What 2008 taught a billion-dollar lender

Name: What 2008 taught a billion-dollar lender
Uploaded: 2026-09-17T08:00:55+00:00
Duration: 47 min 33 s
Channel: HousingWire

00:00Kevin Rodman is the CEO of ABL, Asset-Based Lending.

00:04He spent 24 years at Morgan Stanley and was inside the machine when it came apart in 2008.

00:10Then he walked away and helped build ABL, a company that provides financing options to real estate investors for the

00:17purchase, renovation, new construction, and long-term refinance of single-family and multifamily properties.

00:23Today, Kevin shares stories, insights, and wisdom earned through over 40 years in the industry.

00:40All right, Kevin, thank you for joining me.

00:42Thanks, Zeb. It's great to be here. I really appreciate it.

00:45Yes, sir. Lovely to have you.

00:48Before we dive into the big stuff, can you introduce yourself to the audience and share what you and your

00:54team are doing over at Asset-Based Lending?

00:59Yeah. I'm Kevin Rodman, and I'm the CEO and one of the founders of the company.

01:05And we are a private money lender, and we've been in business for 15 years, and we're tracking to around

01:16a billion dollars in new construction, which is our specialty, fix and flip, and death service coverage ratio, DSCR loans.

01:29And that's what we're doing.

01:31And I was doing a little bit of research on you beforehand, and I saw you spent 24 years at

01:38Morgan Stanley before moving over to Asset-Based Lending.

01:41And I was curious if you could, well, one, if you can kind of walk me through that journey, why

01:46you, after 24 years, Morgan Stanley decided to make the shift over, and what did you learn during your time

01:54there?

01:58Zeb, I could spend three days answering that question, so we don't have that much time.

02:04So let me just say that I was…

02:07I mean, that's a whole career.

02:09That's a book.

02:10I was extraordinarily fortunate that I had the opportunity to join Morgan Stanley when it was a small private company.

02:20I was employee 2,940, roughly, and it was in 1984.

02:28And one of my colleagues told me once after we left Morgan Stanley at a reunion that how fortunate were

02:37we to join the best company in the industry when it had 2,900 people and leave when it had

02:4565,000 people.

02:46Who gets the chance to do that in 24 years?

02:50So I had a great career there, and I became a partner at Morgan Stanley around 1995.

02:58And I grew up in the fixed income division as a bond trader.

03:04I was very much focused on lending money and financing and ultimately moved from government bond trading to our mortgage

03:14department where I first built our warehouse lending business where we were lending to other mortgage companies and then helping

03:23them dispose of their loans, buying them, selling them, securitizing them.

03:27And then we built our own origination business, and I was co-head of that.

03:33And I was president of Morgan Stanley Credit Corporation, which is the company that originated to Morgan Stanley's tens of

03:45thousands of high net worth clients.

03:47And I was CEO of a firm called Saxon Mortgage that we bought, which was a specialty servicer and co

03:55-head of our mortgage conduit, which bought loans from around 600 loan sellers.

03:59And it was great.

04:03It was a great business.

04:05And unfortunately, the crash hit, and it was time for me to retire.

04:12And so you asked what I learned.

04:15Let me just summarize it, okay?

04:19I joined Morgan Stanley when it was the third generation of partners in that company.

04:26The company was started in the mid-30s.

04:29And the chairman was, I think, a second generation.

04:32He was related to one of the founders, maybe a grandson.

04:37And the reason firms like Morgan Stanley and Goldman Sachs are still alive today and firms like Lehman Brothers, Bear

04:45Stearns, Merrill Lynch is a great company, but they had to be bailed out by Bank of America, DLJ.

04:52I could list 20 major firms that died while Morgan Stanley, Goldman and Chase, Jamie Dimon has done an amazing

05:01job.

05:02It's all about culture and discipline.

05:06And I was fortunate to learn culture from these 50 founding partners at Morgan Stanley and take that with me

05:16my whole career.

05:18And these other firms that failed lacked in that.

05:23And so I'm just scratching the surface to tell you, and that's why ABL, the company that I've helped build,

05:33as we've gone from startup, if I had two partners and we put in our own money to start the

05:38company, we ultimately sold the private equity they retired, I stayed on.

05:42But I've carried many of the things that were wonderful about the mortgage family culture with me, and then things

05:50along the way that I learned that needed to be tweaked.

05:54And so we've built a company that has a great culture.

06:00What do you see as the critical or essential elements of good culture that you have established and fostered at

06:11asset-based lending?

06:16Well, for the first 10 years, my partners and I were lending our own money, which was 25% of

06:21our capital pool, and the rest was friends and family.

06:24When you're lending your own money, you think like an owner.

06:27And so now that we are using a much bigger capital pool with private equity, our firm's mission statement is

06:36think like an owner.

06:37And that's kind of squishy.

06:39What does it mean?

06:39What does it mean is every dollar you're using, think of it as your own and make a decision as

06:47if it's your own.

06:48Then we have four sub-principles to that, which is make good loans, always make good loans, protect the firm,

06:57borrower, do everything possible to make the borrower, give them what they need, and always think about what we have

07:04to do to become better in the future.

07:08That's our mission statement, but just quickly, things that really matter from a culture standpoint is total transparency, no secrets

07:19anywhere.

07:20Everyone has to be transparent with everyone else, number one.

07:23Number two, a complete team, absolute total team.

07:28The rule is everybody has to help everybody else.

07:33What's happened at some of the firms I listed that went down, especially in the crash, is they had silos.

07:41For instance, the mortgage division ran the company, essentially, and they got everything they wanted, including massive levered balance sheets

07:52that took them down when the crash happened.

07:55So you can never have a siloed-off superstar that gets better treatment than the rest of the company.

08:03No matter how special somebody is, you can promote them, you can pay them, but at the end of the

08:10day, they have to adhere to the same values.

08:14And then another value we have is you've got to be smart every day.

08:19You've got to treat your customers like they really matter.

08:23Customers come first.

08:26And so another one I love, which is also a little hard to define, but it's learn from your mistakes.

08:37So you have to be – we have a – in our company, we have a 30-day stand-up.

08:43Every employee gets five minutes with their boss, and they're literally standing, and they get to not talk about what

08:52project am I working on, what initiative am I working on.

08:55They get to talk about how do you feel about the last 30 days?

08:58How do you feel about how your career is going?

09:01What's on your mind?

09:03And so you've got to make people feel connected to the company.

09:08You know, it's interesting that that last point that you made, and before you went into it, you said that

09:12it's a little bit hard to define exactly.

09:15I think – actually, I think from my experience, that is a mark of good culture.

09:21I'm fairly wary of organizations where their culture is a mantra that they can recite, and it's very black and

09:27white in its language.

09:29You know, I think that real culture inside an organization is you – it's something that you – it's action.

09:36It's something that you can feel.

09:38There is language around it, right?

09:40But it's not a mantra.

09:43You know, it's not a saying.

09:44It is the things that you do, and then oftentimes you kind of struggle to put the right words around

09:49it, but you can feel it, and you can see it.

09:52Yeah, you know, Zeb, another thing that's critical you have to mention, culture comes from the top.

09:59It doesn't come from the bottom.

10:02My job is to – with my senior leaders – is to create the culture, and we have to walk

10:10it and talk it.

10:11And be real about it.

10:15And we have to teach all the subordinates and, you know, the vice presidents and everybody else that this is

10:22for real.

10:22We take this seriously.

10:26And I think there are other CEOs who probably say, my job, number one, is to be profitable and to

10:35make as much money as possible.

10:37And their companies might be great companies.

10:40You know, my attitude is let's get the culture right, and then let's get the business plan and make a

10:47lot of money.

10:48But I know that a great culture makes employees sticky, and it bleeds into how we treat our borrowers.

11:00And a bad culture still might make a lot of money, but it makes people very unhappy, and that bleeds

11:09into our borrowers.

11:11So you touched on this a couple of times already, and this is something I specifically wanted to ask you

11:18about.

11:18You had a front row seat from the – in the crash in 2008.

11:25Kind of really, I feel like I'm more from, like, inside the machine, right?

11:28You're really, you know, inside that world.

11:30What did you carry out of that period that shaped the way that you run your business and the way

11:39that you think about underwriting loans?

11:41And you may have already – it may be the thing that you already mentioned, which is, like, that no

11:46superstar, you know, group inside an organization.

11:49Is that it, or is there a bigger lesson?

11:52Oh, a much bigger lesson.

11:53We have a month to talk now, right?

11:59So, Zeb, let me go very personal first.

12:04I mean, I could talk for hours about my inside seat running a mortgage division and watching it unfold and

12:13the mistakes I made and other people made.

12:16But personally, I loved being a trader, and I ran trading desks, and then my job got bigger, and I

12:27no longer ran trading desks.

12:29I ran divisions, and I ran the servicing division and the credit division and originations, and it's a lot.

12:37And I ultimately, unfortunately, lost touch with the day-to-day feeling of what risk am I taking and going

12:53home at night and feeling comfortable with the loans I own or the bonds I've traded, you know, what my

13:02positions are.

13:02Is it hedged correctly?

13:05And I had that for a long part of my career, and it was part of my success.

13:09And after I left Morgan Stanley and spent a significant amount of time reflecting on what happened and how did

13:18I miss it, I decided that the best thing for me would be to get my hands dirty again, that

13:30that was when I was most effective.

13:32And so with the startup we had with asset-based lending, my two partners and I, and they also both

13:39had big careers on Wall Street, we were the only underwriters for 10 years.

13:46I was the lead underwriter, and I underwrote over half a billion loans that closed, and the losses on those

13:53loans were less than $400,000.

13:56And I'm really proud of that.

13:58And I went from having a very, very big job at Morgan Stanley to getting on the phone with people

14:08who wanted to buy a distressed home who maybe spoke broken English, and they wanted to buy it at the

14:17courthouse steps,

14:17and me walking them through how asset-based lending could lend them money and make it happen.

14:25And eight out of 10 calls were like, well, no, you can't do that with a 500 FICO.

14:30And so the lesson for me, very personally, I needed to get my hands dirty again and own my risk

14:39again with my own money.

14:40That's what I was going to ask, because you started in 2010, right?

14:45Yeah, we started the company in 2010.

14:47Yeah, and so from the outside looking in, you would, I mean, not like the worst possible time to start

14:55a business.

14:57And so that was the main motivating factor.

15:00You felt like you needed to get your hands dirty again.

15:01Did you still spot or see opportunities in the market that you believe that others just had abandoned as a

15:09result of the crash?

15:11What made you decide to go all in?

15:15I had a partner, wonderful human being, Paul Ullman, and he's since retired.

15:22Paul and his wife decided in 2009, his hedge fund unwound, and he said, let's go buy distressed homes, or

15:33she said, and flip them.

15:34And that's what they started doing.

15:36And they did it in Long Island, and they did three flips successfully.

15:42But it was a lot of work.

15:44It was hard.

15:47And while they were doing it, tradesmen were saying to them, hey, I know about all these houses.

15:54Do you know where I can borrow money to buy this distressed home?

15:59There were distressed homes everywhere.

16:00And Paul and his wife said, wait a minute, I think we can make as much money lending as we're

16:08making, working for nine months, we're renovating these homes.

16:12And why don't we lend instead of fix and flip?

16:17And that's where the idea came from.

16:19And Paul and I, before that, had been talking about what business should we get into post our big Wall

16:28Street careers.

16:29And so that's what we did.

16:32We wrote the business plan.

16:33And actually, Paul started the company with his former CFO, Dan.

16:37And I waited a few years because I had some personal reasons not to do a startup.

16:44But then I joined them soon after.

16:47So that's why that's how it evolved.

16:51And and then we were located in Hoboken, New Jersey, and we started going to real estate meetups and meeting

16:59people.

17:00And suddenly the phone started ringing because there were no other lenders in North Jersey.

17:07And talk to me about your borrower profile.

17:10I mean, I know this is like the very general I know I'm asking you questions that take hours and

17:15weeks to unpack very big, broad questions.

17:18So forgive me.

17:18But you're what is your borrower profile look like?

17:22What is you know what types of people are coming to you?

17:26Zeb, great question.

17:27And I'll answer it fairly quickly.

17:29In the beginning, 2010 to 2015, most of our borrowers were just getting started in this business.

17:38And I'm really proud to say that at ABL, we have a high borrower retention rate.

17:42And and now I've got borrowers that have been with us for 15 years doing their hundredth project.

17:49And rates have gone from 14 and four to nine and one.

17:57And and nowadays, back then, the average home was the average loan was a couple hundred thousand dollars.

18:03Nowadays, our average loan is seven hundred and fifty thousand dollars.

18:06And it's a big problem because, as we all know, we have an affordability crisis.

18:12And most of our borrowers now are doing 10 to 20 deals a year.

18:17And the people who want to enter the market are kind of priced out because, you know, with an average

18:23home at four or five hundred thousand dollars, it's hard for somebody, say, a contractor who's who's renovated and built

18:3230 homes and finally has saved enough money and wants to get into the business.

18:35And it's it's hard because there's a lot more capital that's required.

18:41So I would say for a firm like ABL that's on the larger side in the industry, we are tilting

18:48towards more sophisticated, more highly experienced borrowers.

18:53Sixty five percent of our business is new construction.

18:57And most of our builders have built at least 10 or 20 of the homes that they're currently building.

19:05And and we specialize in infill.

19:08And what that means is we have a borrower who knows every block, say, in a two mile square area.

19:14They know every realtor, they know the people in the town who set the rules on permits and and and

19:22what's allowed and zoning.

19:24And they find they find properties that have value and they really know how to work the local market.

19:34And so that's our typical borrower today.

19:39OK, I wanted to ask you, I saw I guess it was this past year, I know relative last year

19:46to you, you guys re reworked or kind of rebuilt your DSCR program.

19:52Yeah. Can you walk me through some of that?

19:55You know, what was one what was broken?

19:57What needed to be rebuilt?

19:59What makes this version of the product better?

20:03What did you improve upon?

20:03Well, you know, this is very personal to ABL.

20:10And what happened is, is our volume doubled.

20:152023 to 24, we went from 150 million to 300 million.

20:20And we are currently.

20:25We're in the eighth inning of turning over into completely new, modern, AI driven technology.

20:32And back then we were still working off the systems we built that built this company.

20:39And and we just weren't built for that type of doubling in volume of a product that wasn't our original

20:47product.

20:48So our systems were sort of we were sort of shoehorning a very different product into a new construction fix

20:56and flip system.

20:58And so we really kind of broke down over over operational and technology problems with a doubling in a year.

21:10Other firms probably aced it.

21:13We just didn't get it right.

21:15And and so what I mean by didn't get right, we didn't deliver the best possible customer service.

21:21Instead of closing a DSCR loan in 20 to 25 days, which is what it should be, we were closing

21:27in 40 and 45 days and borrowers for getting upset.

21:30And it's the worst thing in the world to have upset borrowers.

21:35And so we decided to retrench.

21:39What retrench means is we simplified the program.

21:44We circled the wagons around a very definable set of underwriting guidelines and pricing.

21:53And now we've everything settled down.

21:58Our our closed times are 20 to 30 days in that product.

22:04We're we're two weeks in bridge and and and new construction.

22:11And our sales force is re-adopting the product.

22:15If you're a salesperson and you've got a a new construction customer you've been with for five years, who's done

22:23100 projects and you introduce them to the DSCR program.

22:27And then ABL takes 45 days to close when they can get a 20 days elsewhere.

22:31That's a disaster.

22:32You know, this business is all about retaining the best clients.

22:37It really is.

22:38And so that's what happened at ABL.

22:42I don't know if it happened at any other firm.

22:44So now we've we've built out the tech.

22:46We've staffed it really well.

22:49We've redefined our guidelines, redefined our pricing, which is very good.

22:53And we're we're getting a lot of traction again.

22:57So I feel I feel I feel badly about, you know, not being prepared for a doubling in volume.

23:04And I feel very good about the decisions we made to to rebuild it.

23:09It's a product that we have to be in this product.

23:13It's just our borrowers need it.

23:15And also when we're underwriting alone, we underwrite both to the intrinsic value of the underlying property, no matter what

23:24we're doing with new construction DSCR.

23:27And we underwrite it to a DSCR exit just to as a data point to understand what it is we've

23:36got in case we end up owning it.

23:38What's what's the rental market look like?

23:41And, you know, are we going to make or lose money on that?

23:45Right.

23:46Another thing I wanted to ask you about or get your take on.

23:49I've had quite a few conversations lately around AI and underwriting specifically.

23:56Where do you where do you sit in that in that in that conversation?

24:01Are you guys investing in AI driven underwriting?

24:08How do you feel about that?

24:10But, Zeb, how do I feel about it?

24:15AI is coming at having lived through, you know, the invention of the smartphone and the invention of the Internet,

24:24which, by the way, was hyped up like crazy and didn't get adopted so fast.

24:30And and now this and other things along the way.

24:33AI is the real deal.

24:36And it is moving much faster.

24:39It's what's available is moving much faster than what I think most companies can adopt.

24:47And and there is no silver bullet for the mortgage industry out there.

24:51You can't go to one provider of software for a end to end mortgage system that that is advertised as

25:02entirely AI driven and actually end up with something usable.

25:06It doesn't exist.

25:07But what does exist are AI solutions across the factory.

25:15What I mean by factory is from salesperson qualifying lead to loan being closed and serviced.

25:20So you asked about underwriting.

25:24So what's you know, first of all, you got to have a great base.

25:30You're you have to have a base of technology that's highly efficient.

25:34And most importantly, is creating a pristine data lake because AI survives off data and the data it's the data

25:45you give it.

25:46In house has to be pristine.

25:49So that's a project we're working on right now because we have 15 years of data that that wasn't particularly

25:56designed for an AI machine learning.

25:58And we're almost done with that project of of scrubbing all of our historical data.

26:04All of our new data has been completely rerouted and and made sure that it's perfect.

26:12And I'd love to talk about what we're doing with clog code.

26:16But regarding underwriting, what we're doing is just getting started.

26:21And what I mean by that is we're taking functions that underwriters were spending time on, like pulling comps for

26:34a what a what a what a what a project might be worth when it's complete from several different sources.

26:41And now we are using AI to just grab that data.

26:45Yeah. Same thing with a borrower might come.

26:51We we are very rigorous about checking out a borrower's experience worksheet.

26:58It's it's one of the four documents that has to be submitted with a loan at ABL.

27:03And they might give us the name of three different LLCs that they've used and and link it to properties.

27:11We can use AI now to go data scrape that instead of looking them up one at a time laboriously.

27:18In fact, we were offshoring that on and because it had to be done manually.

27:23Now we're using AI to do that.

27:28But I I believe what we do with with new construction and fix and flip is still a very hands

27:42on discussion and often very bespoke.

27:45They're not cookie cutter.

27:48Some are, but most aren't.

27:50And so I'm not yet at the point where I'm going to sit here and say,

27:56A.I. is going to replace 90 percent of my people.

27:59I just I don't see it for for our business.

28:05And also.

28:07We really have studied the market in the last year or two with new data that's available that wasn't available

28:15before.

28:16And what we've discovered is that over 50 percent of the of the market, which is over 100 billion.

28:25It's still done like by firms like ABL, where we actually speak to borrowers.

28:32When we underwrite a loan, when we underwrite a loan, we call the borrower.

28:36Our underwriter calls the borrower.

28:38I know it's inefficient and says, tell me about the deal.

28:42That's how Paul, Dan and I built the firm.

28:45And we want a borrower to explain to us exactly what they're going to do.

28:50And maybe it's five or 10 minutes.

28:52But a salesperson has asked them.

28:54We ask them.

28:56Then when it comes to draws, which is what borrowers really care about, the speed of money.

29:02This is the speed of money business.

29:03It's not just money lending.

29:06We now use proprietary technology where a borrower can go to their job site at 8 a.m., videotape the

29:14whole thing, take photographs.

29:16Their draw schedule is already uploaded into our technology.

29:19They push a button on their phone.

29:21It uploads.

29:22I have eight draw managers.

29:25Now, I don't think they're going to get replaced by AI very soon.

29:29They look at every single aspect of that project.

29:32And then they might, through the app, ping the borrower back and say, take another video of the kitchen and

29:39show me the cabinets in Ireland again.

29:44I'm making this up because maybe that's what he's asking for.

29:48And with that tech, 90% of our borrowers are using it, and about 80% of them get their

29:55money the same day.

29:59AI is not very involved in that yet.

30:03But it's easy to envision training AI to look at drywall and look at, you know, foundations and give an

30:18opinion.

30:19But then am I going to give out $100,000 for a foundation without one of my staff looking at

30:26it and saying, agree?

30:29Probably not.

30:30You know, that's, you know, you know, but would I allow an AI program that's been trained by us and

30:38tested that recommends disbursement, you know, that then saves a ton of time?

30:45Maybe that, you know, maybe that tech probably, that tech is available today, I'm sure, that we could license a,

30:54we could train cloud code or license a different AI model to learn what it means to have a completed

31:01foundation.

31:02And then maybe that's going to save five or eight minutes from one of my draw manager's day.

31:07So where I see AI going for a firm like ours is where I'd like it to see it going

31:13is, number one, is it being adopted to make the customer experience better?

31:21What's the purpose of the adoption?

31:23That has to be defined.

31:25And that should always be the goal.

31:28Customer experience has to be better.

31:31Okay, number one.

31:33Number two, is it, can we leverage it so that we can increase our volume without having to hire more

31:43people?

31:44So I never think about it as a tool to have layoffs.

31:54I'm thinking about it as what's better for the customer and how can we double in volume and hire the

32:01least number of people to get there?

32:04And, you know, what's interesting is it's making some people a lot more valuable.

32:13People that really understand how the system works and what borrowers need and people who come to work with great

32:23ideas.

32:24AI is not replacing them.

32:27You know, those people are needed.

32:30There might be other jobs that are highly clerical that will go away.

32:37I mean, let me give you a quick example.

32:39It's just amazing with cloud code.

32:43In order to close alone, other firms might have better tech, but right now, because we're in the middle of

32:49turning over into new tech,

32:51in order to close alone at ABL, our closers have to grab data from several different systems.

32:59Using AI, we've trained AI to grab it.

33:03So now our closers can just look at a screen and see all the data they need to close.

33:09Saved about 15 minutes for closing and probably, you know, an occasional rare error.

33:16So there's a lot of that happening.

33:18And what we've done, this is not a commercial for cloud, but what we've done is we've taken 10 or

33:2615 of our rising superstars and given them a sandbox for cloud code and said,

33:35go do something, take it, think about your job, create something.

33:41And then we have a group that meets every week and trades stories about what they're creating.

33:47And what we can create right now is what I just described, a system that takes existing data and presents

33:56it more efficiently.

33:58Did you hire somebody, was this all done in-house by your own people?

34:03Did you have a consultant, an AI consultant or a programmer come in and say, hey, this is the framework,

34:10this is the system that I'm looking for, build this for us, at least initially, and then we'll work on

34:16it ourselves.

34:17Where's the talent coming from for this?

34:20I'm happy to say we've spent the last two years investing in building up a great IT department.

34:26And we have superstars and they're driving it.

34:32We haven't had to hire consultants to teach us how to use AI tools.

34:40But and I have to tell you that it can be dangerous.

34:45And what I mean by that is, remember, in the beginning, I said, you got to have a pristine data

34:55lake.

34:57And in every firm across every industry in America, if they're using AI, they have to be using a pristine

35:04data lake.

35:04So you can't just hand an AI tool to an employee and say, go create something that changes your job

35:13and have them create new data that pushes into the data lake.

35:18That that that has to be I know I'm getting really granular here that has to be governed by our

35:25IT department.

35:27Right. Because because that's a new source of data.

35:31It has to be scrubbed.

35:32It has to be verified.

35:33It has to be approved.

35:35It has to be mapped.

35:36But to take all these existing sources of data, existing data and combine them into a new view or or

35:45or work with them to eliminate five or 10 minutes of like checking comps, looking for rents, checking borrower experience.

35:57We have it now we're training it to read title reports, you know, read the title, read this title report

36:05and tell me if A, B, C and D are in it.

36:09You know, that all that's not pushing data anywhere.

36:13That's just taking what a human is doing today and asking the machine to do it.

36:18So we're doing that all in house.

36:20Well, I have I got one again, another big broad question for you.

36:26But I got into the industry.

36:30I'm going to I'm an originator myself.

36:32I don't originate anymore.

36:33I still keep my license.

36:34But I got into the industry in 2000 and 2010.

36:40And I, I know that the market over the past couple of years, you know, you're seeing people dropping out

36:48because a large part of it is, you know, if you over the last decade, right, if you couldn't, if

36:56you couldn't sell mortgages floating around from three and a half to five, you know, percent interest rates, there was

37:03something wrong with you.

37:05You know, you there are a lot of originators that got into the business that they they didn't really build

37:11out relationships.

37:13And during the whenever rates dipped in the COVID era, they abandoned the they abandoned the relationships that they did

37:22have with their with their agents and went after the easy, you know, refi.

37:26They just kind of gave up purchases and then whatever rates went back up, then the relationships that they kind

37:31of had previously, they didn't have it all anymore because the agents.

37:35So that's like the, you know, I've seen a little bit of cycles or I've seen a small cycle, I

37:41guess, relatively in the industry.

37:43You've been in the industry around 40 years.

37:45So you've seen far more cycles than I and a lot of people from a very unique seat, I guess.

37:54And I'm curious, what's your perspective on where we're at, both in regards to a market cycle and an industry

38:05shift?

38:06Because I mean, the market is cyclical, right?

38:09And so rates will go back, you know, rates will even out and they'll they'll drop and, you know, purchases

38:15will will kick back up.

38:17That's a that's a historic cycle that's just going to keep repeating.

38:20But while that cycle is happening, I feel like the foundations of the industry are shifting largely due to AI

38:28and the technological innovations that are that are coming about.

38:31So we're kind of at this weird intersection of two, two cycles happening at the same time.

38:39One, what how do you feel about that idea?

38:42And what's your perspective on, you know, where we're at in the shift and looking down the road the next

38:48five or five or 10 years?

38:50What do you think both the industry and the market looks like?

38:55Zeb, great question.

38:58Five to 10 years is a very long time.

39:03And when you say 40 years, it's true and it makes me feel really old.

39:09We're in a weird spot right now.

39:11And the reason we're in a weird spot is because affordability has never been where it is right now.

39:21It's in a stratospheric level that I never imagined would be hit.

39:26And I don't I don't see an easy way out of this problem and just lowering mortgage rates to three

39:36percent, whatever President Trump would like to do, which is going to be hard to do with inflation running where

39:42it is.

39:44If you do the math with the average home at four to four fifty versus two fifty six or seven

39:52years ago, I might have my numbers off a little bit.

39:54But it moves the needle, but not enough people's incomes haven't kept up with with that.

40:02So we have a serious structural problem in this country of not enough housing supply relative to demand.

40:10And the demand is coming largely from the millennial generation and now from the one following it.

40:16I think that's Gen Z.

40:17But, you know, the millennials are the biggest generation in history and they still have something like five to eight

40:24million units of pent up housing demand.

40:27And that's why we've been very successful with new construction.

40:31We moved into it in 2015 because we believed in that and that's part of the cycle.

40:36So, number one, the federal and local governments across this country have to seriously focus on how do they cut

40:47red tape?

40:48How do they create conditions that make it easier for builders to build homes?

40:53We need more supply straight.

40:55I mean, that is the only way out of this problem, because there's no concept of housing prices dropping 30

41:02percent.

41:03I don't even know what would cause that.

41:04It'd be a disaster.

41:06It'd be the one of the worst recessions in history.

41:08We just can't have it.

41:11It's just it's it's kind of hard to imagine because we've only had housing drops like that twice, the depression

41:16and the crash.

41:17So let's not even think about it.

41:19Let's think about creating more supply.

41:22And and and I know there's a bill that both houses of Congress have passed that maybe I forget what

41:30it's called.

41:31But that that that that is being held up right now.

41:35But the road to housing, the road to housing act needs to be passed.

41:39But that's not a magic bullet.

41:44So so so that's number one.

41:46Number two, I think so supply, huge problem.

41:49Got to fix it.

41:50Number two is technology.

41:52And and relative to what you were talking about, about you being a loan officer and being in the industry,

41:59in my experience, I think we're going to see rapid adoption of AI tools in the mortgage industry.

42:10I like to say up until about four or five years ago, I feel that maybe except for Quicken, more

42:18mortgage technology was pretty much stuck in amber.

42:23Seventy percent or sixty five percent of all mortgage companies in the industry used and still use the same mortgage

42:29package, the mortgage system.

42:31And I don't want to name I'm not naming the company and and frankly, that that company's technology wasn't keeping

42:41up with what was possible.

42:44And I'm sure they're going to make massive investments in AI now.

42:50So what's going to happen is everything I've already said, I believe that AI is going to radically transform the

42:58mortgage experience.

42:59I think it's going to make companies massively more efficient.

43:04And so what it's going to do is is it's going to level the playing field.

43:14I believe that AI enabled mortgage systems are going to be readily available in the next several years.

43:23So instead of companies really laboring to adopt great tech, which has been my experience my whole career, I do

43:32believe it's already happening, that there are going to be tools and systems that come out that make it pretty

43:39easy to enter the market.

43:43And here's the critical part, deliver great customer service.

43:48So what we had over all these years is you had to have a good source of capital and you

43:55had to have good tech, you had to have good people.

43:58And then maybe you built a sustainable business that built a great reputation and got borrowers to come back multiple

44:06times.

44:07That's the key.

44:09Acquiring a borrower is expensive.

44:12And where I see both the private money lending industry going, and I'm sure it's transferable to the conforming and

44:23non-QM businesses, is this industry is going to shift to, does your company have adequate capital?

44:36Yes or no?

44:38Does your company have the best possible tech it can adopt?

44:43Probably by licensing AI enabled systems.

44:47Okay.

44:48That's number two.

44:49Number three, do you have great people who, when they interface with your borrowers, deliver to them the best possible

45:00customer experience?

45:01And then the fourth thing is, do you retain your borrowers?

45:06And I believe that's where the industry is headed.

45:11And so what we're going to end up having is a real competitive market for retaining the best borrowers.

45:25And what that means is there's going to be rate pressure.

45:29So because AI is going to allow originators across all the products to originate more efficiently.

45:42And since everyone's going to be able to originate more efficiently, not just one company, it's going to force all

45:51the companies to lower their rates because they're still going to make the same return on equity with less people.

45:59And so that's my grand kind of belief of where we're headed.

46:07And companies that are saddled with old tech and old data, it's going to take them longer to convert.

46:14Meanwhile, new companies are going to be able to enter if they've got, you know, and hire great people and

46:22license great tech.

46:24If they come with great capital, you know, there's going to be lower barrier to entry, I believe.

46:31That's what this tech is going to lead to lower barrier to entry, better borrower experience, ultimately lower rates.

46:38That's that's what I'm that's what I believe will happen.

46:43And everybody who's listening to this podcast, and I hope it's millions of people.

46:48Me too.

46:49Yeah.

46:50Go talk to your representatives and your local government and everywhere possible to make it easier to build homes.

47:00That's a good answer.

47:01Kevin, thank you so much.

47:02I really appreciate the great conversation.

47:04I enjoyed speaking with you and I appreciate you taking the time.

47:08Zab, it was great.

47:09You asked great questions and I wish I had 10 more hours to.

47:14We'll have to.

47:15No, there's more conversations in our future.

47:18We'll have to get you back on.

47:19I would love to.

47:20Thank you very much.

47:22All right.

47:23Bye bye.

47:28Bye bye.

What 2008 taught a billion-dollar lender

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