00:06I'm Allison LaForgia, Managing Editor of HousingWire's Content Studio, and from Las Vegas,
00:12I am sitting with Ethan Winchill, who is the co-founder and president of TrueWork. Ethan,
00:17thank you for joining me today. It's awesome. Awesome to be here. Hope you're having a great
00:21day. I'm having a great day, and I will tell you I'm very excited to hear about TrueWork. So
00:26what led you to co-found the company? When we were first looking at this space back in 2017,
00:34it was right after a big Equifax consumer credit breach. It was when crypto was hot. Everyone's
00:41going to decentralize, give power back to the consumers. And really, that's where it started.
00:45Like, how can we create a way for any time a consumer is applying to anything, mortgages,
00:50apartments, jobs, government benefits, they can compile and share in the information they need
00:56to about themselves to get the thing, to get approved for the thing. So it turns out we do
01:00that today for income and mortgage, but it's really a much broader problem that we're solving
01:04over time. And to your point, income has changed drastically in the past five, let's say 10 years,
01:15really accelerating in the past five years, and then incrementally so after COVID. So how has the rise
01:21of gig work and 1099 income changed the way that lenders need to think about verification?
01:27Yeah. So when we started the company, it was still, the first thing we saw was like,
01:31even for just a wage earner, a W-2 and a pay stub, the best automation solutions only works like
01:37say,
01:38three out of 10 times. So seven out of 10 times, you still had to go and do a bunch
01:41of manual stuff,
01:42collect documents, make phone calls just to do it. But that was just for wage earners.
01:46Now, I think the GSEs have 21 different types of income that you can use to like accumulate to
01:52qualify for a loan. So now you stack on top the fact that like three out of 10 times just
01:56for
01:56wage earners, but now you have the complexity of so many different types of income. You basically
02:00end up with hundreds and hundreds of different pathways you could go down just to get all of the
02:06income for one individual person. And that's an insanely complicated, and it ends up being because
02:10it's a complicated, insanely expensive problem for lenders to figure out how to solve.
02:13So talk to me about how the traditional pathways fail.
02:19So the traditional pathways fail in the sense-
02:22Or fall short.
02:22Yeah. So if you go and need to validate income for a consumer, and you're just looking at their
02:29W-2 and pay stub, maybe to qualify for this loan, you need $100,000 in income. Maybe on just
02:36their
02:36W-2 and pay stub, they only get 75. But that's because all that's in the payroll system is maybe
02:41one part-time job. But these people have two part-time jobs. Maybe they're self-employed and
02:47actually get income from a business that they own and operate as well. Plus, they have rental income.
02:52And again, 21 different income types. So you could keep telling the story for three more minutes.
02:56Right. Ad nauseam.
02:57And really, the system is only set up, or most of the automation systems are only set up for the
03:02happy path, which is like, I make enough income from my one job to clear the income threshold that
03:08I need. And in that path, it does work. But that path is a far minority of times that that
03:14is actually
03:14what's happening on the ground. It sounds simple in concept, but there's so many exceptions in
03:19mortgage. And most companies really struggle to handle the multi-value exceptions.
03:23On vanilla borrower.
03:24Yeah, exactly. And it turns out everyone's basically on vanilla.
03:27Right, right, right. Where I think we've seen so much of a shift, where people have diversification
03:32as far as income. And you really want to give people their best shot about getting into a home.
03:38You want to really put them somewhere that they're going to be happy, that they can afford,
03:41that meets their needs.
03:43Yeah.
03:44So let's talk a little bit about what opportunities lenders have to better serve borrowers
03:50without increasing risk. That asterisk at the end part of that question is the important part,
03:55right?
03:55Yeah, well, I think this comes down to just like, making sure you are for most, like, again,
04:00for most landers, just following the GSE guidelines. The GSEs have rules to follow for all of these
04:07different types of income. The hard part is structuring those rules into an SOP. It's like an
04:13operating procedure for your production teams, and then getting make sure they're actually following
04:16those things. And so that's a lot of, like, the product innovation that we're bringing. And the GSEs
04:21have done great work here to make these APIs available, but it still requires lenders to
04:25integrate with them. So that's, like, kind of the middle where we're trying to play. Like, we'll get
04:28the data. We'll make sure the data is processed in a way that the GSEs have said, yes, this is
04:33the
04:33correct way, and you can verify that with code. And then make sure that, like, that is the aggregated
04:39number that the lenders are using to actually run their calculations and do their underwriting.
04:44So let's dig in a little bit further there and talk to me about how TrueWork approaches that GSE
04:49alignment. Yeah. So we are already, like, validation partners with Freddie and Finn. What that means
04:57today is that when we deliver a verification report to a customer, they can run it through
05:02their automated underwriting systems and receive basically, like, validation that, like, yes, the
05:09report is accurate. We're taking that a step further by actually saying how much income is
05:14represented on these reports. So if we get, say, a bank statement, the Fannie Mae has single
05:20source validation. You can run that bank statement through their systems, and it will tell you,
05:25based on this bank statement and the consistency of direct deposits, this bank statement has $50,000
05:31of annual income in it. So doing those kinds of things for the lenders in one place, so whether they're
05:36getting a pay stub, they're getting a bank statement, they're getting a tax report, they're getting
05:40a document with, you know, alimony payments, all that type of stuff is processed strictly by the
05:47guidelines and all aggregated into one number that they can just use to underwrite. So you make
05:51compliance easy? Yes. Love that. Are you telling me my answers are too long? No, no, no, you make
05:57compliance easy. I think it's important to emphasize because compliance is one of those things that's
06:03business critical. It's not really sexy to talk about. And it's absolutely critical to your
06:08operational team. Yeah. And like vendors will find this out the hard way if they go to ship something
06:12sexy that will not get used because you will have the compliance team that says, wait, we cannot do
06:18this because even though it's going to save us a bunch of money, every time we use this thing
06:21is opening up a $10,000 liability that someone is going to go and call us on at some point
06:26because
06:26you have to follow the rules. Absolutely. Absolutely. So looking ahead, how do you think
06:32verification will need to evolve to keep pace with changing homeownership and workforce trends?
06:40I think it's a lot of the stuff that we've talked about. One thing we think a lot about is
06:50not over rotating towards thinking that we can solve everything in the product. There's so
06:56so, so, so many exceptions that you're never going to build for a hundred percent of the long tail.
07:01And so really thinking about like the services model that you kind of wrap around the product
07:05to deliver to customers. It's one of the things that we've done since day one, like, and actually
07:10like, you know, some tech companies do about, oh, tech, like we'll just build the product. It'll do
07:15it all automatically. And then like the customers will just use it. And it turns out in mortgage,
07:19because there's so many regulations, because compliance is such a, such, so top of mind,
07:23actually being able to physically pick up the phone and speak to a human on our team and say,
07:27here's a problem and understand the nuances of the problem and solve that problem. So that's why
07:32we publish our customer support scores, how long it takes to actually get a customer support ticket
07:38resolved with us. That is live. You can go to our website, look at those stats. It's about five
07:42minutes. And we really think about the services model that we deliver on top of the technology.
07:46And of course, you're trying to do more with the technology over time. No one wants to pick up the
07:50phone call and like, get something clarified. But the ability to do that in the case where you need
07:56it, because the other end of that phone call, there's a person trying to close a home loan.
08:00And so if you don't have that services model around it, the like cost of that exception skyrockets,
08:05because one bad outcome there is like, is catastrophic for the person like impacted.
08:09Right, right. So Ethan, if you have your, if you're looking into your crystal ball,
08:13what's next for TrueWork? There's like the mortgage specific answer, which is just
08:18continuing to march down this journey of helping every lender big and small appropriately be able
08:26to help their borrowers use all 21 different types of income to qualify for loans, put more people in
08:31homes. There's a non-mortgage specific answer to connecting back to why we started the company in
08:36the first place where we are looking at property management and rental screening, helping people
08:44qualify. There's a ton of like fraud and abuse in government sector, in the government sector right
08:50now, helping to stamp that out, helping to help states comply with increased eligibility requirements
08:57for like Medicaid programs to make sure they can continue to deliver those benefits while complying
09:01with these. So there's like both the just solving the problem a hell of a lot better in mortgage
09:06because it is getting so complex so fast and folks are having a tough time keeping up. But there's
09:10also keeping an eye towards the big picture of like, as we do this, we're developing a ton of
09:15competency just in understanding what about the consumer needs to be understood to help them do
09:20any sort of, to transact in any sort of major life event and making sure we're continuing to like
09:25expand the aperture and stay ambitious in that vector too. Fantastic. Well, Ethan, thank you so much for
09:29joining me today and I can't wait to see what's next. Thank you, Alison.
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