Better Home Finance Holding Class Aktie

Good morning. My name is Aaron, and I'll be your conference operator for today. At this time, I would like to welcome everyone to the Better Home & Finance Holding Company First Quarter 2026 Results Conference Call. [Operator Instructions]

And with that, I'm pleased to turn the call over to Tarek Afifi, Senior Corporate Finance and Investor Relations Manager. Tarek, with that, you may begin.

Welcome to Better Home & Finance Holding Company's First Quarter 2026 Earnings Conference Call. My name is Tarek Afifi I'm Better's Corporate Finance team. Joining me on today's call are Vishal Garg, Founder and Chief Executive Officer of Better; and Loveen Advani, Chief Financial Officer of Better.

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

Certain statements we make today may constitute forward-looking statements within the meaning of federal securities laws that are based on current expectations and assumptions. These expectations and assumptions are subject to risks, uncertainties and other factors as discussed further in our SEC filings that could cause our actual results to differ materially from our historical results. We assume no responsibility to update forward-looking statements other than as required by law.

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 GAAP results.

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 in our quarterly report on Form 10-Q with the SEC. More information as of and for the period ended March 31, 2026, will be provided upon filing our quarterly report on Form 10-Q with the SEC.

I will now turn the call over to Vishal.

Thank you, Tarek. Good morning, everyone. Q1 was a strong quarter for Better. We generated approximately $1.64 billion in funded loan volume, exceeding the high end of our prior guidance and growing funded loan volume approximately 89% year-over-year. Revenue from continuing operations grew approximately 52% year-over-year to $47.5 million, and our adjusted EBITDA loss was approximately $19 million, which was a 48% improvement year-over-year.

Just as importantly, we continued scaling the Tinman AI platform and expanding our partnership ecosystem, which remain the core drivers of our long-term strategy. Before discussing product innovation and partnerships, I want to address the macro environment directly and explain how we are thinking about the business in the current rate backdrop.

The company entered 2026 with strong momentum, generating funded loan volume of $450 million, $521 million and $673 million in January, February and March, respectively, a month-over-month growth of 16% and 29% in February and March. What's more in late April, pre-approval volume for our biggest Tinman AI platform partner went from approximately $100 million per day in preapproved customer volume to over $200 million per day in pre-approved customer volume.

That being said, the prolonged conflict in the Middle East has started to show a market impact on interest rates across the mortgage industry with rates for consumers on our platform growing from 5.75% to well over 6.5% in the last few weeks. And this is causing consumers to get stuck in the middle of the funnel, hesitating to lock at a higher rate, particularly if they feel the rate increase is temporary due to the situation in the Middle East.

With our partners' help, we are converting some of these customers who need cash now to HELOCs. But for those looking just for savings per month, we are in a waiting pattern where we will go back to them with a lock as soon as rates come back down.

So the bad news is that conversion rates are down from where they were in Q1 due to macro factors. The good news is that partner volume continues to increase dramatically as the partner opens us up to a broader section of their customer base and products.

Despite the macro noise, we are structurally better positioned than most mortgage platforms for three reasons. Our partnership model creates structurally lower customer acquisition costs and scalable distribution and doesn't require us to spend money upfront, which then can get hung up when conversion cycles blow during volatile market periods.

Tinman AI continues to improve conversion efficiency and operating leverage. Our diversified product mix spans across purchase refi and HELOC. And when refis become more difficult, we can convert a segment of those into HELOCs, which is a tool we didn't have in prior rate cycles. That positioning is reflected in our Q2 guidance. We expect funded loan volume of approximately $1.65 billion, representing approximately 37% year-over-year growth, slower than what we had originally anticipated going into Q2.

Importantly, while funded loan volumes are expected to remain approximately flat sequentially, revenue is still expected to grow meaningfully due to continued mix shift towards higher-margin HELOC products. We currently expect approximately 15% sequential revenue growth in Q2, which we believe is an important signal that the strategy works and the platform works despite the macro backdrop.

We also continue to believe the business is positioned for substantial operating leverage as volumes recover. At the same time, we want to be direct with investors. The timing on when we achieve our $1 billion monthly funded volume target will depend in part on the rate environment. It looked highly doable this time last month. And right now, sitting for this month, it looks like it's going to be deferred.

The long-term trend remains intact, but near-term visibility continues to be impacted by macro volatility and what that does to consumer benefit on a refi. That said, if rates improve meaningfully, we believe the lead funnel is already in place and positions us to accelerate towards that target relatively quickly.

Regardless of the environment, we continue to execute aggressively. In April, we announced a series of deliberate steps to strengthen operations and continue our progress towards profitability. These actions are on track and are even more important against the backdrop I just described.

First, we're removing at least $25 million of annualized costs from our operations beginning in Q2 2026. Second, we expanded our total warehouse capacity by 48% to $850 million since the start of Q1. And third, in early April, we raised $69 million in equity that further strengthened liquidity and operational flexibility.

All of these actions, along with greater focus on AI efficiencies, deep cuts in corporate overhead and the adjusted revenue growth and the change in the mix to HELOC versus refis means we remain in sight of the target of adjusted EBITDA breakeven by the end of Q3 2026.

Turning to partnerships. Our Credit Karma Finance of America and top five non-bank originator partnerships are all live and ramping. These partnerships are especially important because they leverage existing customer ecosystems rather than paid acquisition channels. For example, an increasing portion of Credit Karma's 140 million members are exposed to Credit Karma Home Loans powered by Better at zero upfront CAC to us. We believe that structural CAC advantage will become increasingly important as the industry consolidates.

In late January, we marked the one-year anniversary of our partnership with NEO. NEO grew from a $1.5 billion run rate at onboarding to $2.9 billion in March 2026. Our Tinman AI platform generated approximately $821 million in funded loan volume during Q1, accounting for approximately 50% of total funded loan volume, up from 44% in Q4.

That progression is important. Tinman represented 0% of funded loan volume in 2024, approximately 36% in full year 2025 and now approximately half of total funded loan volume. We expect that percentage to continue increasing in the coming quarters ahead.

Now to product innovation. We had two recent launches I want to highlight, both of which serve buyers in this environment. Last week, we announced the launch of the Better Home Equity card in partnership with Stripe. The card is a Mastercard linked to a Better HELOC, letting customers spend funds drawn from their line with a single flight.

Even more, customers get 1% cash back on all spend, which further lowers their total cost of financing and extends their stickiness in the Better ecosystem from a one-time transaction to a 30-year relationship. We believe HELOC demand remains durable across rate environments, and this product materially simplifies homeowner access to instant long-term liquidity against the value of their home.

In March, we also launched the first Fannie Mae eligible token-backed mortgage in partnership with Coinbase. Qualified customers of Coinbase can pledge Bitcoin or USDC as collateral to fund their down payment without liquidating their holdings, triggering a taxable event. We have a large pipeline of Coinbase customers who are signed up on waitlist for the official commercial release of the product in Q2.

We see digital assets increasingly becoming part of mainstream consumer finance infrastructure, and we intend for Better to lead that transition inside mortgage origination to leverage refi technology to fundamentally lower the interest rates on home finance products for consumers.

We believe the foundation is now in place for Better across our tech platform. Our distribution partnerships, our product expansion and our cost structure and the proof points are becoming visible in revenue growth and path to profitability in sight despite a choppy macro environment.

With that, I'll turn it over to Loveen.

Thank you, Vishal. The Q1 financials reflect continued progress and growing operating leverage from our platform and improving efficiency in our business model. Funded loan volume grew approximately 89% year-over-year to $1.64 billion, while revenue from continuing operations increased approximately 52% year-over-year to $47.5 million.

Importantly, total expenses grew approximately 27% year-over-year. That spread between revenue growth and expense growth reflects the operating leverage embedded within the Tinman AI platform. As Tinman AI volumes scale, revenue growth outpaces headcount and infrastructure growth. In Q1 2026, our adjusted EBITDA loss was approximately $19 million. That's a 48% improvement year-over-year and a 16% improvement quarter-over-quarter.

Looking at product trends in Q1, refinance grew 542% year-over-year. Home equity grew 30% year-over-year, and purchase grew 2% year-over-year. By product mix, 50% of funded loan volume in Q1 was refinance, 36% was purchase and 12% was home equity. By channel, approximately half of funded loan volume in Q1 came through the Tinman AI platform and the other half through direct-to-consumer.

As Vishal discussed, we're starting to see the impact of the prolonged conflict in the Middle East on rates. However, one of the most important dynamics in our model today is mix shift. HELOC products carry materially higher gain on sale economics, which allows revenue growth to outperform funded volume growth, which is reflected in our Q2 guidance.

In Q2, we expect funded loan volume of $1.575 billion to $1.725 billion, of which the midpoint represents 37% growth year-over-year. We expect total net revenues of $53 million to $56 million, of which the midpoint represents 28% growth year-over-year. We also expect an adjusted EBITDA loss in the range of $12.5 million to $14 million, of which the midpoint represents 42% improvement year-over-year.

Importantly, we continue making progress on our path towards breakeven while simultaneously strengthening the balance sheet and improving liquidity. We previously announced at least $25 million of annualized cost reductions beginning in Q2. These reductions are underway and include lower corporate overhead, vendor rationalization and the planned divestiture of our U.K. bank.

On the balance sheet, we ended Q1 2026 with approximately $136 million of liquidity, which includes cash and cash equivalents, restricted cash and net assets held for sale. This does not reflect our recent capital raise of $69 million, which closed after quarter end. We believe the balance sheet today is materially stronger and appropriately positioned to support our path towards profitability.

In addition, we expanded warehouse capacity from approximately $575 million at year-end to approximately $850 million today, representing a 48% increase. That expansion reflects both lender confidence in our platform and the infrastructure required to support future partnership growth.

As Vishal discussed earlier, based on our current operating structure and ongoing cost initiatives, we remain focused on adjusted EBITDA breakeven by the end of Q3. The timing for reaching that level will depend in part on the macro environment and the pace of rate normalization, but the operating model continues to move in the right direction. We believe Better today is materially more efficient, more diversified and more scalable than it was even 12 months ago.

With that, I'll turn back to the operator for Q&A.

[Operator Instructions] Our first question for today comes from the line of Kyle Peterson with Needham.

I guess I just wanted to first start off and clarify a couple of the moving pieces in the guide. I guess, one, have you guys assumed that the macro and kind of this frozen pipeline due to some of the Middle East tensions, have you assumed any improvement or resolution in the back half of the quarter or more of a status quo?

And then I guess also, could you guys just give us a quick reminder on some of the relative gain on sale rates, specifically on the HELOC side. Obviously, it seems like that's really offsetting some of the volume difference, but I think a reminder there would be helpful for everyone on the call.

Sure. I mean we are assuming no resolution. And so I think we've been very conservative with respect to what we're guiding towards because going into April, we knew that volume top of funnel was about to almost double. And going into April, we were very confident in the number that we were quoting, which was $1 billion of volume.

And then the rate spike, the escalation in the Middle East, basically, all that new volume came top of funnel. I think we shared that it went from about $100 million a day top of funnel for pre-approval volume to $200 million a day in the back half of April.

But those customers are not converting at nearly the same rate. We're converting a bunch of them to HELOCs, but a bunch of them that come in just to do a rate term refi or do a debt consolidation to bring down all the rates. They're going to save more if they wait it out than they would getting into it right now. And so we have to give them the right advice for them, and that's what we've always done, prioritize the long term over the short term. So that's what we're doing.

And we think that, that's a coiled spring for when things die down in the Middle East, you're going to see some bumper months as we convert all those customers who are effectively on a wait list to lock when rates come back down.

On the gain on sale, HELOCs are averaging between six to seven points total gain on sale in combination of origination fees and gain on sale premium, whereas traditionally, mortgage on D2C has averaged 2.5 points and on NEO has averaged 3.5 points.

Okay. That's really helpful. And then I guess a follow-up on the HELOC card initiative that you guys have launched. That seems like a really interesting product, I guess. How are you guys thinking about when that goes live later this year, ways whether that increases engagement gives you a competitor edge or monetization opportunities? Just any more color there on how you think that fits in and could potentially help you guys kind of continue to accelerate growth in HELOCs would be great.

Yes. So I think there are many utility functions of the home card. The first utility function is it tracks all your home spend. So it helps you effectively monitor that, and it provides discounts on things that you use for your home. Two, you get 1% cash back. So for a customer, they're effectively getting their rate or fees bought down as a result of that 1% cash back.

Three, it creates a 30-year relationship with the consumer for us versus having a onetime transaction, which means that recurring refis for that consumer, cash out refis will be nearly instant and super -- creates a super engaged customer base for which then we can market other products like what we've done with homeowners insurance, which typically comes up for renewal every year, life insurance, any of these other products that we've traditionally had, we can then have an always-on relationship with the consumer versus a once every three-, five-, seven-year relationship with the consumer.

I think it moves into basically Better being a home finance home operating system for the consumer rather than just a onetime home transaction system. And we think that our partners have already started asking for it. It's just another really good way for a partner to service their customer and maintain that. So a number of our partners are already asking us to replicate what we're doing internally for our D2C business for that. So it gives us another feather in our cap when we go and pitch HELOCs or home equity as a service to other companies or mortgage as a service to other companies.

Our next question is from the line of Ramsey El-Assal with Cantor Fitzgerald.

Has the more challenging macro backdrop caused any slowdown in your partnership discussions or partnership pipeline conversion?

I think it's accelerated, especially within the traditional mortgage broker and retail mortgage lender channel. A lot of people were hoping '26 was the year that they were going to thrive in. And it's looking like with the Middle East conflict, things are tougher. So more and more banks are still looking to get into the business.

Of course, the Middle East conflict and higher elevated rates and oil prices has an impact on the number of customers eligible for refi, but it has an even bigger impact on unsecured consumer credit. And so we're starting to see a lot of inbound from other fintechs, other large consumer credit companies to pivot from their traditional unsecured offerings into a secured offering like a HELOC.

Okay. And could you also comment on the loan mix between Tinman and direct and kind of how the changing environment might play out in terms of your target there. I think it was 60% Tinman by the end of the year. I was just curious if the changing backdrop here has any impact on that target.

I think we're well on our way to achieving that target.

Yes. I think, Ramsey, you're hitting on a great point. Had we been a traditional D2C play, we would have spent money on these leads upfront and not have them convert. Because we're now relying on our partnership volumes, right, we're somehow derisking ourselves from that eventuality.

Our next question is from the line of Rohit Kulkarni with ROTH Capital Partners.

One kind of just comparison of unit economics to the extent you can, can you just flag what's the difference between Tinman platform generated volume versus D2C specifically, like relative kind of CAC profile gain on sale? And longer term, do you see a scenario where the contribution margin for the platform volume would actually be structurally higher than your traditional D2C business?

That's a great question. Right now, we try to price our platform partnerships. So, we make the same amount of contribution margin. Revenue can change, right, because different partners are asking us to do different services for them. But we try to make the same contribution margin that we do on D2C in our platform business. And so as we scale, we're hoping to make sort of around $2,000 per loan contribution margin on mortgage and slightly less than that on HELOCs in our Tinman AI platform business.

Over time, as it becomes -- the sale becomes more and more software, like margin profile is much better on Tinman AI platform. But in the right now, the gains from AI are captured first in D2C, which is why you saw our continued improvement in our unit economics on the D2C business. And then we port those things that work in D2C into the Tinman AI platform business.

Okay. Got you. And regarding the current macro environment and rate kind of changes in the last 45 days. Historically, what is the typical lag in consumer behavior and how that impacts your business, assuming there's a pathway towards more stable macro in the next 60, 90 days. How does that -- how do you anticipate that to impact your business? And over what duration and -- sorry for a multi-quarter here and that, are you assuming any improvement in macro in your 2Q guide?

We're assuming no improvement in the macro in our 2Q guide. And so, we're being conservative there. And we are -- the typical cycle is you can start to see on refis in particular, on rates on refi, in particular, you can see immediately within a week, if a consumer comes in as a pre-approval, if they're going to lock or not or if they're hesitant.

And usually, when they are hesitant, we register in our data, the price point at which they would transact and then we hold them until they come back, kind of like -- think of it like a limit order in stock trading. And then -- so we see that behavior manifest itself out in refis.

Purchase, as you know, is like a six-month cycle. And HELOC, depending on the use case, if it's for debt consol, it can take the consumer a month to decide on what debt to pay off or not and what things that they care about or not. If it's more for home improvement or tuition or other things like that, they typically have a need that needs to be satisfied within a week, two weeks, three weeks.

Yes. Rohit, I think to go with this is, as we think about beyond the second quarter, if the environment stays where it is, we'll have increased indexation towards HELOCs and less so towards refi. And if the macro changes, then that equation will flip.

I see. I got you. And then I know you reaffirmed breakeven EBITDA by end of Q3. Q2 is still close to negative $13 million in EBITDA. Can you help us kind of what specifically bridges that Q2 to Q3? What are the factors under your control? And maybe just layer in the $25 million cost reduction program, how much of that is in Q2? And what other levers do you have in Q3?

Absolutely. Yes, that's a great question. So today, our current financials exclude the U.K. business, which is we're considering that as discontinued ops, right? As we think about getting to our breakeven targets, our current cash OpEx is about $68 million. That's the guidance that we're giving, right? So for us to get to profitability by the end of Q3, we'll have to get to a revenue mix or a revenue component of around low to mid-70s for us to breakeven at the end of Q3.

Our next question is from the line of Owen Rickert with Northland Capital Markets.

Could you talk a bit more about how some of those newer partnerships are ramping today? Are you seeing encouraging trends in engagement and conversion rates so far? And how have those partnerships trended on a monthly basis throughout the quarter?

The newest partnership are ramping extremely well. I mean we literally in the month of April, went from $100 million a day top of funnel to $200 million a day top of funnel. $200 million a day top of funnel just multiplied by 250 business days is $50 billion of pre-approval volume.

And we're still just scratching the surface. Our biggest partner, Credit Karma, we are exposed in many of the products to less than 1% of their customer base. for the top five retail lender, we're just ramping up their salespeople on the HELOC product, and they have hundreds of billions of dollars of MSR on their books that we're going to be targeting, which has a very, very high conversion rate.

Our top three fintech, they're scaling. They're becoming a reasonably decent size of our HELOC volume. And so you've seen like monthly HELOC volumes start to continue to trend up. A little bit of that has been. And then we've got a couple of banks in the queue off of our ChatGPT announcement that we did, I think, about two months ago, and we're hoping to get them closed and operational and live shortly.

Got it. And then on the technology side, where are you seeing the biggest operational or customer-facing benefits from tools like Betsy, Tinman AI and the broader machine learning initiatives?

The biggest benefit is in customer contact capability where consumers are now able to transact with Betsy 24/7, 365. And we're increasing the exposure of Betsy branded for our partners in their funnels. So I think the biggest uplift is going to actually be when we are able to fully deploy Betsy in our partner funnels, not just in our D2C funnel.

[Operator Instructions] Our next question comes from the line of Kartik Mehta with Northcoast Research.

Vishal, one thing you've talked about are partnerships and your partnerships are growing. If in the interim, the mortgage market stays soft, but all of a sudden, we get a big bump up, the war is over and all of a sudden, you get a lot of activity. How do you manage the infrastructure if demand spikes?

We are already getting geared up for something like that. The best thing that we can do is in the old days, we have to rely on humans to staff up and pick up the phone, work late shifts, work weekends. And now we are able to simply leverage Betsy. Betsy loan officer, Betsy loan processor, Betsy loan underwriter.

And in preparation for some of that, we're actually taking off some of the gloves where Betsy was recommending a particular task or a particular path to both a consumer or an internal person and then the internal person was sending it out. We're now just having Betsy be on autopilot after close to over 1.5 years of learning data. And so I think that, that's just going to crush the operating cost framework and allow us to capture all the volume as it comes in.

And Vishal, on a couple of partnerships, you're not the only mortgage provider, but it seems as though you have a competitive advantage because of your technology. Have you seen your partners or talk to your partners about comparing your ability to serve their customers versus others that might be on the platform? And if so, what type of advantage is that giving you?

Our partners typically see an improvement of 2x relative to the incumbent in terms of both productivity and customers served. So that's really the promise that we make to them is "We're going to help you double revenue, and we're going to help you cut your cost structure by 30% to 50%, and you'll make 4x, 5x, 6x more money."

And that's how it's playing out for our existing partners. That's why there's a waitlist of people to get on the Tinman AI platform, the ChatGPT Enterprise Edition. We just are -- we're continuing to work through that and the value prop to the partners is high.

But as you know, like the mortgage industry is an industry that the Internet basically forgot. And so we have lots and lots and lots of mortgage people who are still operating on really old antiquated systems. And what we're also finding is that their staff are used to just those systems. So frequently, we go in and they tell us that, "Hey, we'll keep this staff and then the rest of them, why don't you like adapt them to the new system?" And what they find eventually is that we have to do it all for them. So I think that is also upside in the margin profile that we land with a particular product or a particular implementation and then we expand from there.

Our next question is from the line of Brendan McCarthy with Sidoti.

Just wanted to ask a quick question on Birmingham Bank, the U.K.-based bank. I know you classified it as discontinued operations held for sale. Can you give us any detail on when we might expect a sale regarding timing? Can you give us any color on potential capital release from that sale or perhaps sale proceeds?

Yes. So Brendan, this is Loveen. We're in an active sale process. We had an investment bank to lead that. We're in active discussions with potential buyers, right? That's all I want to disclose at this time, given that we're in active discussions. Even if we do sign, there's a regulatory approval process in the U.K., which is going to take about two to four months. So think of the impact in Q4.

Understood. Looking at the Coinbase partnership with the crypto-backed mortgage product, can you kind of walk us through the economics of that, the revenue profile there and perhaps the launch time line of when we might see an impact in the P&L?

The currently publicly stated launch time line is sometime in late Q2. The revenue profile from that product is starting to manifest itself. Obviously, we have more pricing power in that product than we do in your traditional direct-to-consumer product. And so you should start to see like NEO-like margins on that product.

Got it. That's helpful. Last question, just back to the Q3 breakeven guide for adjusted EBITDA. Just to clarify, I know you mentioned you're assuming a pretty stable environment as it relates to the macro. But is there any risk to achieving that breakeven if rates move meaningfully higher or maybe the Middle East conflict is more prolonged than expected?

We're going to have to cut costs deeper. I think we're pretty committed to that number.

And ladies and gentlemen, that will conclude our Q&A session for today. Vishal, I'd like to turn it back over to you for any closing comments. Thank you.

Thanks, everyone. Q1 was a really good quarter for us. We signed a bunch of really big deals, and we executed on our plan and we beat guidance.

I know it's disappointing for the Q2 guidance for us to not get to the $1 billion mark of loan originations that we had planned to in May, but we're going to make up for that in the context of cost cutting, deeper cost -- change to a HELOC product, which doesn't have a $350,000 balance, has a $100,000 balance, but makes basically the same amount of revenue and using that to continue to drive revenue growth and a path towards profitability, which is what we are expecting in our Q2 guidance, and we're confirming again that we will achieve by the end of Q3 2026.

So, thank you all for continuing to have an interest in believing in Better, and we appreciate you all.

Thank you, everybody. Have a great day.

Ladies and gentlemen, thank you for standing by. My name is Krista, and I'll be your conference operator today. At this time, I would like to welcome you to the Better Home & Finance Holding Company Fourth Quarter and Full Year 2025 Results Conference Call. [Operator Instructions]

I would now like to turn the conference over to Tarek Afifi, Corporate Finance and Investor Relations Manager. Please go ahead.

Welcome to Better Home & Finance Holding Company's Fourth Quarter and Full Year 2025 Earnings Conference Call. My name is Tarek Afifi on Better's Corporate Finance team. Joining me on today's call are Vishal Garg, Founder and Chief Executive Officer of Better; and Loveen Advani, Chief Financial Officer of Better.

In addition to this conference call, please direct your attention to our fourth quarter and full year earnings release, which is available on our Investor Relations website. Also available on our website is an investor presentation. Certain statements we make today may constitute forward-looking statements within the meaning of federal securities laws that are based on current expectations and assumptions. These expectations and assumptions are subject to risks, uncertainties and other factors as discussed further in our SEC filings that could cause our actual results to differ materially from our historical results. We assume no responsibility to update forward-looking statements other than as required by law.

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 GAAP results. 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 in our annual report on Form 10-K filed with the SEC. More information as of and for the period ended December 31, 2025, will be provided upon filing our annual report on Form 10-K with the SEC.

I will now turn the call over to Vishal.

Thank you, Tarek. Good morning, everyone, and welcome to our fourth quarter and full year 2025 earnings call. Before I begin, I'd like to give a warm welcome to our new Chief Financial Officer, Loveen Advani. Loveen is a seasoned strategic and operational finance leader with a strong track record of guiding companies through growth and transformation. He has repeatedly demonstrated the ability to align strategy, capital allocation and execution. His experience and leadership style will be instrumental as we execute our strategic and financial priorities in our next chapter of anticipated growth. What's more, I love him because he gets his hands dirty and his hands on keyboard. When I first met him, he sent me over a model, and we started spending time on it one-on-one late at night. That is the kind of CFO that this company needs for the next stage of its Blitzscale growth, and we are so, so happy to have Loveen on board with us.

Better is a vertical AI platform fundamentally reshaping and revolutionizing the home finance industry. We are building the AI native frontier of consumer finance and in doing so, enabling players with massive customer bases to provide mortgages and HELOCs in an AI-first way to their customers, while empowering the established network of local retail mortgage originators. Adoption across the ecosystem confirms this shift is real and accelerating. This is the power of the Tinman AI platform.

Over the past decade, we have built a first-of-its-kind AI-driven matching engine that connects consumer credit data, income data, asset data and property data with the preferences of roughly 40 different investors on our platform, allowing us to approve mortgages and home equity loans nearly instantly. The result is a process that is faster, cheaper, easier and just [ plain ] better. We are in the middle of a genuine transformation from what was once a direct-to-consumer mortgage business serving consumers who came to Better.com to an AI-native mortgage platform serving the entire mortgage industry.

Over the past decade, we built the technology, the infrastructure and the investor relationships to manufacture mortgages faster and cheaper than anyone else. Today, we're taking that foundation and extending it across the entire ecosystem, powering partners with massive customer bases and enabling local retail brokers and originators to scale in ways that simply were not possible before. That shift is now showing in our results and in the momentum we are building with our enterprise partners. These are large complex partnerships with longer sales and setup cycles than anything we manage in our D2C business, and growing them is not something we do alone. It requires deep collaboration with our partners at every step from integration and onboarding to conversion, optimization and product expansion. The pace of ramp is a shared journey, and we are working hand-in-hand with each of our partners to get things scaling. The progress we are seeing is real. The early data is highly encouraging, and we are more excited than ever about what lies ahead.

Let me walk you through what we are seeing across each of our key partnerships. As you know, we launched the largest platform partnership in Better's history with Intuit Credit Karma, a leading personal financial services company serving more than 40 million monthly active users. Last year alone, Intuit Credit Karma processed 47 million tax returns and reached over 140 million members. In fact, more than 80% of Americans who took out a mortgage last year are members on the Intuit Credit Karma platform. Through this partnership, we are integrating the breadth and depth of Credit Karma's member data, including credit, income and home attributes such as full credit bureaus, tax returns and detailed home valuations directly into the Tinman AI platform.

As you might remember from our public announcement, Credit Karma's goal is to save its members $1 trillion in interest savings on their mortgages. This is no small task, as it implies that our collective partnership, which is saving consumers about $25,000 of lifetime interest on average since we launched in October 2025, needs to fund 40 million mortgages to achieve Credit Karma's goal.

In October 2025, after over 9 months of working together, we went live on the Credit Karma app and since have rapidly ramped and have only penetrated less than 1% of their monthly user base that we believe is eligible for the product. The opportunity is massive, and our primary focus is deepening integration of the Tinman AI platform across the various Credit Karma consumer touch points to better serve the full needs of its entire member base. Also through our Tinman AI platform, we continue to make great progress extending our platform to power local retail mortgage lenders, providing them with the infrastructure to build and scale their businesses on top of our technology.

We continue to scale NEO with their local loan officer teams across the United States experiencing rapid growth. Here, Better enables retail mortgage lenders to build their business on the Tinman platform with near zero customer acquisition cost on this channel. It's been incredible to see the NEO team grow their business from the $1.5 billion run rate they had when they joined to the $2.4 billion run rate they ended 2025 with on the Tinman AI platform. It's proven that the Tinman AI platform eliminates friction, giving originators the opportunity to scale responsibly with 28 new loan officer teams onboarded onto the platform in 2025.

Within 6 months of fully rolling out, NEO increased funded loans per mortgage adviser by 91%, per processor by 17% and per underwriter by nearly 50%. Retail mortgage teams around the country are taking notice of these enhancements and are leaving their existing platforms to join the Better platform and to embark on our shared journey of making retail home lending cheaper, faster, easier and just [ plain ] better.

Next, our top 5 U.S. nonbank mortgage loan originator partner went live this February with just 2% of its loan officers on the Tinman AI platform. And in the coming months, we are working towards expanding to all 3,000-plus loan officers. Early reports indicate superior loan officer experience for users of Tinman versus the prior implementation on their legacy software stack. As this rollout scales to their full loan officer base, we expect this partnership to be transformative for both organizations, adding a significant platform volume opportunity for Better while giving one of the largest mortgage originators in the country a competitive advantage in how they serve their customers.

In addition, Finance of America, which is an industry-leading reverse mortgage lender with access to millions of customers who are typically home equity-rich but cash flow disadvantaged is in its early stages of ramping. Together, we are launching the first HELOC and HE loan product offerings to their customers powered by our Tinman AI. We have high hopes of being able to reach a population that better has traditionally not reached the senior market with our partnership with Finance of America and expect to see significant results from that partnership in the coming quarters ahead.

And finally, we announced a major milestone, the launch of the first conversational credit decision engine for mortgages and home equity loans integrated directly into ChatGPT through our Tinman AI app. Loan officers, banks and fintechs can now receive decision-ready credit outputs in as little as 47 seconds, reducing origination time lines by an average of 21 days. Better is the only application authorized to display credit decisions within ChatGPT, powered by our proprietary MCP technology built on top of Tinman. Tinman can instantly underwrite approximately 95% of mortgage and home equity loan types, and any institution with a ChatGPT enterprise license can deploy it; no traditional aggregators, no markups. This opens a significant new distribution channel and a clear path to expanding into a direct-to-consumer channel over time.

As you might remember, OpenAI and ChatGPT have over 800 million users globally and over 80 million users in the United States with that number growing rapidly. We believe this is the third version of the Internet, and we are first to market with a clear differentiated offering from the other folks that have launched apps on OpenAI and ChatGPT and with the ability to not provide a marketplace or provide a solution, which then requires consumers to leave the platform, but actually to provide a solution that enables consumers to fulfill the entire transaction directly within their ChatGPT interface. Since our OpenAI announcement, we have seen a massive immediate response from across the financial services industry.

Within days of releasing a short demonstration video last week, we've received inbound interest from over 40 financial institutions, mortgage companies, banks, fintechs, all reaching out at the most senior levels to request a demo and work with us on deploying our ChatGPT application. As an example, a bank CEO in the South reached out after seeing the announcement. They want to grow their mortgage business, but not the way they tried before through hiring large teams, building out fixed infrastructure and taking on the operational burden that comes with it.

What resonated with them was the simplicity of the ChatGPT app and the idea that any loan officer in any branch can instantly qualify a consumer for a mortgage through a conversational interface, minimal setup time, minimal training, maximum reach. This is exactly the problem we set out to solve. The mortgage industry has long been trapped in a cyclical model, scaling up headcount in good markets and cutting in bad ones with fixed costs that punish originators when volumes decline.

Tinman fundamentally changes that dynamic. The infrastructure we have built and proven with our current partners can be deployed for any bank, fintech or local originator team. We are giving institutions the flexibility to grow their mortgage business without the operational burden that has historically made that growth so difficult to sustain. We have two strategies when it comes to go-to-market on the Tinman AI platform. The first is to own the future with partnerships like the ones we have done with Credit Karma and OpenAI, where we are developing new ways to reach tens of millions of consumers that are substantially easier and faster for consumers to use and leveraging our technology to create a customer experience and value proposition moat that no one else in the industry can match. The second is to bring the path forward, which is what we have done with NEO and Finance of America and the top 5 mortgage originator.

Better is the mechanism by which these local market experts and large existing mortgage originators with deep relationships can continue to serve both their customers and referral partners. With Better's partnership, NEO is becoming one of the fastest-growing retail lenders in the country. The people didn't change. The relationships didn't change, only the tech platform did.

I'll now touch on our financial highlights, and Loveen will provide greater detail shortly. In the fourth quarter of 2025, we generated $1.5 billion in funded loan volume and $44 million in revenue, representing year-over-year increases of 56% in loan volume and 77% in revenue, respectively. This growth spanned all three of our core product categories, refinance, purchase and HELOC. Our Tinman AI platform generated $646 million in volume in the fourth quarter, representing over 40% of total volume and surpassing our prior guidance of $600 million. This outperformance reflects the demand and growing confidence of our partners in our platform. While the fourth quarter is always seasonally softer, our growth year-over-year outperformed that of the industry average, which was relatively stagnant.

According to MBA data, in the fourth quarter, total residential funded loan volume increased by 4% year-on-year. compared to Better's funded loan volume, which grew 56% over the same period. For the full year 2025, we delivered $4.7 billion in funded loan volume and $165 million in revenue, up 32% and 52% year-over-year, respectively. We achieved this growth despite an approximately $1 billion headwind from the conclusion of our Ally partnership, a testament to the resilience of our model.

We remain on track to reach $1 billion in monthly volume by May 2026 and to reach adjusted EBITDA breakeven by the end of the third quarter 2026. To win in a commoditized market, you have to win on three things: customer acquisition cost, operational cost and cost of capital, what we call the three pillars of competitive advantage. On customer acquisition, our model inverts the traditional origination dynamic. Rather than paying for customers in an open market, our partnerships are structured so that customers are brought directly to us. Credit Karma's over 140 million members, NEO's 70 local branches and 140 mortgage advisers and our top 5 nonbank originator partnering with over 3,000 local mortgage advisers represent embedded distribution at scale, a structural CAC advantage that competitors find extraordinarily difficult to replicate and one that is not easy to sustain without a technological moat.

On operational costs, Tinman automates up to 80% of the repetitive loan production tasks and our Betsy tool resolves underwriting issues instantly by pulling loan facts, guidelines and drafting communications in seconds. The result is a platform that scales production through AI efficiency and growth without additional overhead.

Our cost to process, underwrite and close a loan, and this we're talking about mortgage loans and HELOCs combined together is about $800 a loan, which is far less than anyone else in the industry. We believe that the initial launch, our Home Token will allow us to book an extra $500 per funded loan in revenue. And as we scale that, we believe long term, we're going to be able to achieve significant gains in loan revenue as well as funding cost to the consumer and interest rate to the consumer, which we believe will translate into a significant competitive advantage and moat as a result of the efforts that we have put in.

On cost of capital, we continue to improve our warehouse terms while working to expand capacity to support partnership volume growth. In parallel, we are working towards a secured tokenized credit facility via stablecoin ecosystem that we estimate could lower funding costs by up to 100 basis points once implemented, a structural funding advantage that would be difficult for any traditional mortgage originator to match.

Over the past 3 years, we have built the foundation for this moment. I can tell you, honestly, the last time I felt this excited about Better's future was in March 2021. And we have line of sight once again into growing into the largest mortgage company in America. This is truly a turnaround that we have worked for years to bring to life and one that has been able to be built on the implementation of AI across our entire business and leveraging the Tinman platform that we started working on back in 2014. This is why we think that the moat that we have is more sustainable than the traditional AI native firm versus the traditional incumbent.

We built an end-to-end system that takes 8 different systems in the mortgage industry and pulls them all together into one system so that it's not just the rules that are captured, but all of the context around the human decisions on the data and the rules. And that learning data across $110 billion of loans is what allows us to continue to push forward and lower our cost to produce, improve our conversion rate and build for our partners that are building the future. And we believe that we can continue to do this because the competitive advantage of richer learning data only compounds over time, the more transactions and the more partners you bring into the ecosystem.

We are now firmly in our next phase of growth with momentum, scale and a clear path to adjusted EBITDA breakeven. Partnerships are expanding, adoption is rising, our platform is proven and our AI capabilities are best-in-class, and we are just getting started.

With that, I'll turn it over to Loveen to provide a detailed walk-through of our financials.

Thank you, Vishal. I'm pleased to join Better at such a pivotal moment. The company's differentiated platform positions it as a leader in AI-powered home finance. I look forward to partnering with Vishal and the team to drive disciplined execution, enhance financial performance and create value for shareholders. As Vishal outlined, we're in the midst of a meaningful strategic transformation, shifting from a direct-to-consumer originator to an AI-native platform powering the broader mortgage ecosystem. From a financial perspective, this transition is significant.

Enterprise partnerships of this scale carry longer ramp time lines, but they also carry a far greater volume potential and a far better marginal economics than our legacy D2C model. What gives me confidence is that the financial trajectory is already beginning to reflect this shift. Our platform partnerships are growing rapidly and contributing an increasingly meaningful share of our overall business. To put that evolution in concrete terms, in 2024, our total funded volume was $3.6 billion with 0% contribution from Tinman's AI platform partnerships. In 2025, we grew total funded loan volume to $4.7 billion with 35% coming from our Tinman AI platform.

Looking ahead to 2026, we see a clear path to over 60% of our loan volume coming from our Tinman AI platform business. This is a fundamental reshaping of our revenue mix and a reflection of how we're executing on this transition. Let me now review our fourth quarter and full year 2025 financials. Better continues to generate opportunities independent of the broader economic and mortgage market conditions. With a large addressable market and less than 1% share today, we have demonstrated the ability to grow regardless of macro conditions.

Starting with fourth quarter of 2025, compared to Q4 2024, funded loan volume grew 56% to approximately $1.5 billion. Revenue increased 77% to approximately $44 million. This growth was primarily driven by funding more loans through our Tinman AI platform partnerships. Looking at loan volume by product, refinance grew to 8%, purchase increased 22% and home equity rose 18%. By channel, 44% came through Tinman AI platform partners and 56% through direct-to-consumer. By product mix, 49% was purchase, 37% was refinance and 14% was home equity. For full year 2025, compared to full year 2024, funded loan volume grew 32% to approximately $4.7 billion. Revenue increased 52% to approximately $165 million. These results were driven by the launch of our Tinman AI partnerships and continued growth in our direct-to-consumer business. By product, refinance increased 119%, home equity grew 78% and purchase rose 14%. By channel, 36% came through Tinman AI platform partners, 62% through direct-to-consumer and the remaining 2% from our former Ally partnership. By product mix, 61% was purchase, 21% was refinance and 18% was home equity.

Turning to cost efficiency. In Q4, the total net revenue grew 77% year-over-year, while expenses remained approximately flat. This demonstrates clear operating leverage. We are scaling the revenue at lower marginal costs driven by efficiencies from Tinman AI platform. We continue to streamline overhead while ensuring sufficient resources to support new partnerships. We expect these partnerships to contribute meaningful growth through 2026 and beyond. Unit economics in our direct-to-consumer channel continue to improve. We have integrated AI across every part of our sales and operations workflow. Per loan contribution margin improved 28% quarter-over-quarter from approximately $1,800 to approximately $2,300 per loan.

We continue to expect reducing origination costs through higher conversion, lower customer acquisition costs and improved labor efficiency. In the fourth quarter, our adjusted EBITDA loss was approximately $24 million. That compares to $28 million loss in Q4 of last year and a $25 million loss in the prior sequential quarter. While we aim to reduce losses further on a sequential basis, we're constantly evaluating expense discipline versus investing in growth opportunities. The continued ramp of our business with positive marginal economics is accelerating our path to adjusted EBITDA breakeven. We believe we are at an important transition point, moving from a primarily direct-to-consumer fintech to a true AI platform for the mortgage industry. This gives us confidence in our expectation to achieve adjusted EBITDA breakeven by the end of Q3 2026.

Now a brief update on our balance sheet and capital positioning. We ended Q4 2025 with $227 million in cash, restricted cash, short-term investments and assets held for sale. We maintain strong relationships with our financing counterparties with three warehouse facilities totaling $575 million in capacity as of December 31, 2025. We appreciate our warehouse lenders' continued support as we deploy Tinman AI across the mortgage ecosystem.

Turning to our outlook. For our total loan volume, we expect $1.4 billion to $1.55 billion in Q1 2026, of which the midpoint is a 70% year-over-year growth from Q1 '25. Based on how our partners are ramping, we continue to believe that we will reach a $1 billion total monthly loan volume by May 2026. We expect to achieve adjusted EBITDA breakeven by the end of Q3 2026. This will be driven by volume growth across both our Tinman AI platform and direct-to-consumer channels, per loan contribution margin improvement, pricing gains and corporate cost reductions.

I would note that these growth opportunities have varying expansion time lines, so progress towards breakeven may not be linear.

With that, I'll turn it back to the operator for Q&A.

[Operator Instructions] Your first question comes from the line of Ramsey El-Assal Ramsey with Cantor Fitzgerald.

I wanted to ask about guidance. Your guide assumes that the Q1 loan volume is roughly flat, I think, at the midpoint versus Q4. Obviously, you have a lot of exciting things going on in the company. Just wondering if you could walk us through the drivers. The partnership volume grew nicely versus Q4 quarter-to-date. Does that mean you're expecting flatter growth on the direct side of things? Or what are the drivers should we consider?

Eric, it's Loveen. Thanks for the question. So it's flat because of seasonality. So if you go to Page 17 of our investor deck, we made that point and we've shown the last 6 quarters. So if you look at Q4 '24 to Q1 '25, it was down, right? And this year, from Q4 '25 to our guidance of Q1 '26, it's flat or slightly up. That just shows the kind of growth in the platform.

Got it. Okay. And a quick follow-up for me. I wanted to ask about profitability. Your current target, obviously, is to reach adjusted EBITDA profitability by the end of Q3 this year. How should we think about -- how are your thoughts evolving on medium-term and longer-term profitability, especially kind of in the context of this accelerating shift towards the partnership model? How should we think about your profit profile going forward?

Yes, absolutely. Look, I just started a month back. The first task is to get to profitability by Q3 2026, right? After that, we'll evaluate our growth opportunities along with incremental positive contribution margin, right? So when we evaluate new partnerships, we'll be thinking about a contribution margin in the range of 10% to 15% to as high as 25% to 30%. And we'll be kind of looking at that range as we kind of think about our growth opportunities.

I think there's three different buckets of the product. The first bucket of the product is what we do on D2C. And the second bucket of the product is what we do on Tinman AI platform, where we're closing the loans in our own name. And that's what we're doing with NEO. That's what we were doing with Credit Karma. That's what we're doing with others. And then the third is what's the margin on the business where the lender is closing in their name. That's what we're doing with Finance of America. That's what we're doing with the top 5 mortgage lender, with the top 3 fintech. All of those, those lenders are closing in their name, and we're giving them the platform to do it. It's their salespeople are processors, underwriters and the closers in our software. And so each of those has a different margin profile and a different revenue per loan profile, right, depending on the amount of work that we are doing in that.

Like D2C, of course, we're doing everything from customer acquisition to sales to processing, underwriting, closing and investor marketplace. In -- but we're doing everything else. And then in the pure like processing, underwriting, closing and capital markets, sometimes we're doing cap markets, sometimes we're not. And so it just depends on that, what the revenue per loan is going to be and what the margin is going to be. As the revenue per loan kind of comes down, the margin actually expands because it becomes more and more where they're just using the platform. So the platform alone business can be 60% margin. The D2C business, as you can see from a contribution margin perspective, is a 20% plus margin business on a contribution margin basis. So we're going to get to know that and define that. We feel very confident in the guidance we're giving and particularly the growth that we're manifesting. But I think at those types of growth rates, you can't exactly know what people are going to buy. And we're in the transformation phase of the business. So we'll know more over the coming couple of quarters.

Your next question comes from the line of Kartik Mehta with Northcoast Research.

Vishal, the partnership metrics suggest some massive top-of-funnel demand. And I'm wondering what kind of metrics you're seeing from preapprovals to a funded loan and how kind of that underpins getting to the $1 billion target?

Yes. So Kartik, I think if you think about it in the context of our D2C business that we've previously disclosed, that ends up being around 5%. So if the partner volume starts coming in on a cohort basis, let's assume I get $1 billion of pre-approvals, right? I end up funding about 5% of them. So let's say -- and that funding can take place over 3, 4, 5, 6 months as it bakes because some people don't like the exact thing, they're not fully ready. They come back, they need to get their spouse to agree. All these different things that happen with this fairly significant life stake financing transaction for consumers.

Remember, on average, 32% of their income is going towards us. So it's a major transaction. And there's a bunch of things that go back and forth between when we approve them to when we are able to actually realize the funding event for that. And -- but on a cohort basis, it bakes to 5%. Now in some partners, it ends up being higher because those partners have better brand or deeper matching or deeper integration. And in other partners, it ends up being a little lower. And so we're going to see that play itself out.

And Vishal, where are you in the process from the stablecoin ecosystem use for funding? Obviously, you talked about that, lowering the funding costs and it seems very interesting. So I'm just wondering where you are in that process?

I think we're 6 months away from when it starts to hit the bottom line.

Your next question comes from the line of Brendan McCarthy with Sidoti.

Welcome, Loveen. I just wanted to start on the Credit Karma partnership. At this point, does that span all of your mortgage products? Or is it strictly geared towards refi?

Right now, we have started with refi, and we believe we will then launch HELOC and then from there, purchase.

Understood. That's helpful. And I think looking at the addressable market there, $140 million, obviously, I think it's a lot larger than original expectations. Maybe just over the long term, what do you think is a reasonable penetration rate to drive volume?

In the long term, we expect Credit Karma Home Loans, powered by Better to be the single largest originator of mortgages in this country.

Understood. That's great. Transitioning to the expectation for breakeven adjusted EBITDA at the end of Q3. I assume that will kind of coincide with the $1 billion in monthly funded loan volume. Can you break down your expectations there for volume contribution from D2C, NEO and then Credit Karma as well?

Yes. So as I said in my script, the Tinman AI platform contribution was 0% in 2024. It was about 35% in 2025, and we're expecting about 60% of total volume from that platform, which includes Credit Karma, NEO and other partnerships.

Understood. And turning to fourth quarter results, just looking at the gain on sale margin, I think it declined sequentially just by a little bit here. I assume was that mostly just given to the higher refinance D2C growth?

Yes.

And then last question for me. I saw in the slide deck, it sounds like there's a top three personal lending fintech in the pipeline. I think you mentioned it's currently in the pilot phase. Any detail you can give on that? Is that going to be geared toward more the Tinman mortgage software partnership side? Or do you think it will be similar to NEO or Credit Karma where you'll be doing the originating?

We think in the beginning, it's going to be similar to Credit Karma where we're doing the originating. And then this fintech also has a pretty prominent bank, and so they may choose to onboard to their balance sheet. I think I've said this publicly, the bank capital regulation requirements are going to dramatically change the mortgage landscape. The number of calls we have had from banks post the launch of the ChatGPT app, we have over 45 financial institutions in the United States and outside the United States that have interest in utilizing that platform. I thought it was going to be mortgage brokers. I thought it was going to be retail mortgage lenders, the number of banks that have called because in anticipation of what is happening. I'll double-click into this.

So if you are a midsized bank today and you've got disintermediation from stablecoins, right? You can't just go and get Internet deposits cheaply anymore, right? You've got to go -- your deposit cost of capital is creeping up. You've got to go find assets. And when you've got to go find assets that generate a higher yield, you can't just sit there and put it in treasuries anymore and short duration instruments because then if you're doing that, your cost structure just doesn't allow you to compete with stablecoin.

So what is the thing that you can do with economic growth sort of [indiscernible] with the American consumer a little bit stretched, are you going to go long credit cards? Are you going to go long personal loans? Are you going to go long those assets that people have been doing for the past 5 years? Or now with mortgage reg reform and particularly bank capital levels, are you going to go long credit risk? Or are you going to go long duration? And banks are built to go long duration. And so we're going to see the bank bid for mortgage explode. The bank bid for HELOCs explode. And we are uniquely positioned to accommodate the bank bid for that vis-a-vis our competitors in HELOC land.

Our competitors in HELOC land and have built a one-size fits all, and they are proud of it like box for securitization. We tell any bank, you bring your guidelines, you bring your regional preferences, you bring any of those, and we will accommodate those instantly and to as detailed as you want. And so I think you're going to see a lot of that and a lot more partnerships in that regard. There are going to be -- and also the other thing that's happening is these fintechs are all signing up for bank charters, and they all see it, too. So I think you're going to see sort of like the lines blur between fintech and fintech bank. But I thought it might be worthwhile to just share a little bit of context around that, particularly in light of today's announcement around bank capital rules.

Your next question comes from the line of Eric Hagen with BTIG.

Really good conversation here. Really appreciated your thoughts just now on the bank capital. You noted the cost to underwrite are substantially lower than the industry average. They're around $800, if I heard you correctly. I mean why don't you think those savings are being passed on to borrowers? Like what's the gating factor, which is sort of like bottlenecking the ability to pass along those savings in your opinion? And then...

We are passing the savings on our side to the borrowers. Yes, we are passing on the savings on our side to the borrowers while trying to continue to improve our contribution margin on our path to profitability because we want to be able to keep passing those savings on to borrowers for many, many years to come. So I think our rates are 30 basis points cheaper on average than the average mortgage rate. Our rates are over 50 basis points cheaper than Rocket and loanDepot. And I think the customer in a purchase market is really guided by the local realtor and the local LO. And so I think that -- you haven't seen that. But as refi comes back, Eric, you remember from 2016 to 2021, we went from $500 million of volume to $58 billion of volume as refi was -- about where rates like in 2019, 2020, 2021, we went from $4.5 billion of volume to $58 billion of volume.

And as I think rates come down and refi comes back, there's some serious scale possibility because in refi, we have a clear winning proposition. The American consumer may not be able to differentiate between 5 and 5/8, and 5 and 7/8, you walk down the street and you ask somebody, "Hey, what's 7 divided by 8." We don't teach math like that in American schools anymore. But you tell them, "Hey, do you want to save $422 a month versus $375 a month?" Well, that math is easy to do. And so I think that's sort of where you're going to see that savings really manifest in for the consumer.

Now on the B2B side, that savings is direct and visible. And the average bank cost to produce is about $14,500. And so when we go to these banks and we say, we'll do it for you, if you want flavor A for $4,000 a lone, flavor B for $5,000 a lone, flavor C for $6,000 a lone, that's a very disruptive sale. Now it takes time because that's a CEO, CFO sale because if you look at AI implementation anywhere, if you're pitching that to a mid-level person in the bank, if you're pitching that to the head of origination or right, the head of sales to a bank for mortgage, that's pretty disruptive because what Tinman is doing and how Tinman is able to get to that is really lowering the amount of RoTE work that and RoTE calculation work that today exists in the mortgage industry. And 99% of the mortgage industry is still stare and compare underwriting. Call up any of my competitors, ask the loan officers how those loans are underwritten and they will tell you. And I think that that's just a fact.

Your next question comes from the line of Rohit Kulkarni with ROTH Capital.

A couple of questions on the Tinman AI platform as help us understand what the ramp looks like based on what you know right now, 40% of volume already in Q4. Where do you see that share go as the year progresses? And then based on a lot of these recent developments, like what are the gating factors for you to scale up that distribution for Tinman? Is there some technical integration, some regulatory compliance approvals, training of partners. Just walk us through what would it take for you to convert all the leads that you have on Tinman and then how that cycles into the overall proportion of funded volume?

Rohit, thanks for the question. I'll take the first, and then I'll hand it over to Vishal for the second one. So look, the trend is Tinman AI platform in 2024 was 0% of our revenue. Last year, on a full year basis in 2025, it's about 35% of our revenue. This year, we're kind of saying we expect it to be around 60% of our revenue. Now we're not giving you full year guidance on loan volumes, right? But if you can read the tea leaves and do the trends, our guidance for the first year -- first quarter loan volumes is about 77% growth. And if you can extrapolate that same out, right, not that I'm giving guidance here, right? And our share of the Tinman AI platform increasing from 35% to about 60%, you can see that subsection is growing really fast.

Right, I mean, our large institutional partnerships, where the companies are 10x to 100x our size, it's -- from first demo to term sheet signed is usually 3 months, from term sheet signed to platform launch is usually 2 months after that, from platform launch to pilot done is like 90 days from that and then post the pilot done to get full institutional buy-in and penetration of their customer base, it takes like 9 to 12 months because just we're cutting a lot of cost out. And it's the most complicated financial product sold to consumers. And so there's just a lot of wires to connect. Now the good thing is after it's connected, it's just one. There's just one system. And now with what we've done with ChatGPT, we're really trying to bring that sales cycle and connective cycle down because it's an interface that their internal people already know.

And so that dramatically cuts down that sort of 9-month time line from first demo to like full implementation, probably down to 6 months, down to 3 months if they want to move fast and they don't have any legacy stuff, which is why you're seeing a lot of people that are going to -- that are not in the mortgage business enter the mortgage business through us. For the ones that are already in the mortgage business with all of the massive incumbent infrastructure that they have, it takes them longer. And the bottleneck is we have -- the Biz Dev team with two people as of last quarter, and now there's like five people on the team. And we just want to make sure that the revenue is aligned with the cost.

So we don't like go and hire 100 go-to-market salespeople and then we're out there and then the revenues don't come. And we know that we've got to get the business to profitability and that like we have something that is a whole like one generation ahead of the incumbents, two generations ahead of the tech stack at the banks. And so the nation's largest bank is in the middle of its migration to incumbents. Okay, right? The system that lets one person use the system once at a time. So like they're like in the migration to SharePoint. So I think we have -- we have a lead and -- but like our goal should be like to monetize that lead, but we want to do it in a way that aligns expenses and revenue together.

Okay. Great. And specifically on Credit Karma, perhaps talk about how Credit Karma is helping amplify the benefits and perhaps improve the distribution visibility in their member base. What is the dual handshake, if any, that once you are deeply embedded in a fintech partner like Credit Karma, how does that change the way they promote or provide higher visibility to your offering?

I think Credit Karma is a very advanced company. They have -- again, if you read any of their public materials, they have a system called Lightbox. And we have integrated ourselves into Lightbox. And now the system is determining those offers. Right now, we're at less than 1% penetration of their member base as of March 13. And so we're very excited about the future.

Okay. Great. And maybe one last one from my standpoint is how does -- perhaps you already covered this, the contribution margin or the marginal margin on D2C versus kind of per dollar earned in -- through partnerships. How does that compare right now? And over time, where do you see that evolve? And is that kind of an implied assumption within your EBITDA breakeven in second half?

I think we're not -- because our partnership volume is lumpy, I think we are -- for competitive reasons, we aren't out there sharing that level of granular detail just yet. But you're correct in that like the partner profit, contribution profit per loan varies, again, as I covered earlier, like depending on how and what system resources they use and personnel resources they use. But yes, like our adjusted EBITDA breakeven is based on us achieving the penetration rates on the partners we have signed up.

Your next question comes from the line of Ryan Tomasello with KBW.

Just another question on the Tinman AI platform. There's obviously a range of different models out there in the market that are also providing this broad tech infrastructure to support the origination and funding in the mortgage category. That includes some players building that on blockchain rails. Vishal, you mentioned some of the legacy LOS providers and POS incumbents. So I guess, can you just talk about broadly what you think differentiates better in this third-party infrastructure category from those peers? And then over time, do you think that this platform could be extensible into other categories of consumer credit outside of the mortgage market and HELOC market?

Yes. So I think we -- Tinman is the only platform in its class that allows the loans to be sold to a wide network of investors who can bring their own guidelines and their own pricing into the platform. I think Figure had a platform that allows people to integrate Figure, but then that guidelines for the product are the guidelines for the product. So they have a first lien product that's not a Fannie, Freddie, FHA, and VA eligible product and is a first lien HELOC, the rates are significantly higher than a conforming mortgage, and it's based on the same HELOC infrastructure that they have.

And then the HELOC infrastructure that they have is obviously done amazingly well, but it's got a lot of proprietary components that are not removable. I'll let you use any title company in America you want. I'll let you use any appraisal company in America you want. I'll let you use any home insurance company you want. If you've got an HOA, if you've got a complex appraisal, if you've got like jumbos you want to do, you want to do non-QM, you want to do bank statement loans, you want to do DSCR loans. You want to do any of those things and serve the maximum penetration within your customer base, you kind of have to like if you're -- remember, if you're a partner, you're signing up, I'm bank A, I have 100 customers.

Do I want -- and I'm selling mortgage mostly as an accommodation product today, like I want to serve the customer that has a deposit with me, right? Do I want to partner with a guy who's got a criteria that's built for securitization and on a particular group of things and that's got a 15% approval rate. Or do I want to serve the guy that's got like, we'll go down to 580 FICO FHA loans to lower-income consumers because that customer still has a deposit with the bank and the bank wants to serve that customer.

And I think that, that's the big difference between ours. Our model was built AI mortgage, AI HELOC and their model was built like securitization HELOC and then securitization mortgage. And I think -- so that's just a fundamental difference in the model. And I would say they are really focused on the blockchain, right, and on all of the things that go with that versus we're really focused on AI and customization, mass customization to the largest broadest set of potential partners leveraging AI. So I think that's -- and using blockchain when it makes sense to lower the cost of capital. So I think that's like -- but like I very much respect their team, and they've done an amazing job, right, in building a great platform and really reintroducing the home equity product back to the American consumer. So we're very happy to follow in their lead on the home equity product and continue to be the lead on mortgage innovation.

The other players, I mean, that's just super legacy tech stack, right? Many of them like are entirely still billing by the seat. We're billing by the outcome. Others are billing by our, like they're like we're billing by the outcome. It's just a fundamentally disruptive model. Now some of them are banding together and saying, "Hey, yes, you can buy like the three of us in a bundled offering." But that's like selling Microsoft Office Word and Windows 95 and like selling it together, right? But like you know what happened to copy paste back in your Windows 95 days, right? It's not the same. It's not updating real time. It's not a seamless workflow. It's not any of those things. The customer experience is broken.

And more importantly, you still need all the people, which is why if you think about the entire concept of digital mortgage, the mortgage industry and if you talk to any CEO on mortgage, they are like digital mortgage, it's 2015, it used to cost me $9,000 a loan to make a loan. And it's 2025, it cost me $11,700 to make a loan, like I've gone backwards since 2015, right, as a mortgage company CEO because of digital mortgage, because it's 8 different digital systems, 8 different like pieces of middleware, 8 different groups of consultants I've got to hire and employ all the people that I have to train to be experts in these 8 different systems who can't like do different things in different systems.

The whole -- that's the disruptive power of the AI Agentic architecture. You don't need to train people to do this. There's a machine just does it. And on our machine in Tinman, the people have been doing this stuff. And so we just -- when we want to move a role to Agentic, we just literally have the machine and the AI watch what the humans in that particular task have been doing. And I think there's still like some tasks that are going to require from a regulation standpoint, the need for someone to make the decision, a human to make the decision. And that's totally fine because then that human can make 100 of those decisions a day rather than making two of those decisions a day. So I think that's the future that we're really driving towards. And I think we're pretty unique in that regard.

Appreciate all that commentary, Vishal. And then just one more for me on the Sky stablecoin partnership. If you could just talk about or maybe quantify the cost of capital advantage that, that funding source provides versus your traditional facilities. And also how you see maybe that partnership potentially evolving beyond warehouse into more permanent financing. And then just bigger picture, Vishal, what value you envision DeFi unlocking for the mortgage market over time?

Okay. Wow, I could go on for hours about that. But like I'll try to make it super simple. So I think the initial funding cost advantage is 100 basis points, which is super meaningful, right? Like just right off the bat, I think we make $500 extra per loan, right, -- on a loan. Two, from there, we think fundamentally, mortgage is an underpenetrated asset class amongst stablecoin issuers. And I think as stablecoins become more pervasive, I think stablecoin issuers who are going out for broader yield are going to go and try to find DeFi mortgage assets to invest in. And we believe the mortgages that we make, 95% of which are guaranteed by some form of GSE or agency are the best from a sharp ratio perspective in terms of yield pickup relative to risk.

Like I joke that technically a Fannie Mae mortgage is better than a treasury because you have not only the government guarantee, but you actually have a house and a person. And so you've got three pieces of collateral. So I think that there's just the spread premium for the prepayment risk is not something that is something institutional investors care about, but it's not something as it tends to be delivered to consumers, is something that consumers care about. So I think that like that is going to be really, really interesting. And I think the long-term advantage that DeFi brings to the U.S. consumer mortgage market is 100 basis points of rate reduction. Right now, the premium to hold a fixed rate GSE mortgage over a 10-year treasury is about 200 basis points. And I think we can get that down to about 100 basis points over time.

Your next question comes from the line of Owen Rickert with Northland Capital Markets.

First for me, to go from $1.5 billion in volume to $3 billion in volume per quarter, what needs to happen?

We need to penetrate our existing partners more, and we need to continue to grow NEO and D2C, where it makes sense, where we make money on those D2C loans. But to go from $1.5 billion to $3 billion is just penetrate the existing partners we already have signed up and implemented with.

Okay. Great. And then for the 4 ramping partnerships, can you just rank those in terms of opportunity? We know Credit Karma is obviously #1, but how would you rank FOA, the top 5 nonbank originator and that bank partner?

I think it's Credit Karma Home Loans powered by Better. I think it's the top 5 nonbank originator, and then I think it's FOA and the top three leading fintech.

Okay. And then lastly from me, kind of expanding on that, beyond those four partners, I guess, do you have the bandwidth to get potential partners five, six and seven live in 2026? Or is 2026 more just about ramping those four?

No, I think you should see us launch one marquee partner like every quarter, and you should see us have a bunch of smaller partners launch every quarter.

That concludes our question-and-answer session. I would now like to turn the conference back over to Vishal Garg, Founder and CEO, for closing comments.

Thank you, everyone, for joining. Again, Q4 '25 is a transformational turnaround quarter for the business as we move from being a direct-to-consumer originator on Better.com to being a platform to power every originator in the mortgage industry. And we thank you for your interest, and thank you for being a participant and a partner in our journey to making that happen and in doing so, making home finance cheaper, faster and easier and just playing better for all Americans. Thank you.

Ladies and gentlemen, this does conclude today's conference call. Thank you for your participation, and you may now disconnect.

Ladies and gentlemen, thank you for joining us, and welcome to the Better Home & Finance Holding Company Third Quarter 2025 Results Call. [Operator Instructions] I will now hand the conference over to Tarek Afifi, Corporate Finance at Better.

Tarek, please go ahead.

Hello, everyone, and welcome to Better Home & Finance Holding Company's Third Quarter Earnings Conference Call. My name is Tarek Afifi on Better's Corporate Finance team. Joining me today is Vishal Garg, Founder and Chief Executive Officer of Better.

In addition to this conference call, please direct your attention to our third quarter earnings release, which is available on our Investor Relations website. Also available on our website is an investor presentation.

Certain statements we make today may constitute forward-looking statements within the meaning of federal securities laws that are based on current expectations and assumptions. These expectations and assumptions are subject to risks, uncertainties and other factors as discussed further in our SEC filings that could cause our actual results to differ materially from our historical results. We assume no responsibility to update forward-looking statements other than as required by law.

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 a replacement for and should be read together with our GAAP results. 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, in our quarterly report on Form 10-Q filed with the SEC.

Amounts described as of and for the quarter ended September 30, 2025, represent a preliminary estimate as of the date of this earnings release and may be revised upon our quarterly report on Form 10-Q with the SEC. More information as of and for the end of the quarter ended September 30, 2025, will be provided upon filing our quarterly report on Form 10-Q with the SEC.

I will now turn the call over to Vishal.

Thank you, Tarek, and welcome to our third quarter 2025 earnings call. This has been a pivotal quarter with significant developments for Better as the leading AI home finance company. We have rapidly evolved from a dominant direct-to-consumer business into a platform powering the entire home finance ecosystem, both for consumers directly and increasingly through our growing list of institutional partners. These partners include both local mortgage lenders and financial institutions, and we empower them with our Tinman AI platform to serve their customer needs better.

In summary, over the last couple of months, we announced 3 new partnerships, which we see as deeply validating and believe will meaningfully expand our market reach across the home finance landscape and drive profitability as we track to breakeven adjusted EBITDA by Q3 2026.

We're already pacing to fund $500 million in monthly volume as a result of the growth through these partnerships, and that momentum is accelerating rapidly. In the next 6 months, we are comfortable that this will double to at least $1 billion a month in funded loan volume. Our progress comes mostly from our soft launch during which we have marketed the Powered by Better solution to only a small fraction of our partners' customer bases and seen great success.

This partnership represents the most significant opportunity in Better's history. Excitingly, thanks to our strong unit economics and best-in-class experience powered by Betsy and Tinman, our pipeline of additional partners continues to expand rapidly. We expect to share further updates on these partnerships and additional ones in Q4. Our pipeline of Tinman AI platform clients and partners keeps expanding as the industry is seeing what our platform can deliver.

We are in late-stage conversations to land partners in some of the biggest, most strategic verticals in consumer finance. Examples include; 1 of the top home improvement lenders, 2 of the top servicers in the country, 1 of the top personal lenders and an additional midsized bank. These additional partnerships will add an additional 10 million American homeowners to whom we can algorithmically qualify and market mortgage and home equity products to.

All of these events validates our strategy of diversifying our distribution channels as our AI-driven platforms, Betsy and Tinman deliver the lowest unit cost in the industry while providing the best experience for both customers and partners. This gives us strong conviction that our peak volumes in this rate cycle should comfortably exceed those achieved in the last rate cycle when we originated approximately $60 billion in 1 year or almost $5 billion a month.

We have built a platform that is AI first. We are one of the few players, if not the only one in the U.S. with a single full-scale tech stack, all in one place, all in one flow and entirely API-able via our proprietary MCP server, the only one in the mortgage industry to Agentic AI, which allows us to deliver a better experience at lower cost, scale faster than anyone else and really continue to define the future of this $15 trillion industry.

Better is the network for the largest tangible asset class in the U.S., residential real estate. On one side of this network are the end consumers directly and on the other side are consumers using the Tinman AI platform, similar to that of merchants on platform networks like Stripe or Visa and Mastercard.

On the other side, our investor is seeking to buy cash flow-producing assets secured by U.S. residential real estate. We are the matching, processing and fulfillment engine in between the 2 sides of this network. Our engine is called Tinman, which uses machine learning to triangulate consumer attributes, property attributes and the unique criteria of over 40 institutional investors on the platform, including the GSEs, the FHA and the VA.

We have built a multisided matching engine, something that simply cannot exist outside of what we have built inside Tinman. To contrast, most fintechs operate on a single platform and distribute the product through securitization. With Better, the result for the consumer is a significantly higher approval rate and generally lower interest rates because Tinman matches consumer and property-specific attributes across a broad cross-section of the investors on our platform on a single loan-by-loan basis.

Further, despite Better being balance sheet light and not taking any credit or prepayment risk, the default rate of our mortgages is 1/3 that of the industry average on over $100 billion of originated volume over the past 9 years. So the proof is in the pudding. Our deep proprietary data moat has been instrumental in training our AI models and powering our platform.

Betsy, our generative AI home finance agent built on top of Tinman has learned from over 12 million recorded phone calls, 6 million approved customers, 600,000 funded loan documents and almost 5 billion pages of property and consumer data information, all in one place, all in one end-to-end platform with all of the things that were done by humans on those data all in one place and recorded through the platform.

We believe that this is something that does not exist in anywhere else in mortgage lending or even broadly in consumer finance. Today, we are at feature parity between Betsy and the bottom 80% of human loan officers. Betsy communicates across voice, chat, text and e-mail with consumers nearly instantly to compute various scenarios and learns how to better understand consumers' needs every day through every interaction.

What's more is Betsy can handle millions of consumer conversations at the same time, enabling infinite scalability without adding additional headcount as consumers learn to adopt and integrate their consumer finances and transact with an Agentic AI. Betsy is not just a voice agent or chatbot. Betsy can perform the functions of a human loan officer, processor, underwriter and closer.

Betsy is the user interface, helping consumers step-by-step through their homeownership journey, performing hundreds of thousands of consumer interactions per month and remarkably good at detecting fraud throughout the entire platform. Additionally, Betsy has mastered finding ways to get an approval with the lowest possible interest rate across our network of investors with the lowest post-closing defect rate in manufacturing a mortgage, approximately 19x lower than the industry average.

In fact, as of September, no human underwriter is allowed to decline a loan in our system without checking with Betsy first as to the alternatives that are available to restructure the loan so that the consumer can be approved and move forward in their homeownership journey. We believe this is a first across lending in the United States.

Since we've launched Betsy, our lead-to-lock conversion rate has increased by approximately 84% from 3.3% to 6.1%. This has been transformative to our platform in driving incremental volume and revenue through our platform and it's still very early days. As we scale Betsy at near 0 marginal cost, we expect to further improve our unit economics through cost efficiencies on a per loan basis.

During the quarter, Betsy performed approximately 700,000 customer interactions and our AI underwriting approved over 61% of locked loans with a clear path to 75% in the near future and 90% after that. And our [ loan officer ] productivity in terms of funds per month increased to over 3x the mortgage industry median. We have been heads down over the past few years, honing our technology and optimizing the business for efficiency.

With Tinman and Betsy, we remove the traditional constraints to growth in the mortgage industry, which is typically throttled by a lack of specialized licensed labor, whether it's loan officers, processors, appraisers or underwriters. We can now grow infinitely with AI and with a single unified tech stack at the core.

There's almost no better use case for AI to disrupt a market than the massive and antiquated mortgage market. The majority of the mortgage market still operates on what was built in the 1990s where 8 different separate systems were integrated through dated middleware, old-school FTP servers and disparate databases. What's more, this dominant platform, which has over 80% market share, only allows 1 person to work in the loan file at any time, a file that costs the mortgage industry more than twice as much as Better to make.

AI was designed to disrupt industries like this and yet fails in most cases due to the lack of a singular database architecture, causing huge latencies for any LLM to intermediate data and capture context quickly between disparate systems. Further, the lack of a unified interface prevents LLMs from being able to handle every single task required to fulfill a mortgage. Those limitations do not exist in Tinman.

Tinman shines as a brand-new modern tech stack with AI in action, delivering real tangible, measurable results in a multitrillion-dollar industry at a fraction of the cost. I often think back to when we were building our AI platform, one of the point solution's CEOs said to the then CEO of Fannie Mae, that he thought Better was trying to boil the ocean. And here we are, we have gotten the ocean hot, and it's starting to drive tangible results in a way that is groundbreaking for the industry.

With some macro green shoots in our favor and momentum in winning new partnerships, we believe we are in a position to scale rapidly, profitably and with AI, infinitely. When you look back at the last time rates declined, Better grew its volume by over 100x over a 5-year period and over 10x over a 2-year period in 2020 and 2021.

We are positioned to do it again this time more efficiently and much more profitably, and we believe we can achieve significant market share as this next cycle unfolds. Betsy and Tinman is our flywheel. That flywheel is turning. The opportunity is massive, and we are ready to monetize.

I'll now turn to our third quarter results. Starting with growth, we continue to propel opportunities independent of broader economic and mortgage market conditions. In the third quarter of 2025, on a year-over-year basis, we grew funded loan volume by 17% to approximately $1.2 billion and revenue by 51% to approximately $44 million, driven by funding more loans, both through our D2C channel and our Tinman AI platform.

By product, year-on-year funded loan volume growth during the quarter was driven by home equity volume increasing by 52% year-on-year, refinance loan volume increasing by 41% and purchase loan volume increasing by 5%. We have been rapidly growing our home equity business, taking share in a market that is coming back quickly as Americans are sitting on $35 trillion of home equity, the largest untapped asset class in the country.

We've grown to an approximately $1 billion-plus quarterly run rate of origination volume in Q3 2025 compared to approximately $100 million in Q3 2023, just 2 years ago when we launched. Our model does not require us, unlike many others, to take any credit prepayment or liquidity risk because we can sell HELOCs onto the investor marketplace we have built. We do not rely on securitization, and we are able to mimic what we have done in the mortgage space in HELOCs, allowing investors to buy and bid on loans at a loan-by-loan level, which is unique in the industry.

There are incumbents in the home equity space who have started to create their own version of our investor marketplace. But today, that marketplace only comprises a very small portion of their volume and revenue, whereas for us, the marketplace is 100% of volume and 100% of revenue in the HELOC space.

During the quarter, we broadened our already high approval rates for HELOC products by launching AI-driven HELOC underwriting for small business and self-employed borrowers, making approvals possible using bank statements only. This product opens the door for 36 million self-employed and small business owners who have traditionally been underserved by traditional underwriting methods in the mortgage and HELOC space. It's another example of how we are using AI to widen use cases and enable home finance for more American families to help them save more money.

Turning to cost efficiency. Total net revenue in Q3 grew 51% year-over-year, while expenses remained flat, demonstrating our ability to scale revenue at lower marginal costs. We continue to adjust our cost structure to be leaner in overhead while building adequate resources to support the ramp of our new partnerships, which we expect to drive transformative growth in 2026 and beyond, with the goal of reaching adjusted EBITDA profitability by the end of Q3 2026.

While our initial goal was to achieve further expense reductions this quarter, the team was focused on launching our 3 new transformational partnerships and engaging with additional partners in our pipeline. As a result, the intensity of our cost cutting was somewhat muted compared to the vigor we've had in prior quarters.

Looking ahead, as we get these partnerships up and running and to scale, we expect these anticipated cost savings to materialize in Q1 of 2026. With Tinman AI technology, we automate time and labor-intensive components of the mortgage process, consistently reducing our cost to originate to approximately half of the industry average.

I'll now turn to quarterly business developments. Unit economics in our direct-to-consumer channel continue to improve with revenue per fund increasing to $8,300, while the labor cost to fund continued to decrease to $2,500 and CAC per fund to $3,200, driven by the implementation of AI in every aspect of the sales and operations workflow, resulting in a net contribution margin of $1,772 per fund compared to $1,064 per fund last quarter, and approximately 64% increase quarter-on-quarter.

We have not seen these types of contribution margins since like 2021. We expect to continue to lower the cost to originate as we increase conversion, lower CAC and improve labor costs. And while our D2C business has always been at the forefront of pushing the envelope of what technology can do in the mortgage industry at its core, we are making great advancements in substantially broadening the use of Tinman through our partnerships.

We are very excited to have recently announced 3 new partnerships that we see as deeply validating the Tinman AI platform and believe will meaningfully expand our revenue and drive to profitability in the year ahead.

First, we partnered with a top 5 U.S. personal financial services platform who currently serves over 50 million customers. Under this agreement, our partner will offer home financing products to its end customers using the Tinman platform on a fully white label solution, and we will earn revenue on a per funded unit basis. Essentially, this is mortgage broker in a box for financial institutions across the American landscape.

We are focused on financial institutions that have large banks of customers, 10 million, 20 million, 50 million customers. And we believe that these financial institutions who have traditionally been limited, especially post the global financial crisis and being in the mortgage business or offering mortgages to their customer base will dive right in with our mortgage broker in a box, Tinman AI platform.

We brought this partner from being just a fintech to a fintech plus mortgage broker. There will be no upfront tax spend required by Better as our partner will programmatically feed customer data into Tinman. From there, Tinman will manifest offers delivered through our partners' app, which has tens of millions of monthly active users, all nearly instantly and updated daily. We expect transformative volume potential from this partnership as we scale into their vast customer base.

Second, we entered into an agreement with a top 5 U.S. non-bank mortgage loan originator. By migrating from the incumbent solutions that they've traditionally had for years, if not decades, onto Tinman, our partner's loan officers will dramatically scale their ability to surface eligible customers for HELOC and HELOANs within their customer base.

They'll also be able to mine their MSR book of over $300 billion to offer HELOCs and HELOAN to those customers on a programmatic basis in a way they've never been able to do with the incumbent HELOC solutions that are available to them today. The initial focus will be on home equity products, and we believe there's great potential over time to help the partner unlock new ways to monetize its extensive customer base in a way that has not been done before.

It's important to note that we are not just processing customers who raise their hand and ask for a home finance product. Rather, we are fully integrating Tinman into both of our partners' customer data loads and CRM systems. This allows us to algorithmically mine customer data attributes and property data attributes for these customers, match them to products and investors on the Tinman platform and use our AI to recommend the most applicable offer directly to the customer. We are also completely agnostic to the user interface, be it an iPhone app or a human loan officer in a branch. We serve all of them.

Third, we partner with Finance of America, an industry-leading reverse mortgage lender with access to millions of senior customers who are typically home equity rich but cash flow disadvantaged. Together, we are launching the first HELOC and HELOAN product offerings to their customers powered by our Tinman AI. What's more, leveraging Tinman, we have developed a senior second lien HELOC product that specifically addresses the debt-to-income challenges that limit traditional HELOC products for being offered to seniors and that you typically see securitized by the incumbent players.

Together, we believe these new partnerships demonstrate our evolution in powering the home finance ecosystem as a full suite platform and software, well beyond our direct-to-consumer origins. These partners are now live, and we look forward to sharing updates on our subsequent earnings calls as these partnerships ramp.

In addition to our newest partnerships, we continue to make great progress growing our existing Tinman AI platform with Neo powered by Better, local loan officer teams across the U.S. experiencing rapid growth. The Tinman AI platform approach to local retail mortgage loan officer teams is similar to how Amazon opened its D2C model to a third-party seller marketplace.

Similarly, Better is enabling retail mortgage lenders to build their business on the Tinman platform. And in doing so, we provide the compliance and licensing engine, loan origination system and capital markets marketplace. We have near 0 customer acquisition cost on this channel. And as partners fund loans on our platform, we earn a platform fee and a share of profits. We've grown this channel from 0 just 9 months ago to now approximately 40% of our total revenue.

The Tinman AI platform enables retail loan officer teams to originate more loans, serve more families and lower their cost of funds, dramatically increasing their profitability and throughput versus traditional platforms that these loan officer teams have been on for decades. These officers are transitioning from dated expensive tech stacks where origination of a loan could cost over twice as much as Tinman to Tinman where the cost is just a fraction of that, at approximately $3,000.

The savings goes straight to their bottom line, allowing them to reinvest in their customers, offer lower rates and close more deals within their local markets. Further, we've designed an optimization path to retain customers entering through the direct-to-consumer channel who we might otherwise lose to an outside local loan officer.

By identifying customers who would benefit from more personalized local support, we connect them early on with a partner loan officer instead of losing them to competitors later on in our direct-to-consumer flow. This approach significantly boosts conversion rates amongst these customers, and in turn, strengthens our overall unit economics.

During the third quarter, we funded approximately $483 million in funded loan volume for 1,148 families on the Tinman AI platform, an increase of 13%, respectively, compared with the prior quarter. And coming back to our multipronged distribution, we are also serving the customer by powering banks, credit unions and other large mortgage originators that are seeking to license our Tinman AI software to either enter or reenter the mortgage business.

As our Tinman AI platform approach is like Amazon's third-party marketplace model, you can think of our Tinman AI software channel as Amazon's AWS software model. A lot of banks and credit unions are taking a refreshed look at the mortgage space as the regulatory environment is becoming increasingly favorable. However, bank origination of mortgages has largely been unprofitable given their high cost to originate. This is where our Tinman AI software comes in.

Our Tinman AI software essentially provides mortgage in a box, enabling banks to not only use our software, but also gain access to underwriting resources and sales resources if they so desire. And while the broader software industry charges clients on a per seat basis, we have a disruptive pricing model of charging on a per funded loan basis or outcome-as-a-service, which is very similar to what a lot of the leading AI companies in Silicon Valley are doing.

Over time, we expect this channel to be the most profitable of our 3 channels with SaaS plus level margins since most of the costs associated with this initiative have already been spent on developing Tinman internally for our direct-to-consumer business. Our existing bank partner on the Tinman AI software platform is ramping as we power its entire mortgage origination business from click to close across multiple products and across multiple channels. And we expect revenue from this partnership starting in Q4 2025 with SaaS level margins.

Our overall partnership pipeline is robust, and we are focused on aligning with companies that are leaders in their respective verticals, those with large customer bases and where the Tinman AI platform clearly outperforms legacy systems. Our strategy is simple yet powerful, capture a leading player in each vertical, empower them to scale their mortgage business and home equity business with Tinman and then expand outward across the ecosystem as others follow suit, land and expand.

Verticals that we are interested in include fintechs, BNPL providers, traditional mortgage lenders and servicers. Each of these verticals represent hundreds of billions of dollars in annual mortgage originations. So, by first securing a partner who is a leader in their vertical, we establish credibility, create momentum and open the door to broader adoption across that vertical.

Looking ahead, the opportunity has never been more exciting. We continue to make great progress towards our goals of driving increased volume and revenue, balanced with ongoing expense management and improved efficiency. We remain focused on enhancing our go-to-market strategy with growth being our North Star alongside continued expense management and channel diversification, all with the goal of reaching breakeven on an adjusted EBITDA basis by the end of Q3 2026.

Our path to adjusted EBITDA profitability will be multifaceted, driven by: volume growth in both our direct-to-consumer and Tinman AI platform channels, unit economics or per loan contribution margin continuing to improve as we further lean into AI efficiencies, the scaling of higher-margin partnership channels including Tinman AI platform and Tinman AI software, pricing improvements and continued corporate cost reductions.

While our unit economics are already profitable at the contribution margin level, increasing volume will allow us to offset additional corporate expense. We note that these growth opportunities come with varying levels of expansion and profitability profiles and will change based on the broader macroeconomic trajectory. As a result, our path to adjusted EBITDA breakeven is unlikely to be linear on a quarterly basis, and we do not anticipate the same level of burn reduction each and every quarter.

During the third quarter, we had an adjusted EBITDA loss of approximately $25 million, down from $27 million last quarter and $39 million 1 year ago. In particular, for the 3 large partnerships we signed, we had a significant amount of resources in sales, operations and technology dedicated to launching those partners that were not revenue generative, but will create significant growth in the years ahead. As these partnerships launch and start to generate revenue and contribution profit, we expect burn to come down more dramatically in the coming quarters ahead in 2026.

Now to touch briefly on our balance sheet and capital positioning. We ended the third quarter of 2025 with $226 million of cash, restricted cash, short-term investments and assets held for sale. In addition, we continue to maintain strong relationships with our 3 financing counterparties, which provided a total capacity of $575 million as of September 30, 2025. We expect that our recently announced partnerships will require us to increase those warehouse lines meaningfully to accommodate the expected funding demand.

On capital positioning, we rightsized the capital structure earlier this year, retiring approximately $530 million of convertible notes for $110 million cash payment and $140 million note, generating $211 million of positive equity.

As announced in our 8-K, our CFO, Kevin Ryan, will be concluding his time with us. We are so grateful for everything Kevin has done for this company; taking us public, rightsizing our capital structure and building out our finance and accounting function. We wish him the very best in his new endeavor and are excited about the strong candidates in consideration for the CFO role. We hope to share the outcome of our new CFO search with you soon.

In the U.K., we were pleased that Birmingham Bank grew its loan book by 44% in the third quarter sequentially versus the second quarter of 2025 as we have implemented our technology stack into the bank, and in doing so, enabled the bank to become the fastest-growing specialist mortgage lender in the U.K. With respect to our non-core U.K. assets, we continue to exit those positions and expect these divestitures to continue to benefit our adjusted EBITDA through the remainder of 2025.

Turning to our outlook. The Tinman AI platform loan volume continues to grow rapidly, and we expect over $600 million of AI platform originations in Q4, which would be growth of over 24% versus Q3. For the full year 2025, we expect total funded loan volume to increase year-over-year, driven by tailwinds from growth initiatives, including Tinman AI platform, offset by continued macro pressure and the loss of our Ally business, a roughly $1 billion headwind.

We expect further improvements to adjusted EBITDA losses for full year 2025 versus full year 2024 through a combination of AI-driven improvements in conversion rates, efficiency gains and continued corporate cost reductions. In the medium term, while we expect D2C to continue to grow nicely, we expect it to become a smaller part of the total revenue mix as our partnership channels scale faster. We spent the past 3 years building for this moment. Our platform is proven, the housing cycle is turning, our AI is scaling and our partnerships are just beginning to ramp.

About a year ago, we met the Neo Home Loans team, and I saw firsthand the experience they were able to deliver in a branch or over a Zoom call, and I thought to myself, how can we make this accessible to everyone? How can we take this 4 seasons experience that the Neo team delivers and deliver it at a 4 points price to the average consumer? That got us thinking. At the same time, we had launched Betsy, the first voice-based AI loan assistance, and we've been able to do amazing things with Betsy. Today, we believe Betsy is better than 80% of the typical loan officers operating today.

I'm so excited to demo our AI mortgage adviser today, which is able to replicate the experience of being in a branch or on a Zoom call with someone with 10, 20, 30 years of experience with a deep knowledge base, someone who's done billions of dollars of loans and one who can walk you through every aspect of the process that is life's biggest financial transaction, one American families are still fundamentally insecure and unknowledgeable about. We'll be launching the AI mortgage adviser in a pre-release, and you can sign up to join us at better.com/tinman. Please take a look and let us know what you think.

[Presentation]

[Operator Instructions] Your first question comes from the line of Owen Rickert with Northland.

I guess, quickly, can you just dive a bit deeper into the 3 recent partnership announcements and how you expect each of these to ramp as we head into 2026?

Sure. So, with respect to the large financial services platform, we expect that to ramp over time, over the next 6 months, specifically as we increase the penetration of their users in their app that see the offers from us and the number of users every day that -- they drop into Tinman to surface offers for. And those offers will be sent via stories in their app, notifications, text messages, things like that.

And so, we're just going to increase those. And we've created a specific pod for this partner because it's such a large partner, and we need to [ tap ] into that pod. And so while we expect the overall size of the partnership to manifest itself into multiple billions of dollars a month, it's going to take a bit of time for us to also ramp up and see what labor is going to be required, what percentage of that partner's customers are comfortable talking to an AI, what percentage of that partner's customers need to talk to a person. So, we're working all of that out.

With respect to the other partnerships, the large mortgage originator, we're going to start first with their direct-to-consumer team, then we're going to start rolling it out to the team that does MSR and MSR recapture. And then from there, we're going to start rolling it out to their loan officer teams all around the country to market HELOCs and HELOANs to. And -- so, there's going to be a ramp in that regard as well over the next 6 months or so.

And then, with Finance of America, we are launching the HELOCs and HELOANs first to their customer base, then to their partner originators and then across to their wholesale channel. And so, I think that is also going to take another 3 to 6 months to fully ramp up as well as the second -- the reverse second lien HELOC product, which we are rolling out in beta right now, which we're going to then ramp up across their entire network.

Got it. And then secondly, you did hit on this pretty early on in the prepared remarks, but how would you characterize the future partnership pipeline right now? And what does that look like today? And maybe how is this pipeline -- how has it evolved over the last few months?

I think as our partners are able to see how fast we're able to implement some of the earlier partners that we have now launched, the quality of the user experience, the ability to get approved for a mortgage programmatically, the ability to take something that traditionally has been very passive and sold passively by these partners and then have that be done in an active algorithmic way, the partner pipeline has really, quite frankly, exploded. And -- so, we are seeing a lot of demand.

The other thing, just from a macro perspective, the largest incumbent solution has been forcing -- has been going through an SDK change and has been forcing re-integrations with all of its partners for its clients. And so, it's been an interesting moment where a lot of people are very, very frustrated with the incumbent solutions that are out there and are looking for something new. And so, I think it's sort of like luck is when preparedness meets opportunity. And I think we're pretty thankful to be in the position that we're in now.

Your next question comes from the line of Brendan McCarthy with Sidoti.

Really appreciate the demo there with Ryan, I thought that was great. Just wanted to start off circling back to the new partnerships, particularly the one with the top 5 U.S. personal financial services platform. Can you give us detail on what the ultimate volume opportunity looks like there? 50 million customers is obviously a huge number. Just curious as to what you think the addressable market is in terms of volume.

Yes. So, I mean, if you go to ChatGPT and you type in what is the mortgage penetration rate for a financial institution in the United States with 50 million customers, it will tell you the -- it ranges from 10 basis points of that customer base to 15 basis points of that customer base. So, let's use like a low average, 12 basis points. You multiply 12 basis points by $50 million, that gives you 60,000 originations a year, 60,000 originations times an average balance of like $400,000 gives you about $24 billion.

So, I don't know exactly what the number is. I'm not committing to that number, but that's sort of -- if we were able to just do it in an average passive manner at some branch, what we think we can achieve could be multiples of that if we're able to sort of algorithmically mine and surface offers directly to consumers in their mobile app.

Understood. That's very helpful. And next question, just looking at the guidance, really implying strong growth there, I think, from -- I think you said the $500 million monthly loan volume run rate to about $1 billion, just really a step-up there. What's really underpinning that outlook? Is it just strictly the partnerships? Is the growth in D2C? Is there any interest rate assumptions there? Just curious as to kind of what's underpinning that.

No, we're assuming interest rates stay the same. And yes, I mean, as you can see in D2C, we have been focused on making more money per loan in D2C rather than growing volume, though volume has grown pretty substantially, especially if you take out on a quarter -- on a year-on-year basis, if you take out the Ally volume that we had last year, organic growth has been over 50%. And so, when you layer that on, if there's a rate cut, I think D2C is going to fly. But other than that, like we're just assuming that the rates stay the same. And so, the numbers I've given you and I've indicated assume the interest rate environment doesn't change.

Your next question comes from the line of Kartik Mehta with Northcoast.

In the press release, you indicated that you anticipate about $1 billion of loan volume in the next -- at the end of 6 months because of these partnerships. Does that assume that each of these partners will be fully ramped? Or are you anticipating the ramp to take longer? So really, the $1 billion could be a lot more once the partnerships get fully integrated?

I think it could be a lot more than once they get fully integrated.

And then just the per funded contribution margins increased significantly. The one volatility is in the CAC. So, I'm just -- what's your anticipation for CAC as we move through 2025 and then 2026? I'm assuming they'll start trending lower as the partnerships become a bigger and bigger part of the loan volume. But wanted to get your perspective on that.

Yes. I mean with the partners, there's no CAC, right? There's no upfront CAC. The D2C CAC remains quite high. Purchase, which remains challenged in this market environment, you're spending money this quarter to book loans in 6 months, 12 months, 18 months when the consumer actually buys the house and books the loan. I think one thing that may be underappreciated about Better is, over the past 3 years, we've given out over 1 million preapprovals to consumers. And those consumers have not been able to find a house, or it's been too expensive for them to find a house.

And so, that CAC that you see there is elevated because for all the consumers that are not able to find a house that they want to buy, basically, we eat that CAC in that specific quarter. But then when that consumer finds a house they want to buy, then when they come through, then it shows as lower CAC. And so, the mortgage industry CAC, customer acquisition cost problem is even further compounded by the long gestation cycle of consumers on the Internet and when they get preapproved and when they actually find a house.

So, we do expect as rates -- if rates come down, that the CAC will come down materially across the board for purchase or for refi. I mean just to give you some context, in the last rate cycle, when rates were coming down, our CAC on refi was $1,000 a loan. And so, there's a lot of positive convexity in the CAC as consumers -- as the rate environment changes and consumers' propensity to get preapproved and then actually fund increases.

Your next question comes from the line of Bose George with KBW.

This is actually Frankie on for Bose. I want to start with, can you just walk through the ways in which AI efficiencies can increase revenue per funded loan. On Slide 16, you noted that this will be driven through enhanced sales and operational performance. So, can you just touch on that?

Yes. So, I think what you'll see is our revenue per loan is continuing to grow up, right? And I think the reason for that is Betsy is able to supplant the loan officer whenever the loan officer is not able to either pick up the phone, answer a question, turn around a new preapproval based on data that the consumer has provided. Sunday afternoon, 4:00, they want to put in an offer that they saw. Betsy is there for them in a way that traditionally, your human loan officer isn't able to be.

And so that's enabled us to, one, make our competitive pricing slightly less competitive and increase the gain on sale. Number two, as our volumes are going up and it allows us to not have to staff up with as many people. I think as you can see, like on a year-on-year basis, volume and revenue went up substantially over 50% and expenses actually stayed the same, and therefore, the burn came down substantially by like about 35%, 40%.

And so, that's sort of how Betsy is allowing us. It's allowing us to be more responsive, which means lower discounts, superior service, really build a service offering for consumers. And then, on the flip side, not have to hire as many people as we scale volume and automate the processes like processing loans, underwriting loans, closing loans that traditionally have been done by people.

Great. That's very helpful. And then can you just help us understand what types of incumbent solutions you're replacing in your partnerships? Is it both the LOS system and POS system?

Yes. So, we have integrated with a number of POS systems that are out there where, let's say, if our client wants to keep the POS that they're using today, that's fine with us. We'll take all of the other stuff. We generally do replace the incumbent LOS. And in many cases, we replace the POS, the LOS, the pricing engine, the CRM system, the document generation engine, the notary and closing engine and the warehouse software. So, we're like, when the client signs up with us, we might replace as many as 8 to 10 different systems that the client has.

Your next question comes from the line of Mikhail Goberman with Citizens JMP.

If I could ask about expenses, and I appreciate the comments -- prepared remarks about the expenses and how you're planning to deal with the partnerships with regard to that going forward. I believe you mentioned a target for the first quarter of next year. Is there any sort of a number or a run rate that we can put on that?

No, I think we're hoping that within the next 6 months, we get to $1 billion a month origination run rate. I think we're hoping that we continue to have scale in our expenses. We're hoping that we continue to drive a lot of the corporate cost reductions forward. We've been really busy this last quarter. So I think I personally wasn't able to pay as much attention to some of the legacy contracts and things like that, that we need to kind of continue to still beat out, 3- or 5-year contracts that we signed back in 2020, 2021 that we're like working to sort of reset with more AI-driven type solutions. I think there's still a lot of cost savings left, which is why we're -- we continue to drive to achieving profitability while growing scale at the same time by Q3 2026.

Great. Appreciate that. And if I can fit in one more. Just your general thoughts on the stability and strength of the mortgage industry in general, given where we are with interest rates and sort of wobbles, I guess, you could say, with the economy a little bit. Just your general thoughts on consumer -- the borrower and the consumer and how the whole system is developing going forward.

Yes. No, I think -- look, I really believe that we're headed into a recession. I believe that that's going to result in a couple of things from a macro standpoint. I think there's -- you would think that heading into a recession, purchase mortgage would be disadvantaged. But there's millions of people who have wanted to buy a home over the past 4, 5 years who missed out the 2019 to 2021 rate environment.

And they are -- have been building up their savings and they're looking -- and a lot -- any of them who have owned equities in the past couple of years, they have been building up wealth to go and buy a home. So I think that you're going to see purchase mortgage originations stay sort of where they are. You might not have like the boom that you did in 2020 and 2021 if we have a real recession.

And then on the flip side, there's like 20 million people that can start to save money as rates go below 6% if we do actually enter into a recession. And I think that, that's pretty significant. And then lastly, in the current period, let's assume we just stay in this sort of muddled medium inflation, 6% plus interest rate environment, home equity origination still such a small number compared to what they were pre-global financial crisis or where they are relative to the total size of home equity that people have in their homes, which is now, I think, $22 trillion of tappable home equity according to the latest TransUnion report.

And I think, for us, we have both the secular tailwinds of a very competitive business model in D2C that we are now continuing to improve the conversion rate on. I think as you might have seen like in the earnings release, like we talk about the conversion rate going from 3.3% to over 6%, like an 81% increase, right? That's just like grinding out, like putting the AI in places where the humans are not able to do as good of a job, right, to satisfy the consumer, just keep on grinding away at that. And so that, I think, is super meaningful and will continue to drive both unit economics and growth in the D2C channel.

And then when we're taking on partners that we're taking away from incumbent platforms, they are - quite bluntly, we're stealing market share. And so -- and that's the fastest-growing part of our business. And so there, if the mortgage market stays the same, if it's -- whether it's $1.5 trillion in originations or $2.5 trillion in originations, of course, we'd love it to be $2.5 trillion in originations. But where we're moving partners from incumbent solutions that are built in the '80s, '90s, 2000s onto our tech stack, there -- we're relatively agnostic to the cycle. And if the cycle comes our way, then that's even better.

Your final question comes from the line of Doug Harter with UBS.

Vishal, I was hoping you could talk about, as you're guided to getting back to breakeven and to profitability, what type of volumes do you need to accomplish that?

I think depending on the mix, I think we get to $1 billion plus, and we have a good shot at it. Obviously, the margins in our partnership business are higher than that in our D2C business. But even D2C is getting to a place where the margins are pretty healthy on a contribution margin basis.

But yes, I think we get to $1 billion plus. And then, depending on the mix, we get to beyond that I think per month. I think you have a very, very, very good business that's driving towards breakeven.

And then, can you talk about, is there different revenue that you're generating with partners for a home equity origination versus a traditional first lien mortgage?

Yes. I think home equity originations, I mean, the loan amounts are much smaller, but the gain on sale is higher. And between the gain on sale and the fees, you're making -- on the mortgage side, you're making maybe $8,000 a loan and on the home equity side, you're making like $6,500 a loan. I think it's very important to remember in both of these cases, we're not retaining, in mortgage, the MSR. We're not taking credit risk. We're not taking prepayment risk. We're not taking any of those risks.

In home equity, we have yet to scratch the surface on what scale looks like, right? There are other people in the home equity market selling their loans at 107 or booking a gain on sale at 107, we're at 103.5. So, there's a long way to go in bridging that gap. But when those people are booking those loans at 107, they're taking principal -- prepayment risk, they're taking credit risk, they're booking resids, all that sort of stuff.

If you like compare on an apples-on-apples basis, on a pure marketplace basis, I think we're getting a pretty good deal, but I think we'll probably still have another point or 2 that we can squeeze out on our home equity originations.

There are no further questions at this time. This concludes today's call. Thank you for attending, and you may now disconnect.

Thank you, everyone.

Okay. Hello, everybody, and thanks for tuning in today. My name is Brendan McCarthy. I'm an analyst here at Sidoti, and I'm thrilled to welcome Vishal Garg, the Founder and CEO of Better Home & Finance. Vishal, thanks for joining us today.

Thanks so much, Brendan, for having me here. I'm excited to talk about Better with you all.

Absolutely. So I've been covering the company for a little bit less than a year now. Obviously, it's received a big jump in investor interest as of late. But I really want to take the next 30 minutes or so to focus on the fundamental outlook of the company, some of the key demand drivers, and we can talk about the outlook going forward.

But to start, Vishal, I think it'd be great to hear your vision for the company dating back to 2014 when you started the firm as well as the early operating years of the company.

Totally. I think I started the company because I went through a mortgage process and lost the house that I was going to buy with my family to an all-cash bid. And I said, wow, how does it take 60 days for a bank to basically try to figure out like three major pieces of data about my credit history, my debt-to-income ratio and the value of the house. And I was at that time trading mortgage-backed securities, and I could figure that out in like six seconds for every loan and every mortgage-backed securities trust. I just couldn't understand the disconnect.

And then I dove deeper and I found out it costs an average mortgage company like $12,000, 28 people to make an 800-page PDF that we all call the closing statement. And I said, wow, they've got to be a better way to do this. And if it's so hard for me, someone who is like steeped in fintech and mortgages to go get a mortgage, how hard is it for the average American. And so I sought to make the mortgage process cheaper, faster, easier through technology, using APIs instead of people making the process instant and enabling any homeowner, if they're buying a home to be able to be effectively like a cash buyer and any homeowner, if they're refinancing or going a home equity loan to be able to get their savings instantly rather than in months. And that's what we started Better with.

And what we did from a technical perspective was recognize that what we wanted to do was effectively a three-way matching engine. So we have consumers set of attributes, right, your credit score, how much money you make, your payment histories, how many dependents you have. And then you have a property which has a set of attributes, how much is it worth? When was it built? Is it a condo or single-family home? What's the lot size? And then match those two with investors who have criteria. They want to buy loans that have consumers with 740 FICO scores, living in single-family residential in these particular states with these sets of attributes.

And so I sought to build a large-scale matching engine that would match consumer and property data with investor criteria for the largest tangible asset class in the world, which is residential real estate, which in the United States is worth over $30 trillion and globally, over $160 trillion and basically operated as if the Internet didn't exist. And that's what we started to do. We built a machine learning-driven matching engine that automated the mortgage process. And then more recently, we've built an AI layer on top of the machine learning to build an end-to-end platform that saves consumers and our mortgage partners time, money and expense and frustration in either getting a mortgage or making a mortgage for their customers.

Absolutely. And you saw a fair bit of success under this model back in 2020 and 2021, much more favorable operating environment. And you generated profitability, I believe, back in those years. Can you talk about how the business really operated back in that time frame?

Oh, totally. I mean we went from doing about $500 million of volume in 2016 to over $58 billion of volume in 2021, almost 100x growth. I think we were the fastest-growing fintech in America at that time. By 2021, we were doing more mortgages than BofA was doing and just a shy hair of what Chase was doing across all their branches and all their people in the United States. In 2020, when we did about $25 billion of mortgages, we generated about $800 million in revenue and about $250 million in adjusted EBITDA. That's a really great level of profitability that we were able to generate when the rate environment was a lot more benign.

Now the challenge was that going into 2021, the bulk of our model was reliant on doing refinances for consumers. And when rates went up by 450 basis points, in a much faster way than either we or the market anticipated, a lot of that refinance volume dried up. Basically, the total addressable market for our product dried up by over 95%. And so we had to really pivot hard to build what we have today, which is a much more scalable business model powered by advances in AI and built not just from a direct-to-consumer standpoint, but also built to enable other mortgage originators, fintechs and banks to be a participant in the mortgage business.

That's great detail. And I think that's a key point for investors to understand is this was a much different business back in 2021 when you did capture a large share of volume. So, you mentioned 2022, obviously, the increase in interest rates presented challenges. How are you still able to really focus on growth? And you mentioned product build-out during that time frame. What was the focus during some of those more challenging years?

Oh, totally. I think we've always been a product and tech-centric company. I think it's very different, right? Like most mortgage companies in their DNA are mortgage companies. They are built by mortgage loan originators who strive to build their own business who typically were mortgage brokers or loan officers and other companies. And so they take a very mortgage-centric mindset and a sales-centric mindset and a people-centric mindset to the problem.

We've always said, what is the problem that we're trying to solve and how can we use technology to solve that problem. And we take it from a much more product-centric mindset, which is how can this product take something that is a pain point for the customer and solve it. So in '22 and '23, as rates went up, we did -- we focused on a couple of things to pivot the product experience. The first was we knew that we were going to have to change the mix from 95% refi, 5% purchase to something that was inverted and basically, the majority of our business was purchased with the rest of it being refinance.

In order to compete on the purchase market, well, Better's always had the lowest rates through a combination of being able to pass by savings from its technology platform and savings from our investor marketplace back to the consumer. Rates mattered less to a purchase mortgage customer. They just want the house. And so what we've learned is people who are shopping for a home, they care about two things. They care about speed and certainty, getting to yes and knowing that, that yes is actually good to go. They care about that a lot more than they care about the interest rate. So we leaned very heavily and in 2023, launched the one-day mortgage.

Now the underpinnings of being able to take something that takes 45 days to go from a lock loan to a commitment letter at a typical mortgage company and getting that down to one day was where we had to apply technology and a parallel path processing environment. And so we really leaned hard to figure out how to do that so that we, on average, today, are able to deliver a commitment letter once you upload your purchase contract and lock your loan within eight hours. 42% of our purchase commitments are actually delivered in less than 15 seconds. And all that is done through what we've built as the AI. So we've always built a machine learning-driven platform. In true AI speak, what they call that is a supervised learning network, where basically the platform learns a set of repetitive tasks over and over again and then is able to optimize the pathways to fulfilling that task.

What we were able to do when OpenAI came out with its first version of ChatGPT and introduced the Gen AI models is take a lot of the things that were still requiring human judgment where the rules were not yet codified or where the consumer was interacting with a person on our side and start having the AI do those tasks as well. So we leaned really heavily into that very early on. It was made a lot easier for us than it was for any other mortgage company because we are the only mortgage company with its entire full stack operating system from click to close all on one platform. That means 12 million recorded phone calls, 6 million approved customers, 600,000 funded loan documents. 4.8 billion pieces of pages of information. All of that was completely in one place for the AI agent to learn from and to figure out and to create the same level of judgment such that today, we are at feature parity between our AI loan officer, Betsy, and a typical refinance loan officer.

What's more? Betsy is able to surface problems that might come up with a file and come up with solutions way faster than any typical loan officer would be able to do the math on. And it's able to do that while knowing all of the criteria and understanding all of the requirements across the entire network of 45 different mortgage investors that we have on our platform, almost 45,000 pages of underwriting documentation and rules and it's able to do that nearly instantly. And so that's the other big thing about what we did with the platform. We leaned really, really heavily into Gen AI, utilizing our unique machine learning-driven system, Tinman and more importantly, that data advantage that we had for learning data, which was clean learning data, all observable by our AI models inside of Tinman.

And then the third thing that we've done is expand our product offering. So we leaned very heavily into launching a home equity product. We saw others who had leaned into home equity or started home equity businesses back in 2018, 2019, start to actually be able to penetrate and that American consumers were sitting on $30 trillion plus of home equity. And while we had a product cash out refi that touched that, cash out refis didn't make sense for consumers that had gotten a 3% interest rate and had other debts and other things like that.

What's interesting about what we did with home equity is we created, again, a multi-path platform. That is simply unable to exist outside of what we built in Tinman because most fintechs build a single path platform and then distribute the product at the back end through securitization. And so the typical fintech that had gotten into the home equity space had a red light, green light type typical model of student loans or personal installment loans, not a multifactorial multi-pathway model like what we've built inside Tinman to be able to address an investor marketplace.

Now the utility function of that to a consumer is that you get a much higher approval rate for the product and a likelihood of a lower interest rate because you're matching the consumer and the property-specific attributes across a broad cross-section of investors, investors, including real estate investment trust, mortgage investors, the GSEs and then also banks. And that's way better than just one investor with a conduit into a securitization.

So we've been able to grow that home equity business so dramatically. Last year, it grew over 250%. We're at about $1 billion run rate in originations on home equity, up from $100 million just two years ago. And we're growing 6x faster than the other public competitor figure. And our business model doesn't require us taking any of the credit risk or prepayment risk because we're able to sell the home equity lines of credit onto the investor marketplace that we've built, mimicking what we do in the mortgage space.

Absolutely. And that's a key differentiator for the company when you look at the balance sheet and the funding mechanism. Let's talk about that in a little more detail. So this is really a balance sheet-light lending model. How can investors really think about that concept?

I think you have to think about us more like a Stripe for mortgage and home equity or a Visa or Mastercard, where we're a network. On the front end are consumers or partners who have consumers on their platform who are using the platform to find ways to sell mortgages and home equity products to their customer base. And so that's very similar to merchants like on Mastercard, Visa or Stripe.

On the flip side, you have investors who are seeking to buy cash flow producing assets secured by real estate. And so we are just the matching engine in between and the processing and fulfillment engine in between. And so we don't take credit risk, we don't take prepayment risk. We don't even take liquidity risk in that like the bulk of our mortgage products, 95% are GSE eligible. So there's a ready market trillions of dollars in size in that.

And then on the home equity side, we've got an investor marketplace of 8 funds and banks and investors, and we're continuing to grow that. So the likelihood of us being stuck with any particular loan is super low compared to a lot of the other originators out there who are loading up loans into a warehouse line, relying on securitization, reliant on rating agencies.

And look, I lived through that through the credit crisis with my first fintech company, 2008, 2009, 2010. It wasn't pretty when credit risk goes up, prepayments go up and liquidity dries up. And I think that's what we've done with our platform. And I don't think people understand that really in the equity markets today. And I think when they do, our multiples are going to be very different from the ones that we trade at today, which are more like balance sheet fintech lender type multiples.

Absolutely. I agree. I think it's an important point for investors to look at. And while we're on the topic of the balance sheet, let's talk about the restructuring that you completed last year. The balance sheet is in much better shape going forward. And now it seems like you're really positioned for growth with the recent ATM announcement in the 8-K a couple of weeks ago. Can you talk about warehouse capacity now? How can investors think about the balance sheet as a whole?

Totally. I think we really rightsized the cap structure of the company starting early this year when we retired about $375 million of debt for a cash payment of $110 million. And in doing that, we generated $265 million of positive equity to the balance sheet, which was, I think, at that time, even bigger than our market cap. And if you look at our market cap today, is 1/3 of our market cap that we generated in positive equity.

I think what that also freed us up to do was really look at a variety of strategic options for the company and enable us to start partnering up with other fintechs who had a strategic model around using what they had built in other verticals and leveraging it to mortgage and home equity. And then lastly, where that has left us is we currently have about $575 million of warehouse capital I think we've announced two large deals that we've 8-Ked that alone will require us to increase that to about $2 billion to accommodate the funding demand that's going to come out of that on a monthly basis.

So while we don't give guidance, I think those numbers should provide some pretty healthy color on where we expect those two partnerships and how much volume we expect those two partnerships to generate in the near future. And what's been really great is having turned around the business, having now starting to show real growth across our mortgage products and starting to show deep partnerships with major originators, leaders in their category like the one we announced this morning with Finance of America, which is the leading home equity and mortgage provider to the over 55 demographic.

We're not partnering up with the small guys. We're partnering up with like these real awesome big players to help them launch on the Tinman AI platform. We're getting a really positive reception from the Street and the banks to be able to provide that capacity to grow to $2 billion a month in origination capacity for us.

Absolutely. I think that provides a great line of sight there into future volume growth. And I want to get to that as well, the B2B distribution side and the catalyst there. But let's do a deep dive into the tech stack at this point. I'll turn it over to you and really how can investors think about what Tinman is, how it facilitates the origination process from the borrower perspective? And then also more on the back end, how it kind of drives some of those operating efficiencies for Better.

Sure. So, Tinman, I think, is unique in that it is built as a matching engine at a data field level. It is not producing a loan than dropping it like we used to in the old days into an Excel sheet, stratifying it up and then selling it off to investors or putting it into a securitization. It is literally matching attributes to criteria on a singular data field level.

What that permits us to do is as a consumer is going through the process and we're capturing more and more data about them, either through what they supply or what they get -- we get from an API pull, we're able to narrow down at specific moments in time to what is the bare minimum required to generate a pre-approval, what is the bare minimum required to generate a lock and then what is the bare minimum required to generate a commitment letter and then finally a closing statement.

And this is not specific to any particular loan type. Tinman fundamentally can do this for any underlying financial asset that requires effectively an underwriting workflow. And we've built it for the hardest financial asset to underwrite, the consumer mortgage and the one that has the greatest amount of variability and also the greatest amount of liquidity. But it allows us to effectively create and launch new products much more easily than the rigid systems that exist today in mortgage land, where over 85% of the mortgage market still operates on a system that was really built in the 1990s where you can't even have more than one person at a time working in a file.

Just to like contextualize that, many of you guys are a little older like me, right? And like you remember, when you're working in a dock and it was on SharePoint and you had to tell your teammate, hey, can you get out of the dock and so I can like put my edits in. That's actually how 90% of the mortgage industry software platforms work. And not only are there one of them, but there are literally eight of them required to make a mortgage.

And then you have Tinman, which is a brand-new tech stack where at the core architectural level, you have data field level matching. And then wherever the data is unverified and requires verification, it triggers a task that can either be fulfilled by the machine operating and getting that information directly via an API or by the machine generating a task for a third-party service provider like a title agent or an appraiser to automatically go and fetch and then take that data back and parse it and close out the task or for a person, whether they're here or somewhere else, employed by us or employed by someone else to go and fulfill that task. And each of these tasks and activities at the underlying level are coded with the lowest friction pathway to go and achieve fulfillment and they operate on a waterfall model where if the lowest friction pathway isn't available, it goes to the next pathway goes to the next pathway.

This is what enables us to be so efficient in the manufacturing process of a mortgage, where if you look at just our last earnings deck, you can see the cost at Better to make a mortgage between sales labor and operations labor is 70% lower than that of the typical industry average if you go and look at the most recent Mortgage Bankers Association data. And I think that, that's super interesting because here is where you have the building blocks of real AI in action delivering real tangible, measurable results in a multitrillion-dollar industry. So that's the underlying architecture and rules-driven logic of Tinman.

On top of that, we overlay the Gen AI. So we built Betsy from a consumer sales perspective to be the world's first real AI loan officer. And in doing that, what we had to do was most AI implemented on top of a CRM system usually fails because of the hallucination rate. Particularly in financial services, you've got to get the numbers right. What makes Betsy so powerful and its ability to actually be able to go end-to-end and more importantly, the calculations aren't done by the LLMs. The calculations are actually done by the calculation and rules engine inside Tinman. And so Betsy can do all the humanistic aspects that AI is so good at, taking in third-party data, helping consumers or partners understand things, providing context, providing -- but then all the calculations are actually done in Tinman. And so unlike other LLM-driven models, Betsy is right 100% of the time on the calculations, which is what gives us the confidence to put her out there into the world doing hundreds of thousands of consumer interactions a month.

The next part of what we've built on Betsy is AI processing and AI underwriting. Again, when Betsy is doing AI processing or underwriting, it's asking for the next marginal document or piece of data to fulfill and consumers might have it in many different ways. So Betsy is then able to go and figure out, hey, this customer can't prove their income just using a typical W-2 because they're driving for Uber or they're a freelancer. And so automatically, we'll go and parse through that customer's bank statements, which will get directly via API or get via like permission access and then go and calculate income that way. So in doing that, it's not sitting there waiting like typical mortgage industry processors.

On the underwriting side, Betsy is remarkably good at detecting fraud or things that are inconsistent. And since it's storing all of the data elements and is able to reference against different data elements to figure out fraud, it's enabled to effectively underwrite in a way that's better than most typical underwriters. It's also able to surface ways for consumers to get approved that a traditional human underwriter may not remember across 45 different plus underwriting guidelines.

Today, Betsy is so advanced that actually no underwriter -- no human underwriter at Better is allowed to deny a loan without actually having Betsy review it as a second look. That's really powerful. If you think about what that means, right, Betsy is actually a superior agent at finding solutions for consumers to be able to get approved and funded than a typical human underwriter is.

Now you take all of those things together and what you end up getting what matters to customers and what matters to our business partners is a much higher approval rate on your chances of getting your customer or yourself approved, the lowest possible interest rate across a network of investors where you're optimizing for fundamentally the cost of capital, the lowest error rate in manufacturing a mortgage in the industry, 30x lower than the industry average, right? And this is important in an industry like mortgages where back during the credit crisis, 47% of the mortgages made were underlying faulty data and had reps and warranties issues.

And then lastly, what's really important to us is the success rate of the customer. So our delinquency rate on our mortgages, even though that we lean super hard into the underwriting criteria because we're running a matching engine, we go down as low as 580 FICO. We go as high as 50 DTI. We go as high as 97 LTV, all within the parameters of the GSE programs and the FHA and VA. Even at that, our delinquency rates are 1/3 of that of the industry. So you have better rates and a higher chance of approval for consumers and business partners. And at the back end, a much lower default rate and a much lower error rate on manufacturing of the mortgage.

This is why we think people are signing up, both consumers and partners, business partners. And the ones signing up, like we've got over $100 billion plus of volume that's already been signed up. onto the platform. And we're just still scratching the surface in what is a $2 trillion-plus annual volume business. And I think that that's what's super exciting. It's not just what is the tech or how we made the tech or what it does. It's actually what results it tangibly provides to consumers and our business partners.

Absolutely. That is very interesting. And I think that you've talked about -- there's an example out there of transitioning loan officers onto the Tinman platform from some of those legacy systems. And that is the NEO powered by Better, which your company -- I guess it's not technically an acquisition, but you acquired the loan officers last year. Do you want to talk about that deal and really how the impacts have been felt with NEO?

Totally. I mean we're becoming a magnet for the industry's top loan officers to come and build their business on. So like rather than spend a lot of the time in the first six, seven years of our life competing against the local loan officer, much like what Amazon did with its D2C and opening it up to third-party seller marketplace, we now have local loan officers building their businesses on Tinman. They're moving from these super inefficient old-school tech stacks where it costs them $12,000 to make a loan and moving to Tinman where it costs them a fraction of that, like 70% less than that. And therefore, drops more money back to their bottom line that they can invest in their customers or lowering rates for their customers or doing more deals in their local market.

And then on top of that, they're getting a better economic construct than they typically would from one of these old-school mortgage companies. And we've seen that NEO now scale up to a $200 million revenue origination run rate. They've added about $500 million plus of new mortgage originators volume onto their platform, and we're setting up to try to grow over 100% again next year to build like a really great platform for the best loan officers in the industry to come and build their business on.

Again, similar to like third-party seller marketplace for Amazon, but maybe more in financial services land, similar to the models that LPL and Envestnet have used to disrupt the traditional RIA space.

Absolutely. That makes sense. And so for NEO, you have cost savings, more efficient production from the loan officer perspective. Now what are some of the benefits to Better as far as your financial results? How does that ultimately flow through to your financials?

I think one of Better's core costs as a D2C originator historically has been customer acquisition costs. So with NEO, we have zero customer acquisition costs. Our typical customer acquisition cost of $3,000 a loan goes to 0 because these loan officers have local relationships already built over 10, 15, 20 years of being in business in a local market.

The second thing it does is it improves our conversion rate because we would -- better for the longest time, we were almost at 6% market share if you think about like how many people we preapprove as a percentage of annual American home shoppers. But the people that we actually convert into loans is 120th of that amount. Where did the other people go? Well, half of them didn't buy a home, but the other 90% of those customers, they transacted with a local loan officer.

So now if we're able to identify the customers that likely need the help of someone local, someone physical, first-time homebuyers, credit insecure customers, down payment in secure customers, and we're able to channel them to a local NEO loan officer. And rather than losing the business to a local loan officer, we're actually able to amplify the business that our local partners get and in doing so, dramatically increase the conversion rate that we're getting for these customers, which then also improves our unit economics across the board.

Absolutely. That makes sense. And you recently announced, I think it was last week or the week prior, a new B2B platform partnership where I believe it was a nonbank mortgage originator is going to ultimately transition onto the Tinman platform. I know financial details of that are slim at the moment, but you plan to release more in the coming weeks. Can you talk about that deal or that partnership a little bit more?

Yes. It's one of the top five mortgage companies in America. We're really psyched. We're going to help their loan officers migrate from an incumbent platform where they get 10%, 15% approval rates on to Tinman where they're going to get 50%, 60% approval rates on HELOCs and HELOANs through our platform and at better unit economics. So I think that's the other thing is like really, it was a win-win for everyone. They have an incumbent base of customers that's millions of customers in size. And now they're marketing HELOCs and HELOANs.

But again, if you're someone who has a relationship, who you know personally in a local market, and you offer them a HELOC and HELOAN and you get them to the table and you only get approval rates of 10% to 15%, you're not going to do that. And so we think there's this huge opportunity to partner with local loan officers or mortgage companies that have lots of local loan officers in whatever form they are in and enable them to access the HELOC marketplace that we've built plus the product, which dramatically improves approval rates and lowers interest rates for their customers. So we have very high hopes for this partnership, and we think it's just the beginning of us penetrating that channel of partner.

The other big partnership that we announced is a partnership with a large financial services company with over 50 million customers. So if you think about that in the context of like size, like the other I'll use examples, but like if you go into and do a little bit of research, you'll see some of the other big banks that are out there that have 50 million customers and what their mortgage penetration rates are. And if you take that mortgage penetration rate and you just simply multiply that by $50 million, you'll get an understanding of the size and scope of that partnership and the amount of loans that we're going to be able to build up to as we deploy that partnership to all of that partners' customers.

So, I think those are really exciting and deep validating partnerships. And you'll hear more about them as we officially launch them, get some customer success stories and then are able to share details about both origination volumes, but also the names and the size and scope of the partnerships.

Absolutely. It certainly seems potential volume catalysts there are notable with the two partnerships. And you mentioned the second partnership involves your ability to offer Tinman under more of a mortgage as a software type solution for companies. Can you talk about that initiative a little bit?

Sure. So this partner has not traditionally been in the business of brokering or making mortgages. And I think that's the case with a number of banks that left the mortgage business post the financial crisis. It's the case with a whole bunch of fintechs that have huge customer bases, but for other products who now, as their customer bases are aging, don't want to lose that relationship to your traditional big behemoth bank when that customer wants to go and get a mortgage, which is typically the type of credit that people really gravitate to and where there's a unique moment in time where a financial institution can change the existing relationship that they have with a customer or a customer is open to changing the relationships that they've had in the past with their incumbent providers.

And so we're launching a mortgage product with this partner, and we have very high hopes for what it will bring for their customers in terms of both savings and relationship stickiness compared to had they gone with someone else.

Absolutely. And what does the revenue opportunity look like for Better under that B2B partnership model? How does that ultimately flow through to your financials?

We make economics both as the fulfillment and funding agent and also as the software platform provider.

Got it. That makes sense. And when you look at these partnerships, how can you describe the pipeline looking ahead? Are there -- are you having conversations every day with other firms? Or how can investors think about the pipeline there?

Yes. So totally, our strategy is a bit of a land-and-expand strategy. So there's like numerous verticals where we think the Tinman AI platform does a superior job to the incumbent software providers that are all sort of like 1990s floppy disk-based platforms that have been migrated to the cloud, but underlying architecture has basically remained the same.

And so when we think about that, we think, hey, for instance, we want to be with a fintech that has a large customer base that -- for other loan products. Hey, we want to be with a buy now, pay later provider that has a large customer base. We want to be with a traditional mortgage company that has a large customer base. We want to be with a large servicer with a large customer base and so on and so forth. And in each of these, we want to like capture one of the industry leaders, like the top three in the industry or in that vertical and then from there, empower them, grow with them and then land and expand from there.

So that's what you're going to see us manifest over the coming 12 months with our strategy. And in each of these verticals, there's hundreds of billions of dollars of annual mortgage origination, and you're going to see us tap the leader and then from there, expand to others in the space.

That's very exciting. And we'll transition to the growth outlook here. I know we've touched on a lot of different areas. But when you look ahead, you've pointed to the goal of being or generating positive adjusted EBITDA by the third quarter of 2026. What ultimately gets you there when you look at your results?

I think, one, direct-to-consumer, particularly in the home equity business continues to scale and scale dramatically. So I think you should see that. And the unit economics are already positive in our direct-to-consumer business, and you can see them get better as we're able to unearth more and more value for our customers through, and generate more positive unit economics. So that's one. Two, for our partners, NEO will continue to scale. And we're expecting that business to continue to grow rapidly in the way that it has, and that will continue to generate positive profit contribution to Better. And then three, all these partnerships that we've done will hopefully scale into the size that we think where we have deep penetration into those partners' customer bases.

And as you know, these partnerships come at margins that are more significant than D2C or the NEO business because we are talking more about software margins and AI platform margins rather than the margins typically associated with mortgage or direct-to-consumer fintech.

And so with all of that, if you think about like how much money we lost last quarter and that number has continuously come down quarter-on- quarter-on-quarter, you can see a pathway where all of that starts to really like glide our path down to zero, which is where we hope to be by this time next year.

Absolutely. And how does the interest rate environment really play into that outlook? I mean what other -- I guess, what variables could really cause you to really speed up that time line or maybe even delay that time line a little bit?

Yes. So I'm talking about something in like with the current interest rate environment in place. If rates come down by 100 basis points between now or sometime next year, which is -- people are projecting anywhere from 50 basis points to 150 basis points of rates, you're going to go from 5 million customers being in the money for a refi to 20 million customers being in the money for a refi. Last time, we went from nearly 0% market share to 2.5% market share in refi within the space of three years.

And the system is more fully built. Betsy is ready to rock and roll. Betsy, unlike other people who have millions of customers, but are staffed with 10,000 people in a call center and those people do an average of five loans a month, and so therefore, are helping 50,000 customers a month, Betsy can do one million calls all at the same time. And so I think you'll see us aggressively gain market share if and when rates come down and be very aggressive about that. And I think there is a totally different profit picture in mind for this business.

Great. That's very exciting. We had a couple of questions flow in from attendees here. From your perspective, what's the single biggest current barrier preventing Better from becoming the dominant operating system for mortgage origination involving Tinman and Betsy.

Legacy contracts. The incumbent providers have like people on three-year, five-year, eight-year type contracts with inflation escalators per seat, like per seat, can you imagine per seat pricing in the age of AI? Like if you're doing per seat pricing, you're automatically like saying, let's make this the most inefficient process possible. Let's go from 28 people making a mortgage to 48 people making a mortgage.

So, honestly, it's these legacy contracts. And when we encounter a lot of our partners, they're like, wow, I would love to do this, but I've got this legacy contract. Let's talk in '26 or '27. And I think that's okay. There's more than enough fish that are just whose contract cycles are expiring in '26 for us to be able to make hey. But it's legacy contracts that people are stuck in.

That makes sense. That makes sense. Well, Vishal, we really appreciate the time today. It's been very helpful. Glad we got to go through the company in more detail. I'll pass back over to you for any closing remarks.

Thanks, Brendan. We're super excited about the future. The last four years were really tough. We never gave up. We kept on investing in the tech, kept on investing in the AI. And now we're coming out of it. If we have a benign rate environment, I think we're going to scale much faster and much better than any time that we did back in 2020, 2021. We won't repeat a lot of the same mistakes. We'll be super lean and hungry. And we're really appreciative of you taking the time to help us have a forum to tell our story. Thanks.

Likewise, looking forward to continuing to cover the company, and thank you, Stocktwits, for broadcasting the event. We appreciate everybody tuning in today. Have a great day.

Hello, and thank you for standing by. My name is Lacy, and I will be your conference operator today. At this time, I would like to welcome everyone to the Better Home & Finance Holding Company Second Quarter 2025 Results Conference Call. [Operator Instructions] Thank you. 

I would now like to turn the conference over to Tarek Afifi. You may begin.

Welcome to Better Home & Finance Holding Company's Second Quarter Earnings Conference Call. My name is Tarek Afifi, 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. 

In addition to this conference call, please direct your attention to our second quarter earnings release, which is available on our Investor Relations website. Also available on our website is an investor presentation. 

Certain statements we make today may constitute forward-looking statements within the meaning of federal securities laws that are based on current expectations and assumptions. These expectations and assumptions are subject to risks, uncertainties, and other factors as discussed further in our SEC filings that could cause our actual results to differ materially from our historical results. We assume no responsibility to update forward-looking statements other than as required by law. 

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 GAAP results. 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 in our quarterly report on Form 10-Q filed with the SEC. 

Amounts described as of and for the quarter ended June 30, 2025, represent a preliminary estimate as of the date of this earnings release and may be revised upon filing our quarterly report on Form 10-Q with the SEC. More information as of and for the quarter ended June 30, 2025, will be provided upon filing our quarterly report on Form 10-Q with the SEC. 

I will now turn the call over to Vishal.

Thank you, Tarek, and welcome to our second quarter 2025 earnings call. We appreciate everyone joining us today and for your continued support as we advance our mission to make homeownership better, faster, and easier for our customers by building an AI-native technology platform that revolutionizes the entire homeownership journey, helping consumers go through the entire mortgage and home equity process in as little as 1 day. 

We continue to drive progress towards this vision in which every customer can seamlessly buy, sell, refinance, insure, and improve their home online instantly at a competitive price. These objectives are: one, leaning into growth in AI to drive increased volume and revenue; two, continuously improving our efficiency driven by ongoing advancements in our technology; three, diversifying our product and go-to-market strategies along with our distribution channels; and four, reducing our corporate costs as a percentage of our revenue, all with the goal of achieving profitability. 

Better is the first scaled mortgage tech platform built to empower consumers and more recently, empower local mortgage bankers and financial institutions with Tinman technology to serve their end customer needs. This sets us apart from the rest of the mortgage industry and in the face of market challenges, creates tremendous greenfield opportunity for Better. We remain focused on driving towards profitability by continuing to lean into Tinman technology and AI with Betsy executing approximately 600,000 consumer interactions in Q2, our AI underwriting growing to over 43% of locked loans with a clear path to 75% in the near future and our loan officer productivity in terms of funds per month increasing to over 3x the mortgage industry median. 

We've been talking about our path to profitability in the medium term for some time. With all of the advancements in our AI platform and the progress that we are seeing in bringing on not just mortgage advisers that are local market professionals, but also other large-scale enterprises that want to enter the mortgage business through our platform, I am pleased to share that we now have the visibility and expectation to achieve adjusted EBITDA breakeven by the third quarter of 2026, basically within the next year. Kevin will speak more on this shortly. 

We have built a platform that is AI-first. While consumer adoption behavior of AI takes time, it is increasing at an exponential rate. We are one of the few mortgage companies, if not the only mortgage company in the U.S., with a full-scale tech stack in one place, all in one flow and entirely APIable to Agentic AI. Betsy has been built from scratch on our knowledge base that has been developed on 12 million-plus recorded phone calls, 500,000-plus funded loan files with the entire consumer financial graph and property graph matched to the investors' detailed line item fact-based criteria and 6 million pre-applications over the past 8 years, and it is continuing to learn every day from every customer interaction. 

Since we launched Betsy AI, our lead-to-lock conversion rate has increased by over 30% from 3.3% to 4.4% which is massively meaningful to drive incremental volume and revenue and squeezing profitability out of each loan. Now as you can tell, we've still got a really long way to go to keep on improving that lead-to-lock conversion rate. But as we scale Betsy at near 0 marginal cost because it's all built on our own internal proprietary Tinman platform, we believe that we can further improve our unit economics as the mortgage market stabilizes over time with relatively de minimis increases in fixed CapEx. 

Betsy has led to an even better customer experience. For customers who opt to speak with the human, Betsy will help find the most talented individual on our sales team for that customer to interact with for their specific needs. Since we've adopted Betsy, our Net Promoter Score has increased from 39 to 64, putting our score in line with companies like Google and Apple and far superior to that of traditional mortgage companies and financial institutions. Betsy is built on top of our machine learning pricing and eligibility engine, which we internally call DE, which uses the consumer's financial graph and the property graph, and each specific data element is matched to the criteria set by each individual mortgage investor directly within our platform. 

It is able to run hundreds of thousands of pricing permutations across the now over 45 mortgage investors who buy the loans on our platform as they are funded on a loan-by-loan basis. These loan purchases include GSEs, banks, REITs, and increasingly private credit funds, all of whom bring different guidelines, risk-return preferences, and other criteria to our platform. They represent over $1 trillion in demand, bidding on loans each day that match the criteria and portfolio needs, and with our platform fulfilling those criteria at an error rate that is substantially lower than the industry's. 

Over the next 1 to 2 years, we expect to significantly grow our investor network, particularly as the private credit market moves further into consumer asset-based finance. Within consumer lending, mortgage and home equity is over 85% of the total addressable market and is particularly attractive to private credit as it has a robust track record in recessionary periods on a basis relative to unsecured consumer debt like personal loans, credit cards, and BNPL loans. 

Our credit and underwriting quality are best-in-class. Yet aside from the short window that we hold the loans due to settlement, we do not take any credit risk as we have forward commitments to sell each loan to investors the moment they are locked and funded. This model remains unique in the fintech landscape, where a very large number of the originators that started out as marketplaces have now moved on to actually holding credit risk on their books. Better is doing exactly the same thing today as it did when it opened its doors in January of 2016. We do not hold credit risk on the assets that we originate. And we believe this will serve us well if we enter into a recessionary climate. 

As we look to the second half of 2025 and beyond, our strategic priorities remain focused on what lies in our control. Our first priority is to continue to propel growth opportunities independent of broader economic and mortgage market conditions. In the second quarter of 2025, on a year-over-year basis, we grew funded loan volume by 25% to $1.2 billion and revenue by 37% to $44.1 million, driven by funding more loans, both through our D2C and Tinman AI platform channels at higher gain on sale compared to the period past. 

During the quarter, year-on-year funded loan volume growth was driven by HELOC and home equity loans increasing by 166%, refinance loan volume increasing by 109% and purchase loan volume increasing by 1%. Our overall growth in the quarter is attributable to the strategic investments we've made in technology, product innovation, and distribution expansion, including Betsy AI, our Tinman AI platform strategy with NEO powered by Better being proven out, and the efficient expansion of D2C driven by the efficiencies we are gaining implementing AI throughout the entire platform. 

These strategic initiatives have positioned us to capitalize on a broader set of market opportunities, enhance our operational efficiency, and continue to drive sustainable growth with revenue growth outstripping loan origination volume growth, both in the quarter that just passed and what we expect to be in the quarters to come. Our second priority on the path to profitability is to continue to reduce our expenses and improve our operational efficiency with the goal of reaching adjusted EBITDA breakeven by Q3 2026, essentially within the next 12 months. 

With our Tinman AI platform, we have been able to automate time and labor-intensive components of the mortgage process and continuously reduce our cost to originate to approximately half of the industry average. Over the coming 12 months, we expect to drive that even further to have it reach approximately 1/3 of the industry average and then continue to keep growing as the consumer adoption of AI and interaction with AI continues to improve our ability to take costs out of the manufacturing process of mortgage. 

While we expect loan origination expenses will increase as we grow volume, 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 unit economics. 

Lastly, our third priority is to continue diversifying our product and platform distribution channels. We serve the end consumer now, both through our direct-to-consumer model and through our AI platform model, which includes Tinman as a platform and Tinman as a software. In our D2C business, we serve the consumer directly on better.com. We were founded on revolutionizing the consumer experience for the home finance process. And as such, our D2C business has always been at the forefront of pushing the envelope on what technology can execute in the mortgage industry. We have funded over $100 billion in loans on the D2C platform, which has served as a basis for training the AI and continuously creates a positive feedback loop, improving each and every day. 

Our D2C business allows us the opportunity to roll out and test new AI features at a scale and with a speed that others simply cannot match. And within our D2C unit channel, our unit economics continue to improve as we continue to drive AI throughout the entire process. As you can see in the earnings deck that we've distributed along with our materials, our contribution margin or per loan profitability has continued to increase as the operating cost of fund has continued to decrease, driven by both conversion gains and the implementation of AI in the sales and operations workflows. 

More specifically, in Q2 2025 for D2C, revenue per loan was $78.86 per loan. Our cost per fund was $68.22 for a contribution profit of $1,064 and a contribution margin of 13%. Again, we have continued to optimize our pricing so that we remain competitive with the major players in the market. But as you can see, our total cost to originate is about half that of the mortgage industry average, which includes our customer acquisition costs. And we expect to continue to drive that down as we both increase conversion and lower CAC, and improve labor costs and thereby lower the cost to fund significantly. 

Next, we serve the customer through our Tinman AI platform, powering local retail loan officers across the United States, for which we continue to see early rapid growth. In this model, we are effectively serving as a platform provider and P&L partner in the mortgage origination process with nearly 0 customer acquisition cost because the mortgage retail loan officers bring their customers, their relationships, and their transactions to bear on our Tinman AI platform. We are quickly disrupting the traditional retail mortgage origination market by onboarding loan officers and branches onto our Tinman AI platform, empowering them to do more loans than they've ever done before, remove friction from their fulfillment process, and expand their capacity to help more customers through the lead flow that we generate from. We expect over time that these loan officers will be able to compress a staggering 80% of their back-office costs by using our platform. 

The market for the Tinman AI platform business is massive, and we are just getting started. For context, over $1.2 trillion of mortgage volume in 2024 was originated by retail loan officers and mortgage brokers on antiquated technology and high operating costs. Just 1% of that market would translate to $12 billion in new loan volume, with again, nearly 0 customer acquisition cost to better. We continue to make great progress on the Tinman AI platform with our first and now well-proven launch of NEO Powered by Better. We began production with NEO at the start of 2025 and have high aspirations for the road ahead. 

In Q2, we funded 429 million loans for 1,009 families with NEO Powered by Better, an increase of 164% and 176%, respectively, compared with the prior quarter. The unit economics of our Tinman AI platform are quite strong. Specifically, in Q2 2025, for every loan funded on the Tinman AI platform on NEO Powered by Better, we generated a contribution profit of $6,172 on a revenue per loan of $15,538, resulting in a contribution margin of 40% for the Tinman AI platform. As we are able to increase penetration of the Tinman AI platform's processes for the retail loan officers, we expect that margin to increase even further, enabling us to either compensate these retail loan officers more handsomely or help drive more profits for them and their branches over time, which we believe, combined together, create like a holy trifecta. 

Tinman AI platform enables retail loan officers to do more loans, serve more customers while working the same hours, and with a lower cost to fund, resulting in dramatic increases in profitability for their business versus being on a traditional retail platform or mortgage broker platform. It is this trifecta that is allowing us to recruit additional local loan officers from highly successful retail mortgage companies, including loanDepot, Nationwide, and Movement Mortgage, just to name a few. Just this last quarter, we onboarded loan officers from these companies that funded over $180 million last year in loan volume. And going forward, we expect to attract even more of these talented high-volume mortgage loan officers in the retail channel due to the superior technology and model offered to them by our platform. 

Furthermore, the specialized nature of these loan officers are broadening our reach into new loan types that are more nuanced or complex but come with higher margins. These loan types include nonconventional FHA, VA, and jumbo loans. As we continue to expand with NEO Powered by Better and the Tinman AI platform at large, we expect to do more of these specialized loan types with higher gain on sale margins and deeper efficiency through our tech. 

As we have proven the Tinman AI platform with NEO Powered by Better with the entire mortgage industry watching, we have been inundated with other mortgage teams and companies wanting to move their business to the Tinman AI platform. We see massive opportunity in the road ahead with other traditional mortgage originators and are making solid progress executing on a robust pipeline of future clients and partners. I'm proud of the independent achievements we have made with both our D2C and Tinman AI channels. And now to take it a step further, we are working to bridge the 2 together. 

I'm particularly excited by the testing we are now conducting, whereby our AI selectively matches preapproved D2C purchase customers based on a full set of parameters about them and the property that they're buying with localized NEO Powered by Better loan officers who are experts in their particular geographic areas. These loan officers also have terrific relationships established over decades with the realtor community in these markets, and so are able to easily integrate with the existing workflows that those realtors prefer. Once implemented at scale, we see the potential for a significant increase in conversion and incremental volume and revenue at very healthy margins for both the D2C business and the NEO Powered by Better business. 

While we are still in beta mode, we believe this approach can further improve the unit economics of our D2C business over time by generating revenue from customers who would otherwise have not converted on our online platform. In other words, these preapproved leads would have come in through D2C self-serve, realize that they prefer a high-touch experience with a local market expert, and thus been at risk of falling out. Now the AI is selectively determining on an individual basis if that lead would have been more likely to convert with a local market expert on the Tinman AI platform. And our matching algorithm will continue to learn and improve over the next 6 to 12 months, just in time for the 2026 purchase season. 

Just to give you a reminder, Better generates over 250,000 preapproved mortgage customers every year. When applied to our average dollar loan volume of nearly $300,000, this implies a total volume potential of $75 billion. And yet our total market share of actually funded purchase originations is currently less than 50 basis points. Our market share by home shoppers per year as a function of the amount of loans that we are preapproving is actually over 10x that, nearly 5%. This showcases the massive opportunity we have by opening a different method of conversion for the customers that come to us for a preapproval. 

And coming back to our multipronged distribution, we are serving the customer by also powering banks, credit unions, and other larger mortgage originators that are seeking to license our Tinman AI software to become more efficient and customer-centric. We have built a highly fine-tuned platform for our own business and customers, and we are now seeing demand from others in the industry to directly license our software to use in their own businesses.

 A lot of banks and credit unions are taking a refreshed look at the mortgage space as the regulatory environment is becoming more favorable. However, bank origination of mortgages has largely been unprofitable given their higher cost to originate. This is where our Timman AI software comes in. Our Timman AI software essentially provides mortgage in a box, enabling banks to not only use our software, but also gain access to underwriting resources and sales resources if they so desire. By using the Timman AI software, banks and credit unions no longer need to invest in a variety of different systems, pay millions of dollars in system integration costs, upfront costs, implementation costs, seat licenses, or any of those sorts of things. Gone are the days of 8 different software platforms sort of speaking to each other, stitched together by middleware, by consultants that charge hundreds of thousands of dollars just to integrate these systems, and with no unified data set for any type of machine learning to operate on. We are changing the industry altogether. 

What's more, our pricing model is fundamentally different. It is what is now coming to be in vogue amongst AI companies as outcome as a service. We are simply charging our customers on a funded loan basis so that their cost event for processing, fulfilling, underwriting, even selling a loan becomes directly tied to the revenue event and takes the risk out of the transaction for these partners, which is a massive differentiator to the traditional software pricing model in the mortgage industry and in financial services in general. 

We are pleased that our first bank partner on the Tinman AI software platform has begun funding loans on our platform. In this partnership, we are powering their entire mortgage platform from a software perspective, from click to close with their sales and operational personnel across the full range of products that they offer, including non-QM and other niche products entirely on Tinman. 

To get them up and running, not just for conforming FHA VA but also for niche non-QM products, took just under 3 months from LOI signing to loans flowing through our software. And we believe this can ramp to over $4 million a month in monthly revenue in the near medium term, based on the pipeline that we have. We believe an even larger addressable market exists within the mortgage ecosystem for a holistic one-stop software solution powered by the industry's leading AI engine, Tinman. 

To put the opportunity into context, over 5 million mortgages were built on the Encompass platform in 2024. To the extent that we can achieve even 1% penetration of the Encompass customer base based on our current pricing, we believe that could drive an incremental 50,000 new loans and $75 million of revenue at software margins to better per year. We have an extremely strong pipeline of partners who want to execute either their entry into the mortgage business or their growth in the mortgage business by leveraging the Tinman platform, which provides them the ability to scale nearly infinitely in terms of sales and underwriting without having to scale people, which is what the entire mortgage industry hurt from the bust that came in the period of 2022 to 2024. 

Most mortgage CEOs do not want to repeat what they had to go through during that time. And thankfully, Betsy enables them to have nearly infinite scale featured parity with a traditional loan officer doing refinances and the ability to flex up or flex down their marketing spend to meet the balance sheet needs that they have. That is unique to the mortgage industry. It is unique within consumer lending, and we are bringing that power across the board to some of the largest financial services companies in the United States. And again, we are excited to share with you as these partnership discussions mature and we execute and launch with these partners. 

So to recap, while our D2C business has always been at the forefront of pushing the envelope of what technology can do in the mortgage industry at its core, we are making great advancements in substantially broadening the use of Tinman, which is like years ahead of the industry through diversification on both the Tinman AI as a platform for other mortgage originators and Tinman AI as a software service to solve the mortgage industry's broken tech stack. 

Looking ahead to the second half of 2025 and beyond, the opportunity ahead of us has never been more exciting. We remain focused on enhancing our go-to-market with growth being our North Star, alongside with continued expense management, channel diversification, all with the goal of getting to profitability on an adjusted EBITDA basis in the next 12 months.

While we will continue to invest in building the leading AI platform in the mortgage industry, Tinman, to improve our customer experience and further drive down labor costs and make our platform more efficient and scalable, ultimately, the goal that we have is to now drive the business to profitability, and we hope to achieve that on an adjusted EBITDA basis within the next 12 months. 

Let me now turn it over to Kevin Ryan, our Chief Financial Officer, who will discuss the quarterly performance and our financial strategy going forward. Kevin?

Thank you, Vishal. As we've discussed on prior calls, even with the continued challenging market environment and heightened macro volatility weighing on our industry, we continue to make great progress towards our goals of driving increased volume and revenue, balanced with ongoing expense management and improved efficiency. Our goal has been to reach profitability in the medium term. We now have the pathway and visibility to guide to adjusted EBITDA breakeven by Q3 2026, driven by volume growth in our direct-to-consumer and Tinman's platform channels, per loan contribution margin continuing to improve, the continued expansion of higher-margin channels, including Tinman AI platform and Tinman AI software, pricing improvements, and continued corporate and vendor cost reductions. 

We would like to note that these growth opportunities come with varying levels of expansion and profitability profiles and will change based on the broader macroeconomic trajectory. As a result, our path to adjusted EBITDA breakeven is unlikely to be linear on a quarterly basis, and we do not anticipate the same level of burn reduction each and every quarter. 

In the second quarter of 2025, on a year-over-year basis, we grew funded loan volume by 25% to approximately $1.2 billion and revenue by 37% to $44 million, driven by funding more loans to both our D2C and Tinman AI platform channels. We had an adjusted EBITDA loss of approximately $27 million. By channel, second-quarter funded loan volume was 64% generated through direct-to-consumer and 36% generated through Tinman AI platform, along with B2B. By product, funded loan volume was 67% purchase, 20% second lien, and 13% refinance. 

On a sequential quarter-over-quarter basis, Q2 funded loan volume was approximately up 39% and revenue was up approximately 36%. This revenue growth was driven by increased volume from NEO Powered by Better, which is higher gain on sale margins. Our continued push towards increased pricing and a tailwind from a loan loss reserve release. We expect to continue to drive growth through Tinman AI efficiencies, distribution channel diversification, and optimized marketing while balancing these growth expenses with further corporate and fixed vendor cost reductions. 

Turning to expenses. During the quarter, total expenses decreased approximately 3% in Q2 compared to Q1. We continue building our Timman AI platform and Timman AI software channels, leaning into productivity-driven savings through AI deployment across the mortgage business and driving costs down further in our corporate functions. We are excited about using AI to drive the business towards growth and profitability, similar to the advances we experienced in 2016 to 2021, when we grew originations by over 100x. 

Now to touch briefly on our balance sheet and capital positioning. As we discussed on our last call, we closed a major debt restructuring with our partners at SoftBank in April. The accounting entries are a bit complicated and are laid out in the release. Big picture, we increased our GAAP equity by over $210 million, and we meaningfully reduced our corporate debt. We ended the second quarter of 2025 with $241 million of cash, restricted cash, short-term investments, and assets held for sale. 

In addition, we continue to maintain strong relationships with our financing counterparties with 3 warehouse facilities for a total capacity of $575 million as of June 30, 2025. We are particularly excited that the Tinman AI platform loan volume is continuing to grow in line with forecast, and we expect over $500 million of AI platform originations in Q3, which is growth of over 16% versus Q2. For the full year of 2025, we expect funded loan volume to increase year-over-year, driven by tailwinds from growth initiatives, including Tinman AI platform, offset by continued macro pressure and the loss of our Ally business, a roughly $1 billion headwind. 

In the U.K., we were pleased that Birmingham Bank grew its loan book by 90% in the second quarter sequentially versus the first quarter of 2025. While we continue to undergo efforts to exit our noncore U.K. assets, we expect the divestitures of 3 smaller noncore U.K. businesses to start being a benefit to our adjusted EBITDA in the second half of 2025 as a result of the dispositions. We expect further improvements to our adjusted EBITDA losses in 2025 as compared to 2024 through a combination of AI-driven improvements in conversion rates, efficiency gains, and continued corporate cost reductions. 

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

[Operator Instructions] Your first question comes from the line of Bose George with KBW.

Actually, when you talk about partners trying to enter the space using your technology, can you help characterize who they are? Are they financial companies who haven't figured out a way to offer the product effectively? Or just any color there would be great.

Sure. I think there's -- like within the space, let me define a couple of different partners that are entering. You have the next-gen wealth management companies who want to continue to scale the ladder to compete with the UBS, Charles Schwabs of the world, right, and become full-scale wealth management platforms. The one wealth product -- the one lending product every wealth management firm really needs is mortgage. And so we have partnered with one of the top 3 sort of robo-advisers investment firms and are beta testing a product. And we're seeing more and more incoming calls from folks like that who are -- have customer bases of anywhere between 1 million to 20 million customers who want to offer a mortgage or home equity product as an additional product to their wealth management offerings. 

The second is your traditional fintech lenders. All the big fintech 1.0 lenders that have dominated personal installment loans, have dominated BNPL, now significant customer bases, again, between 1 million to 10 million customers on these platforms. Those folks are now trying to figure out how to get into home equity. And the traditional home equity software product or software platforms are really nonexistent because the home equity market pretty much died after the global financial crisis and has only come back to life in the past couple of years. And there are really very few white labelable third-party origination platforms that are seamless across the full stack from click to close on home equity, and particularly those that don't require you to deliver the loans specifically to one takeout, one securitization takeout. 

So there are 2 or 3 other platforms that are licensing their software, but they require you to deliver the loans to a particular takeout. They don't necessarily let you hold the loans on your own books, all these sorts of things, or the fees charged are pretty exorbitant. So we're getting a lot of influx on that on the home equity side from those fintechs. And then the third is just the mega fintechs, the ones with the 20 million-plus customers, right, who basically missed the mortgage boom in 2020 and 2021, now see rates coming down and are starting to see customers have demand. And a lot of those need a very scalable solution. A lot of them have implemented AI on their own side for their businesses and are looking for solutions that can kind of provide infinite scale should the rate environment change. And so we're talking to those as well. 

And we're in beta with some of them. We've launched partnerships with some of them. And as those scale, we're really excited to talk to you more about them as they become a material source of our revenues.

And then when you talk about, Kevin, the cost to originate at the industry average and declining, how much volume do you need broadly on the overhead side just to have that benefit really kind of drop to the bottom line more meaningfully?

I think it already is. I mean if you look at Page 18 on our deck with respect to unit economics, where we are on D2C, right? I think D2C suffers from a high CAC and the way that CAC gets accounted for, particularly in terms of purchase loans, right, because CAC is sort of in period, but the loans take 6 to 9 months to make. But you can look at the labor cost per fund in Q2 2025 on D2C is under $2,500, and that compares pretty favorably to the industry's $6,500 to $7,000 of labor cost to fund. And our data cost per fund continue to come down as the conversion rate keeps going up. 

A lot of the time, we are pulling data on consumers, giving them a preapproval, getting credit income asset data that we're paying for, but they're not converting. So as we improve the conversion rate, we talked about in the call that we improved the conversion rate by almost 30% because of Betsy from the quarter. And you can see just right there, data cost per fund have gone down from $1,200 to $800. And we see room for that to continue to come down, both via economies of scale and continued improvement in when and how we pull the requisite data for the consumer. 

And then lastly, the gain on sale revenue has improved by almost 10% just quarter-on-quarter, again, being more responsive to customers, meeting them where they are, when they want to communicate with us has enabled us to have a less of a discount in terms of our product offering and improve our gain on sale on average. And so that's been beneficial. 

I think we -- just on the D2C, if we were just the D2C business alone, I think we'd have to double or triple the business to get to sort of breakeven based on where we are on contribution margin and where the burn is coming down to on a monthly basis. But with the B2B platform business, the Tinman AI platform business, the margins are a lot bigger, almost double or triple those of the D2C business. And there, we just need to kind of grow those and the volume to grow to similar amounts as what we're getting in D2C to achieve that breakeven, which is why I think for the first time in 4 years, we have transparency and dramatic line of sight into how to get to breakeven.

Your next question comes from the line of Brendan McCarthy.

Just wanted to start off on the lead-to-lock conversion rate with Betsy. You mentioned that increased meaningfully. I guess what's really driven that? And what are some of the dynamics behind customer interaction to really lead that improvement?

The biggest thing is expanded functionality by Betsy was going previously answering questions, getting missing data. Betsy is now able to take you all the way through lock and then even go and ask questions around processing, ask you about missing documentation. On the back end, Betsy is re-underwriting all the loans that the underwriters are doing, where they might have to suspend a loan or deny a loan post-lock. And so it's substantially improving the choices that consumers are getting and the intelligent workarounds with the variety of investors on our marketplace. So that's all driving greater efficiency. We're getting -- we're approving a larger percentage of our customers. 

We're finding solutions for them instantly, like, for instance, a consumer -- just as an example, a consumer is coming in and their debt-to-income ratio doesn't qualify them to get preapproved for a mortgage or for a refinance. But there's 2 debts there that they came in for a rate term refi, but there's 2 debts that if they also took out a little bit of cash, they could pay off, and then their DTI would qualify. Traditionally, for a human loan officer to make all those calculations is quite difficult. They're trained on sales, not on math. But Betsy is able to effectively instantly do that in our flow, and that's saving a pretty significant number of people and qualifying these people in a way that other loan officers and certainly other loan platforms simply don't do. 

A lot of this that we're doing actually is really interesting because we're learning from our retail loan officers, what are the things that make them more successful and able to both command a premium pricing in the market and effectively help more customers. And those same things that our retail loan officers are teaching us, we're now embedding into both our D2C workforce, but more importantly, into Betsy to help Betsy learn that functionality and do it for the consumer instantly.

I appreciate the insight there, Vishal. And turning to the B2B side, specifically Tinman AI as a software. Can you talk about that pipeline there? I know we had -- I know you had mentioned there was a small to medium-sized bank in the pipeline that may have been more near-term for a potential partnership. Any updates on that front?

Yes. We're pumping loans through that. It's really awesome. They're about $1 billion-sized bank in the mortgage business, and they're fully adopted. And we've been able to get them up and running in a way on a new software platform in mortgages, which typically takes 9 months and millions of dollars of consultants and integration costs, and they're up and running in less than 90 days. And as the volume that they pump through their pipes grows, we think that that can be a pretty significant revenue stream for us. 

We have a couple of other big partners in the pipeline, one of the top 10 mortgage companies in America. We -- many of the big fintechs that I mentioned earlier on a question on the call. And so we're super pumped about that software business and about empowering other mortgage companies or those in the fintech landscape to effectively use the software to originate loans in a way that's superior to the traditional sort of 8 different systems stack that most people have today.

Your next question comes from the line of Rayna Kumar with Oppenheimer.

This is Abigail Rutter on for Rayna. It sounds like the testing you guys mentioned is working pretty well. Could you guys provide any additional color here to expand on this opportunity? And then how do you expect it to work through the cycle?

Well, we expect it to be the software business to be a much higher margin business than even the platform business, which is a 40% margin business. I mean we've spent $1 billion developing the software.

The biggest players in the market have pretty significant or effectively monopolistic and have very significant chunky market share and started their lives out as Fay disk-based software. The biggest player in the market today still allows only one person to be in the loan file at a time. I mean, not pre-judgmentally, but what is the AI agent going to do? She's going to ask the loan processor to check out of the file, like it's a library book, and so that it can go in and make an entry or change of fact. It just -- I think it's just open hunting season on that front. We've hired -- made some recent hires to build that business out. And you'll hear from us in the very near future about some major contracts getting signed, implemented. And once they're up and running, we'll be able to talk about them. 

With respect to the potential size because of the fundamental difference in our model, where we're providing one full-stack solution, people will adopt it, and then they'll adopt it for 100% of their production. Initially, they'll use it parallel path with the existing incumbent solutions that are out there. They'll start with home equity, HELOCs, then they'll migrate more of the products over. And we're going through that entire process and defining the full value chain and the extractions. 

And yes, like I think if you look for us on social media, if you look for us on like LinkedIn, you'll see some of the advances that are coming out regularly in the software and with the partners that we're implementing the software for.

And then can you just talk a little bit more about the home equity business and that volume? And just any more color on kind of what drove or is driving that growth?

Sure. I mean we've had about -- from year-to-year, from Q2 '24, we did $90 million of home equity volume in Q2 '25, we did $240 million. That's 260% growth. I think we are the fastest-growing home equity lender in America today. And home equity has a lot of the same features that made us great in refi, like helped us grow from $500 million in refi volume in 2016 to $58 billion in 2021 in 5 years, 100x growth and which is that it's us and the consumer, we're able to provide the things that we do better than anyone else, make the process cheaper, faster, easier and do it in a marketplace fashion rather than in a delivering into a securitization shelf fashion, which means that we are able to deliver to multiple different investors and provide consumers the highest chance of getting approved, and that's allowed us to maximize our D2C margins and D2C dollars. 

So if you have originator X and they've got a pretty narrow criteria, they're delivering to a securitization shelf, they're constrained by the rating agencies. That's harder for them to change. And so then they buy a click online, they've got a chance of converting that click X percent. Similarly, if a mortgage broker refers a customer to originator X, then they've got a low chance of getting approved. Now if that same click online can convert at a better rate -- at a better approval rate, with better because we've got a marketplace at the back end, that makes our ability to grow on the D2C channel pretty substantial. Again, like we're at a $1 billion run rate on HELOC and home equity origination, and we started this product less than 2 years ago. And we're scaling that so fast, right? Last quarter, we were 148. So we've grown 35% plus on quarter-on-quarter on that product. 

So we're just -- we think that the market is massive, and it's got a lot of the features of the product are the things that we're really good at better here.

Yes. And I'll add that the consumer acceptance of the product is way up. It slowed down after the crisis, as Vishal mentioned before. But mortgage rates have stayed high, home appreciation since COVID has been very high. So that $1 billion can get to $2 billion quite easily. We're just going to keep pushing in that product because we think the consumer -- it can really help the consumer out this part of the cycle.

And also every HELOC, every home equity customer that we're booking today is a refi tomorrow when rates come down eventually. It's a 0 customer acquisition cost refi. And as you can see, on D2C customer acquisition cost is 45% to 50% of revenue for us. So when we take that out, as rates come back down, each one of these HELOC customers, we're going to be putting them into a cash-out refi or rate to refi, and that's going to cost us $0 in customer acquisition cost. So again, just onboarding consumers onto the better platform, warming them up for the refis that come. 

Your final question comes from the line of Eric Hagen with BTIG.

Can you talk about how the software maybe adjusts for or tailors around fluctuations in interest rates? Can the AI get smart about capital markets conditions to get ahead of the market, if you will? Like we all know that mortgage banks can be slow to respond to shifts in interest rates, but does the AI help augment the speed at which consumers are shown a rate based on what's going on in the market?

Yes, it makes it instant. It's now starting to write the alerts that go out to the consumers. It's enabling us to enter into features that will make trading interest rates or trading mortgages very similar to trading equities. And it's able to just manifest the best execution and reprice our products in a singularly faster fashion. So your traditional bank might take a while to update the rates on their site or through their distribution channels. Usually, mortgage bankers get daily rate sheets or best X. The AI doesn't need to do a rate sheet; the AI can go across all the permutations across all 45 investors across thousands of products instantly and find the best one that matches the consumer, fits their needs, and provide that range of options to them. 

It's a true game-changer. I think it's extremely underappreciated in this market where the price of credit continuously changes. And it's going to -- you're going to see sort of a Robinhood moment in this business in the same way that you saw it in equities.

Yes, that's really interesting. A follow-up on the conversion rate. I mean, can you share more specifics on how the Tinman platform helps retain the borrowers' attention and get it from the point of lead generation to the next phase? Like we know the platform is really good at lead gen, but how does it kind of systematically support a that stronger conversion rate, especially with the different entities that are using the platform?

Sure. So the Tinman platform has traditionally been really great at serving consumers that are -- have great credit, have good income, are comfortable with doing major financial decisions online, right? So like while the TAM in mortgage is huge, the TAM of consumers who are comfortable doing these things entirely online self-driven has always been smaller. And so what we've been continuously trying to do over this period of time is wherever that human assistance is needed instantly, to staff up for that with people is extremely expensive. right? Like someone would, for instance, say, abandon their application somewhere during the flow, right? 

Now we could build -- we've built triggers that enable us to know that this person abandon the application. But because all the labor in the industry, like the loan officers, all the salespeople, they all have to be licensed and then those licenses are on a state-by-state basis, unless you've got tens of thousands of people sitting around waiting for these triggers to happen, like and paying them on payroll, it's really hard with our low-cost D2C model to reach the consumer at the point of decision or reach the consumer at the point of indecision or fatigue or confusion. And now we're able to do that instantly and have an outbound call done by Betsy. As you can see, the interactions with Betsy have scaled up massively over the past 3 or 4 months, as it's just gotten better and better and better and gotten plugged more and more and more. It's almost organic now between Betsy and Tinman. 

And so it sort of is becoming one system with Tinman being sort of the calculation engine and matching engine, and Betsy being the support to the human, but in a lot of places, like the supplanting of the human, where the human is simply unavailable. And I think that that's really enabled us to continue to grow. I mean, like we grew unit volume 35% in the last quarter, and we subtracted people on the sales team.

That concludes today's question-and-answer session. I will now turn the conference back over to Vishal Garg, CEO and Founder of Better Home & Finance Holding Company, for closing remarks.

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 better mortgage, a better rate, and a better process, leading to both improving their financial stability and living a better life for them and their families. The past 5 years have been extremely challenging for us given the state of the market, interest rates, but now we're playing offense hard again, aggressively pursuing growth, monetizing the platform that we've built and the AI we've developed on top of it, and doing so independent of the broader economic and mortgage market conditions. We now have clear line of sight in how we win in the current environment with our advances in our Tinman AI platform and our Tinman AI software business and the improvement in unit economics, all together contributing to allowing us to clearly tell you today that we're going to be able to be breakeven as a business on an adjusted EBITDA basis in the next 12 months. 

I think that's the focus that you all should take away from this call. We now have a path out of a really terrible environment, and we have nearly infinite scale if the interest rate environment changes. Thank you for all your support. Thank you for staying with us, and we look forward to sharing a lot more good news with you over the coming year ahead.

This concludes today's conference. You may disconnect.