00:06Live from Las Vegas, I'm Zeb Lowe, here with Michael Kelleher. Michael, thank you for joining
00:09me. Thank you, appreciate it. Yeah, so the last time that you spoke with HousingWire,
00:14you were filling us in on Sapien's decision. So what's the latest there?
00:18Yeah, there's been a lot of changes since last time. I think the most important change is
00:22we've gone from what was a concept to a category. So Forrester has now named us a leader in
00:30decisioning AI. And in addition to that, we now have real use cases with banks and credit unions,
00:37non-QM lenders, correspondent lenders, wholesale lenders. So we have a lot of momentum in the
00:44category. I would even say we have an acceleration going into 2026. I think going from concept to
00:50the category is a pretty bold statement. What do you think is driving the acceleration that you
00:55mentioned? Yeah, I think it's two things. One, we have real use cases now. So we have lenders that
01:02understand today's technology has a difficult time managing decisions and more importantly,
01:10keeping up with the changing of decisions. So we have non-QM lenders reaching out to us about
01:15building an AUS. We have banks and credit unions talking to us about portfolio AUS or maybe a HMDA
01:24or compliance problem they're trying to solve. We now have correspondent in wholesale reaching out to
01:29us to try and reduce some of the costs there at that transition. And I think the other thing is
01:35just
01:36when you have a use case in the market and other lenders hear about decisions that used to take three
01:41days or taking three minutes for certain lenders, they come to conferences like this, they start to
01:46talk. When you're able to solve pain and you're able to bring that competitive edge to it, those two
01:52things can be a powerful combination. You mentioned non-QM. We've seen in the past couple of years at
01:56HousingWire, we've done a lot of content over the rise of the non-QM market and how it's growing in
02:03its relevancy and not what it was 10 years ago. So what are you guys seeing in relation to the
02:08non-QM
02:09market? Yeah, non-QM is on fire. I couldn't be more excited about non-QM for the industry as a
02:15whole. And I've been able to channel that through my connections and really showcase to these non-QM
02:22lenders, you need it to increase your volume. But at the same time, there's a lot of manual components
02:28to it. So you have manual underwriters and different underwriters making different decisions,
02:34which produces different exceptions. And the turnaround time starts to get longer. So these
02:40non-QM lenders would come to us and say, how can we have an AUS like Fannie or Freddie? Is
02:49there a way
02:49we as a non-QM lender could possibly have an AUS? And a lot of them said, maybe you can't
02:55have it.
02:55It's art versus math. But we were able to sit down with them and show them that our authoring tool
03:01is
03:01able to take their guidelines, their matrices, and bring it into a world where we're able to
03:08look at eligibility. We're able to look at exception management. We're able to then produce document
03:15checklists and conditions. And overall, the outcome becomes eventually being able to automate it
03:22and govern those decisions and bring an auditability to who's making those decisions, when they're making
03:29them, how they're making it. And so we've brought the AUS to non-QM.
03:34What about banks and credit unions? Is that that much of a different market for you guys? Or is it
03:38really kind of all one and the same? It is for me, I suppose, handling the sales cycle. Those are
03:44much,
03:44much longer sales cycles. But at the end of the day, our lead into those banks and credit unions is
03:50very similar. They have portfolio products, whether it's a jumbo program or a specialty loan,
03:58or maybe it's community lending. But they all typically have the same thing. They have their
04:05guidelines on Excel sheets, or if they're a more advanced bank, they have what's called loan cards.
04:11But these loan score cards are usually very out of date. And so they're coming to us same way,
04:17saying, if we could have an agency solution, how would we build it? And so we look at them and
04:25we
04:25try and figure out how they could take those loan score cards and start to automate or start to build
04:33the decisions where they have a governance to it. They have an auditability trail. They have a
04:39versioning. So they're able to then say, this was the decision made by this person on this version,
04:46and this was the outcome at a click of a button. And the auditors like that. And the banks are
04:51loving
04:52this new AUS.
04:53So traditional software can't handle this sort of workload. Why not? What's the problem?
05:00What's the catch there?
05:03Traditional mortgage lending software is just very linear. We take an application,
05:08and then we try to approve the application. We underwrite it, we approve it,
05:12we close it, and we sell it. And the complexity of decisions has grown so much over time. The ability
05:23to need speed now with it or add AI to it has brought more complexity. I've actually found
05:30building some of those decision rules is the easy part. How do you maintain them over time? How do you
05:37handle the changes? And when the changes are maybe at the state level, or maybe they're at a different
05:42compensation level, and where do you document them? Are you able to version them? So the decision
05:48layer that Sapiens is able to bring allows you to keep your existing software. It listens on the APIs.
05:55It provides a decision layer so that any question you have that you can answer with data, you can build
06:04in Sapiens' decision, and begin to bring those decisions and surface them in the technology you
06:10have today. And today's technology wasn't built to handle that.
06:15What about on the correspondence and the wholesale side?
06:20Yeah, very excited about correspondence. We had a lender come to us to automate
06:25a AUS on a particular loan. They came and they looked at some of the UI that we've made available
06:33across our sectors. And they were able to discover that what they do, which is really the same, they're
06:41looking at investor overlays of multiple investors, investor guidelines, maybe some document checklists,
06:48maybe some dates or certain types of conditions they need. Well, our ability to handle that in batch,
06:55whether it's overnight or in line or both, and then provide exceptions that are needed, allows the seller
07:03and the buyer to have more transparency into what could possibly cause a repurchase and maybe handle
07:12it before they close versus chasing it down the line. And so it's one of the rare times I've
07:17seen where it can be digested on the buyer and seller side. And it allows really at scale,
07:23which is what Sapien's decision is all about, the ability to handle that bulk and provide a better
07:29understanding to all parties involved. Gotcha. Talking about compliance, that's always a headache for
07:35lenders. So what's Sapien's approach to tackling those obstacles?
07:39We wanted customers to realize that we got our feet wet in compliance.
07:44That's where we started. Freddie Mac brought us in to work with them to be really the engine
07:50behind LP. So we understand the importance of having an audit trail, having versioning.
07:57And so we've had a couple of banks reach out to us and say, Humda's a problem. They have a
08:02lot of
08:02full-time employees that work on it throughout the year. Then they rush at certain points of the year.
08:06And it's really checking Humda fields, matching them up with running AMI, area medium income, and then
08:15running it against census tracts. And at any point, if the vernacular on the LAR doesn't match up any of
08:22the fields or the documents, that could be an invitation to come in and audit. So that is what
08:28we're doing. We're running that decision layer where the banks have worked with us or the credit unions,
08:35but they've worked with us to author what decisions should be made in real time and in batch overnight
08:42over their data. And that way there's an audit trail and they're able to show who made what decision,
08:48when they made it, on what version. And if the auditor comes in, they're actually able to press a
08:55button and show that entire audit trail. So it could eliminate, it just lowers your regulatory
09:03risk or exposure. Right. So the picture, what I see is a picture being painted of lenders adopting
09:09this across all channels. Is that a fair assessment? Yeah. That's what's exciting about what I do is
09:16there's no specific niche. If there is a decision to be made that can be solved with data,
09:24it is a great reason to reach out to Sapiens decision. And, you know, that's what we always
09:31say is start with one decision. Right. Well, so Forrester, I saw recognize Sapiens as a leader in
09:37AI decisioning. And so what does that, is that validation? What does that mean? What does that feel
09:43like? It feels great. I know the entire Sapiens decision team worked extremely hard on it. To be called a
09:50leader by Forrester is certainly important. They look at AI decisioning as the combination of the
10:00disciplines that were traditionally siloed. So business decisions, data analytics, and machine
10:08learning. And so to bring it all together into a decisioning layer that you can run orchestrated AI
10:16over is what, or the reason a lot of these banks, credit unions, non-QM lenders, correspondents,
10:24come to Sapiens decision. But I think what makes us most proud is it's not just about the technology
10:31with Forrester. You're judged on vision. You're judged on execution. And with Forrester, you're judged
10:37on the feedback from the customers specifically on what the use cases it's being used for,
10:43the satisfaction with the use cases. And so being awarded that is more than just you have great
10:50technology. It's, we are battle tested. We've been around for 15 years. We're in the public sector.
10:57We're in the government sector. We're in large insurance. We're in large banking. And now we are
11:03making a big effort to bring it down channel, show we're battle tested at scale, but we're ready to work
11:09with the non-QM lenders, the correspondents, the banks, the credit unions, even the IMBs.
11:14I think that actually, that ties into my last question that I have for you. So for any lenders
11:17that are watching is what's the, what's the big message, what's the takeaway that you would like
11:21for them to receive? The big message is this industry believes that technology solves everything in
11:30mortgage. And at the end of the day, mortgage companies do not need to be technology companies.
11:36They win on the decisions they make, the decisions on how accurate or what pricing they should have,
11:45their decisions on how they're going to underwrite files, even their decisions on their willingness
11:49to be riskier or less risky. And so that's where Sapien's decision brings that extra advantage to those
11:57that are ready to embrace it. Because if you're not moving forward in this industry, you're falling
12:02behind. It's moving so fast. So the message is find that one decision in your company, that one piece
12:09that you think is slowing down the process, that one piece that you maybe believe is a real risk
12:18to the company. To put it simply, that one piece that keeps you up at night, find that one decision,
12:25start with us, let us just solve that. And I always say it's like the matrix, you'll start seeing
12:29decisions everywhere. And then you'll wonder how you lived without it. All right, Michael,
12:34thank you so much. Appreciate the time. Thank you.
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