at our e commerce space, I mean, setting there to help the small business or the e commerce business, we're helping them buy inventory, so they can they can deploy. So, yeah, they run a sale, they run low on inventory, they use us as a backstop to be able to fill back up the inventory. I just said on consumer side as well as small business. [21:22] I'm just impressed you've been able to do this because there are competitors that only do one of these things that you're dealing with. So like billd.com does this in vendor management construction. Obviously, Paylocity and Clearco in the e commerce space. Like all the areas you just mentioned, there are billion dollar competitors. So how are you winning? How are you going into these markets and sort of building a better mousetrap? [21:45] >> Look, we have an amazing team. We really do. Mean, the team has been around this space for a very long time. We also have great connections into the financial markets. So we've been able to get the lines of credit, the things we need to do in order to be able to provide the service. Our platform today services banks and credit unions and ABSs forward flows, as well as our own balance sheet. You know, we have a [22:09] >> lot of optionality for our customer and we continue to grow the optionality to be able to make sure that we can aggressively price, that we can give them the right product at the right time with the right amount of money, you know, to fulfill whatever it is that they're trying to do at that point. [22:23] I have a bunch of other questions on how you securitize and all that, but unfortunately, we're running low on time. So I'll just simplify the question. How much debt capacity do you have right now? You're doing 900,000,000 a quarter, how much could you lend? [22:35] >> We can easily get to a billion to billion 5 with what we have right now. It's a combination of warehouses, ABSs, forward flows, bank commitments, things of that sort that make that happen. But we know we can get to at least a billion 5. And the question really is in this market, we're seeing some pullback from some of our competitors. And I think it's an opportunity, we have the right kind of product and the performance and [22:58] >> portfolio, I think we're going to continue to take advantage of the marketplace where it's at. [23:02] And what you know better than anybody, what are these kinds of companies getting valued at today? Is it a multiple, like let's look at 2021, is it a multiple on your three thirty or do you get a multiple, lower multiple on loans done 2,100,000,000? [23:15] >> It's a challenge. This is the challenge for valuation, right? The challenge of valuation is a very fast growing company, earnings lag. So typically, these are discounted cash flow models, I'm really looking more at a multiple of revenue Typically, a lot of times it's either forward or post, but a lot of times they're looking forward now because on a really fast growing revenue company, they'd probably look more like in our case, the $600,000,000 than they would look [23:43] >> at the $330,000,000. You know what I'm saying? So, but that is a valuation challenge because a fast growing company will continue to have massive scale and efficiencies of scale and growth in revenue that won't show up in earnings in the first year. So you really kind of need to do it more as a discounted cash flow we see primarily over a five year period or even a ten year period to pick up the value of what [24:05] >> you're creating. [24:06] So if you do this analysis last year, what did you guide the business out if you're on a DCF model on it? I mean, it's gotta be in the billion, I mean, definitely in the billions, right? You pass 5,000,000,000? [24:15] >> So we're, I'm gonna hold that at this particular point. [24:19] Guys, I got so much. The flow was so good. We're smiling, we're laughing, and then I hit him with valuation and he shuts down. [24:26] >> Yeah. Here's the deal. We're making money. We'll make 100 plus this year. [24:31] 100,000,000 net? [24:33] >> Yeah. 100, 120. And we're one of the only ones that are growing at the rate we're growing and making that level of profit. So we're going to let the markets decide that at some point, but we felt like we're in a really great spot. Feel like the things are moving in the right direction, the predictability of the models continue to get better, the AI's growing fast on both the credit, but also on the pricing of the [24:59] >> products. And it's really accelerated our growth and we're pretty excited about where we're at. [25:05] Let me just put this, the one hundred twenty five Warburg put in, more or less than 5% of the business. [25:15] >> Warburg's an amazing partner. [25:18] This guy's a great politician over here. [25:23] >> Look, Warburg was the first institutional round that we've taken. And they've been amazing partners. Like they have been really, really good. I think we do well as a company, so that helps the relationship. [25:35] They were debt first, imagine, right? Were they one of your debt partners early on? [25:38] >> No. [25:39] Oh, they weren't? Oh, wow. [25:40] >> No, no. [25:40] They didn't [25:41] >> come in until 2000 they came in during COVID. So even during COVID, the models had really, really helped. The beta risk was still low. And they followed us for about six months and then jumped in. And so, yeah, great great partners. You know, they put in a $175,000,000 now themselves into the company. So, you know [26:02] How much was secondary? [26:05] >> None. No. [26:06] Oh, I thought you're gonna say all of I thought all of it would be secondary with you printing out a 100,000,000 in free cash flow, why wouldn't it all be secondary? [26:13] >> Well, remember, we continue to pour that money back into the business right now to continue to grow it. At the pace we're growing, you need to feed the proverbial beast, right? So that money keeps going back into the organization and we have taken no secondary. We have poured all the money back into the company to keep the coffee growing. [26:30] Well, Tom, okay, last question as we wrap up. How do you keep early employees excited about an eventual payday? You're not public, there's no secondary options. They've been with you since 2014. You maybe use options to recruit them. When are they going to see money? [26:44] >> We're gonna let the market When the market's ready, we'll be ready. [26:48] >> Look, We have an amazing team of people. A lot of these people I work with me at least two to three other companies. [26:56] >> And they believe in kind of the overall dream and where we're going. Our success is squarely on their shoulders. [27:04] When did you hire your last CFO, your current one that's with you? When did you hire him or her? [27:08] >> 2019. [27:09] Interesting. Alright, guys. I expect an s one filing in q three this year. You heard it here first. Tom, let's wrap up with let's wrap up with I'm gonna get him in trouble. Yeah. Tom, let's wrap up here with the famous five. These are easy. Number one, favorite business book. [27:26] >> You know, my mind is mine is I'm a Jim Collins fan. Right? And so anything really Jim Collins writes, I'm a big fan of. Good to Great is probably my favorite. [27:38] Number two, is there a CEO you're following or studying? [27:43] >> Yeah. I mean, I think Jamie Dimon has got to be the guy. Right? He's he's been very, very much on top of his game. [27:49] Number three, what's your favorite online tool for building lendingpoint? [27:55] >> Oh, boy. Then I I I don't know that I can answer that question. I'm gonna offend somebody. [27:59] Alright. We'll skip that one. We'll skip that one. Stay stay neutral. Number four, how many hours of sleep do get every night? [28:04] >> About six. [28:06] And situation, married, single kids? [28:09] >> Married and married and two daughters. [28:11] Two kiddos. And how old are you, Jim? Or Tom, sorry. [28:16] >> Young. I'm 58. [28:18] >> 58. [28:19] Last question. Take us...