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Market Pulse is a monthly podcast by Equifax, in partnership with Moody’s Analytics. Equifax hosts bring you interviews with industry experts on the latest economic and credit insights that can help drive better business decisions. Whether you’re in financial, mortgage, auto or another service industry, we help make sense of the latest economic conditions that impact you. This podcast series supplements our Market Pulse webinars, which occur on the first Thursday of each month.
Hello and welcome to a special edition of the Equifax Market Pulse podcast recorded here in Las Vegas at the MBA Annual 2025 conference. I'm Tanya Cleve, SVP of Solutions Sales for Equifax. And today we're diving into technology and innovation and how data workflows and automations are driving real change for lenders and how they manage their operations, borrower experiences, and their competitiveness in the market. Yeah, and I'm thrilled to be joined today by Craig Rebmann product and evangelist at Dark Matter Technologies, a leader in workflow automation and loan origination solutions. So Craig has spent many years partnering with lenders, helping them modernize operations, adopt emerging technologies, and driving smarter, faster mortgage experiences. So, welcome, Craig. Thank you for being here.
Craig Rebmann (01:10):
Thank you very much, Tanya. Yeah. Thank you so much for having us on and give us an opportunity to, to chat.
Tanja Cleve (01:17):
Well, we're thrilled for you to be here. So let's just kick started. So beyond rates and affordability mm-hmm . What are your observations that mortgage lenders are facing in terms of process efficiencies and how can technology help them?
Craig Rebmann (01:33):
Yeah. great question. So lenders are really looking to move as much forward in the process as they can. Yep. A lot of that is through data, and a lot of that is through moving a lot of those capabilities into the application itself, even. But one of the things that really kind of changed over the last couple of years with inventory getting so small, right. Fallout rates have gone through the roof and it's really interesting because a lot of them are qualified borrowers who just can't find a house. So it's increased the net cost to the lender of doing business on some of those things. And some of them have even started to look at maybe I need to pull things back to the right a little bit to not incur some of those costs. But the, the benefits of getting that data upfront. Is so powerful from the standpoint of being able to feed a truly automated pre-approval. Right. And even automated conditional approval once you have property information the benefits are, are so great that there's still a lot of lenders that are trying to capture as much upfront as they possibly can.
Tanja Cleve (02:32):
Absolutely. We're hearing something very similar, particularly around credit income employment. Yeah. And and even automation, right? So automating some complex income profiles such as self-employed borrowers or layered income, and how can automation and technology help there?
Craig Rebmann (02:51):
Yeah. So one of the things that that, sorry, I'm going to
Speaker 4 (02:55):
Hold for a second. We're just going to shift the mics a
Tanja Cleve (02:57):
Little bit. Okay.
Speaker 4 (02:58):
We're not seeing your, all of your face. Okay.
Tanja Cleve (03:02):
Johnny, could
Speaker 4 (03:02):
You help me with the tape for a sec? Sorry. He's going to have to get under, oh, real quick. , we got it taped up so
Tanja Cleve (03:10):
That it doesn't shift. Oh. Do you want me to around?
Speaker 4 (03:11):
Okay, you're fine. Cool. And we're going to shift gears. You got a little more wiggle room. Okay. We're just going to shift yours over a little bit. Awesome.
Tanja Cleve (03:20):
Ah, okay.
Speaker 4 (03:20):
We're going to take a look. So that last question you, I tried to wait until you asked a new question, . Okay. If you don't mind just kind of picking it up there and we'll just cut it in. Okay, perfect. Alright. We're just going to make sure it looks okay on camera.
Tanja Cleve (03:33):
I think I jumped forward on my question, but I'll go back to it.
Speaker 4 (03:36):
Okay. Okay. We're still rolling.
Tanja Cleve (03:39):
Still rolling. Just pick it
Speaker 4 (03:40):
Up on that last
Tanja Cleve (03:41):
Okay. Very similar things that we're hearing as well. Lenders are looking to explore capturing data earlier in the process, start to begin that underwriting assessment and evaluation and drive smarter, more productive conversations with consumers and borrowers about the loan product or, you know, how to navigate the journey. How can technology and automation help with some of the more complex borrower profiles, particularly around salaried I'm sorry, self-employed income? Oh, yeah. Or even layered income. Yeah.
Craig Rebmann (04:12):
So one of the things that a lot of lenders are looking for first is just the data to understand that it is a more complex borrower. And getting some of that information up front. And that can be, like you said, self-employment information. It could be information about the fact that the property's in a trust. Yeah. Maybe you need to get more information from that borrower before you really start incurring some costs on that, on that loan. Make sure they're really in the game and they're going to give you everything you need. Yeah. So those components, just understanding the complexity of the transaction upfront in a systematic way is a, is a really key part. But then when you're talking about the self-employed borrowers, data from tax information is a huge help Right. In that space. And being able to bring that in is really beneficial.
Craig Rebmann (04:48):
In the absence of it, you're looking at tax returns and nobody really wants to look at tax returns. Right. that's been a big focus on our side with our AVA product of being able to extract data from tax returns and do some of those calculations for lenders to kind of prepare things for underwriting. Yeah. So we kind of look at that, you know, we look at a process orchestration kind of a, a mindset and looking at how do you, how do you navigate around some of those challenges that end up coming into play. If you look at just following a normal process, it's kind of like following a GPS, but when you can start pivoting and rerouting yourself Yeah. It's more like ways. Yeah. Right. And that's kind of the way we look at the role of automation in the application process and in the back office components that are occurring kind of under the scenes, along the way, you get consent for credit, go ahead and pull credit. Have those liabilities in the application at the time that the borrower gets to that point. Right. And then they can tell you what they're planning to pay off. Right. You getting so much more information front, it's so much more powerful.
Tanja Cleve (05:45):
Yeah. I love the comparison to Waze. I turn Waze on and I forget it. I love that you mentioned cost. Yes. And so I'm curious you know, your observations in tight margin environments, how are mortgage lenders balancing the need and desire for innovation and automation with cost control?
Craig Rebmann (06:05):
That's a really great question. And really what it all comes down to is capacity management, because lenders are going to be looking at it from the standpoint of I either need more capacity and I'm looking at gaining efficiency. Yeah. Or I have excess capacity and Yeah. In the down market, that's kind of the, the case. But either way, kind of balancing out that process of looking at how you're going to get the most out of the staffing that you have. And what we've been hearing at the conference today is it's a much more optimistic view of the market Yeah. From what we've been hearing from Yeah. From people. And a lot more of the conversation is about scalability versus the certainly at a, at a reduced cost. But if you think of that, that human resources being a fixed cost mm-hmm . And you can expand that, that upper limit on what they can do, that relevant range of that fixed cost. Yeah. What you've really done is you have a pretty low initial cost on it, volume can come down pretty low and you can still have healthy margins. Yeah. But as that, as that volume increases and you build the, the, the volume coming through mm-hmm . You have high margin, high scale and it's just a beautiful thing. Yeah. So efficiency gains are valuable in any market. If it's a down market, you still want the efficiency gain to be able to Right size. That's right.
Craig Rebmann (07:23):
But in a nut market it's the margin bumper. Yeah. Yeah.
Tanja Cleve (07:27):
It's gravy. The, the meetings that I've attended with, with customers and lenders, it's a lot about process and evaluating our process and then determining how we layer technology to, to manage that process or those points in the, in the origination journey that tend to create back and forth with the consumer. And how do we, how do we mitigate that on the front end either with data process, technology, automation. So maybe shifting gears a little bit and maybe forward thinking. A lot of change seems to always happen in our industry and we've got new programs like the new direct licensing fee with FICO generating a lot of conversation and discussion around impacts to consumers and potentially impacts to challenges within operations. And so curious for your perspective on how technology and, and partners can help enable these types of changes with pricing and distribution that's happening in the market.
Craig Rebmann (08:27):
I think end of the day, lenders are really looking for a way to get a good feel for willingness to pay that is correlated to default risk at a reasonable cost. And they, that's really ultimately what they're, what they're looking for. And of course, the GSEs have to be behind it and have to be willing to buy the loans that, that are scored in whatever model is used. Yeah. I think that with the additional model opportunities that are out there and that are, that are being approved by the GSCs today, it's really, they're not new. Yeah. We've been working on this for a couple of years. Yeah. Trying to really understand how to best implement them. Yeah. I think what's really the, the acceleration has really just kind of made lenders have to take a look at how they get their arms around the impact.
Craig Rebmann (09:12):
Yeah. And as a 720, a 720, a 720, that's probably the bigger answer. And I know you all have done a lot of work around that space to help lenders understand those differences, which I think is, is hugely helpful. And that, that I think is where people are going to start to really see the benefit and be able to choose the right path and then use the automation to help determine, okay, for this particular loan, based on the complexity of the loan and the characteristics of this borrower, this is the scoring mechanism that I need to use.
Tanja Cleve (09:38):
Absolutely. Yeah. Yeah. So we're working to partner with lenders to help them perform that analysis. Right. So do that during live production, do an archive study, and really determine for themselves and in partnership potentially with investors and their different product portfolios, to your point, what's, what's the right solution? Yeah. And then working with industry and technology partners in the market on delivery and how do we actually operationalize that? So, yeah. Yeah. We can't really have a conversation about technology and innovation without talking about AI . So there's a lot of buzz in the industry around AI and, and a lot of, you know, cool improvements as well. What's your perspective on what's next for AI and mortgage and, and what should lenders be thinking about?
Craig Rebmann (10:24):
This is kind of a passion part for me. I'm great , I'm a big fan of digging into the impact of AI in business. And I've got a product background, but I've always been about the application of technology into the business Yep. Versus just technology for technology's sake. Yep. And I think that what we've been seeing is a lot of lenders doing a lot of feeling around to kind of see what's the right place for AI mm-hmm . And based on the way that the, that LLMs are structured today, a lot of the, the initial use cases have been around gathering information Yep. Bringing that information to customer facing resources to help them be more efficient and answering questions and getting through those sorts of things. Make them better informed. Yeah. we started to see more of that start to push where lenders are a little more comfortable with the idea of the borrower interacting with artificial intelligence and chatbots.
Craig Rebmann (11:12):
Yeah. And that's fantastic. But that next horizon is really around artificial intelligence actually doing something, actually automating a process and actually taking, taking steps, taking it to the next step, taking steps Yeah. To automate these. When we start talking about ag agentic ai, that's where the, the coordination of that automated work with the human is so critical. And that's where process orchestration comes in. Yep. To give you that, that control tower over the top of that, all those different flight plans going on of all that automation and getting the human engaged at the right time with the, with the right skillset to make the right call to the borrower Yeah. To bring that human touch in. And, and maybe it's just a conversation to let them know, yeah, your appraisal came in low, we're looking through everything right now. Yep. No cent, no need to panic. Or maybe it's you know, maybe it's an opportunity to pick up that borrower that dropped off of the application midway through and you're just getting the opportunity to go make that, you know, make that contact and try to get that deal.
Tanja Cleve (12:14):
You hear a lot right now about that human interaction with ai. Yeah. It seems to be a really important factor in determining how you leverage it when you leverage it, and how you maximize your human capital Yeah. To interact with the technology and then your customer, the consumer.
Craig Rebmann (12:30):
I wonder, it seems to be a hot topic. One of the key areas around that is lenders are not comfortable with the idea of AI making a decision. No. Yeah. And it's, it's going to be this whole chain of things. You're going to use artificial intelligence to prepare the file. You're going to use deterministic rules engines to make a recommendation, and then you're going to use human judgment to ultimately review all of that information and make a decision. Yeah. And that combination is, I think, the winning recipe.
Tanja Cleve (12:54):
The winning recipe. So sticking with sort of, you know, data and integrations, lenders are battling multiple systems between a point of sale, a loan origination system or CRM, and that data management across systems is very, very important. And so how do you view partnerships between technology providers to help them link and create these connected ecosystems? Yeah. How can technology help?
Craig Rebmann (13:20):
Honestly, integration conversations now are so interesting because everybody has APIs Yes. And everybody's interested in everybody else writing to their APIs. Yeah.
Tanja Cleve (13:27):
That's the name of the gate
Craig Rebmann (13:28):
. So, but the APIs are really the gateway into each other's systems. Yeah. And the ability to do API calls set web hooks in place using event notifications back and forth. So that really the control tower, and typically we see this happening from an LOS that's a selfish perspective maybe on our part, but it's kind of where we, we believe that control tower belongs. Yeah. Being able to use those web hooks and event notifications and automated calls to interact with the various systems across the ecosystem. Yeah. Whether we're calling someone's API or someone is calling our API and we're just sending them a notification that it's time to make the call APIs are the, the way to get that done. Yeah. And that we just recently rolled out our developer platform to make it easier to work with our APIs. Oh, great. As an example. Yeah. So that, and then over the course of first half of this year, we're planning on adding model context protocols so that agents can interact with the APIs. Oh, great. To make that just a broader ecosystem of capability. All part of having opened up our ecosystem.
Tanja Cleve (14:30):
Yeah. Love that. Love that. Congratulations on the coming enhancement. Thank you. So how can the integrations and bring data earlier in the process help with borrow experience and reduced cycle times?
Craig Rebmann (14:45):
So one of the, one of the things that we think is really critically important is the data on the loan has to, has to be controlled by one system at the end of the day. Yep. And again, selfishly we believe that's the loan origination system. Yeah. having all that data in the loan origination system is really important. To that end, when we developed our own point of sale processes, we did not set them up with separate databases. They write to the Empower API in real time, as you know, page by page, as the applicant is walking through and, and entering their information, all of that information is funneling into Empower. And the power of that is not just that. Okay. The LOS is up to date. That's great. Yeah. But it also means all of the automation capabilities can trigger. So the part that we were talking about where I get have consent to pull credit Yeah.
Craig Rebmann (15:30):
We can pull credit behind the scenes. Yeah. We start getting employment information, we start getting income information, we can start running verifications behind the scenes. Yeah. All of those kinds of things start adding to the value of the borrower has a cleaner process. They have a greater chance of getting an automated pre-approval Yeah. Or an automated conditional approval mm-hmm . And they're getting real time status. Yeah. As things are happening in the back office and the borrower comes back to the portal and they take a look at what's going on, or they're getting notifications about things, everything is real time. It's pulling that data right away.
Tanja Cleve (16:00):
Absolutely.
Craig Rebmann (16:00):
That is in my mind the best way that you improve borrow experience is you bring them closer to the data.
Tanja Cleve (16:07):
It's the power Yeah. In real time. Absolutely. Yeah. We were just having a discussion with you know, a lender and, and one of the challenges they're faced with is this income conversation with the consumer or the customers happening maybe 10 to 14 days by the time it gets to underwriting. Right. And so how do we maximize technology and data so that their sales teams are empowered to have that informed conversation with that borrower much earlier in the process about additional income or potentially different products or offerings to, to help them get to the net result that they're looking for.
Craig Rebmann (16:41):
That's a huge, a huge part of it. And it's not just having calculated the income. It's like, then what does that mean? Yeah. Do I have declining income over a couple of years here? Do I need to have a conversation with a borrower about, okay, what's going on with your business? Yeah. You know, those kinds of conversations are really important to, to putting together a quality loan and the more that that data can be leveraged to develop that full picture and then really identify these are the things that need attention. Yeah. that's, yeah. That's really important to the whole process.
Tanja Cleve (17:12):
And a great experience for that borrower too. Like, I'm rooms, I'm engaged, I feel part of the process. I don't feel that I'm in the dark.
Craig Rebmann (17:20):
And the last thing that you want is you, you're three days out from closing and Oh, wait a minute, there's this fire now. Oh yeah. Because we just now notice this, the earlier in the process that stuff can be found. Number one, there's less panic. Number two, the bar's not going to come back at you and say, when the, why the heck didn't you ask me about this earlier? Why me, I supply that two weeks ago? Right. That whole process, it makes everything cleaner. Yeah. And then having all that upfront, we'll see this a lot more as we get into more of a re refine market. Yeah. You can close faster. Yeah. You know, since so much is purchased today, get into the house faster, you know, you're kind of stuck to the contract date. Yeah. But in the refi market, you can move a lot faster.
Tanja Cleve (17:56):
Yeah. Okay. So
Craig Rebmann (17:59):
Tanja Cleve (18:00):
Budgets, I think in any industry are under a microscope, certainly in mortgage. How would you advise lenders to continue to strategically invest or increase their investment in technology spending so that they are optimally positioned for a turn in the market? I
Craig Rebmann (18:17):
Think the, there's two key steps that have to happen. First, number one is identifying your needs. Yeah. What is it that, that, you know, where, where are your pain points? And number two, talk to your existing technology providers mm-hmm . Because it's amazing how often we talk to a client and find out that what they're asking for and what this other lender's asking for and this other lender's asking for are all the same thing. How similar mm-hmm . And then sometimes the lenders can save investment because we then take that on and add it to our product. Yeah. Those kinds of conversations can be incredibly meaningful or it may just give ideas of different ways to do that. Yeah. There might be capabilities that their existing providers under their existing vendor management already can solve for them. Yeah. That they don't, they don't need to necessarily go too far out. I think. So I would say asking, doing those two steps first is probably the
Tanja Cleve (19:07):
Yeah. Yeah. And I think particularly for any lender who's looking to increase their investment in technology to your point, they may not have a full view of what their current partners can offer because their strategy is now changing and, and they haven't explored the offerings that align now to the new strategy. So I love, I love that. Right. Check with your current partners and see what they can offer for
Craig Rebmann (19:28):
You. Yeah. Optimize, optimize, optimize, optimize.
Tanja Cleve (19:30):
Yeah. . Curious for your perspective too, on what do you think is sort of under leveraged or, you know, something that maybe lenders aren't thinking enough about as it relates to technology and innovation?
Craig Rebmann (19:44):
So one thing that I think is really interesting that there's not been a lot of conversation about mm-hmm . And maybe it's just being so well handled that it doesn't need the additional conversation is what's going on with appraisals and UAD, the 3.6 model. It's a lot of change. It's a lot of change, a lot of change going on in the valuation space. And it is crickets. Yeah. You don't hear anybody talking about it. They don't, which I'm assuming means figs are going really well and they're feeling good about it, happy and feeling good about it, . And I knows it from our perspective, we certainly feel that way, but it, it is surprising that there's been so little conversation, and maybe it's a case study in how to make a large transition like this Oh yeah. Effectively, yeah. Maybe that's the, the case or maybe it's something people need to be paying more attention to.
Craig Rebmann (20:23):
I don't know. Yeah. One of those two things. Yeah. but in terms of areas that I think people need to, to really invest, and I would direct this kind of at senior leadership folks Yeah. Get them. If you are not already with artificial intelligence, get hands on with artificial intelligence, playing around with chat GPT or Claude or Gemini, or pick the, the tool of your choice and just get comfortable with it because it's going to make your conversations with your teams so much more meaningful and understandable. And I think in, in some cases, it also allays some of the concerns. There's always the risk that it makes people a little too excited about Yeah. What's possible. Yeah. But I think that, that that's, it doesn't cost anything. Yeah. To, to get your hands dirty on it and start understanding that. And then experimentation across the teams is how you get your teams comfortable with it too. Yeah. so I think that's, that's really a critical step. Yeah. And Tela Gallagher, a quick shout out to her is doing some fantastic sessions here at MBA Oh, great. To train people to help educate people on just getting familiar with artificial intelligence, getting familiar, setting your arms around it. So I'll give her a big shout out.
Tanja Cleve (21:31):
I think we have an AI hub in the corner and I, and I love starting simple. Right. Just get comfortable with it. Use AI in your own personal life. Yeah. And then you can start to, and I think I've done that a little bit. I'm experimenting myself and I think what it's done for me is to help understand, back to your point earlier around that human interaction coupled with ai. Yes. Right. I think some people are nervous that AI removes that human interaction or the need. And I think as you start to interact with ai, you see both sides of the coin. You see the value that it brings. Yeah. But you also see how the human interaction can really amplify and target the use of AI at the, at the right time.
Craig Rebmann (22:12):
A hundred percent. It just changes the human interaction. Yeah. The way that people interact with work is just different when there's certain components of it that have already prepared, prepared for them. Yeah. They're doing more review maybe. Yeah. And in some cases, you know, okay. Some people feel it's kind of zen-like to review an asset statement. Yeah. first, one last thing I want to do is go through all those transactions. If AI will do that for me, and then I could just look at, okay, these are the interesting transactions that I need to pay attention to. That, you know, makes a lot more sense to me. But having those workflows developed in a way that you have a meaningful way to have somebody review or have that human in the loop, it's still very important, particularly with LLMs. Because they you know, by definition they make stuff up that's, it's what they do. So it's a new muscle,
Tanja Cleve (22:57):
That human loop.
Craig Rebmann (22:57):
Yeah.
Tanja Cleve (22:58):
It's a new muscle for sure.
Craig Rebmann (22:59):
It's really important to keep that human in the loop and have them reviewing what's going on.
Tanja Cleve (23:03):
Yeah. Love that. Well, Craig, thank you for joining us at our Equifax booth here at MBA. How might our listeners follow up if they have additional questions for you?
Craig Rebmann (23:13):
Two ways. I'm a LinkedIn and I'm, I check it probably more often than, than I should. But that's, that's probably the easiest way. Or email at craig.rebmann@dmatter.com is yet another way. So either of those are great. Okay. Thank you so much. Terrific. This has been so fun.
Tanja Cleve (23:31):
Yeah. Thank you for the insights and the partnership, and we look forward to seeing how dark matter continues to enhance and improve the lending experience.
Craig Rebmann (23:39):
And we're looking forward to all the things Equifax is bringing to the game.
Tanja Cleve (23:42):
Thank you so much to, to you all for tuning in. Make sure you stay tuned for the Equifax Market podcast for what's next. In the next conversation here at the MBA, we'll need to redo that closing , I need to redo that one. That's fine. Yeah. Yeah. Let's do over, do over. Okay. Just that sentence. Okay. And thank you to everyone tuning in.