Speaker 1: Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2: Hello and welcome to another episode of the All Thoughts podcast.
Speaker 2: I'm Tracy Alloway.
Speaker 3: And I'm Joe Wisenthal.
Speaker 2: Joe, do you remember a month or so ago we
Speaker 2: recorded an episode all about why mortgage rates were going
Speaker 2: up even though the FED has cut Yes.
Speaker 4: This was a big one at the time, and I
Speaker 4: think it still is really important. Basically, there's this intuition
Speaker 4: that people have that the FED effects policy by cutting rates,
Speaker 4: and one thing that happens when rate cuts is that
Speaker 4: borrowing costs go down. In one form of borrowing that's
Speaker 4: very popular is mortgage rates. But we're in the middle
Speaker 4: of a rate cut cycle. The FED cut fifty in September,
Speaker 4: then kind of another twenty five minutes sobsequent meeting, But
Speaker 4: mortgage rates have generally not moved down at all, and
Speaker 4: in fact moved up after that fifty basis point cut.
Speaker 4: By the way we're recording this November twenty fifth, we
Speaker 4: haven't seen much improvement at all, and so there is
Speaker 4: this I don't know if it's really a mystery, but
Speaker 4: there is certainly a story about the FED in the
Speaker 4: middle of a rate cut cycle, and yet it not
Speaker 4: really feeding through to a lot of.
Speaker 3: Kinds of borrowing.
Speaker 2: I don't think it's a mystery. We did a whole
Speaker 2: episode on it. You're explaining what's right.
Speaker 3: You're right, We explained it all. You're right.
Speaker 2: But what I was gonna say is, as part of
Speaker 2: that conversation, you asked a really interesting question, which for once,
Speaker 2: for once, which is why can't we have a one
Speaker 2: click mortgage REFI do you remember that?
Speaker 5: Yes?
Speaker 4: So you know, like I've refiled a mortgage in my life.
Speaker 4: It's kind of annoying. You know, if you're in the
Speaker 4: right situation, you can save money and it's probably worth it,
Speaker 4: but it involves a lot of paperwork, et cetera. And
Speaker 4: you know, I think we're so used to one click
Speaker 4: financial transaction, maybe two clicks or whatever.
Speaker 6: You know.
Speaker 4: One of the things that came up is that there
Speaker 4: are often a lot of mortgages out there that theoretically
Speaker 4: are sort of in the money where the borrower the
Speaker 4: homeowner could take advantage of lower rates, but they don't
Speaker 4: for whatever reason. Perhaps one reason is they don't know
Speaker 4: that rates have getting down. Perhaps another reason is they
Speaker 4: can't be bothered to do all the paperwork and stuff
Speaker 4: and so there are these lag effects, and so I've
Speaker 4: always sort of wondered, why can't you just have a
Speaker 4: one click, one click refive well.
Speaker 3: As a new lower rate.
Speaker 2: As someone who lives in fear of paperwork, I think
Speaker 2: this is an interesting question and we should talk about it.
Speaker 2: And it turns out we actually have the perfect guest.
Speaker 2: We're going to be speaking with someone who was involved
Speaker 2: in a one click mortgage lender. Mike You, co founder
Speaker 2: and CEO of Vesta. Mike, thank you so much for
Speaker 2: coming on all thoughts.
Speaker 6: Yeah, thanks for having me.
Speaker 2: So why don't you give us a very quick career summary?
Speaker 2: Why are we talking to you?
Speaker 6: Yeah, so I've spent my entire career in the mortgage
Speaker 6: industry on the tech side purely. I like to joke
Speaker 6: that everyone who ends up in mortgage origination stumbles into
Speaker 6: it by accident. So I worked at Blend.
Speaker 4: Kids don't dream of like one day I'm going to
Speaker 4: be a mortgage originator. You didn't dream of that when
Speaker 4: you were in a elementary school. Anyway, keep going.
Speaker 3: Sorry.
Speaker 6: I actually when I'm recruiting engineers here at Vesta, I
Speaker 6: tell them I'm like, you know, lots of founders will
Speaker 6: give you some weird story about how they've dreamed about
Speaker 6: doing this thing since they were twelve. I can tell
Speaker 6: you the story like that, and you wouldn't believe me anyways,
Speaker 6: So let's be honestly stumbled into it. I started at
Speaker 6: a mortgage tech startup, Blend in twenty sixteen, so the
Speaker 6: company was about fifty people back then, and we built
Speaker 6: a ton of the bar we're facing experience for big banks,
Speaker 6: big mortgage lenders, et cetera. But the goal really being
Speaker 6: how you make the process more digital, like it was
Speaker 6: all pay performs back then, even for the barer to
Speaker 6: fill out, and then how do you know, eventually consolidate
Speaker 6: that down into one click or one tap if you're
Speaker 6: on mobile. That company went public in twenty one, but
Speaker 6: I left in twenty twenty to go and build a
Speaker 6: different startup, Vesta, where I think a lot of what
Speaker 6: we struggled with that Blend was the core infrastructure in
Speaker 6: the back end of the system made it really hard
Speaker 6: to consolidate the mortgage process, accelerated, cut costs for lenders,
Speaker 6: save time, and make it easier for borrowers, and so
Speaker 6: kind of working on the back end system of record
Speaker 6: now where I think a lot of the other technology
Speaker 6: problems are and I think, as this is about one
Speaker 6: click mortgages, I think there are of course some technology limitations,
Speaker 6: which is why we started the whole company, But there's
Speaker 6: also a fun variety of regulatory implications that I'm sure
Speaker 6: we'll dive into today too. Great.
Speaker 4: You know what's funny is I think not only on
Speaker 4: the podcast did we talk about why were there no
Speaker 4: one click refise available? I think we specifically put out
Speaker 4: a call. We were like, have you've ever been in
Speaker 4: a startup, some y combinator thing which is attempted to
Speaker 4: do one click? Reach out to us? And you were
Speaker 4: one of the I don't know if Blend was ever
Speaker 4: a y combinator thing, but that's not really that important.
Speaker 4: But you answered the call literally and you heard it and.
Speaker 2: Sore the odd lots call.
Speaker 4: Answered the odd lots call to You're the perfect guest. Obviously,
Speaker 4: we want to get into what you're doing it investa
Speaker 4: and just how it all works. Talk to us a
Speaker 4: little bit more. What did Blend do to attempt to
Speaker 4: solve the problem of I don't know if it really
Speaker 4: gets to one click, but simplifying or streamlining the mortgage
Speaker 4: application process.
Speaker 6: Yeah, it's really funny because it's only been ten years,
Speaker 6: but ten years ago, actually, if you wanted to get
Speaker 6: a mortgage, you couldn't even go and apply on the internet.
Speaker 6: I would actually say in the early days of Blend,
Speaker 6: you know, twenty sixteen, seventeen, we'd talked to lenders and
Speaker 6: they would be like, you don't understand people applying for
Speaker 6: a mortgage. They don't want to do it online, which
Speaker 6: just blew our mind. And there are a lot of
Speaker 6: you know, old school loan officers who are like, I
Speaker 6: call my borrower and I interview them, and I literally
Speaker 6: take the paper it's called the ten oh three or
Speaker 6: the uniform Residential Loan Application. I take this paper form
Speaker 6: and I fill it out with a pencil. I pull
Speaker 6: over to the side of the road. My bar was
Speaker 6: talking to me on the phone. I take them through
Speaker 6: my process and I fill it out with pen and pencil.
Speaker 6: Then I give it to my assistant and they go
Speaker 6: like type it into the back end system. And we
Speaker 6: were getting this kind of pushback left, right and center
Speaker 6: in the early days, really just around the idea that
Speaker 6: people wouldn't want to apply online. And then rockets big
Speaker 6: Super Bowl, the ad came out push button Get Mortgage,
Speaker 6: and then all the banks are like, oh, well, if
Speaker 6: Rocket's going to do it, we'd probably need something competitive
Speaker 6: with this, And I would say that was really an
Speaker 6: inflection point for that company. But so much of it
Speaker 6: was like, if you want to get to a one
Speaker 6: click mortgage, well, first of all, you need people applying
Speaker 6: for the mortgage on the Internet, not via physical paper.
Speaker 6: And then it really becomes about how do you start
Speaker 6: to pull in the data from all these various sources.
Speaker 6: So Blend was one of the first to work with
Speaker 6: some of the GSS on getting asset data direct from
Speaker 6: the banks and pulling that into the mortgage application so
Speaker 6: you can get faster underwriting and not needing to upload
Speaker 6: a whole bunch of paperwork and bank statements. Similar things
Speaker 6: for like income data, and then people are making big
Speaker 6: pushes around property data and AVMs. It's a whole variety
Speaker 6: of data sources you've kind of got to stitch together
Speaker 6: in order to really save the barrow from sending in
Speaker 6: a whole bunch of paperwork. Because one thing that I
Speaker 6: think is a little less obvious when you send the
Speaker 6: lender your pay stub, you're not just proving that you
Speaker 6: have the income. They actually take a bunch of the
Speaker 6: numbers on that pay stub that they didn't ask you
Speaker 6: to fill out anywhere, and fill that out in a
Speaker 6: spreadsheet or something to calculate your income based on their
Speaker 6: models and what the GSS tell them to do and
Speaker 6: things like that, and so so much of it was
Speaker 6: just if you can digitize the process and get that
Speaker 6: data in a structured format from a whole bunch of sources.
Speaker 6: At the beginning, the belief was that's really going to
Speaker 6: drive you towards a faster and more efficient process and
Speaker 6: eventually one quick So you.
Speaker 2: Mentioned the GSS a couple times there. I imagine if
Speaker 2: you're doing a mortgage, at some point you're going to
Speaker 2: have to get the guarantee from Fanny and Freddy, and
Speaker 2: so you're going to have to go through them. What
Speaker 2: are their systems, Like you mentioned you worked with them, Like,
Speaker 2: how did you plug in to the GSE systems?
Speaker 6: Yeah, So, as you might expect from a couple of
Speaker 6: large financial institutions that are also now under conservatorship, their
Speaker 6: systems are definitely of varying degrees of maturity. One thing
Speaker 6: that I will say that I actually really appreciate about
Speaker 6: both Fanny and Freddy is they have invested a lot
Speaker 6: in technology over the last decade. I think when you
Speaker 6: get down to it, financial products are all The nice
Speaker 6: thing is there's no physical commodity, right, It's all money
Speaker 6: and numbers in a ledger, And so I think they've
Speaker 6: definitely started to embrace their role more as needing to
Speaker 6: provide technology to the ecosystem that is modern, that is effective,
Speaker 6: but very honestly like the core piece of technology they
Speaker 6: built that gives you guidance on whether your loan is
Speaker 6: going to qualify or not. For sell to Fanil Freddy.
Speaker 6: It's called Desktop Underwriter in the Fanny case and Loan
Speaker 6: Product Advisor in the Freddie case. The original versions were
Speaker 6: built in the nineties and so definitely some older systems
Speaker 6: it's all still you know, XML system to system conversation
Speaker 6: if you can integrate to them at all. Some of
Speaker 6: the systems don't have any capability for system to system integration,
Speaker 6: and so if you want to actually sell the loan
Speaker 6: to Fanil Freddy, someone has to go to their existing
Speaker 6: loan origination system, download an XML file, log into their
Speaker 6: website and upload it. So there's definitely, I would say
Speaker 6: varying degrees of modernization and capability across those technology systems.
Speaker 6: And that is I would say, no more true at
Speaker 6: Fany and Freddi than it is that most of the
Speaker 6: major financial institutions you think about, even most of the
Speaker 6: smaller lenders you think about, it's all kind of on
Speaker 6: the spectrum of everything was built between one and thirty
Speaker 6: years ago, and everyone's got to kind of move. Thirty
Speaker 6: years is long left in technology. Everyone's got to kind
Speaker 6: of move and rebuild a new version of this, new
Speaker 6: version of that.
Speaker 2: Oh yeah, Joe, I remember you know those charts that
Speaker 2: show like all the acquisitions that a Jpmore oh yeah,
Speaker 2: or a Bank of America has done. It's sort of
Speaker 2: like a flow chart. Yeah, every single one of those
Speaker 2: probably has a different IT system, right, So I always
Speaker 2: hear that one of the big difficulties in building a
Speaker 2: giant bank is basically sorting out the.
Speaker 4: IT totally big institutions, you know, it's easy to sort
Speaker 4: of assume that sort of CLOSEI government institutions are going
Speaker 4: to be worse on so forth, and maybe sometimes that's
Speaker 4: correct and sometimes that's not. But big gigantic institutions, particularly
Speaker 4: ones that had all kinds of mergers and roll ups,
Speaker 4: et cetera. They all have this, and this has been
Speaker 4: something that's come up a little bit in the past.
Speaker 4: We've done some episodes on bank software in general, and
Speaker 4: so I'm not particularly surprised to hear that Fanny and
Speaker 4: Freddy have a lot of still work to do, even
Speaker 4: if they have invested.
Speaker 3: Why is it hard?
Speaker 4: Maybe from your perspective, from the perspective of either a
Speaker 4: Fany or Freddy or just any other gigantic financial institution,
Speaker 4: how would you describe why it's challenging to update these
Speaker 4: systems so that they resemble the type of software we're
Speaker 4: used to in twenty twenty four.
Speaker 6: Definitely, Maybe I'll start even way back, like fifty years ago.
Speaker 2: Are we going to talk about Kobyl? I hope, so
Speaker 2: we can.
Speaker 6: Talk about Cobyl if you'd like. But I think it
Speaker 6: actually when I was at Blend, I was fortunate enough
Speaker 6: to work with tim Myoppolis, who was before I Blend,
Speaker 6: the CEO at Fanny May and he has this line
Speaker 6: which really stuck with me, which is that everyone says
Speaker 6: that banks are like slow adopters of technology, but the
Speaker 6: problem with banks actually is that they were very early
Speaker 6: adopters of technology, right going back to everything really is
Speaker 6: just a number inside a spreadsheet at a bank. There's
Speaker 6: no corn that you're shipping or gold bars or whatnot.
Speaker 6: Anctial services industry was really an early adoperative technology. What
Speaker 6: that means is they installed a lot of technology very
Speaker 6: very early on that then became harder and harder to
Speaker 6: rip out. And one thing that we find, for example
Speaker 6: at BESTA where we're replacing one of these core systems,
Speaker 6: when I talk to other founders in the technology space,
Speaker 6: it's much easier to install a new system to replace
Speaker 6: a spreadsheet that just like so obviously doesn't work. The
Speaker 6: enterprise security is terrible, the controls are terrible, et cetera.
Speaker 6: Then to get someone to upgrade a system that you
Speaker 6: know kind of works for them. It's clunky, it's inefficient,
Speaker 6: it's slow, but it isn't a burning pain where they like, oh,
Speaker 6: if I don't modernize, I'm going to lose the business
Speaker 6: or lose my job or something. On the other hand,
Speaker 6: I would say there's a very strong incentive in all
Speaker 6: these big institutions if you try and do like a
Speaker 6: huge modernization project of a big existing system of record
Speaker 6: and it doesn't work, you're basically putting your job on
Speaker 6: the line. And if it does work as a CIO
Speaker 6: or a line level CIO at a bank, you're getting
Speaker 6: a small promotion. I was just that the trade off
Speaker 6: is pretty bad.
Speaker 4: I was just going to ask, like, how much is
Speaker 4: it tech qua tech versus institutional inertia and incentives that
Speaker 4: really create that problem of why it's harder to upgrade.
Speaker 6: I think it's mostly institutional inertial incentives. There certainly is
Speaker 6: a lot of work that actually goes into it, right,
Speaker 6: and so you've got to get budget, et cetera. Yeah,
Speaker 6: but it's all very tractable. I will say in financial
Speaker 6: services there are relatively few technology problems that are like
Speaker 6: fundamentally hard technology problems, like we're not launching rockets over here.
Speaker 6: They all tend to be people problems. Organizational problems are
Speaker 6: problems that get in the way.
Speaker 2: Can you talk to us about the sort of life
Speaker 2: cycle of a mortgage in terms of technology, so like
Speaker 2: what's the first thing that happens, what system is it
Speaker 2: put into, and then where does it go next?
Speaker 6: Sure, so we're talking one click refive today, So we'll
Speaker 6: start with a refive in let's call it a relatively
Speaker 6: idealized case. Let let's stop the real ideal, which is
Speaker 6: like the bar is going to get an email from
Speaker 6: their servicer right which says, hey, you're in the money, Like,
Speaker 6: we service your loan, we know what you pay, we
Speaker 6: know what rates are, we know you know roughly our
Speaker 6: credit profile. We can tell you that you probably want
Speaker 6: to refinance. So the consumer is going to click on
Speaker 6: that link and they're normally going to go and fill
Speaker 6: out an online application. Today they're going to go type
Speaker 6: in a whole bunch of their data. Again, I think
Speaker 6: you probably know your servicer has a ton of data
Speaker 6: on you. Do you really need to type it in?
Speaker 6: And this varies kind of depending on how tech forward
Speaker 6: your servicer is, but often people are still typing in
Speaker 6: their whole application. Again, they're uploading a whole bunch of documents.
Speaker 6: And this is kind of sitting in the consumer facing system,
Speaker 6: which today is you know, they call it a point
Speaker 6: of sale. This is the space where really Blend is
Speaker 6: the category leader now. And so the bar is going
Speaker 6: to kind of type all that information in, They're going
Speaker 6: to hit submit. That's going to push it to what's
Speaker 6: called the loan origination system on the back end, and
Speaker 6: you can think of that as both the system of
Speaker 6: record and it's going to do all the compliance checks.
Speaker 6: It's where the people are going to do all the
Speaker 6: processing and the underwriting or any automated underwriting might happen.
Speaker 6: And it's also the system that's going to be integrated
Speaker 6: to like fifteen other systems. So one really annoying thing
Speaker 6: about the mortgage ecosystem is to produce your loan from
Speaker 6: front to back, you're probably hitting at least fifteen different
Speaker 6: technology vendors.
Speaker 4: Can you run some what are some of these in?
Speaker 4: What different parts of the stack are they serving? You
Speaker 4: don't have to list all at fifteen, but give us
Speaker 4: an example of like the various things that need to
Speaker 4: be hit and who's doing them.
Speaker 6: Yeah, so I think of it as there's a whole
Speaker 6: bunch of stuff around the property, right, so you've got
Speaker 6: to go to a title company, you've got to go
Speaker 6: to an appraisal management company kind of get the appraisal.
Speaker 6: So there's a whole bunch of stuff around the property.
Speaker 6: Someone's got to check what flood zone it's in. And
Speaker 6: we'll get into why some of the rules are really
Speaker 6: hard to change. But if you want to know what
Speaker 6: flood zone a property is in. I mean you can
Speaker 6: go on house Canary or Zillow and kind of figure
Speaker 6: that out pretty quickly. If you want to sell a
Speaker 6: mortgage to the GSS, you've actually got to hit one
Speaker 6: of their four or five designated flood certificate providers for
Speaker 6: an official flood certificate quote unquote, which is really just
Speaker 6: you know, those are the providers that signed a deal
Speaker 6: with the gs S where they get the FEMA maps
Speaker 6: that everyone else gets and they produce a piece of
Speaker 6: paper that's official enough and the GSS trust them. So
Speaker 6: that's a provider you basically have to hit. And so
Speaker 6: there's a whole variety of property you know, vendors you've
Speaker 6: got to hit around those categories. There's a bunch of
Speaker 6: bar er vendors you've got to hit around. The pulling
Speaker 6: credit is the obvious one, but you're going to want
Speaker 6: to verify their income. You're going to want to look
Speaker 6: them up in fraud databases. So there's a whole set
Speaker 6: of those, and then there's a bunch of compliance stuff
Speaker 6: to do. So generally, you know, there are entire companies
Speaker 6: that are dedicated to I have all the data in
Speaker 6: the mortgage, and I'm going to prepare the disclosures for you.
Speaker 6: Like the disclosures are so complicated, that's less a technology problem.
Speaker 6: That's like that those companies have an army of lawyers
Speaker 6: who basically read all the regulatory updates, all the updates
Speaker 6: in each of the thirty eight hundred counties in the US,
Speaker 6: any state updates, any investor updates around exactly what you
Speaker 6: have to tell the consumer before they can kind of
Speaker 6: sign a lian on their property, which, as you know,
Speaker 6: like some states are very onerous about that. And so
Speaker 6: between compliance and property and kind of checking the borrower,
Speaker 6: there's just this whole constellation of stuff that has to
Speaker 6: be done, a lot of data sources and a lot
Speaker 6: of rules.
Speaker 2: Talk to us a bit more about the rules then,
Speaker 2: Like I'm curious how these rules come into place, what
Speaker 2: sort of factors they're being based on, and then how
Speaker 2: often they actually change.
Speaker 6: Yeah, I kind of think of rules in two buckets. There.
Speaker 6: Of course, the regulatory rules, so you can imagine a
Speaker 6: ton of those regulatory rules were driven by seven eight
Speaker 6: and a lot of the things that we saw during
Speaker 6: the Great Financial Crisis or that kind of led up
Speaker 6: to the Great financial crisis, so a lot of regulatory
Speaker 6: stuff around what you disclose the consumers around you know,
Speaker 6: you have to qualify their ability to repay in order
Speaker 6: to have a compliant loan. So there's lots of regulatory stuff.
Speaker 6: And then there's investor rules, which overwhelmingly you know, come
Speaker 6: from Fanny er Freddy. There is a small private label
Speaker 6: market and some other stuff. One thing that is true
Speaker 6: about all of these rules, right the investor rules and
Speaker 6: the regulatory rules, is they're both kind of set again
Speaker 6: talking about organizational inertia by pseudo government institutions that have
Speaker 6: really been burned by mortgages in the last two decades,
Speaker 6: and so they're pretty you know, nervous about that, and
Speaker 6: there's very little incentive to simplify the process to remove rules,
Speaker 6: and so the rules change. I would say every month
Speaker 6: or two you get a few new rules from the investors,
Speaker 6: but they very rarely subtract rules, which tends to be
Speaker 6: a reason that you end up with. I want to say,
Speaker 6: the fan selling Guide is now twelve hundred pages basically
Speaker 6: of rules that the loan has to satisfy. And these
Speaker 6: rules can vary from you know, relatively straightforward things like
Speaker 6: you can't refinance an FAJ loan within a certain amount
Speaker 6: of time after the loan was originally originated, so there's
Speaker 6: like a seasoning requirement. You know, there's a lot of
Speaker 6: documentation rules, like if you're going to provide an income
Speaker 6: to Fanny May, you normally have to have a pasteb
Speaker 6: and in W two attached to it to kind of
Speaker 6: verify that income. And you get into like really complex
Speaker 6: and arcane rules as well, once you get into twelve
Speaker 6: hundred pages, like are you allowed to have a ten
Speaker 6: percent increase in income year over year and use that
Speaker 6: new income, Well, you have to document that a certain way.
Speaker 6: If it's about thirty percent, you have to document it
Speaker 6: another way. So a whole kind of slew of rules,
Speaker 6: which is why you have this huge body of people
Speaker 6: basically that have to work on every single loan because
Speaker 6: they have to learn all the rules.
Speaker 4: So one thing that would be really nice and gets
Speaker 4: to the one clickness of what we're trying to get at,
Speaker 4: is if it were really easy to pull in data
Speaker 4: quickly from all these disparate providers. So I go to
Speaker 4: your website and I want you to know my income,
Speaker 4: and maybe I want you to know my assets that
Speaker 4: I have, but I'm not sure if that's as important
Speaker 4: in a mortgage. And I want you to know the
Speaker 4: location of my property so that you can do various things,
Speaker 4: including see what the floodplain looks like. The various providers
Speaker 4: of this stuff, so one of the providers might be
Speaker 4: my payroll provider. Another provider might be the bank that
Speaker 4: I use, the bank online, et cetera. How forthcoming are
Speaker 4: they in making these systems easy for a third party,
Speaker 4: say yours or a Blend or some other fintech or
Speaker 4: a rocket, et cetera, to just go access them such
Speaker 4: that I don't have to download PDFs and then re
Speaker 4: upload them somewhere else.
Speaker 6: Yeah. So I imagine you're asking because you know the
Speaker 6: is going to be their very mixed results. So when
Speaker 6: it comes to banks, for example, there have been a
Speaker 6: whole advent of new kind of players that help you
Speaker 6: connect your banking data. Claid is the big one exactly,
Speaker 6: and then the banks, I would say, clearly had mixed
Speaker 6: feelings about it. People are worried about the security of
Speaker 6: people typing their bank password on something that's not the
Speaker 6: bank's website. They're very notably over the last ten years
Speaker 6: or so but a number of times in Chase just
Speaker 6: shut off PLAIDS access, and so there certainly was some
Speaker 6: complexity in that relationship. Earlier on with you know, some
Speaker 6: of what's going on in open banking in the US.
Speaker 6: I think the idea that you'll have access to your
Speaker 6: own asset information is definitely a place the regulators are
Speaker 6: pushing as well, and that gets easier and easier every year.
Speaker 6: Payroll is a particularly interesting one. It's a very hot
Speaker 6: topic in the mortgage world now because everyone basically uses
Speaker 6: a product offered by appuifacts called the work number, which
Speaker 6: you may have heard of. So the work number it
Speaker 6: basically they have a partnership with ADP where ADP charges
Speaker 6: them a very large amount of money actually to use
Speaker 6: the borrow's social to look up the data. Work number
Speaker 6: turns around and marks that up a whole bunch. So
Speaker 6: they also charge a ton of money to the lender.
Speaker 6: So I've heard of lender spending you know, like four
Speaker 6: or five six hundred dollars a loon like to close
Speaker 6: one loan to get that income and employment data in
Speaker 6: this digitized way via the work number, which is I
Speaker 6: think obviously ridiculous, And so there certainly is some struggle
Speaker 6: going on with the data ecosystem. There are a bunch
Speaker 6: of startups now trying to basically do a plaid did
Speaker 6: where the barer can log into their payroll provider. One
Speaker 6: problem you might imagine with that is like, do you
Speaker 6: know your payroll password? Because I don't even know you
Speaker 6: know who my provider is, no idea, and so there
Speaker 6: certainly is some difficulty in getting the data together. I
Speaker 6: would say that Ecosystem's made a lot of progress on
Speaker 6: that in the last ten years, but payroll and income
Speaker 6: tends to be a lot harder because it's much more fragmented.
Speaker 6: And with banking and open banking and every bank you
Speaker 6: know has some kind of electronic system of record, that's
Speaker 6: a problem where I'd say they've made a lot more progress.
Speaker 2: How much does mortgage financing depend on just your sort
Speaker 2: of basic mail. I want to be able to say
Speaker 2: the housing market is powered by FedEx or something.
Speaker 6: So actually every closing I wouldn't say every closing package,
Speaker 6: but the vast mandory of closing packages in this country,
Speaker 6: like you go to your lender or a title office
Speaker 6: and you sign the closing doc and the notes and
Speaker 6: whatnot to actually the legally binding piece of paper that
Speaker 6: says there is a lean on my property. Now, like
Speaker 6: I have to pay this loan back, and that gets
Speaker 6: FedEx back to the lender, and the lender then you know,
Speaker 6: scans it, they upload it to their electronic system and
Speaker 6: they turn around and they like FedEx that to a
Speaker 6: doc custodian. And some lenders are more efficient with their
Speaker 6: FedEx schemes than others on like it just goes straight
Speaker 6: to the doc custodian and the DAK custodian scans and
Speaker 6: sends it to them. But I would say that very
Speaker 6: much all of the actual debt and recording and like
Speaker 6: all of the legally binding stuff, probably ninety percent plus
Speaker 6: is still physical pieces of paper that are getting mailed around.
Speaker 6: There was a big trend, especially in twenty twenty, around
Speaker 6: how do you digitize those notes? Hey do you e closing?
Speaker 6: Then it's a matter off. You've got to get thirty
Speaker 6: eight hundred counties to accept it, all the title companies
Speaker 6: have to accept it, et cetera. So the big network
Speaker 6: problem again, you're probably hearing a theme of it's just
Speaker 6: like organizational inertia. Yeah, but you've very much can say
Speaker 6: that home financing is still powered by FedEx because pretty
Speaker 6: much everyone, I mean, we have a field in our
Speaker 6: system where people are like, we need a FedEx tracking
Speaker 6: number field for the note, like not even kidding. That
Speaker 6: could be really cool if you could integrate that to
Speaker 6: FedEx to like automate like looking at the tracking. And
Speaker 6: it's like, of course you can do that technology wise,
Speaker 6: but sometimes you ask yourself, like, what problem are we
Speaker 6: really solving here? Guys, like we should just move it
Speaker 6: to the cloud.
Speaker 4: So I think the last time I applied for a mortgage,
Speaker 4: it's late twenty seventeen, and I just remember like documents
Speaker 4: and documents and checkboxes, and I didn't read any of
Speaker 4: those documents, had just signed the checkbox, and I assumed
Speaker 4: it is all okay, Well were all those checkboxes I
Speaker 4: was or signature boxes that I was putting a digital
Speaker 4: signature into.
Speaker 6: A lot of those signature boxes are basically people disclosing
Speaker 6: your rights, So very similar.
Speaker 3: To yeah, yea disclosure.
Speaker 6: Yeah, It's like you sign something that gives them authorization
Speaker 6: to pull your credit in many cases, and then you
Speaker 6: sign something that you know it's like, hey, here's your
Speaker 6: credit score and here's how it was calculated. In the
Speaker 6: state of California, you might something which is like if
Speaker 6: you are getting an FAHA loan with lead paint, which
Speaker 6: I hope you didn't, there's a disclosure that says, hey,
Speaker 6: like we determined that the house has some old lead paint,
Speaker 6: Like sign here to acknowledge that we disclosed that to you.
Speaker 6: And then the other thing that happens is because each
Speaker 6: of these disclosures are legally mandated and it's really hard
Speaker 6: to make sure that you signed all of them in
Speaker 6: the one go, they'll just say, hey, when you first
Speaker 6: apply for the loan and we disclose through the terms,
Speaker 6: we're going to stick all of those disclosures in there,
Speaker 6: and then when you get to the closing table, we're
Speaker 6: going to put them in there again, just so we've
Speaker 6: belt and suspender that you know you've signed it. Like
Speaker 6: you're at the closing table, you're not going to walk
Speaker 6: away now, Like, let's just make you sign it one
Speaker 6: more time. So, probably if I had the guests, you
Speaker 6: got fifty or something disclosures, depending on the state you
Speaker 6: were in, there's a whole bunch of you know, state
Speaker 6: some states are more owners than others. We probably also
Speaker 6: signed each one and average like two and a half times.
Speaker 4: I did just real quickly, how different was that experience
Speaker 4: for me in twenty seventeen then it would have been
Speaker 4: in two thousand and seven, before the mortgage crisis.
Speaker 6: Well, in two thousand and seven, you can imagine there
Speaker 6: were way fewer disclosures. Actually, in twenty fifteen they passed
Speaker 6: what's called TRID or tie the rest but integrated disclosures,
Speaker 6: which is actually the main reason you can't have a
Speaker 6: one click coage today. So TRID puts a minimum timeline
Speaker 6: as well, where you have to give people, you know,
Speaker 6: within three days of getting what's called a full application,
Speaker 6: you have to provide them an estimate of all the
Speaker 6: fees that like really clearly in a very standardized format,
Speaker 6: discloses all the fees that comes with a bunch of disclosures.
Speaker 6: And then you have to give the bar or seven
Speaker 6: business days from giving them that loan estimate to close
Speaker 6: the loan. And so we actually talk in mortgage now
Speaker 6: a lot about the ten day mortgage, because you actually
Speaker 6: can't have a one click mortgage purely by virtue of
Speaker 6: the fact you need that seven day waiting period. There's
Speaker 6: some other timelines and there even if you got rid
Speaker 6: of that seven day waiting period, you'd still have to
Speaker 6: remove a whole bunch of other regulatory timelines to really
Speaker 6: get it down to one day. But in twenty fifteen
Speaker 6: they released this new regulation which I would say made
Speaker 6: it a lot more onerous, a lot more documents to sign,
Speaker 6: and I mean it's good, right, Like pre twenty fifteen,
Speaker 6: people were getting loans and they were getting bait and switched,
Speaker 6: and you know, people were having new fees pop up
Speaker 6: that they didn't know about. And now all that stuff
Speaker 6: is really strictly regulated, but it definitely as to the
Speaker 6: paperwork party.
Speaker 2: So how did Blend actually try to solve all of this?
Speaker 2: Because when I listen to you talk about all these
Speaker 2: sort of challenges in the mortgage market, it just sounds
Speaker 2: like an unsolvable kind of spider web of requirements.
Speaker 6: Yeah, it certainly is very challenging. I wouldn't call it.
Speaker 6: You know, nothing is really unsolvable except the regulatory timeline
Speaker 6: is going to be what it is. But for a
Speaker 6: lot of it was, hey, can you really get to
Speaker 6: a one click and tell the bar or that they're
Speaker 6: clear to close? And what that means is we've fully
Speaker 6: underwritten everything. We know that you're going to close. The
Speaker 6: only thing we're really waiting on is the compliance clock.
Speaker 6: And so you kind of split it up into the
Speaker 6: various things that get underwritten in the loan. So in property,
Speaker 6: for example, the most clear thing you have to do
Speaker 6: in order to say I can instantly underwrite your property
Speaker 6: is they have to be able to get no appraisal
Speaker 6: and get instant title. And today, title insurance is this
Speaker 6: whole other thing that I'm sure you could do ten
Speaker 6: episodes on. Some people have asked, which everyone, yes, I
Speaker 6: would say every two years. Some Silicon Valley person tweets
Speaker 6: that like, title insurance is a racket and someone should
Speaker 6: go take it out, and I always get that tweet
Speaker 6: texted to me like ten times. But there's this complexity around. Well,
Speaker 6: the problem with title insurance is actually someone does have
Speaker 6: to go to the county office still in a bunch
Speaker 6: of counties, and go downstairs into the basement of the
Speaker 6: courthouse and get the key and unlock it and go
Speaker 6: like look up the records for that house or something
Speaker 6: like that. So you have to figure out how you're
Speaker 6: going to make title insurance instant, which there are a
Speaker 6: whole bunch of startups that have worked on are working
Speaker 6: on have had some success in digitizing that process. In
Speaker 6: some counties, you've got to make the appraisal instant, which
Speaker 6: basically means you have to get a message from Daniel
Speaker 6: Freddy that for this particular property, they've written alone on
Speaker 6: it recently enough that you don't have to appraise it again.
Speaker 6: And so that's the property side. Those two things you
Speaker 6: can imagine combined already, like you're taking one hundred percent
Speaker 6: of properties in the US, and you're shrinking your hip
Speaker 6: box to like twenty year or twenty five percent or
Speaker 6: something like that, and then you've got to get the borrower.
Speaker 6: And for Blend, a lot of the approach was, well,
Speaker 6: we partner with a lot of big banks, and so
Speaker 6: can you get the banking data directly from those banks
Speaker 6: and use that to either figure out the income or
Speaker 6: use something like the work number to instantly get income.
Speaker 6: You can verify assets and income and the property, and
Speaker 6: then you can of course, pulling credit is the easiest one,
Speaker 6: because we've been able to pull credit digitally for decades
Speaker 6: and decades in this country. If you can kind of
Speaker 6: check all four of those boxes, then you're quite a
Speaker 6: bit further towards a instant clear to close, you're still
Speaker 6: not fully there. There's a bunch of stuff around the
Speaker 6: margins you've got to go and sort out. But it
Speaker 6: really is a matter of blocking and tackling, executing detail
Speaker 6: by detail. And it's like, there are twelve hundred pages
Speaker 6: of rules. I've probably read those twelve hundred pages of
Speaker 6: Fanny rules three or four times, and you've just got
Speaker 6: to systematically tick them off one by one.
Speaker 4: What are you doing now at VESTA that you weren't
Speaker 4: doing and blend.
Speaker 6: Yeah, So a lot of the struggle that we had
Speaker 6: up on was you really, because you own the front
Speaker 6: end of the process, is you could get to fully automated.
Speaker 6: You could pull it all in and be done. The
Speaker 6: problem was, you know, you heard how I talked about
Speaker 6: appraisal title. You kind of shrink the hit box for
Speaker 6: what you can do fully automated. And so what we
Speaker 6: found was that if you fully automated, like let's say
Speaker 6: you really could fully automate one percent of lenders loans,
Speaker 6: that would be great, but they're still you know, spending
Speaker 6: a ton of manual dollars, a ton of you know,
Speaker 6: operational people on ninety nine percent of their loans. And
Speaker 6: the big problem was all the data that you got
Speaker 6: at the front it was really hard to use that
Speaker 6: to drive efficiencies at the back of the process or
Speaker 6: for you know, any of the loans that did have
Speaker 6: even one manual touch, like I ticked through all these rules.
Speaker 6: You can imagine if only ten rules had to be
Speaker 6: done by a human. Well, now it's got to go
Speaker 6: through this manual process. And what it does today is
Speaker 6: it goes through this old manual process where they basically
Speaker 6: have to underwrite the whole loan manually because the system
Speaker 6: doesn't have an understanding of what's already been done. It's
Speaker 6: not you know, task or workflow oriented, and people basically
Speaker 6: have muscle memory. So the underwriter is going to look
Speaker 6: at everything, order the appraisal, whatnot, even if they don't
Speaker 6: have to. And so a lot of what we realized
Speaker 6: was the back end of the process was making it
Speaker 6: really difficult to realize any efficiency from the good work
Speaker 6: you're doing at the front end because the change management
Speaker 6: and organizational inertia of you know, you've got three thousand
Speaker 6: people on your mortgage manufacturing line so to speak, doing
Speaker 6: exactly what they've always done, and the software isn't really
Speaker 6: guiding them to do anything different, Like it's not it's
Speaker 6: not a piece of software like you might be used
Speaker 6: to working in today, like Slack gives you notifications for example.
Speaker 6: It's really almost like a spreadsheet with a different UI
Speaker 6: layer on top of it, and you've got to figure
Speaker 6: out exactly what you're going to do. So a lot
Speaker 6: of it was how do you change the way the
Speaker 6: operation works so that people are doing a lot less.
Speaker 6: And then the other big thing was with the existing
Speaker 6: loan origination systems being so difficult to integrate to that
Speaker 6: was one of the biggest hindrances and actually getting all
Speaker 6: of the data and making that process one click. Was
Speaker 6: that you couldn't actually do all of the jobs that
Speaker 6: needed to be done by that old system, like the
Speaker 6: old system that has all of the integrations I mentioned,
Speaker 6: and they have hundreds of integrations to all these data providers,
Speaker 6: like coordinating the appraisal. So you ended up having to
Speaker 6: build around the old system instead of through the old
Speaker 6: system to achieve a lot of this stuff, and that
Speaker 6: just seemed like so clearly the wrong way to do it.
Speaker 6: Now the downside is have to go and modernize the
Speaker 6: old system. Which is a really hard problem. But by
Speaker 6: kind of modernizing the old system, you unlock a the
Speaker 6: operational efficiency that you actually get from all this data
Speaker 6: and then be a much easier platform for everyone who
Speaker 6: wants to build a front end to get that data
Speaker 6: through your integrations and through your processes that the lender
Speaker 6: already has that exists manually today of having to recreate
Speaker 6: it on the side to try and automate it, if
Speaker 6: that makes sense.
Speaker 2: I have a slightly random question, which is, given that
Speaker 2: we're talking about technicalities, how easy is it to commit
Speaker 2: some sort of mortgage fraud nowadays? Totally random, not out
Speaker 2: of personal interest.
Speaker 6: Yeah, I did listen to your recent episode about government
Speaker 6: Fraudry Joe was the one I think was very interested.
Speaker 3: Yeah, I was the one interring to start doing fraud.
Speaker 6: Yeah. Mortgage fraud, I think is actually quite difficult these days,
Speaker 6: mostly because there are so many human eyeballs that look
Speaker 6: at the loan and so let's take something really simple,
Speaker 6: like you wanted to like doctor a document, like probably
Speaker 6: the most straightforward thing because it's not like mascal fraud.
Speaker 6: It's like somebody is like, I want a mortgage on
Speaker 6: my primary residence. I can't afford it, and I'm just
Speaker 6: going to doctor the documents to make my income look bigger. Well,
Speaker 6: first you have to hope the lender doesn't check some
Speaker 6: third party verified data source, or they don't reach out
Speaker 6: to the employer, which they often do. And then you
Speaker 6: have to hope that like your document makes it through
Speaker 6: the processor are looking at it, and the underwriter looking
Speaker 6: at it, and the closer looking at it, and the
Speaker 6: underwriters especially they're looking for things that don't add up.
Speaker 6: And so I would say mortgage fraud is probably really
Speaker 6: pretty too, very difficult to actually accomplish today. It sounds
Speaker 6: a lot harder to achieve than, like, you know, figuring
Speaker 6: out how to get some Medicare dollars. Yeah, so it's
Speaker 6: probably not worth squeeze. Now, we'll like generative AI make
Speaker 6: it way easier to make fake profiles and all that stuff.
Speaker 6: Maybe that's something that I think lots of people worry about,
Speaker 6: But today I would say it's definitely the mortage industry
Speaker 6: has done a pretty good job of doing that, and
Speaker 6: I'd say the regulators have done a good job of
Speaker 6: making it really hard, just given everything that happened two
Speaker 6: decades ago.
Speaker 3: Back to the question of refise.
Speaker 4: So you mentioned that theoretically, if you're a homeowner and
Speaker 4: you're in the money on your mortgage, that is to say,
Speaker 4: where it would make economic sense for you to refi.
Speaker 4: You might get an email or something it's like, hey,
Speaker 4: you should refi and you can save this much. But it's,
Speaker 4: as we're talking about, it's gonna be a lot of
Speaker 4: paperwork and all this stuff. After our episode came out
Speaker 4: several weeks ago, someone on Twitter, they said, why can't
Speaker 4: we have a mortgage product that you pay a higher
Speaker 4: premium upfront, but it's a floating rate mortgage that only
Speaker 4: resets downward. In other words, basically, if rates drop lower,
Speaker 4: your mortgage mechanically drops with it. And again, obviously, if
Speaker 4: you're going to have that, you theoretically that's a more
Speaker 4: valuable option and you pay some premium upfront, but then
Speaker 4: in theory, you save all of this effort and time
Speaker 4: and document checking and human hours that go into this.
Speaker 4: In your mind, does that seem like a plausible financial
Speaker 4: product that could exist.
Speaker 6: Seems like a totally reasonable financial product. I think that
Speaker 6: there may even be somebody doing it. And like the
Speaker 6: private label securities market, there is a market basically hedge
Speaker 6: funds that will like underwrite non qms what they're called
Speaker 6: mortgage products and offer those to lenders, and lenders can
Speaker 6: originate them. One thing I will say is it seems
Speaker 6: unlikely to come from the GSUS just because so much
Speaker 6: of the gs's mission these days is affordability and democratizing
Speaker 6: home ownership. And I can't really think of a marginal
Speaker 6: person that that products would get into a home.
Speaker 4: Right, So even if it makes sense, that's just now
Speaker 4: we'll move the dial.
Speaker 6: Yeah, I think it makes sense from a you know,
Speaker 6: like single person financial instrument perspective, like I would love
Speaker 6: to have one of those, for example, But I think
Speaker 6: that from the kind of stated policy goals of the
Speaker 6: biggest investors in the market, it's just not really something
Speaker 6: that oligns with their policy goals, and so I can't
Speaker 6: see that being a big area of where we're going
Speaker 6: to see a bunch of those in a decade.
Speaker 2: So a lot of mortgages get bundled together into mortgage
Speaker 2: backed securities. I'm curious, like how much of that granular
Speaker 2: detail about pay and you know, lead paint in the
Speaker 2: house and things like that gets ported over to the
Speaker 2: securitization aspect of it.
Speaker 6: So it's really not a lot. I actually I have
Speaker 6: capital markets people reaching out to me all the time,
Speaker 6: being like, if you have a modern loan origination system,
Speaker 6: you can solve my problem if I can't actually get
Speaker 6: any of the data or much of the data that
Speaker 6: you underlines these instruments when I am going and securitizing
Speaker 6: them or trading them or whatnot. But generally comes out
Speaker 6: as much banking technology still is today is you export
Speaker 6: a big CSV of some of the data fields. You
Speaker 6: take a bunch of docks and you send them off,
Speaker 6: and then that CSV, which you know, they fancily call
Speaker 6: it tape, but really it's a spreadsheet, just gets ingested.
Speaker 6: And now you've taken a process that had three thousand
Speaker 6: fields and hundreds of pages of docks, and you've boiled
Speaker 6: that down into like fifty or one hundred fields that
Speaker 6: describe the mortgage, which maybe is for the best, Like
Speaker 6: I'm not really sure that people buying mbs should be
Speaker 6: thinking about, you know, the specific credit profile of the
Speaker 6: thousand different mortgages that are chopped in there and put
Speaker 6: in and so it's nice that there's some standardization, but
Speaker 6: it's definitely very lossy, and I will tell you it
Speaker 6: is something that mortgage traders complain to me about a lot.
Speaker 4: So what's realistic. It doesn't sound like you'd ever get
Speaker 4: like true one click, because it's you know, at a minimum,
Speaker 4: you're probably going to have to tell the front end
Speaker 4: who your.
Speaker 3: Payroll is and who your bank is, and a few
Speaker 3: other things.
Speaker 4: What is a plausible version of if you know there's
Speaker 4: continual coordination among different banks, if Fanny and Freddy continue
Speaker 4: to update their technology so that you know, it's a
Speaker 4: little easier, what could it look like if I were,
Speaker 4: say you're say, in ten years.
Speaker 3: I'm applying for a mortgage again.
Speaker 6: I think it's very reasonable to strive for a world
Speaker 6: where it is, you know, to your point, as close
Speaker 6: to one click as possible on the very front end.
Speaker 6: Maybe you're talking about like a ten minute application max,
Speaker 6: where you connect some accounts once that's done. I think
Speaker 6: that what you should get instantly is one of basically
Speaker 6: three decisions. Hey, you are definitely clear to close. You're
Speaker 6: going to get your disclosures, and then we're just going
Speaker 6: to wait ten days and we'll close you. Option two
Speaker 6: is hey, you as a barwer are definitely clear to close,
Speaker 6: but we need some additional information on the property. So
Speaker 6: you're going to wait ten to fourteen days, you're going
Speaker 6: to pay for the appraisal, and we're going to close
Speaker 6: you or three is basically unfortunately, you know, we're not
Speaker 6: able to close you. Here some things you can do
Speaker 6: to improve your stance. I think that property is probably
Speaker 6: going to be the thing that even if you ask
Speaker 6: me ten years from now, it's like it's really a
Speaker 6: question of there will always be those corner cases. It
Speaker 6: feels like where the gs are going to want to
Speaker 6: see an appraisal unless they're the big credit profile change
Speaker 6: or if they get privatized. You know, there's all sorts
Speaker 6: of things that can happen in ten years. But I
Speaker 6: think those three outcomes being ten minutes away fingertips wwise
Speaker 6: from the bar when you close in ten days is
Speaker 6: very much attainable, and it's really what everyone in the
Speaker 6: industry is and ought to be working towards.
Speaker 2: Does blockchain solve this? And I mean that's somewhat serious.
Speaker 3: It's a good question.
Speaker 2: Because, like I've often thought like one of the few
Speaker 2: real world applications of blockchain technology could be in the
Speaker 2: mortgage assignation space where you have that sort of chain
Speaker 2: of title moving around constantly. But also I'm thinking, like
Speaker 2: from a wallet perspective, if you could have like a
Speaker 2: personal profile that carried with it you know, your pay
Speaker 2: and yeah, how much your worth and et cetera, you
Speaker 2: could use that too.
Speaker 6: Yes, So those are two very interesting use cases on
Speaker 6: the wallet perspective. The way that I think about blockchain
Speaker 6: helping here is almost lets you build like a more
Speaker 6: encompassing decentralized credit bureau. And decentralized is actually really important
Speaker 6: because I don't think the banks are super excited about
Speaker 6: the idea of helping build like a fourth credit bureau,
Speaker 6: like they built three and now they pay the three
Speaker 6: for their own data, which I think is a little
Speaker 6: bit difficult for them. And then you know, the regulators
Speaker 6: are not super excited about the centralized credit bureaus, et cetera.
Speaker 6: And so I think the idea that each consumer could
Speaker 6: have their own key that unlocks, you know, access to
Speaker 6: all of their data on this decentralized credit bureau that
Speaker 6: all the payroll providers and financial institutions, et cetera are
Speaker 6: writing to, is very much an idea that has legs.
Speaker 6: It's really hard to implement for you know, a lot
Speaker 6: of similar organizational inertial reasons. But I do think that
Speaker 6: is a real use case for blockchain, be it solves
Speaker 6: the incentives problem where people are basically like, I don't
Speaker 6: want there to be one middleman with every consumer in
Speaker 6: America's financial data, and so blockchain, let's you kind of
Speaker 6: like decentralize and split that up. So I think there's
Speaker 6: some really interesting avenues there that people can go down,
Speaker 6: and there are some companies I think actually looking at
Speaker 6: that on the title front, what I usually tell people
Speaker 6: on could title beyond blockchain? Absolutely? Is it an interesting
Speaker 6: use case? Absolutely? The hard part of digitizing title is
Speaker 6: getting thirty eight hundred counties to even move to like
Speaker 6: putting capturing the records digitally and not in the courthouse basement.
Speaker 6: Getting thirty hundred counties to move to blockchain seems further
Speaker 6: away than that, not closer.
Speaker 4: I don't know if I've ever mentioned it on the
Speaker 4: show before. I once had a gig right after college
Speaker 4: in which there was some company out in California doing
Speaker 4: some of his bestest lawsuits, and they needed names of
Speaker 4: all these people who had been partied to some suit.
Speaker 4: I don't they're maybe putting it together a database for lawyers,
Speaker 4: and part of my job was to go to various
Speaker 4: county courthouses all around rural Texas in central Texas and
Speaker 4: go to the basement and just literally pull out files
Speaker 4: and ask for names. I'm just going to ask one
Speaker 4: last question since Tracy hit one tech buzzword, which is
Speaker 4: blockchain generative AI. Whether it's in the field of scanning
Speaker 4: documents or understanding documents quickly in your work right now,
Speaker 4: is there a substantive use that you're getting out of
Speaker 4: this technology.
Speaker 6: Yes, it is definitely to your point, it's scanning and
Speaker 6: understanding documents, and so you can think of mortgage the
Speaker 6: way that I think of it high level is it's
Speaker 6: a whole bunch of data and it's a bunch of rules,
Speaker 6: and the rules are well defined by investors, the government, etc.
Speaker 6: And the data is just data, and so data and
Speaker 6: rules to you know, a lot of this conversation should
Speaker 6: be a one click experience, like we've known for decades
Speaker 6: how to run rules on data. And a lot of
Speaker 6: the problems come about because the rules are written in
Speaker 6: the twelve hundred pah PDF and there's a little gray
Speaker 6: and someone has to learn them, and the data in
Speaker 6: a bunch of documents and a bunch of you know,
Speaker 6: disparate places from the borrower, and so it's not structured.
Speaker 6: And so if you can bring structure to the data
Speaker 6: and structure to the rules, both of which generative AI
Speaker 6: is really good at. Right. It can read the Fannia
Speaker 6: Selling Guide and turn that into code rules. It can
Speaker 6: read a document and turn that into data points. If
Speaker 6: you can use generitive AI to structure those two things,
Speaker 6: then you still have structured data, structured rules, and that
Speaker 6: they're you know, whatever rules the GSE said, So you
Speaker 6: don't have these compliance things with ohs AI underwriting below.
Speaker 6: But we're seeing a lot of really promising results taking
Speaker 6: the most cutting edge large language models and applying them
Speaker 6: to these documents, both to write the rules for us
Speaker 6: and to lift the data off the documents.
Speaker 2: All right, Mike, you thank you so much for coming
Speaker 2: on all lots and explaining to us why we can't
Speaker 2: have a nice thing.
Speaker 6: Yeah, thanks for having me.
Speaker 3: That was amazing.
Speaker 4: Mike, you're the perfect guest. Thank you so much for
Speaker 4: coming on.
Speaker 6: Yeah, that was fun. Thanks for having me.
Speaker 2: Joe, that was really fun.
Speaker 3: That was really fun.
Speaker 4: I thought Mike was exceptionally clear at explaining how all
Speaker 4: this works. And although it's still annoying the process of
Speaker 4: getting more and lots of documents that I didn't read
Speaker 4: and attached my signature to, Like, I guess I understand
Speaker 4: a little bit more.
Speaker 2: Why now, do you remember after the financial crisis there
Speaker 2: were all these problems with loan documentation and I remember,
Speaker 2: like there's a big thing about assigning mortgages in blank
Speaker 2: that all turned into like court cases. Yeah, I kind
Speaker 2: of wonder, like.
Speaker 4: We did a great episode on that with David Yeah,
Speaker 4: David Dian of the American Prospect, Like in twenty fifteen.
Speaker 4: What was the name of his book, David chain of Title. Oh, yeah,
Speaker 4: we did an episode with David Dan chain of Title.
Speaker 4: At how crazy that was. It was just the state
Speaker 4: of disarray in documentation after the mortgage crisis. But you
Speaker 4: understand why it is when you still have, you know,
Speaker 4: so much at the county level and the county level,
Speaker 4: I guess for obvious reasons, not feeling any particular pressure
Speaker 4: to update or digitize.
Speaker 3: Or modernize or coordinate all of their systems.
Speaker 2: Yeah, that's really it isn't It sort of like a
Speaker 2: Hodgepodge of State and count Law. I feel like we're
Speaker 2: going to be waiting a while for a solution to this.
Speaker 4: Yes, and I've sort of hinted at it before on
Speaker 4: the podcast, but for very arcane reasons that I'm not
Speaker 4: going to get into. I do have a loan that
Speaker 4: will need to be refinanced at some point in the
Speaker 4: next couple of years.
Speaker 2: You're very optimistic, Joe about interest rates.
Speaker 4: No, I'm very pessimistic and I'm very anxious about it.
Speaker 4: But if I'm not optimistic about the path of interest rates,
Speaker 4: maybe I'll be optimistic that in a couple of years
Speaker 4: the process is at least a little bit better than
Speaker 4: it was the last time I applied for a mortgage.
Speaker 2: Well, see, you'll have to tell me how many documents
Speaker 2: like get mailed out and stuff, although I guess most
Speaker 2: of that is on the sort of like lender and
Speaker 2: servicers side.
Speaker 3: But I'm not looking forward to it.
Speaker 2: Yeah, all right, shall we leave it there.
Speaker 3: Let's leave it there.
Speaker 2: This has been another episode of the All Thoughts podcast.
Speaker 2: I'm Tracy Alloway. You can follow me at Tracy Alloway.
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Speaker 5: Thanks for listening, bend In