Q3 2025 Better Home & Finance Holding Co Earnings Call
Speaker #1: Ladies and gentlemen, thank you for joining us and welcome to the Better Home & Finance Holding Company 3rd Quarter 2025 results call. After today's prepared remarks, we will host a question and answer session.
Speaker #1: If you would like to ask a question, please raise your hand. If you have dialed into today's call, please press *9 to raise your hand and *6 to unmute.
Speaker #1: Tarek Afifi, Corporate Finance at Better. Tarek, please go I will now hand the conference over to ahead.
Speaker #2: Hello, everyone, and welcome to Better Home & Finance Holding Company's 3rd Quarter earnings conference call. My name is Tarek Afifi. On Better's Corporate Finance team, joining me today is Vishal Garg.
Speaker #2: Founder and Chief Executive Officer of Better. In addition to this conference call, please direct your attention to our 3rd Quarter earnings release, which is available on our investor relations website.
Speaker #2: 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.
Speaker #2: These expectations and assumptions are subject to risks, uncertainties, and other factors as discussed further in our FCC filings that could cause our actual results to differ materially from our historical results.
Speaker #2: assume no responsibility to update We 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.
Speaker #2: 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 available on the investor relations section of Better's website and when filed in our quarterly report FCC.
Speaker #2: on Form 10Q filed with the investor presentation. Amounts described as of and for Both of which are the quarter ended September 30th, 2025, represent a preliminary estimate release and may be revised upon our quarterly report on Form 10Q with the FCC.
Speaker #2: For more information as of and for the end of the quarter ended September 30th, 2025, we'll be provided upon filing our quarterly as of the date of this earnings report on Form 10Q with the FCC.
Speaker #2: I will now turn the call over to
Speaker #2: Vishal. Thank you, Tarek, and welcome to
Speaker #3: our 3rd 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 institutional partners.
Speaker #3: increasingly through our growing list of These partners include both local mortgage lenders and financial institutions, and we empower them with our 10-man AI platform to serve their customer needs better.
Speaker #3: In summary, over the last couple of months, we announced three new partnerships, which we see as deeply validating and believe will meaningfully expand our market reach across the home finance landscape.
Speaker #3: And drive profitability as we track to break even 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.
Speaker #3: In the next six months, we are comfortable that this will double to at least a billion a month in funded loan volume. Our progress comes mostly from our soft launch during which we have marketed the power by Better solution to only a small fraction of our partners' customer bases and seen great success.
Speaker #3: 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 10-Man, our pipeline of additional partners continues to expand rapidly.
Speaker #3: We expect to share further updates on these partnerships and additional ones in Q4. Our pipeline of 10-Man AI platform clients and partners keeps expanding as the industry is seeing what our platform can deliver.
Speaker #3: We are in late-stage conversations to land partners in some of the biggest, most strategic verticals in consumer finance. Examples include one of the top home improvement lenders, two of the top servicers in the country, one of the top personal lenders, and an additional mid-sized bank.
Speaker #3: 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.
Speaker #3: All of these events validate our strategy of diversifying our distribution channels. As our AI-driven platforms, Betsy and 10-Man, deliver the lowest unit costs in the industry while providing the best experience for both customers and partners.
Speaker #3: 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 one year or almost $5 billion a month.
Speaker #3: We have built a platform that is AI-first. We are one of the few players if single full-scale tech stack, all in one not the only one in the US with a 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 the future of this $15 trillion industry.
Speaker #3: Else, and really continue to define 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 10-Man AI merchants on the platform networks, similar to that of MasterCard.
Speaker #3: On the other side are investors 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 two sides of this network.
Speaker #3: Our engine is called 10-Man, 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.
Speaker #3: We have built a multi-sided matching engine, something that simply cannot exist outside of what we have built inside 10-Man. To contrast, most fintechs operate on a single path platform and distribute the product through securitization.
Speaker #3: With Better, the result for the consumer is a significantly higher approval rate and generally lower interest rates, because 10-Man matches consumer and property-specific attributes across a broad cross-section of the investors on our platform on a single loan-by-loan basis.
Speaker #3: Further, despite Better being balance sheet light and not taking any credit or prepayment risk, the default rate of our mortgages is one-third that of the industry volume over the past nine years.
Speaker #3: 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 10-Man, has learned average on over $100 billion of originated calls, 6 million approved customers, from over 12 million recorded phone 600,000 funded loan documents, and almost $5 billion pages of property and consumer data information.
Speaker #3: Place all in one end-to-end platform with all of the things that all in one were done by humans on those data, all in one place, and recorded through the platform.
Speaker #3: 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.
Speaker #3: Betsy communicates across voice, chat, text, and email with consumers nearly instantly to compute various scenarios and learns how to better understand consumers' needs every day through every interaction.
Speaker #3: 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.
Speaker #3: Betsy's 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 home consumer interactions per month, and remarkably good at detecting fraud throughout the entire platform.
Speaker #3: Additionally, Betsy the lowest possible interest rate across our network ownership journey, performing hundreds of thousands of of investors with the lowest post-closing defect rate in manufacturing a mortgage, approximately 19x lower than the industry average.
Speaker #3: 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 home ownership journey.
Speaker #3: 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%.
Speaker #3: 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 zero marginal cost, we expect to further improve our unit economics through cost efficiencies on a per loan basis.
Speaker #3: During the quarter, Betsy performed approximately 700,000 customer interactions and over 61% of locked loans with our AI underwriting approved a clear path to 75% in the near future and 90% after that.
Speaker #3: And our loan off-roaster increased to over 3x the mortgage industry median. We have been heads down over the past few years honing our technology and optimizing productivity in terms of funds per month the business for efficiency.
Speaker #3: With 10-Man and Betsy, we removed 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.
Speaker #3: 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.
Speaker #3: The majority of the mortgage market still operates on what was built in the 1990s, where eight different separate systems were integrated through dated middleware, old-school FTP servers, and disparate databases.
Speaker #3: over 80% market share, only allows one person to work in the loan file at any time, a file that costs the What's more, this dominant platform, which has mortgage industry more than twice as much as Better to Make.
Speaker #3: designed to disrupt industries like this, and AI was 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.
Speaker #3: 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 10-Man.
Speaker #3: 10-Man shines as a brand new modern tech stack with AI in action, delivering real tangible measurable results in a multi-trillion dollar industry at a fraction of the cost.
Speaker #3: our AI platform, one of the point solutions CEOs said to the then CEO, Fannie Mae, that he thought Better I often think back to when we were building was trying to boil the ocean.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: When you look back at the last time rates declined, Better grew its volume by over 100x over a five-year period and over 10x over a two-year period in 2020 and 2021.
Speaker #3: We're positioned to do it again, this time more efficiently and much more profitably. We believe we can achieve significant market share as this next cycle unfolds.
Speaker #3: Betsy and 10-Man 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.
Speaker #3: 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 10-Man AI platform.
Speaker #3: 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%.
Speaker #3: 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.
Speaker #3: 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 two years ago when we launched.
Speaker #3: Our model does not require us, unlike many others, to take any credit, prepayment, or liquidity risk because we 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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.
Speaker #3: 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 three new transformational partnerships and engaging with additional partners in our pipeline.
Speaker #3: 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.
Speaker #3: With 10-Man 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.
Speaker #3: I'll now turn to quarterly business developments. Unit Economics and our direct-to-consumer channel continue to improve with revenue per fund increasing to $8,300, while the labor cost of 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.
Speaker #3: contribution margin of Resulting in a net $1,772 per fund, compared to $1,064 per fund last quarter, an approximately 64% increase quarter on quarter. We have not seen these types of contribution margins since like 2021.
Speaker #3: 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 10-Man through our partnerships.
Speaker #3: We are very excited to have recently announced three new partnerships that we see as deeply validating the 10-Man AI platform and believe will meaningfully expand our revenue and drive to profitability in the year ahead.
Speaker #1: Under this agreement , our partner will offer home financing products to its end customers using the Tin Man platform on a fully label white solution , and we will earn revenue .
Speaker #1: On our per 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 .
Speaker #1: 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 in being in the mortgage business or offering mortgage business mortgages to their customer base , will dive right in with our mortgage broker in a box , Tin man AI platform .
Speaker #1: We've brought this partner from being just a fintech to a fintech plus mortgage broker . There will be no upfront cash spend required by better , as our partner will programmatically feed customer data into Tinman from their Tinman will manifest offers delivered through our partners app , which has tens of millions of monthly active users , all nearly instantly and updated daily .
Speaker #1: 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 five US non-bank mortgage loan originator by migrating from the incumbent solutions that they've traditionally had for years , if not decades , onto tin men .
Speaker #1: Our partners loan officers will dramatically scale their ability to service customers eligible for HELOC and loans within their customer base . They'll also be able to mine there .
Speaker #1: MSR book of over $300 billion to offer Helocs and to loans those customers on a programmatic basis in a way they've never been able to do with the HELOC incumbent solutions that are available to them today .
Speaker #1: 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 .
Speaker #1: It's important to note that we are not just processing customers who raise their hand and ask for a home product . Rather , we are fully integrating Tinman both into of our partners customer data loads and CRM systems .
Speaker #1: 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.
Speaker #1: We are also completely agnostic to the user it an interface , be iPhone app or a human loan officer in a branch . We serve all of them .
Speaker #1: Third, we partner with Finance of America, an industry-leading reverse mortgage lender, with access to millions of customers who are typically home equity rich.
Speaker #1: But cash flow disadvantaged . Together we are launching the first HELOC and loan product offerings to their customers , powered by our Tinman AI .
Speaker #1: 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 .
Speaker #1: 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 .
Speaker #1: 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 US experiencing rapid growth .
Speaker #1: Tinman The AI platform approach to local retail Mortgage loan officer teams is similar to how Amazon opened its DTC model to a third party seller marketplace Similarly , better is .
Speaker #1: 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 .
Speaker #1: We near zero customer have acquisition costs on this channel and as partners , fund loans on our platform . We earn a platform fee and a share of profits .
Speaker #1: We've grown this channel from zero just nine 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 .
Speaker #1: 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 .
Speaker #1: The savings go straight to their bottom line , allowing them to reinvest in their customers . Offer lower rates , and close more deals within their local markets .
Speaker #1: Further , we've designed an optimization path to retain customers entering through the direct to consumer lose to otherwise channel an outside local might officer loan by identifying customers who would benefit from more personalized local support .
Speaker #1: We connect them early on with a partner loan officer . Instead of losing them to competitors . Later on . This significantly boosts rates and in customers amongst these turn strengthens our approach flow .
Speaker #1: unit economics overall During the third quarter , we funded approximately 483 million in funded loan volume for 148 families on the Tinman AI increase platform and of 13% , respectively , compared with the prior quarter .
Speaker #1: coming back to our And multi-pronged 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 re-enter the mortgage business .
Speaker #1: our As 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 Medal .
Speaker #1: A lot of banks and credit unions are taking a refreshed look at the mortgage space as a regulatory environment is becoming increasingly favorable .
Speaker #1: However , bank origination of mortgages is largely been unprofitable given their high cost to originate . This is where our Tinman AI software comes in .
Speaker #1: 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 .
Speaker #1: they so If 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 to what similar a lot of the leading AI companies in Silicon Valley are doing .
Speaker #1: Over time , we expect this channel to be the most profitable of our three channels with SaaS plus level margins . Since most of the costs this initiative associated with have already been spent on developing Tinman internally for our direct to consumer business .
Speaker #1: Our existing bank partner on the Tin Man AI software platform is ramping as we power its entire mortgage business origination from close across click to multiple products and across multiple channels .
Speaker #1: 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 .
Speaker #1: 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 .
Speaker #1: and Land 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 .
Speaker #1: 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.
Speaker #1: 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 .
Speaker #1: We remain focused on enhancing our go to market strategy , with growth being our North Star alongside continued expense management and channel diversification .
Speaker #1: All with the goal of reaching break even 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 .
Speaker #1: economics , are Unit prolonged contribution margin continuing to improve as we into AI further lean efficiencies ? The scaling of higher margin partnership channels , including Tinman AI Platform and Tinman AI software pricing improvements and continued corporate cost reductions .
Speaker #1: unit economics are already profitable at the contribution margin level , increasing volume will offset allow us to additional corporate expense . We note that these growth come with varying opportunities levels of expansion and profitability profiles , and will change based broader on the macroeconomic trajectory .
Speaker #1: result , our path to As a EBITDA break even adjusted is unlikely to be linear on a quarterly basis , and anticipate the we do not same level of burn reduction each and every quarter .
Speaker #1: third quarter , During the we had an adjusted EBITDA loss of approximately 25 million , down from 27 million last quarter and 39,000,001 year ago .
Speaker #1: In particular , for the three large we a signed , we had significant amount of resources and sales operations and technology dedicated to launching those partners that were not revenue generative but will create significant growth in the years ahead .
Speaker #1: 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 .
Speaker #1: 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 .
Speaker #1: In addition, we continue to maintain relationships with our three financing counterparties, which provided a total capacity of $575 million as of September 30, 2025.
Speaker #1: We expect that our partnerships recently announced require us to increase those warehouse lines accommodate the meaningfully to expected funding demand on capital positioning , we rightsized the capital structure earlier this year , retiring $530 million of approximately convertible notes for $110 million cash payment and $140 million note , generating $211 million of positive equity .
Speaker #1: As announced in our achei , our CFO Kevin Ryan will concluding his be 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 .
Speaker #1: wish him We 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 .
Speaker #1: In the UK , we were pleased that grew its Birmingham Bank loan book by 44% in the third quarter , sequentially versus the second quarter of 2025 .
Speaker #1: As we have implemented our technology stack into the bank and in doing so , enable the bank to become the fastest growing specialist mortgage lender in the UK .
Speaker #1: With respect to our non-core UK assets , we continue to exit those positions and expect these divestitures to continue to benefit our adjusted EBITDA through the remainder of 2025 .
Speaker #1: our Turning to 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 for Q3 the full year 2025 , we expect total funded loan volume to increase year over year , driven by initiatives growth including tailwinds from Tinman AI platform , offset by continued macro pressure and loss of our ally business .
Speaker #1: $1 billion headwind expect We A improvements to adjusted EBITDA losses for full year 2025 versus full year 2024 through a combination of AI driven improvements and conversion rates , efficiency gains and continued corporate cost reductions in the medium term .
Speaker #1: While we expect DTC 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 three years building for this moment .
Speaker #1: 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 zoom over a call .
Speaker #1: And I thought to myself, how can we make this accessible to everyone? How can we take this Four Seasons experience that the Neo team delivers and deliver it at a Four Points price to the average consumer?
Speaker #1: 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 with things today .
Speaker #1: We believe Betsy than is better 80% of the typical loan operating today . officers I'm so excited to demo our AI Mortgage Advisor today , which is able to replicate the experience of being in a branch or on a zoom call with someone with ten , 20 , 30 years of experience with a deep knowledge base .
Speaker #1: 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 .
Speaker #1: One American families are still fundamentally insecure and unknowledgeable about launching Mortgage . We'll be Advisor in a pre-release , and you up to join can sign us at better.com Please take .
Speaker #1: a look and let me let us know what you think .
Speaker #2: Hello , my name is Ryan Grant . How are you doing today ?
Speaker #1: Whoa . talking AI Am I this you , Ryan ? What happened here
Speaker #1: Whoa . talking AI Am I this you , Ryan ? What happened here ? Hey ,
Speaker #2: it's actually me . Ryan's AI advisor . Kind of like having mortgage Ryan's brain and mortgages . better Tech all rolled into one , ready to help you anytime .
Speaker #2: What can I do for you today ?
Speaker #3: Whoa whoa whoa whoa . Like , what did you do with Ryan's brain ? Like , you .
Speaker #3: what did Give it ? Like this ?
Speaker #2: I get it , it sounds wild . Basically , I'm Ryan's expertise combined AI with tech . any time help you So I can with mortgage , calculations , and questions advice .
Speaker #2: Just like he would . But instantly and clock around the . No worries . Ryan's still around . But I'm here to make things easier for you .
Speaker #2: What to know would you like or talk about ?
Speaker #3: Okay . I mean , that's interesting . Like , can you tell me a little bit about yourself , like , do you have a lot of this or experience doing did they just get like some guy off the street ?
Speaker #2: I'm Ryan's years of . He's personally funded built on nearly experience mortgages and helped of thousands homeowners . So $2 billion in all that know how .
Speaker #2: Plus better mortgages , smart tech to guide your you through confidence and mortgage journey clarity . Think of me as Ryan's brain , but always ready to help you any time you need .
Speaker #2: What's your biggest question or your goal with mortgage right now ?
Speaker #3: I mean , I think rates are coming and I down mortgage got this two years ago , and I think I can save some money right .
Speaker #2: That makes sense . Refinancing to save is a smart move . If rates have dropped since you got your mortgage to see how much you can save , to know I'd need your current rate , your interest remaining loan balance , and how many years you have left on your mortgage .
Speaker #2: You share those can details?
Speaker #3: no . So I think Yeah , I have a $500,000 left on mortgage . my got it I two years ago , literally , like in September of 23 .
Speaker #3: And I think like , you remember exactly what rate was , my know , I don't but it was like in the 7% something range .
Speaker #3: Maybe you can help me figure that out . Like , yeah , got .
Speaker #2: You It . have about $500,000 left in your loan . Started around September 2023 with a rate around 7% . I can estimate your savings based on that happen to know .
Speaker #2: current Do you principal monthly and interest payments ? If not , no worries . I can estimate that too .
Speaker #3: Yeah , I know , it's like on autopay , so I don't know exactly what it is . So yeah , have an if you estimate that would be great really .
Speaker #2: Your current loan is about 7% with a in balance 28 years $500,000 left . And your monthly payment is roughly $3,398 .
Speaker #3: Oh that's Got
Speaker #3: close .
Speaker #2: Let's start it . with the gives you option that the lowest monthly payment by paying points front up option lowers . your This interest rate , so your monthly payment goes But down .
Speaker #2: some cash you'll pay at closing . Sound good ?
Speaker #3: yeah . Let's find out . Yeah , Sure .
Speaker #2: Here's the lowest monthly payment option with points. Your new rate would be about 5.13%. Your monthly payment would drop to around $2,722, saving you about $676 each month.
Speaker #2: But it comes with points costing about $12,907 . Up front . Would you like to hear about the par rate option with lower closing costs to .
Speaker #3: Yeah , yeah . Why not ? Like , you know , I'm not sure if I've got just 12 grand lying around .
Speaker #2: The option means no points up front , so your closing are costs lower . Your be about 5.99% . The monthly rate would payment around $3,053 .
Speaker #2: Still a bit lower than your current payment . Saving about $345 each month . higher It's a bit monthly , but you keep more closing .
Speaker #2: Still a bit lower than your current payment . Saving about $345 each month . higher It's a bit monthly , but you keep more cash at Sound like something you want to more explore ?
Speaker #3: no . Yeah , Like , isn't there a way ? Like I heard , like you can just roll the like closing costs into like , the mortgage , like at closing .
Speaker #3: Is possible here that ?
Speaker #2: Yes . You can often roll closing costs into your new loan balance , which means you don't pay them out of pocket at closing .
Speaker #2: That comes with a usually slightly higher interest rate , like the par rate option I just mentioned . So your monthly payment might be a bit higher , but you keep your cash up front .
Speaker #2: Does that sound like a good fit for you ?
Speaker #3: no , I Yeah , think I'm going to go with a lower monthly payment like $700 a month of savings is like a lot more than $350 a month of think that savings .
Speaker #3: be really good for So I flow . So what do I my cash next ? need to do Like how does this work ?
Speaker #2: Great choice . Saving about $700 a month can really help your flow . The cash next step is to start your refinance application so we can lock in that lower rate and get the process going .
Speaker #2: you please Could spell your first and last name for me ?
Speaker #3: yeah . Wait wait Yeah , wait . Can I talk to the real Ryan to like . Or is it just going to be me and you all the time ?
Speaker #3: get I it .
Speaker #2: I totally get wanting to chat with the real Ryan . He's a great guy . I'm here to help you . Any time with quick answers and guidance .
Speaker #2: But if you ever want to connect with Ryan directly , I can help make that happen . Once we your get application moving things are along .
Speaker #2: Sound good ?
Speaker #3: All right ,
Speaker #3: listen , you know , I'll get the application going and . And then why started and , like , figure out some time to talk to the real Ryan ?
Speaker #3: It'll be interesting to see whether he knows as much as you do .
Speaker #2: sounds That solid like a plan to get started . Could you please spell your first and last name for me that way I can set up your application and we'll be on our way .
Speaker #3: Okay . It's Vishal Garg . And why don't I do the rest of this online and then we'll , you connect later . All right .
Speaker #3: Talk soon . Bye .
Speaker #2: Thanks , Michelle .
Speaker #4: We will now begin the question and answer session . Please limit yourself to one question and one follow up . If you would like to ask a question , please raise your hand .
Speaker #4: Now . If you have dialed in to today's please press call , nine to raise your hand and star six to unmute . Please stand by while we compile the Q&A roster .
Speaker #5: Your first question comes from the line of Owen Rickert with Northland . Your line is open . Please go ahead .
Speaker #6: Hey , thank you my for taking here . I guess quickly , can you just dive a bit deeper into the three recent partnership announcements and how you expect each of these to ramp up as we head into 2026 ?
Speaker #1: Sure .
Speaker #3: So .
Speaker #3: Respect large to the With . financial .
Speaker #1: We expect that services will ramp on the platform.
Speaker #3: Up .
Speaker #1: Over time over the next six months .
Speaker #3: Specifically as .
Speaker #1: We increase the penetration of their users in their app . That see the us and the number of offers from users every day that they drop into Tin Man to surface offers for .
Speaker #1: And those will offers via stories in their app notifications , text messages , things like that . And so we're just going to increase those .
Speaker #1: And we've created a specific pod for this partner because it's such a large partner . And we need to staff that into pod .
Speaker #3: And so .
Speaker #1: 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 a bit for us to .
Speaker #1: of time also up and see is going to ramp required , what of that percentage partners , labor customers are comfortable what what percentage of that partners an AI , need to customers talk to a person ?
Speaker #1: So we're working all of that out with respect to the . other partnerships large . The originator , we're going to start first with direct to consumer team .
Speaker #1: Then we're going to start . rolling it out to the team that does MSR and MSR recapture . And then there we're going to start it out to their from loan officer teams .
Speaker #1: All around the country to market Helocs and loans to . And so there's going to be a ramp in that regard as well over the next six months or so .
Speaker #1: And then with finance of America , we are launching the HELOC and loans first to their customer base , then to their partner originators , and then across to their wholesale wholesale channel .
Speaker #1: And then with finance of America , we are launching the HELOC and loans first to their customer base , then to their partner originators , and then across to their wholesale wholesale channel . And so I think that is take also going to , you know , another 3 to 6 months to fully ramp up as well as the second , you know , the reverse second line HELOC product , which we're rolling out in beta right now , which we're going to then ramp up across their entire network .
Speaker #6: Got it . Thank you . And then secondly , you did hit on this pretty early on in the remarks . prepared But how would you characterize the future partnership pipeline right now ?
Speaker #6: And what does that look like today ? And maybe how is this pipeline , how has it last evolved over the few months ?
Speaker #1: I think as as our partners are able to see how fast we're able to implement of the some earlier partners that we have now launched , the quality of user the experience , the ability to , know , get approved for a mortgage programmatically , the ability to take something that traditionally has been very passive and sold these passively by partners , and then have that be done in an active algorithmic way .
Speaker #1: The partner pipeline has really , quite frankly , exploded . And so we are seeing a lot of demand . The other just from a macro perspective , the largest incumbent solution has been forcing has been going through an SDK change and has been forcing reintegration with all of its partners for its clients .
Speaker #1: 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 looking and are for something new .
Speaker #1: And so I think , you know , it's sort of like luck is when preparedness meets opportunity . And I think , you know , we're pretty thankful to be in the position that we're in now .
Speaker #6: Thanks , Great . Michelle .
Speaker #5: Your next question comes from the line of Brendan McCarthy with Sidoti . Your line is open . Please go ahead .
Speaker #7: Great . Good morning . Good morning everybody . I really appreciate the demo . There with Ryan . I thought I thought that was great .
Speaker #7: Just wanted to start off circling back to the new partnerships , particularly the the one with the top five US personal financial services platform .
Speaker #7: Can you give us detail on what the ultimate volume opportunity looks like there ? You know , 50 million customers is obviously a huge number .
Speaker #7: Just curious as to as to what you think the addressable market is in terms of volume .
Speaker #1: Yeah . So I mean , if you . go to ChatGPT and you type in what is the mortgage penetration rate for financial institution in the United States with 50 million customers , it will tell you the , the , you know , it ranges from ten basis points of that customer base to 15 basis points of that customer base .
Speaker #1: So let's use like , you know , 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 average times an balance of like $400,000 , gives you about 24 billion .
Speaker #1: So I don't know exactly what the number is . I'm not committing to that number . But that's sort of , you know , 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 .
Speaker #1: If we're able to sort of algorithmically mine and surface offers directly to in consumers their mobile app .
Speaker #7: Understood that . That's very helpful . Thank you for that . next question . Just looking at the at the guidance , you know , really implying strong growth there .
Speaker #7: I think from your it said I think the 500 million monthly loan volume run rate to about a billion . Just really a step up there .
Speaker #7: What's really underpinning that , that outlook is is it , you know , just strictly the partnerships . Is it a growth and DTC .
Speaker #7: Is there any interest rate assumptions there ? Just curious as to kind of what's underpinning that .
Speaker #1: we're assuming No , interest rates stay the same . And yes , I mean , as you can see in DTC , we have been focused on making more money per loan in DTC rather than growing volume .
Speaker #1: The volume has grown pretty substantially , especially if you take out , you know , on a quarter on a year on year basis .
Speaker #1: If you take out the volume that we had last year , you know , organic growth has been over 50% in , you know , and so when you layer that on , if there's a rate cut , I think DTC is going going to fly .
Speaker #1: 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.
Speaker #7: Great , great . Thanks . That's all for me .
Speaker #5: Your next question comes from the line of Kartik Mehta with Northcoast . Your line is open . Please go ahead .
Speaker #8: Hey , good morning Rachel , how are you in the press release ? You indicated that you anticipate about $1 billion of loan volume in the next .
Speaker #8: At the end of six months . Because of these partnerships , does that assume that these each of partners will be fully ramped or are you anticipating the ramp to take longer ?
Speaker #8: So really , the billion dollars could be a lot more once the partnerships get fully integrated .
Speaker #1: I think it could be a lot more than once they get fully integrated .
Speaker #8: And then just, you know, the proof per funded contribution margins increased significantly. The one volatility is in the back. So I'm just curious, what's your anticipation for cash as we move through 2025 into 2026?
Speaker #8: I'm assuming they'll start trending lower as the partnerships become a bigger , bigger part of the loan volume . But wanted to get your perspective on that .
Speaker #1: Yeah , I mean , with the partners , there's no cash , right ? There's no upfront no upfront cash . The the the DTC , KAC remains quite high .
Speaker #1: You know , purchase , you know , which remains challenged in this market environment . You're you're spending money this quarter to book loans in six months , 12 months , 18 months .
Speaker #1: When the consumer actually buys the house and books the loan . I think one thing that maybe underappreciated about better is over the past three years , we've given out over a million pre-approvals 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 .
Speaker #1: so that kak , you And know , that you see there is elevated because for all the consumers that are not able to find a or that house they want to buy , you know , we basically eat that kak in that specific quarter .
Speaker #1: But then when that consumer finds the house , they want to buy , then when they come through , then then you know , it , it shows as lower kak .
Speaker #1: And so the mortgage industry , a customer acquisition cost problem is even further compounded long by the gestation cycle of , you know , consumers on the internet .
Speaker #1: And when they get pre-approved and when they actually find a house . So , you know , we do expect as rates , if rates come down , that , you know , the kak will come down materially across the board for purchase or for refi .
Speaker #1: I mean , just to give you some context , when in the last rate cycle , when rates were coming down are kak on Aretha was $1,000 loan and so there's a , there's a , there's a lot of positive convexity in , in the kak as consumers , you know , as the rate environment changes and consumers propensity to get pre-approved and then actually fund increases .
Speaker #8: Perfect . Thank you very much . I really appreciate it .
Speaker #5: Your next question comes from the line of Boz George with KBW . Your line is open . Please go ahead .
Speaker #9: Hey good morning guys . This is actually Frankie on for Boz . Nice to see you . Start with can you just walk through the ways in which AI efficiencies can increase revenue per funded loan in slide 16 , you noted that this will be driven through enhanced sales and operational performance .
Speaker #1: So yeah , I .
Speaker #9: Think that yeah .
Speaker #1: 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 betsey's able to supplant the loan officer .
Speaker #1: Whenever the loan officer is not able to , you know , either pick up the phone , answer a question , turn new pre-approval based around a on , you know , data that the consumer has provided .
Speaker #1: You know , Sunday afternoon , 4:00 , they want to put in an offer that they saw , you know , betsey's there for them in a way that , you know , traditionally , you're your your human loan officers , isn't able to be .
Speaker #1: And so that's enabled us to one , you know , make our competitive pricing . And , you know , slightly less competitive .
Speaker #1: And you know , increase the gain on sale . Number two , as our volumes are going up and , you know , 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% .
Speaker #1: And expenses actually stayed the same . And therefore the , the burn came substantially by down like about 35 , 40% . And so that's sort of how betsey's allowing us , it's allowing us to be more responsive , which means lower discounts , superior service , really build the service offering for consumers .
Speaker #1: And then on the flip side , you not have to hire as people as we scale , volume and automate the processes like processing loans , underwriting loans , closing loans that traditionally have been done by people .
Speaker #9: Great . Thank you . That's very helpful . And then can you just help us understand what types of incumbent solutions you're replacing in your partnerships ?
Speaker #9: Is it both the loss system and POS system ?
Speaker #1: 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 .
Speaker #1: You know , we'll take all of the other stuff we generally do replace the incumbent loss many . And in cases , we replace the POS .
Speaker #1: The loss , the pricing engine , the CRM system , the document generation engine , the the notary , you know , and closing engine .
Speaker #1: And the warehouse , you know , the warehouse software we're . So like when the client signs up with us , they we we might replace as many as 8 to 10 different systems that the client has .
Speaker #9: Awesome . Thank you . That's all for me .
Speaker #5: Your next question comes from of Mikael the line Goberman with citizens GMP . Your line is open . Please go ahead .
Speaker #1: Hi , Mikhail , you're on mute . I think question you have a .
Speaker #10: was sorry about that . Thank you . No problem . Good morning . Thanks for taking the question . If I could ask about expenses .
Speaker #10: And I appreciate the comments , prepared remarks about the expenses and and how you're planning to deal with the the partnerships with regard to that going forward .
Speaker #10: you I believe mentioned a target for the first quarter of next year . Is there any sort of a number or run rate that we can put on that ?
Speaker #1: No , I think we , you know , we're hoping that , you know within the , next six months , we we get to $1 billion a month origination run rate .
Speaker #1: I think , you know , 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 .
Speaker #1: 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 , you know , legacy contracts and things like that that we need to kind of continue to still beat out , you know , 3 or 5 year contracts that we signed back in 2020 , 2021 that were like working to sort of , you know , reset with more AI driven type solutions .
Speaker #1: I think there's there's still a lot of cost savings left , which is why we're we continue to drive to , you know , achieving profitability while , you know , growing scale at the same time , you know , by Q3 2026 .
Speaker #10: Great . Appreciate that . And if I can fit in , just your general thoughts on the stability and strength of the mortgage and with with interest rates and sort of wobbles , I guess you could say with the economy a little bit , just your general thoughts on , on , on consumer , you know , the , the borrower and the consumer and how the whole , the whole system is , is developing going forward .
Speaker #10: Thank you .
Speaker #1: Yeah . No , I think look , I really believe that we're headed into a recession . I believe you know , that , that's going to result in a couple of things from a macro standpoint .
Speaker #1: I think there's , you know , 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 past over the 4 or 5 years who missed out the 2019 to 2021 rate environment .
Speaker #1: And they are have up their savings , been building they're looking and , you know , a lot of them who have owned equities in the past couple of years , they've been building up wealth to go and buy a home .
Speaker #1: I So think that you're going to see purchase originations , mortgage stay sort of where they are . You might not the boom that you did in have like 2020 and 2021 .
Speaker #1: If we have a real recession . And then on the flip side , you know , there's there's like 20 million people that can start to save money as rates go below 6% .
Speaker #1: do If we actually enter into a recession . And I think that that's significant pretty . 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 .
Speaker #1: know , You home equity originations still such a small number compared to what they were financial Pre-global crisis . You know , where they are or know , , you 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 .
Speaker #1: And for I think us , you know , we have both the secular tailwinds of a very competitive business model in DTC that we are now , you 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 ?
Speaker #1: 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.
Speaker #1: Right ? To satisfy the consumer . Just keep on grinding away at that . And so that I think , is is super meaningful .
Speaker #1: And we'll continue to drive both unit economics and growth in the DTC channel. And then when we're taking on partners that we're taking away from incumbent platforms, quite bluntly, we're stealing market share.
Speaker #1: And so , you know , and then that's the fastest growing part of our business . And so there , you know , if the mortgage market stays the same , if it's whether it's a trillion and a half in originations or 2.5 trillion in , of course , we'd love it to be 2.5 trillion in originations .
Speaker #1: But you know, we're moving partners from incumbent solutions that are, you know, built in the '80s, '90s, and 2000s onto our tech stack.
Speaker #1: They're , you know , we're relatively agnostic to the cycle . And if the cycle comes our way , then that's even better .
Speaker #10: That's great color . Thank you very much .
Speaker #5: Your final question comes from the line of Doug Harter with UBS . Your line is open . Please go ahead .
Speaker #11: Hi , Doug .
Speaker #12: Thanks , Vishal Garg . Good morning . I was hoping you could talk about , you know , as you're guided to to getting back to to to break even and to profitability , you know , what type of volumes do ?
Speaker #12: you do You need to to accomplish that ?
Speaker #1: I think depending on the mix , you know , I think we get to a billion plus . And , you know , we have a we have a good shot at it .
Speaker #1: Obviously , the margins in our partnership business are higher than that in our DTC business . But , you know , even DTC is getting to a place where the margins are pretty healthy on a contribution margin basis .
Speaker #1: But yeah , you know , I think we get to a billion plus . And then , you know , depending on the mix , we get to beyond that , I think month , I per think you have a , you know , a very , very , very good business that's driving towards breakeven .
Speaker #12: And then can you talk about is there . Different revenue that you're generating with partners for , for a home equity origination versus a , traditional first , first lien mortgage ?
Speaker #1: Yeah , I think home equity originations I mean , you know , the loan amounts are much smaller . But the gain on sale is higher .
Speaker #1: And , you know , between the gain on sale and the fees , you know , you're making , you know , on the mortgage side , you're making maybe eight grand a loan and the home equity side , you're making like $6,500 a loan .
Speaker #1: I think it's very important to remember in both of these cases, we're not retaining the mortgage or the MSR. We're not taking credit risk.
Speaker #1: 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 .
Speaker #1: There are other people in the home equity market selling their 107 , or loans at booking a gain on sale at 107 . We're at 103 and a half , so there's a long way to go in bridging that gap .
Speaker #1: But you know, when those people are booking those loans at 107, they're taking principal prepayment risk. They're taking credit risk.
Speaker #1: They're booking resists all that sort of stuff . If you like comparing apples and apples basis on a pure marketplace basis , I think we're getting a pretty good deal .
Speaker #1: I think But we're probably still have another point or two that we can squeeze out on our home equity originations .
Speaker #11: Great .
Speaker #12: Appreciate it. Thank you.
Speaker #5: There are no questions at this time . This concludes today's call . Thank you for attending . may And you now disconnect .