Q1 2025 Better Home & Finance Holding Co Earnings Call

TORONTO 2013 Pan Am and Pan Am World Championships

Speaker Change: Hello and welcome to the Better Home and Finance Holding Company, First Quarter 2025 Results Call. All lines have been placed on you to present any background noise.

Speaker Change: After the speaker's remarks, there will be a question and answer session. If you would like to ask a question during this time, please press star one on your telephone keypad. I would now like to turn the conference over, over to Tarek Afifi Corporate Finance. You may begin. Thank you very much.

Speaker Change: Welcome to Better Home and Finance, Holden Company's first quarter earnings conference call. My name is Tarr Kapiti, corporate finance at Better. Joining me on today's call are Vishal Garg, founder and chief executive officer of Better and Kevin Ryan, chief financial officer of Better.

Speaker Change: In addition to this conference call, please direct your attention to our first quarter earnings release, which is available on our Better Relations website. Also available on our website is an investor presentation.

Speaker Change: Certain statements we make today may constitute forward-looking statements within the meeting of federal securities laws that are based on current expectations and assumptions.

Speaker Change: These expectations and assumptions are subject to risks on certainties and other factors as discussed further in our FCC filing that could cause our actual results to differ materially from our historical results.

Speaker Change: We assume no responsibility to update forward-looking statements other than as required by law.

Speaker Change: During today's discussion, management will discuss certain non-GAAP financial measures, which we believe are relevant in assessing the company's financial performance. These non-GAAP financial measures should not be considered replacements for and should be read together with our gap results.

Speaker Change: These non-GAAP financial measures are reconciled to GAAP financial measures in today's earnings release and investor presentation, both of which are available on the investor relations section of Better's website, and when filed our quarterly report on form 10Q filed with the SEC.

Speaker Change: Amounts described as of and for the quarter ended March 31st, 2025, represent a preliminary estimate as of the date of this earnings release and may be revised upon filing our quarterly report on the form 10Q with the SEC.

Speaker Change: More information as of and for the quarter and in March 31st, 2025 will be upon filing our quarterly report on form 10Q with the SEC. I will now turn the call over to Vishal.

Vishal Garg: Thank you and welcome to our first quarter 2025 earnings call. We appreciate everyone joining us today and for your continued support as we advance our mission to make home ownership better, faster and easier for our customers by building a technology platform that revolutionizes the home ownership experience.

Vishal Garg: I want to set the tone for today's discussion by reiterating that while the mortgage industry and housing markets are facing challenges, this dynamic creates tremendous greenfield opportunity for us because we are truly the first scaled up AI platform filled to empower consumers and now also empowering local mortgage brokers and banks with the technology to serve their customers.

Vishal Garg: The mortgage industry is massive, estimated by the MBA to be 2.1 trillion in total origination volume for the full year 2025, which approximately 1.4 trillion is purchased, and approximately 700 billion is refunded.

Vishal Garg: So even just a 1% share of this massive time would result in 14 billion of volume for better approximately 3x from where we are today

Vishal Garg: We continue to drive progress towards our mission in which every customer can seamlessly buy, sell, refinance, and shore and improve their home digitally.

Vishal Garg: Online, Instantly, and towards executing on our key objectives, which are...

Vishal Garg: One to lean into growth and AI to drive increased volume and revenue.

Vishal Garg: Two, ongoing efficiency improvement driven by continuous advancements in our technology and the implementation of AI through our entire operating model.

Vishal Garg: and three diversification of our distribution channels and corporate cost reductions.

Vishal Garg: In the first quarter of 2025, on a year-over-year basis, we grew funded loan volume by 31% to 868 million and revenue by 46% to 33 million, driven by funding more loans both through our DTC and Tin Man AI platform channels.

Vishal Garg: Last month we were very pleased to announce the retirement of Better's outstanding convertible debt and right size the liability structure.

Vishal Garg: This transaction is expected to create approximately $200 million of positive pre-text equity value and create a path to long-term value creation for our equity shareholders.

Vishal Garg: Removing this debt overhang is a monumental achievement and key milestone to our capital structure and Kevin will talk to this in more detail.

Vishal Garg: In the meantime, we remain focused on driving towards profitability in the mid-term by continuing to lean into Taman technology and AI, with the Betsy AI loan assistant executing 127,000 consumer interactions in March.

Vishal Garg: Our AI underwriting, growing from over 40% of lock loans to 75% in the near future and increasing loan officer productivity in terms of loans per month to over 3X the mortgage industry median.

Vishal Garg: As we look forward to the second half, 2025 and beyond, our strategic priorities remain focused on what lives in our control.

Vishal Garg: Our first priority is to continue to thoughtfully propel growth. In the first quarter, year over year, funded loan volume growth was driven by increases across all three of our main product categories, with home equity products and refinance loans being the largest growth drivers.

Vishal Garg: Specifically, he lock and home equity loan volume increase 207%, reef and ant loan volume increase 64% and purchase loan volume increase 9%.

Vishal Garg: Disgrowth is attributable to the strategic investments we've made in technology, product innovation, and distribution expansion.

including the launch of Betsy Voice-based AI loan officer.

Vishal Garg: Deployment of our Tinman AI platform strategy with the addition of Neo powered by better and efficient expansion of D to C.

Vishal Garg: These strategic initiatives have positioned us to capitalize on market opportunities, enhance operational efficiency, and drive sustainable growth.

Vishal Garg: Our second priority is to continue to reduce expenses and improve operational efficiency with the goal of reaching profitability in the medium term.

Vishal Garg: While we expect loan origination expenses will increase as we lean into growth, as we further implement Betsy into the sales processing and underwriting workflows, we expect continued operating leverage with revenue growth outpacing expense growth.

Vishal Garg: Using our Teen Man AI platform, we have been able to automate time and labour intensive components of the mortgage process and reduce our cost to originate by over 40% of the industry average.

Vishal Garg: We believe our continued investments in AI with our product and engineering road maps well on track will significantly drive down costs further, resulting in improved operating efficiency and superior customer experience.

Vishal Garg: Lastly, our third priority is to continue diversifying our product and platform distribution

Vishal Garg: We now have three ways of serving the customer using our technology.

Vishal Garg: Director Consumer, Tin Man AI as a platform, and Tin Man AI as a software.

Vishal Garg: In our D to C business, we serve the consumer directly on better.com. Better was founded on revolutionizing the consumer experience for the home finance process. And as such, our D to C business has always been at the forefront of pushing the envelope on what technology can do in the mortgage industry at its core.

Vishal Garg: Within the D to C channel, contribution margin or per loan profitability is increasing as the operating cost to fund is decreasing due to implementation of AI in both the sales and operations workflows.

Vishal Garg: Next, we serve the consumer through our Tin Man AI platform, powering loan officers across the United States locally for which we are seeing rapid early growth.

Vishal Garg: For context, over $1.2 trillion of mortgage volume in 2024 was originated by retail loan officers on antiquated technology and high operating costs.

Vishal Garg: We are quickly disrupting traditional retail mortgage origination by onboarding loan officers and the branches onto our Tin Man AI platform and powering them to do more loans than they've ever done before, removing friction from their fulfillment process and expanding their capacity to help more customers.

Vishal Garg: These loan officers keep the pricing they've been able to get historically based on the service level that they provide locally and within their communities and networks, all while compressing a staggering 80% of their back office costs using our platform.

Vishal Garg: As we've discussed on recent earnings calls, Neo Powered by Better, our first and now proven traditional retail mortgage originator, leveraging the Tin Man AI platform is deeply benefiting from our AI technology and digital lead funnel.

Vishal Garg: Supercharging their loan officer teams who have demonstrated track records and customer service excellence within the communities they serve.

Vishal Garg: Further, Betsy, the first AI voice-based loan assistant for the US mortgage industry is being individually branded for each loan-off certain year and rolled out through their entire sales force.

Vishal Garg: We are making great early progress with Neopower by Better, well ahead of our internal expectations and have high aspirations for the road ahead.

Vishal Garg: Since the beginning production in January 2025, we have onboarded approximately 115 neo-lone officers

Vishal Garg: Currently, neo-lonal officers are doing three loans a month and we have the goal of crippling this plus, their capacity to 10 loans a month, thereby also increasing their earnings to react and helping them serve even more families than they do currently.

Vishal Garg: In January , we funded $2 million of loans for four families.

Vishal Garg: In February , we funded $42 million for 104 families, and in March, we funded $119 million for 258 families.

and this is during the slow season in mortgage origination.

Vishal Garg: This is the first successful launch of taking an entire mortgage company.

Off of their traditional mortgage industry software stack with incumbents.

Vishal Garg: and the other antiquated mortgage technology that NEO had been working with before. And within 90 days, getting them to exceed the loan volume they previously had, while dramatically increasing their efficiency.

Vishal Garg: And as we have proven this out with Neo, with the entire mortgage industry watching, we have been inundated with other mortgage teams and companies wanting to move their business to the Tin Man AI platform.

Vishal Garg: We see massive opportunity in the road ahead to replicate the success of meal powered by better with other traditional mortgage originators.

and lastly, Lee.

Vishal Garg: We are serving the customer by powering banks that seek to license our Tinman AI software to become more efficient and customer-centric.

Vishal Garg: We have built a highly fine tuned platform for our own business and customers, and now there is demand from others in the industry to license our software.

Vishal Garg: This quarter we are excited to sign an agreement with a bank partner to power their entire mortgage platform from a software perspective, from click to close.

Vishal Garg: with their sales and operations people across the full range of products that they offer, including non-QM and other niche products entirely on tenement.

Vishal Garg: As you all know, banks that traditionally have to offer mortgages, but the cost to originate these loans to their customer base has been well over $10,000 per funded loan, making bank origination of mortgages largely unprofitable.

Vishal Garg: To be clear, banks want to originate mortgages, but they know they need to invest in technology to make it a profitable business in any environment. That is a huge opportunity for better and thin men.

Vishal Garg: Notably, this will be the first implementation of Tinman as a direct competitor to the point-of-sale system, plus the RM system, plus pricing engine, plus document engine, plus loan origination software, plus underwriting calculation engine setup that the vast majority of the mortgage industry has.

Vishal Garg: Mostly not talking to each other with scale data.

Vishal Garg: Wed.

Speaker Change: The ability to have only one person logged in at a time.

Speaker Change: Creating the massive workload and massive cost that it takes to make a mortgage the traditional way.

Speaker Change: We look forward to sharing more information about disrupting this entire software stack in the coming quarters ahead, as we believe a very large addressable market exists within the mortgage ecosystem for our holistic one stop software solution.

Speaker Change: Sure by the industry's leading AI engine came in.

Speaker Change: To put the opportunity into context over 5 million mortgages were built on the encompass platform in 2024.

Speaker Change: To the extent that we can achieve even 1% penetration of the encompass customer base. We believe based on our current pricing that could drive an incremental 50000, new loans and $75 million of revenue to better per year.

Speaker Change: And unlike other traditional mortgage software or SaaS platform does not charge on a per seat or a per application basis. Rather we are uniquely charging on a per funded loan basis, whereas the revenue event for the mortgage company is directly tied to the technology cost.

Speaker Change: Which is a fundamentally disruptive model to the traditional software players in the industry.

Speaker Change: And enables the full adoption of AI because unlike those other players we are paid on a per successful transaction basis not by filling seats.

Speaker Change: Our filling the application funnel.

Speaker Change: Okay.

Speaker Change: To sum it all up while our DTC business has always been at the forefront of pushing the envelope of what technology can do in the mortgage industry at its core.

Speaker Change: We have started making great advancements and diversifying our product and platform distribution channels, notably through the tinman AI platform, both empowering local loan officers and mortgage brokers and empowering banks with our software.

Speaker Change: Looking ahead to the second half of 2025 and beyond from opportunity ahead of US has never been more exciting we remain focused on enhancing our go to market with growth being our Northstar alongside continued expense management and channel diversification.

Speaker Change: We will continue to invest in building the leading AI platform in the mortgage industry, Tim managed to improve the customer experience and further drive down labor costs, making our platform more efficient and scalable ultimately driving the business to profitability.

Speaker Change: Furthermore, we are substantially broadening the use of tinman through diversification on both tinman AI as a platform for other mortgage originators and tinman AI as a software service to solve for the mortgage industry is broken textile.

Speaker Change: With that let me now turn it over to Kevin Ryan, Our Chief Financial Officer, who will discuss the quarterly performance and our financial strategy Kevin.

Kevin Ryan: Thank you Vishal.

Kevin Ryan: As we've discussed on prior calls even through a continued challenging market environment and now heightened macro volatility we continue to make great progress towards our goals of increased volume and revenue balanced with ongoing expense management and improved efficiency.

Kevin Ryan: In the first quarter of 2025 on a year over year basis, we grew funded loan volume by 31% to $868 million in revenue by 46% to $33 million driven by funding more loans go through our DTC channel and Tinman AI platform.

Kevin Ryan: We had an adjusted EBITDA loss of $40 4 million and total GAAP net loss of approximately $50 6 million.

Kevin Ryan: By channel first quarter funded loan volume was 71% generated through direct to consumer and 29% generated through tinman AI platform, along with B to B B.

Kevin Ryan: Byproduct funded loan volume was 67% purchase, 18% second lien or home equity and 15% refinance on.

Kevin Ryan: On a sequential quarter over quarter basis versus Q4, 2020 for Q1 funded loan volume was down approximately 7%.

Kevin Ryan: As Q1 is always seasonally the slowest quarter in the DTC business and this compared quite favorably to our prior guidance of down 10% to 15%.

Kevin Ryan: We are pleased that despite the sequential quarter over quarter decline in volume revenue was up approximately 30% revenue grew in the quarter. Despite the expected decline in volume due to volume from Neo coming on board with higher gain on sale margins.

Kevin Ryan: Our continued push towards increased pricing and a tailwind from the loan loss reserves.

Kevin Ryan: Turning to expenses during the quarter, when excluding onetime costs related to cleanup items from the spot transaction total expenses decreased approximately 11% in Q1 compared with Q4 of 2024, and we reduced the adjusted EBITDA loss on a month over month basis during the quarter.

Kevin Ryan: Loan origination expenses were down in Q1, a sequential basis versus Q4 of 24.

Kevin Ryan: While these loan volume related expenses will increase as we further lean into growth operating leverage will rise as revenue growth outpaces expense growth.

Kevin Ryan: Turning to our balance sheet and capital structure last month, we announced the retirement of approximately $530 million of convertible notes.

Kevin Ryan: Approximately $200 million of positive pre tax equity value to continue expanding our AI mortgage platform.

Kevin Ryan: We are very pleased to reduce the debt overhang and improve our balance sheet positioning and strategic optionality with the completion of the debt restructuring or a priority squarely remain growth and profitability.

Kevin Ryan: We continue building out our tinman AI platform and <unk> software channels lean into productivity driven savings through AI deployment across the mortgage business and drive costs down further in our corporate functions. We are excited about using AI to drive the business towards growth and profitability.

Kevin Ryan: <unk> to the advances we experienced in 2016 to 2021, when we grew originations by over 100 times.

Kevin Ryan: Turning now to our outlook.

Kevin Ryan: We remain focused on managing towards profitability in the midterm and we expect to drive growth through efficiency from command AI distribution channel diversification and optimized marketing we're balancing these growth expenses with further corporate cost reductions.

Kevin Ryan: For the second quarter of 2025, we expect funded loan volume to be up compared to the first quarter of 2025, driven by efficiencies in our Kinmen AI platform. We are particularly excited that the tinman AI platform loan volume is pacing well ahead of our internal plan in March.

Kevin Ryan: In April despite the heightened macro volatility and we expect over $450 million of Neil originations in Q2, which is growth of over 250% versus Q1.

Kevin Ryan: Additionally for the second quarter, we expect core expenses, including compensation and benefits to be down relative to the first quarter for the full year of 2025, we expect funded loan volume growth to increase year over year, driven by a tailwind from the growth initiatives, including neo powered by better offset by continued macro.

Kevin Ryan: <unk> and the loss of the Allied business of roughly $1 billion headwind.

Kevin Ryan: We expect growth to come, particularly in the second and third quarter of the year at which point, we expect Neil powered by better to be more fully ramped and to benefit from improved seasonal tailwind. We also expect further improvement to our adjusted EBITDA losses in 2025 as compared to 2024.

Kevin Ryan: Due to a combination of efficiency gains and continued corporate cost reductions.

Kevin Ryan: Lastly, we continue to undergo efforts to exit our noncore U K assets will focus on growing Birmingham Bank, we expect to more than double the UK bank originations again in 2025, as we deploy AI with the goal of building a leading AI driven specialist mortgage bank in the United Kingdom.

Kevin Ryan: We expect the exiting of three smaller noncore U K businesses to start being a benefit to our adjusted EBITDA losses in the second half of 2025 as a result of their disposition.

Kevin Ryan: With that I'll now turn it back to the operator for Q&A.

Kevin Ryan: Thank you if you would like to ask a question. Please press star one on your telephone keypad. If you would like to withdraw your question simply press Star one again.

Speaker Change: Please ensure that your phone is not on mute when called upon thank you.

Speaker Change: Your first question comes from Kartik Mehta with Northcoast Research Your line is open.

Vishal Garg: Hey, good morning, Vishal on Kevin.

Kartik Mehta: You talked about the new platform and obviously, how much success, you're having with it as you've looked at early stages. I know you talked about 90 days, but what do you think.

Kartik Mehta: A fair number of times before the loan office or really can have the impact of that model. How do you expect that to trend over the next 12 months.

Kartik Mehta: I think they start to see the impact within 30 days.

Kartik Mehta: And that starts with taking out <unk>.

Kartik Mehta: Huge chunk.

Kartik Mehta: <unk>.

Kartik Mehta: Sales related tasks that the the loan officer has to do.

Kartik Mehta: Other than speaking to the consumer so they immediately start getting back hours of their day.

Kartik Mehta: Spending either putting data into the system getting data out of the system. Following up from the system following up with processors underwriters on where loan files are at where our customer files or at all of that is done automatically by the system. So they immediately start getting time back then and there.

Kartik Mehta: They start getting productivity back because the customers that they've locked they are not having to chase them up for the documents there.

Kartik Mehta: The engine is doing it directly if there is some problem with the document the engine is doing it directly for them and then they encountered the AI underwriter, where if a loan file needs to get restructured and Im really excited about the AI underwriter because it captures the logic across all 35 of our investors.

Kartik Mehta: <unk> lines right, we're talking almost like 40000 pages of guidelines and pricing that updated three times a day, it's capturing all of that and it basically gives like the loan officer. The means of addressing the customer's question, Hey, how do I get a lower rate hey, how.

Kartik Mehta: Could I qualify for a bigger mortgage hey, how like.

Kartik Mehta: What do I need to do to get this loan approved.

This new thing came up or I want to also be a car or my dad doesn't want to co sign any more but my mom does all of that it's just totally does it instantly something that would have taken a human underwriters three to 10 hours to resolve its getting back answers in three to five seconds. So people are <unk>.

Kartik Mehta: Seeing it immediately and that's why we're seeing the traffic come in from these other loan officers, we already have on top of the Neo $2 5 billion. We're talking about we already have inbound on another 50 billion.

Kartik Mehta: Loan officers, who are funding loans today, who are excited and interested in the platform now all 50 billion is not going to pan out as people are going to have things in their cycle and people are going to figure it out, but we have created a mechanism by which if you're already successful retail mortgage law.

One offs, our retail mortgage team our retail mortgage company you can get full transparency you can get total control and you have to share a much smaller percentage of your profits with our platform and get Max productivity increases so what we're promising the retail.

Kartik Mehta: Loan officer is we're going to help you make three times more money.

Kartik Mehta: And cut costs in half.

Kartik Mehta: And that's a pretty compelling value proposition.

So thank you for that and just as a fall.

Kartik Mehta: Hum.

Kartik Mehta: Any more loan officers in 2025 would you like to onboard and I didn't know if there is a capacity or if there's a way that you wanted to.

Kartik Mehta: Gil.

Kartik Mehta: In terms of adding to the platform.

Kartik Mehta: Yes, so to be comps to be honest like.

In 2021, we had 5000 loan officers.

Kartik Mehta: Here, we are onboarding of 150 of them on the retail channel.

Kartik Mehta: So the.

Kartik Mehta: The other thing that the platform provides is effectively infinite capacity to any loan officer team.

Kartik Mehta: And so I think we'd like to grow I think we'd like to triple or quadruple the neogen, we're already going to double it.

Kartik Mehta: This coming quarter as Kevin mentioned in terms of production. So I think there is.

Kartik Mehta: There is a lot of capacity ahead.

Speaker Change: Thank you very much I appreciate it.

Brendan Mccarthy: Question comes from Brendan Mccarthy with Sidoti Your line is open.

Brendan Mccarthy: Great. Good morning, everyone. Thanks for taking my questions here just wanted to start off looking at the unit economics, just curious as to how the unit economics at the loan level.

Brendan Mccarthy: Trended year over year, and I guess really I mean to get an idea of how do you quantify the AI functionality and really you mentioned the operating Leverages is kind of positioned to improve looking forward.

Brendan Mccarthy: Are you able to quantify maybe how much you expect that to improve looking ahead.

Kevin Ryan: Yeah, Kevin do you want ask that question on the Bakken I.

Speaker Change: I can fill in.

Kevin Ryan: Yes, let me start I think Brendan has a couple of things here. So the unit economics have improved I'd just take Q1.

Kevin Ryan: February was better than January March was materially better than February and when you look at our absolute aggregate losses March was came in about $7 million of materially lower and the mortgage company that essentially was breakeven in March and so the unit economics as a direct result of the AI improvements are coming faster.

Kevin Ryan: Serious now there's always a market cyclicality to it as it relates to purchase season purchase season kind of deferred a little bit here given some of the macro so that's not going to be linear but to date. It's been it's been pretty linear today, but I would assume that's going to be two month over month over month, where youre going to see this.

Kevin Ryan: <unk> and so I'll kind of.

Vishal Garg: Maybe just guide you through the income statement. So the majority of the savings Youre going to see through the continued technology improvements are going to be in the compensation and benefits line that number is going to go up as we onboard the loan officer that Vishal just talked about right as we add those comp and Ben is going to go up but it's going to go up slower.

Vishal Garg: Then revenue and it's continued to improve I think our comp and Ben as a percentage of revenue, it's getting materially better and will continue to get better and that's always been one of our challenges. The other place youll see it is in loan origination expense.

Vishal Garg: We will that will continue to come down so basically think of that as non comp expenses on a per loan basis, we're safely below $1000 alone.

Vishal Garg: And going even lower on that line item and that is really as a direct result of being able to deprecate vendors renegotiate vendors drive better deals and.

Vishal Garg: We use our technology to really lower the expense the non comp expense cost of manufacturing alone.

Vishal Garg: So those are those are the principal areas you will you will see it.

Kevin Ryan: Great Kevin.

Vishal Garg: Right.

Vishal Garg: Yeah.

Vishal Garg: Yes, I think the Northstar is getting the total cost of production of a loan down to $500 alone.

Vishal Garg: $500 of sales labor, a $500 of op flavor and $500.

Credit Bureau income verification and all of those other sort of external vendor costs, and we're driving hard towards that.

Vishal Garg: And if we are able to do that we're going to be six times cheaper than the industry's cost of manufacturer a retail mortgage originator today outside of Salix.

Vishal Garg: <unk> expenses spending $7500 alone.

Vishal Garg: Basically get alone all the way funded through the box. So we think that there is there is certainly a lot more to gains coming out of the AI, we're starting to actually see it in the numbers.

Speaker Change: As Kevin mentioned, the mortgage company, becoming profitable this quarter, which was which.

Speaker Change: It hasnt been in many many quarters and we're going to now be able to like continue to grow. The important thing is is that as you know mortgage is a scale business and so.

Speaker Change: What we did this quarter with the addition of two additional methods of addressing reaching the market one surely on a software basis and the second on a platform basis is going to drive substantially more volume through the entire funnel, that's going to enable us to get a better pricing across our vendor contracts.

Speaker Change: Get better execution on.

Speaker Change: Hiring and deploying labor and really get the benefits of scale that plus the AI.

Ken Bryan: Ken Bryan.

Speaker Change: That makes sense I really appreciate the insight.

Speaker Change: Looking ahead, and then I wanted to talk on the balance sheet first of all congratulations on the convertible retirement I think that's a big big piece of the story, but.

Speaker Change: Just curious as to maybe longer term, what kind of leverage level makes sense for the business and kind of how do you think about the balance sheet at this point versus where you'd like to be.

Speaker Change: Sure. So I'll start Michel May want to supplement I'll make a few comments as you think about our balance sheet and leverage. The first is to date, we have always sold servicing release. So we run a very capital light business model, we don't really we're on $1 billion balance sheet.

Speaker Change: But half of that will be loans held for sale and those loans are recycling quite quickly right.

Speaker Change: Particularly post the Softbank transaction, because I think as we talked about in the 8-K, when we did the deal we didn't use as much cash at all it's actually do that deal, but we did sell loans held for sale that were unencumbered that we chose not to pledge to warehouse lines in order to fund that.

Speaker Change: Transaction so.

Speaker Change: From a leverage perspective, I don't really think about it.

Speaker Change: Debt to equity per se like where a lot of other companies may because they run a big servicing asset on the balance sheet that they presumably for most lever.

Speaker Change: Through a financing facility against the MSR.

Speaker Change: But what I will say the $155 million in new debt, we've put on it does not mature to the end of 2028.

Speaker Change: It's fully peck.

Until we're profitable we've informed our partner our lender that we will be picking the interest and so that will accrue.

Speaker Change: But we will not cash payout and so we're quite comfortable with $155 million of debt due at the end of 2028, and I think the combination of market improvement and all of the self help we're doing and the work we're doing around technology. When we think refinancing that three years from now.

Speaker Change: Should be well within our purview, so we feel quite comfortable with our current leverage.

Speaker Change: Great. Thanks for the insight there, Kevin and one more question for me.

Speaker Change: Yeah No. This is constantly a point.

Speaker Change: A point of growth year, the b to B partnerships, what other opportunities are you seeing for <unk> partnerships and maybe you could talk about the pipeline there.

Speaker Change: Do you want to start that one vishal.

Speaker Change: Yeah. So I think there is.

Speaker Change: So I'll give you some context on the banks that we signed up.

Speaker Change: With respect to the.

Speaker Change: I think basically.

Speaker Change: Two flavors of BW partnerships going forward.

Speaker Change: First is a software only partnership.

Speaker Change: There, we what we what we saw with <unk>.

Speaker Change: Al I, leaving the business in all the banks that we've pitched for ally like deals over the past couple of years is that a lot of the systems and the processes that these banks have.

Speaker Change: I think they're they're all in downsizing mode for the mortgage business and quite frankly, they are not keen to outsource the bulk of the.

Speaker Change: Front office and back office like a full package.

Speaker Change: Like what I was doing to us.

So now with the ability for the banks to utilize our software.

Speaker Change: And basically then also scale up and down on the services. So if they need a marginal processor a marginal underwriter they can.

Speaker Change: They can use us, but if they don't they don't have to.

Speaker Change: But they can just use the software and get the efficiencies out of the software for their loan officers and their processors and underwriters. We think that's a much better go to market strategy and we think we're going to be able to scale that up.

Speaker Change: Pretty rapidly.

Speaker Change: A whole host of Fintech and banks.

Speaker Change: Waiting.

Speaker Change: As we deploy this one bank across and get it across the finish line to give you some context.

Speaker Change: <unk>.

Speaker Change: For a typical bank to deploy the traditional mortgage industry stack we're talking.

Speaker Change: 1 million to $5 million in integration implementation cost and nine months.

Speaker Change: This one bank client, we had them up and running on conforming loans in three days and then they asked us to get up and running across their entire product set and also do wholesale for them and we've got them up and running in 60 days.

Speaker Change: Zero implementation costs zero third party vendor fees nothing so all per.

Speaker Change: Funded loan basis.

Speaker Change: So with this one bank just on the volume they are transitioning to the platform from what they did last year, we're going to make 4 billion plus in revenue.

Speaker Change: And we think now would adding wholesale capabilities, we might be at.

Speaker Change: $10 million to $12 million in revenue over the next 18 months on an annualized basis with this one bank alone. So and there is small to medium sized bank. So the pipeline is looking really good on that the second part of the <unk> pipeline that we have discovered.

Speaker Change: Really does work for US is other fintech, who want to get into the mortgage business.

Speaker Change: Wealth management Fintech.

Speaker Change: Lending platforms.

Speaker Change: Yeah.

Speaker Change: Personal loan platforms, and we're seeing a lot of interest from those platforms to start to diversify into home equity.

Speaker Change: And eventually into mortgage and be prepared to turn their customers into mortgage customers.

Speaker Change: And these platforms have done a really good job aggregating millions and millions of users over the past couple of years selling everything from buy now pay later personal installment loans and we make it really easy for them to get into the mortgage business without having to hire aloes and underwriters and processors and so on so forth. So we hope to share with you.

Speaker Change: Positive feedback and details and signed some big deals over the next nine months.

Speaker Change: This year on with.

Speaker Change: With many of these large fintech platforms. So I hope that covers like the two different types of <unk> that we're going to see going forward.

Speaker Change: Absolutely very helpful. Thanks, Vishal, that's all for me.

Speaker Change: Yeah.

Speaker Change: The next question comes from Reena Kumar with Oppenheimer. Your line is open.

Speaker Change: Hey, Good morning. This is Jay Cohen on for Arena. Thank you for taking our questions and congrats on Onboarding. Your first bank partner as part of the Tinman AI is software opportunity.

Speaker Change: I was just hoping you could expand on how this relationship works in terms of the economics and operational workflow and what does the go to market look like to capture additional bank partners. Thank you.

Speaker Change: Sure.

Speaker Change: So the way that it works is that.

Speaker Change: We take all of their existing software and it goes away and they get one platform.

Speaker Change: We load up the pricing that they want and give them self serve pricing control.

Speaker Change: We load up the underwriting criteria, they want and they can have that attached to the pricing. So it's the only eligibility plus pricing platform in the industry. So they can add an additional underwriting criteria and.

Speaker Change: Charge upward down for it on an overlay basis, all in one flow and it automatically triggers what needs to be tapped out both to the consumer and the processor and underwriter. It doesn't all automatically so it's really easy to learn once they kind of get the hang.

Speaker Change: You have it and we basically deploy an account manager and a product manager to help them do that on the other side, we've created a retail origination module for them for their bank.

Speaker Change: Branches, we've created a wholesale origination module for them and a direct to consumer module for them for their website and so they deploy that and they've taken the application basically taking the same workflow that they have today, but with an AI assistant handling everything so they basically can now be on 24%.

Speaker Change: 365 days, a year for their customers and their aloes can become three times more productive and start reaching the productivity that betters that Lowe's have traditionally had in the industry.

Speaker Change: And then from there there are underwriters are able to just basically become exceptions managers and.

Speaker Change: And basically all of those folks get trained by our team we have a Swat team that goes there did get deployed and then from there they are up and running.

Speaker Change: The math on that is.

Speaker Change: Her loan for our funded loan we're earning about $500 per funded loan in software fees and platform fees and basically they don't have to deal with a different vendors. They don't have to deal with multiple systems integrator. They will have to deal with any of that stuff and so for them that's very very compelling.

Speaker Change: It's not just compelling on a cost basis, it's compelling because were increasing the throughput of their people by two to three X.

Speaker Change: Which substantially takes the costs down in terms of originate and gets it more like better cost originate plus brings them scale. Because then they're not the limited by each marginal for the next marginal alone they want to do they have them or hire a new loan officer.

Speaker Change: And a new processor and a new underwriter and having to manage all of that anytime they have a staffing shortage. They can then just tell us kind of like you know what AWS dead. We're doing for mortgages basically you can turn on or turn down instantly capacity and.

Speaker Change: Hey, just to accommodate it.

Speaker Change: Great. Thank you I appreciate the details.

Speaker Change: Once again, if you have a question once again, if you have a question. It is star one on your telephone keypad.

Speaker Change: Your next question comes from Eric Hagen with <unk>. Your line is open.

Eric Hagen: Hey, Thanks, good morning, guys.

Eric Hagen: Back onto the balance sheet, maybe I mean, how does the restructuring give you better negotiating terms with lenders and other counterparties.

Eric Hagen: Talked about the bank partnerships I mean, how does the restructuring itself play a part maybe in your ability to like source to maintain those relationships.

Eric Hagen: Again like the restructuring itself does that make you more competitive with some of the other entities who may be looking at those similar partnerships.

Kevin Ryan: Yeah sure. So Eric Good morning, It's Kevin I'll start and then Michelle might want to supplement.

Speaker Change: It's certainly helpful. I think as we kind of.

Speaker Change: We disclose where getting created about $200 million of equity creation as part of the deal I think there were people who definitely looked at US and said you have a relatively high debt load.

Speaker Change: Certainly for a company that is kind of at the low point of the cycle hopefully cycle improves here.

Speaker Change: All the AI improvements will kind of drive us through the cycle irrespective of where the what the cycle does but I think we've definitely fixed the balance sheet and that we've taken equity up debt down.

Speaker Change: As the course of this deal and so when people do their kind of high level diligence.

Speaker Change: On us as a partner I think they are really looking at is for the technology. What we can provide all the things. We saw just went through right. That's that is what they're really looking for.

Speaker Change: They certainly want to make sure they have a strong counterparty as well or is it going to work with for years and years and years to come and so we feel like on the margin we've improved our pitch to them as a result of the balance sheet transaction, but we did the bouncing transaction because it was just the right thing to do for shareholders.

Speaker Change: And it was the right.

Speaker Change: The right kind of ROI on the use of the cash we used to actually get the deal done.

Speaker Change: Great color there I appreciate that.

Speaker Change: I mean, we hear constantly about the the range of borrower profiles the need for loan officers, so effectively tailor alone to the borrowers profile I mean, how do you guys work with the software to address these different profiles, how do you benchmark that.

Speaker Change: Flexibility to again address the different loan profiles or is it really more effective.

Speaker Change: Instead think of a better platform as really just being the cheapest and most efficient platform for the borrower whose profile is down the fairway so to speak in the midst of the software isn't really trying to be.

Speaker Change: Super tailored.

Speaker Change: How should we kind of think about like where you guys program. Thanks.

Speaker Change: I think thats, a really great question.

Speaker Change: For the first seven years of our life.

Speaker Change: Scatter was great.

Speaker Change: Four straight down the fairway customers.

Speaker Change: And.

Speaker Change: We just crushed it in terms of cost and efficiency on conforming jumbo.

Speaker Change: So medium Ti.

Speaker Change: 80, LTV type plants and that fueled our growth and I would say really onboarding. The retail loan officers, we've had to build out the functionality for every loan type and man in the past 120 days.

Speaker Change: Three plus borrowers who even knew that was the thing that apparently bank of mom and dad is really big in retail right and you need to have three plus borrowers. So we had to build that into our system and now we have infinite borrowers.

Speaker Change: Can you can qualify even at 12 borrowers on open files that we have to build all the cost of the products we have to build the.

Speaker Change: Construction loan product, we have to build all of these additional products all into the system and now the system Crushers all of those loan products for the bank, we have to onboard banks non QM.

Speaker Change: Statement Doc light system that crushes it and more importantly.

Speaker Change: The AI underwriting automatically is matching the consumer to the full product set and exposing the full product set the loan officer doesn't have to do any work to remember any of this stuff. It doesn't have to go from the loan officer from our conventional product and then go through the funnel go through underwriting then come get kicked out and then get matched to a different pre.

Speaker Change: <unk> and so on and so forth just like all happening instantly and so I think.

Speaker Change: One of the things that tinman is going to now be a known for is not just in.

Speaker Change: Super cost efficient, but actually capturing the full scope of products that are available on our platform, which by the way is helping D to C dramatically improve its unit economics, because all these people that we were previously turning away in D. C that we didn't have a product for we now suddenly have a product for so.

Speaker Change: This is.

Speaker Change: The growth of <unk>.

Speaker Change: Tinman AI and the breadth of the product offering has happened it was improving conversion across.

Speaker Change: All of our channels.

Speaker Change: Yes, I mean, Eric. The addition, Vishal just said it but the addition of products is one of the biggest stories for us over the last three to six months through.

Speaker Change: <unk> NAV.

Speaker Change: Onboarding of <unk>, it's been a it's been a game changer as it relates to rolling out products.

Speaker Change: Right.

Speaker Change: Color from you guys. This morning I appreciate you.

Speaker Change: The next question comes from Bose, George with <unk>. Your line is open.

George Bose: Hey, guys good morning.

Speaker Change: Thank you.

Speaker Change: <unk> on your comments about the way we could distribute it.

Speaker Change: Hello systems, nor the companies that Youre speaking to like to thank you noted generally honest system like encompass and then they're looking at you guys as a lower cost higher efficiency alternative or is it kind of it.

Speaker Change: Can you just characterize people youre talking to.

Speaker Change: The people, we're talking to are on encompass or simple nexus.

Speaker Change: And the bank that has that we've on boarded was on encompass and.

Speaker Change: EMEA was on campus and fundamentally I think the.

Speaker Change: The efficiency gain from moving from.

Those two systems plus all the vendors this ecosystem around it.

Speaker Change: Two to our platform is.

Speaker Change: It's pretty dramatic.

Speaker Change: <unk>.

Speaker Change: These companies, obviously have huge sales forces long contract cycles.

Speaker Change: But I think what's been really fortuitous for us.

Speaker Change: Yes.

Speaker Change: This is all happening now at the same time as everyone is reevaluating all of their technology to determine whether it can work with the AI agents in LLS.

Speaker Change: And our.

Speaker Change: Basically the bulk of these technologies that exist in mortgage land they can't because you have seven or eight systems.

Speaker Change: If you've talked to open AI. They will tell you the maximum number of function calls the BLM can do at the same time as two to three function calls right. So now how are you going to do.

Speaker Change: If you've got a delimiter on two to three functions pause right now how are you going to do it across eight systems without the type of latency that we're talking about for a minute to latency and nobody wants that so you can't deploy AI agent.

Speaker Change: On any of these old broken systems.

Speaker Change: So I think it's sort of like a seminal $19 95.

Speaker Change: 1999 moment, where.

Speaker Change: Suddenly the internet of things, while now AI is a thing in <unk>.

Speaker Change: None of these systems equipment. That's why you haven't seen I mean, we've rolled out Betsy six months ago.

Speaker Change: And you Havent seen anything out of the industry other than an appointment scheduling Bob.

Speaker Change: For loan officers.

Speaker Change: On top of like you can book me.

Speaker Change: So I think fundamentally you were where.

Speaker Change: Our lead is like a generational lead here and.

Speaker Change: And.

Speaker Change: I have been super surprised by the industry response.

Speaker Change: Particularly from very large mortgage companies, reaching out to us and saying Wow. This worked.

Speaker Change: I assume you get it worked for them Youll get it to work for us come out and see us.

Speaker Change: And and so we're going to scale into this.

Speaker Change: Okay, Great that's interesting.

Speaker Change: Thanks, and then you have companies that you speak to noted any concerns about it essentially.

Speaker Change: Brian technology from a competitor and so to the extent this thing grows meaningfully as any sort of alternatives like maybe separate this out or is that.

Speaker Change: Too early to think about things like that.

Speaker Change: I think it's too early to think about that.

Speaker Change: <unk>.

Speaker Change: I think the.

Speaker Change: The companies that we're talking to.

Speaker Change: We're not in retail.

Speaker Change: We're not.

Speaker Change: They don't view better dot com as a competitor.

Speaker Change: And I have been transparent with them better dot com <unk> might become.

Speaker Change: 25% of our business or even 10% of our business.

Speaker Change: Over time.

Speaker Change: And.

Speaker Change: I think.

Speaker Change: I think yes, there is that but then there's also the.

Speaker Change: When you are facing a potential extinction event.

Speaker Change: You are less worried about like buying a <unk>.

Speaker Change: Cool that helps you get past that extinction event.

Speaker Change: From someone who could or would have maybe be a competitor.

Speaker Change: Okay makes sense. Thank you.

Speaker Change: Okay.

Speaker Change: This concludes the question and answer session I'll turn the call Michelle Clark for closing remarks.

Speaker Change: Okay.

Speaker Change: Thank you all for continuing to support us as we build America's leading AI mortgage platform and in doing so help consumers get a marriage get a better rate have a better process, which let them have a better house and a better life, while the past five years have been challenging for us given the state of the market. We're now playing offense part again, we're looking forward to executing on our <unk>.

Speaker Change: <unk> efficient growth and to share more positive news with you in the quarters ahead.

Speaker Change: Thank you.

Speaker Change: This concludes today's conference call. Thank you for joining you may now disconnect.

Speaker Change: Yeah.

Speaker Change:

Speaker Change: Yeah.

Speaker Change: Okay.