Leveraging Predictive Analytics to Expand Relationships

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You're listening to Leaders and Lending from
Upstart, a podcast dedicated to helping consumer

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lenders grow their programs and improve their
product offerings. Each week, here,

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decision makers in the finance industry offer
insights into the future of the lending industry,

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best practices around digital transformation, and
more. Let's get into the show.

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Welcome to Leaders in Lending. I'm
your host, Jeff Keltner. This

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week's episode features my conversation with Ben
Vega from Umquo Bank. I've been and

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I dive into a lot of topics, starting with an interesting project he had

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recruiting commercial bank clients into the wealth
management organization. I thought interesting, how

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you break down the barriers and build
a program across silos in the organization.

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We talked about specifically a lot of
the human digital how those two things play

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together, what U was doing in
that space, which that was really interesting

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their big bank attack program during PPP. Also, I think of fasting my

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conversation experiend what's what they mean by
scored lending and what the future of score

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aring and maybe alternative data looks like
where that can be valuable. I think

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it's a great conversation and anyone can
learn a lot from it, So please

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enjoy this conversation with Ben Piggott.
Then, thanks for making the time and

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joining the podcast today. I really
appreciate it. Absolutely happy to be here.

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Before we get into the content,
there's a bunch of interesting stuff to

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talk about, but I always love
to start with this question from my guests.

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How did you wind up in the
banking space. It's not usually the

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childhood dream of most of the people
I talked to, so I'm curious what

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path led you to where you're at
today. Absolutely, I think this is

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a popular question amongst most banking professionals
as well. I started off probably a

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more traditional route. I was going
to college George Mason University in Northern Virginia,

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and the bank down the street offers
college tuition reimbursement program, so that

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was Chevy Chase Bank. I was
a teller there and they were helped to

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pay my way through college. After
I had graduated at a four year degree

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and also had four years experience.
But I also got a little bit more

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exposure to just what all, you
know, the different avenues that you could

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go through in a banking career,
and I decided to stick with it.

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Moved over to Unqua Bank in the
Pacific Northwest. Started off in our branches,

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so we call them stores at the
time. Was there for a year

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that I moved into our private bank
for wealth management, and that was pretty

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interesting journey. Get a lot of
exposure in the wealth management piece because a

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lot of your customers are orderlining on
the consumer side, business side, commercial

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side. So having that for five
years, I mean, I really did

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get a lot of exposure to the
different products and services that we offer through

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some different types of synergies that we
did. I went into our frontline strategy

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group, but prior to that,
actually we'll probably circle back on this at

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the topic of the conversation. When
I was in our wealth management group,

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we started a program where we were
partnering with our commercial bank because we're trying

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to identify customers that were within our
commercial and the business owners that would be

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a good fit for wealth management.
So they had commercial loans with us,

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but they didn't have any type of
personal relationship. So I started down this

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initiative where we were going to get
the commercial bankers to introduce clients to our

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wealth management and get that wealth management
offering to them. Utilizing some of the

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information that we had collected through the
underwriting of their commercial loan, and this

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was ended up being very successful and
eventually, as we had some other groups

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look in to how the organization was
operating, I was then moved under what

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we called our Frontline Strategy group.
So Frontline Strategy was helping build the strategy

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with our core baking lines of business. This is retail bank, home lending,

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commercial SPA, etc. Basically the
profit centers that we have, the

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different avenues that we have with than
the bank itself. As we went through

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another merger, I took a kind
of an adjunct kind of dog leg in

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my career and I went over to
our ALM side or asset Liability Management,

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working in our treasury group for our
interest rate sensitivity analysis. Did this for

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about two and a half years,
three years, and this is where we're

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putting out the regulatory reports on how
a banks that it was income gets impacted

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through different rate scenarios. Basically a
pretty important topic. Right. Just I'm

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alexy to sexy last right, And
it was funny you say that because I

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was said, you know, recruited
into that group, and I thought this

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was good, good, a good
way to start rounding out my banking career.

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I had always been focused more on
the production side, hadn't yet looked

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at the balance You haven't yet looked
at banking from the balance sheet finance side.

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So this was really good experience.
When I was first moved over there,

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you know, interest rates were flat
for quite a while, and then

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I started going over there. This
is when the rate high really started and

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things got a lot more interesting,
especially because of the reporting that we were

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putting out. And really what happens
is we run sixteen different scenarios. So

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we'll start with our base scenario,
which is just the current economic environment.

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What's your net interest income going to
look like in one year without any movement

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to rates, and then we'll look
at it what happens if rates go upwards

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one hundred basis points two hundred,
three hundred, four hundred in a ramped

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scenario, so slowly increasing, then
also again in a shock scenario. Then

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on the inverse of that, what
happens when they go downwards? You know,

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yeah, the one to four percent
and then diving into the analysis of

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that was actually really fascinating as well
too. So you're looking at most of

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our loan portfolios you know what has
changed month over month? How is the

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sensitivity? You know, how has
our net interest income increased, our dink

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decrease from the prior month? Based
on some of these scenarios, and you

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would see what are we doing on
our lending side, our cash side,

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you know, how is our cash
looking? So four dollar question, but

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were you guys looking at the asset
valuation for a long long duration assets on

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the book? So we always we
had them marked to market already, so

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that was one thing that was helpful
for us, you know, so we

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we had run the book that way
and what we did see though were mortgages,

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right, so we were having in
higher rate environments. Generally, what

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happens is pre payments start too slow, so people aren't going to be paying

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off their loan as quickly, which
in the inverse of that, we're getting

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less cash back to then reinvest at
the higher rate. So that was kind

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of one of the impacts that we
were looking at when you look at mortgage

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portfolios or the different portfolios that we
were invested in, so mortgage backed securities,

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so you would see kind of slower
durations on these types of security portfolios

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that we were invested in and that
you know, for me, this was

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I had never really looked at that
part of the balance in our investment side.

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I was always more focused when we
you know, for core baking lines

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of business, to look at your
deposits, your loans and you know,

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getting these different types of investment folios
that we put cash into. That was

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that was really interesting. But we
were very uh, we're very sound on

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how we do that. So luckily, you know, we had already been

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marked to market. Our book was
pretty fair in that aspect of it.

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Um. You know, I'm assuming
you're getting into what happened last four weeks,

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but best we know, yeah,
interest rate risk right, what's right?

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I know, I know. And
so from there, um, one

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of the executives that we had in
the frontline strategy group, they're saying,

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hey, we we want a product
manager for our scored lending channel. Um,

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and I thought it would be a
great fit. So I moved into

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that. So that's what brought me
into our Scored Lending product manager position in

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the role that I'm currently into now
and so quite an interesting career. Actually,

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it all started with helping you know, an extra five thousand dollars a

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year to pay to my tuition and
now I found something that I really loved

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and been fortunate enough to be able
to build on my experiences throughout my banking

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career to get to the role.
But I'm at now and that's uh.

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You know, some people maybe aren't
as fortunate to be able to do that.

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But luckily, within the organization I
have, they really kind of promote

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that and they have done a good
job retaining employees and training them up.

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So everything I want to get to
scored lending. Yeah, we let first

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go back to this really interesting project
you talked about where arguing with the commercial

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bank. Yeah, management class,
and I want to ask a question and

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too fragile. This feels like the
kind of thing that is obvious. I

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mean, like, no, we
have a bunch of people who own small

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businesses that are doing well. We'd
like to have their personal banking as well

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thanking. And yet I find that
often either the organizational silos end up creating

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friction, where like this is the
commercial bank, this is these we don't

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we don't we don't communicate, or
you have data silos ended up making it

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very hard to actually like access the
information. Right. So I'm curious what

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challenges you faced in trying to do
that and how you overcame them, because

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it to me feels like one of
the things where you go, well,

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every bank should of course be doing
this, and I think off and they're

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not in there are hurdles in the
way. So I'm curious about your experience

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in those fronts getting the organization on
board with like cross pollinating across right to

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right referent parts of the organization.
Yeah, any kind of data or technology

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issues you had trying to like,
you know, often you can't get data

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about the absolutely true customers into your
your you know, personal your wealth management

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systems because they're just totally different,
speak, different languages kind of thing.

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So I all kind of go back
to the genus of this product, right,

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your project that we have, and
exactly that light bulb moment right where

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like this seems like a no brainer. You know, here we have commercial

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loans. Uh, the borrowers or
guaranteurs of these loans are more than likely

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qualified for some type of wealth management. Yeah, it's just in the nature

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of that. So let's you know, we're we're collecting you know, this

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information to underwrite the commercial loan oft
in time, those guarantees. So there's

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some type of personal financial statement that's
coming over with these guaranteurs that we can

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review and you know, take a
look at and say, hey, this

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this person has, you know,
this amount of assets, and we think

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that, you know, we would
be a great benefit over here in our

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wealth management division. And it wasn't
necessarily so much, or maybe it was

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just as much as a fact that, yes, we want to have a

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full relationships. As much of a
fact is that we're kind of branded as

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a business bank of choice, but
at the same time we want to know,

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hey, we offer these services too, and oftentimes customers they really enjoy

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the service that they're getting from their
commercial partners, and so we try to

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build off of that and say,
hey, that service still matches on our

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consumer side, whether it be the
wealth or side over here, and oftentimes

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they just don't know about it.
So that was the idea and not executing

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that idea. You're right, it
wasn't as easy as I thought it was

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going to be. And there's a
couple of couple of different reasons why.

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One so even with our culture,
we have a very strong service culture.

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So that's also another reason why I
thought, hey, this is going to

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work great, you know, I
mean, who's not going to want to

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refer their customer over to an internal
department. And it turns out that it

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is a little trickier than that,
and it has to do one there is

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a human element to it where we
had to be very proactive, or I

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say we myself, I had to
be very proactive in identifying these customers first.

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And so going into what you're saying
with a data issue, there isn't

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some gigantic database where I can just
kind of run a query or filter on

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you know, hey, you know, give me the individual borrowers. I

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have asset sizes of this, but
preferably you know, in an investments or

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cash or you know, let's exclude
their primary residence, etc. So one

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it ended up being, okay,
let's start identifying the types of commercial loans,

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you know, the size, industry, maybe location, like do we

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have a wealth management office in proximity
to where this borrow lives from. They're

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very manual to review the personal financial
statement and any other types of liquidity statements

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that we got from these borrowers.
And then from there, let's call on

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the relationship manager kind of give them
a prospect sheet say, you know,

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very socializing. This is one of
the things was actually deposit gathering, saying

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hey, you know, we offer
and this is what we actually found.

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This This was really the ticket that
helped them get the leg in the door

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with both management was that these barrowers
usually did have some type of relationship with

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us on the consumer side, but
they weren't in the best product for them,

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meaning that they were also in a
product that is probably the easiest to

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open, quickest to open, to
do the transaction. Maybe they were just

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using it as a checking account,
but we did have other products due to

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the assets that they had, would
offer them, you know, some type

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of like wire services, you know, so like hey, you know,

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you would give free wire services,
free cashers, checked higher interest rates paid

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on deposits of this amount. Let's
make sure you're in the right product.

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So that was a very low hanging
fruit. Let's service the customer and make

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sure they're in the correct product,
because if they're not going to be in

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the correct product with us, a
competitor is going to come down the way

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and say, hey, your bank's
not doing that for you. Will we

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do this for those types of balances, So that was kind of the very

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first versation that we would have with
these borrowers. Other ones would say,

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we would like to introduce them,
but there's I don't want to go like

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too deep into the tea year,
but there's incentives, you know, I

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mean there we we we hadn't thought
necessarily about incentive plans um, so it

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would say, well, who's going
to own this relationship? But you know

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who, who's going to actually own
this customer once I start to introduce them

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over there? How do we build
the team around this customer? And that

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was not so much a point of
I'm not going to refer but there was

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there was definitely some logistics at the
point of the point of service that you

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know, are you going to you
know, is this customer going to think

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that I'm their bank? Are they
going to think that you're their banker?

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How are we going to manage this
relationship together? How are we going to

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build this team around a customer together? And who's going to be the point

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of contact? And so those are
certain things that we wanted to hash out

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first um in order for that to
happen. So what ended up being it

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did end up being successful, but
there were certain things where it wasn't just

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as easy as hey, this is
um you know, here's a customer that

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we have and let's we're just going
to reach out to them, not include

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the relationship ship managers start sending them
uh information regardless, And we wanted to

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be very thoughtful about how we approached
it, very considerate of the relationship and

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at the end of the day,
we wanted to make sure we're building the

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team around them with the with the
game plan and so at this and I

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think the topic that we're on human
digital, right, there's kind of these

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pros and cons and when I when
I think of human digital, because this

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was a very human approach that we
were doing, you know, very manual,

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I would guess, I would say, you wanted to compare human and

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digital to manual to automation. There's
a very manual approach. You know.

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There was a lot of eyes on
what is going to happen. We were

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kind of thinking through different scenarios where
opposed to how do we how would we

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scale something like this? Right,
like this works good, We're doing it

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one at a time. It's it's
it's working out. But hey, I'm

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one person. I'm going through personal
financial statements one at a time. I'm

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literally pulling images of applications, loan
documents, and this isn't going to be

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something that we can scale to.
And like many organizations, it was also

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at need because or banking organizations,
I should say, up until this point,

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you know, we had primarily grown
through merger and acquisition, merging with

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other smaller community banks, and so
here you have this portfolio of customers that

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maybe do have one foot in the
door, or they had come from a

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different organization that didn't offer the types
of services that we currently offer, and

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so it was really a good time
to take a look at these types of

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relationships and identify customers that we could
potentially grow. We expand upon those relationship

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we've grown through merger and acquisition.
Now we really want to start focused growing

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organically. And as I was going
through this, yes, right, idea,

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but one it's not scalable. And
what we ended up doing, which

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was actually really one of the first
things are first of its kind for our

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organizations. We partnered with the local
company and they we started doing something called

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next Best Offer or what we dub
umph was Smartly and what this had done

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was identify model customers and we're doing
this for our Treasury management suite of products.

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It's kind of expanding a little bit
more as well. But we were

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saying, you know, here's a
model customer, model customer being. You

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know, here's a customer that is
satisfied with the relationship. Maybe I shouldn't

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use word satisfied. That's a little
too and us. But you know,

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here's a customer that is using our
products and is profitable, right, and

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we have their primary checking account.
We can see through their checking different types

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of transactions that they're going on,
maybe payments, right and oftentimes we're looking

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at payments. Here, here's a
customer that's paying vendors x amount at this

249
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type of frequency over this time period, and this would be a good opportunity

250
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for commercial card ach services, positive
pay certain things like that. And so

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what this what smart lead does is
it does is automatically right in a digital

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way. So every single night,
it's going to go through our data that's

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process and it's going to start submitting
leads to bankers to follow up with customers

254
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saying, hey, did you know
your customer has X y z over here

255
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or is processing x amount of transactions
during this time frame? And we have

256
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a product for that, right that's
actually going to benefit them most oftentimes save

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them money because the different way accounts
are set up. You know, the

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types of volumes that you have cost
x amount if you're not using this service,

259
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you know. So that's one thing
that we're doing is called UNCA Smart

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leads from from a digital standpoint opposed
to the human approach that I had so

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kind of a juxtaposition there when it
comes to what we were doing years ago

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with the Commercial Bank and MUTH Management
to what we're doing now. And there's

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also been a lot larger of a
cultural shift in regards to partnering. So

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in addition to this this digital element
that we're using with Uncle Smart Leads,

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I think the pandemic, you know, this was an event that really helped

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rallied our associates around seeing the value
of partnering together, right. I think,

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you know, there's a lot of
talk that we have that hey,

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we're we're you know, individually,
we're not as great as we are together.

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Right, So as as a team
building a team around a customer,

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we can serve us a lot better
than we could, you know, versus

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if they were just only being serviced
by a loan in our commercial banking center.

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So what's happened with the pandemic was
there was a paycheck protection program and

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what we ended up seeing at the
you know, at the end of by

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this head concluded right the FED there
was a set amount of dollars that they

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were going to lend out. And
you know, as a lender, you

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have their customers trying to keep their
business open, try to keep their employees

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paid, all fighting for the same
pool of money in a short amount of

278
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time. And so we were getting
applications not only for our customers, but

279
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for customers from other banks saying,
hey, you know, my bank can't

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help me. Can you guys help
me get this applications so we can get

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funded. And you know, of
course the answer was yes, you know,

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let's let's do the right thing for
our community, because these are local

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often that small businesses in our community
that they can't get ahold of someone,

284
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you know, at maybe a larger
institution down down the street, but they

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could get ahold of us. And
even though they didn't have any relationship with

286
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us prior to that, we were
going to get this loan application through as

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fast as we could and as best
as we could for this customer. And

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this was a time period where I
mean, I you know, everyone was

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submitting these applications to the SBA website
twenty four hours around the clock. We

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ended up doing three billion approximately in
these loans, which for h I think,

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I think that was definitely the largest
in organ for community lender our size.

292
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But we were we were, you
know, it was quite the effort

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that we had. But to take
this to the next level, what we

294
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also looked at doing was then following
up with those customers that didn't have a

295
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relationship with us, right, So, and we kind of in term we

296
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we dubbed this I think, you
know, something along the big bank attack

297
00:20:03.119 --> 00:20:07.799
or something of the sort there.
Yeah, well I love the big bank

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attack, right And and the idea
was like, hey, let's let's grow

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and expand these relationships, you know, I mean, we we had gone

300
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to bat for these customers and we
got a foot in the door with the

301
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PPP loan, and we know that
if we start putting some of the people

302
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that we have in front of them
there there, they are really going to

303
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love us and they're going to move
that over. So the same idea came

304
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from now we start with one relationship
maybe be on the loan side, how

305
00:20:33.359 --> 00:20:37.039
do we expand this into a greater
relationship. And we had our store associates,

306
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commercial bankers, other that you know, follow up with these businesses and

307
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start moving over the entire banking relationship. And this ended up being a very

308
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successful program for us as well too, which also really highlighted what we can

309
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do together with all the services that
we offer. And so that also helped,

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you know, a lot of people's
minds set shifted that Hey, this

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you know, servicing the customer,
doing what's best for the customer is also

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best for myself as an individual producer. You know, like customers happy they

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have people that they can talk to
that I know are going to provide the

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same level of service that I do. Anywhere they go, no matter who

315
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they call, they're going to get
that level of service. So that really

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helped change that mindset when it came
to, you know, going back to

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00:21:23.000 --> 00:21:26.519
your original question, you know,
how do you oaks are overcoming these internal

318
00:21:26.559 --> 00:21:30.200
referral systems? Right? I think
there's one aspect of yes, it does

319
00:21:30.319 --> 00:21:33.839
need to come top down, you
know, it does. There is a

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00:21:33.880 --> 00:21:37.279
top down communication that needs to be
Have, there's you know, an incentive

321
00:21:37.319 --> 00:21:40.759
plan you need to make sure that
bankers are incentivized too, But at the

322
00:21:40.759 --> 00:21:42.680
same time, you know, touching, and there's also a digital piece of

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00:21:42.759 --> 00:21:48.079
they where this is a very human, you know, decision, whereas what

324
00:21:48.119 --> 00:21:51.319
we did with umpus smart leads,
we helped hate that human decision out of

325
00:21:51.359 --> 00:21:53.599
it, and we just started using
the data to help generating some of these

326
00:21:53.680 --> 00:21:56.799
leads as well too. So we're
kind of approaching it from from two aspects

327
00:21:56.839 --> 00:22:00.839
of it, where you know,
that is something that can get improved with

328
00:22:00.880 --> 00:22:06.000
a digital solution, you know,
helping with these types. It's not necessarily

329
00:22:06.000 --> 00:22:08.599
AI, but it is predictive analytics
where we're taking a model customer and seeing,

330
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hey, what other customers do we
have within our portfolio that BEHAVE,

331
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Like this customer meaning do they have
a loan? What types of transactions are

332
00:22:15.759 --> 00:22:19.039
they doing? Hey, well,
that actually is similar to the transactions this

333
00:22:19.079 --> 00:22:23.440
customer is doing, and this customer
is enjoying using ACG positive pay, so

334
00:22:23.759 --> 00:22:27.440
let's offer that to them as well. So there's there's definitely some digital tools

335
00:22:27.519 --> 00:22:32.279
that can help with BANG. Think
about that n that line, I mean

336
00:22:32.519 --> 00:22:34.799
not in the line, but this
kind of melding. I feel like there's

337
00:22:34.799 --> 00:22:37.680
a there was a world, there
was a period of time, and there's

338
00:22:37.680 --> 00:22:40.599
still something to feel like. The
personal is replaced by the digital, and

339
00:22:40.640 --> 00:22:42.359
it's going to be all at the
point of interaction, all a digital style

340
00:22:42.400 --> 00:22:47.160
interaction, no humans in the loop. And then we've got the very relationship

341
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heavy stuff. And I feel like
there's consumers are doing both things right.

342
00:22:49.720 --> 00:22:52.400
They still want to talk to people, they also want to self serve in

343
00:22:52.440 --> 00:22:56.599
the digital interaction model in different times. How do you think about how and

344
00:22:56.640 --> 00:23:00.559
where you balance those two things,
how they work together? Like, what

345
00:23:00.680 --> 00:23:03.079
is the strategy for combining the human
and the digital? Where do you at

346
00:23:03.079 --> 00:23:07.480
one being more valuable than the other? They work together in certain strategies.

347
00:23:07.599 --> 00:23:11.960
Curious how you think about the way
these two technologies are two interaction modes play

348
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together in you in the future.
Hey there, Sarah Butch here, VP

349
00:23:15.680 --> 00:23:21.519
of Consumer Lending at First Federal Bank
of Kansas City. Three years ago,

350
00:23:21.680 --> 00:23:26.839
we had plans to improve our lending
to load to modern income communities. Fast

351
00:23:26.880 --> 00:23:32.279
forward three years, we've grown our
lending distribution to LAMI communities by over ten

352
00:23:32.319 --> 00:23:37.119
percent thanks to upstart. If you'd
like to learn more about fb case's journey

353
00:23:37.119 --> 00:23:41.839
with Upstart, check out the free
case study at upstart dot Com Forward slash

354
00:23:42.000 --> 00:23:48.880
Lenders. That's Upstart dot Com Forward
slash Lenders. All right, back to

355
00:23:48.960 --> 00:23:53.279
the show, right. I think
probably the best answer to that question I

356
00:23:53.359 --> 00:24:02.480
have is actually our our go to
mobile application, and so go To is

357
00:24:02.640 --> 00:24:07.880
what we've really dubbed for our human
digital strategy. It is a mobile application

358
00:24:07.160 --> 00:24:14.519
where you were putting the banker in
your pocket quite literally. And what's happening

359
00:24:14.640 --> 00:24:19.200
is that within this application, we
have store associates who are chatting with you.

360
00:24:19.359 --> 00:24:23.079
So if you need something you can
launch just go to application and you

361
00:24:23.160 --> 00:24:26.720
have your banker there. And it's
kind of the blend where you see other

362
00:24:27.519 --> 00:24:32.079
types of chat bots AI chatbots banks
investing in that. Well, we're saying,

363
00:24:32.079 --> 00:24:33.079
no, we want to keep it
human. You know, we want

364
00:24:33.079 --> 00:24:38.240
to give you the access that you're
used to with the phone getting serviced,

365
00:24:38.319 --> 00:24:41.160
but at the same time, we
want to make sure that you're having a

366
00:24:41.240 --> 00:24:48.039
human interaction. And that was really
what we had invested in. It's been

367
00:24:48.079 --> 00:24:52.240
going on five six years, maybe
maybe a little bit longer than that,

368
00:24:52.319 --> 00:24:56.720
but within the last four years go
To we dubbed it go to and that's

369
00:24:56.720 --> 00:25:00.200
where we're starting to see a lot
more users interact this channel, and they

370
00:25:00.240 --> 00:25:06.119
do really enjoy it because one,
they can get their questions answered, they

371
00:25:06.119 --> 00:25:10.279
can take care of their day to
day business, but they're also talking to

372
00:25:11.319 --> 00:25:15.079
a real life person, and that
I think is kind of where we wanted

373
00:25:15.119 --> 00:25:18.160
to make sure that was still having
these human interactions. We're still occurring through

374
00:25:18.160 --> 00:25:22.920
a digital channel, so we're in
the space right, We're on your phone,

375
00:25:22.960 --> 00:25:30.039
we're in your pocket, but we're
also utilizing our associates to have everyday

376
00:25:30.079 --> 00:25:33.839
conversations with our customers, so they're
still getting that same experience that we would

377
00:25:33.839 --> 00:25:37.640
have in person. I'll ask two
questions following up to that, which is

378
00:25:37.920 --> 00:25:40.440
one, how do you think about
the mode of interaction? I mean,

379
00:25:40.480 --> 00:25:42.480
you have like text based digital interaction
with the real human, you are,

380
00:25:42.599 --> 00:25:47.359
right indeo based digital teraction with the
real human phone call, and you have

381
00:25:47.440 --> 00:25:49.799
video. Are you focused on one
of the other? Are you seeing interest

382
00:25:49.839 --> 00:25:53.400
in different modes? I'm curious what
mode people are enjoying or what you're using

383
00:25:53.440 --> 00:25:59.519
for that kind of human digitally mediated
humans right right, So we're seeing a

384
00:25:59.559 --> 00:26:03.559
lot more of the interaction come through
our chat based platform. And what we're

385
00:26:03.599 --> 00:26:07.599
also seeing is less volume come through
call centers, right, so instead of

386
00:26:07.599 --> 00:26:10.799
having to staff up call centers over
the phone, we're seeing more people engaging

387
00:26:10.880 --> 00:26:15.480
through the chat interactions through Uncle go
to M and then from there, you

388
00:26:15.519 --> 00:26:18.640
know, we have this whole what
we call our digital call center, right,

389
00:26:18.680 --> 00:26:25.039
and so from their associates are still
able to identify opportunities that they come

390
00:26:25.039 --> 00:26:29.119
in. So a customers asking for
a loan, you know, we can

391
00:26:29.160 --> 00:26:32.839
get them over to the channel to
get that application process. And this is

392
00:26:32.839 --> 00:26:37.000
a good in a mediory because not
having the ability to apply now or apply

393
00:26:37.480 --> 00:26:40.759
through a website at this point in
time, but still having the ability to

394
00:26:40.799 --> 00:26:44.599
talk to someone about a loan and
get that process started is a very you

395
00:26:44.640 --> 00:26:48.359
know, like a huge advantage for
us as an institution opposed to here,

396
00:26:48.440 --> 00:26:52.000
fill out a form and someone will
get back to you, you know in

397
00:26:52.319 --> 00:26:56.319
a day or two. Ah yeah, right, Whereas like I might as

398
00:26:56.319 --> 00:26:59.960
well have just walked into a branch
or I might have been by that time.

399
00:27:00.400 --> 00:27:03.920
Especially with all the fintech businesses are
going in, It's like, hey,

400
00:27:03.160 --> 00:27:08.000
I can get my loan applied for
and funded in forty eight hours,

401
00:27:08.039 --> 00:27:11.400
you know, online versus you know
what's going to take me to actually have

402
00:27:11.440 --> 00:27:14.920
to walk down the street, Oh
you're not open, or I had to

403
00:27:14.960 --> 00:27:18.880
make an appointment or you know what
other you know, you know that that

404
00:27:18.000 --> 00:27:22.359
period of time, um, you
know could really be a game changer for

405
00:27:22.400 --> 00:27:25.839
some of the uh, you know, regional banks that we have. So

406
00:27:25.920 --> 00:27:30.519
being able to have that conversation with
our customers right there in their pocket and

407
00:27:30.559 --> 00:27:33.400
get that process started one day sooner, right, is just you know,

408
00:27:33.440 --> 00:27:37.799
an advantage that we we're definitely trying
to capitalize on and get into that space.

409
00:27:37.880 --> 00:27:41.480
Yeah, the the ability to execute
and deliver quickly is certainly something customers

410
00:27:41.519 --> 00:27:47.240
are demanding. I mean not just
you're wanting, but you know kind of

411
00:27:47.319 --> 00:27:52.359
demanding at this point toil for Uber
and Amazon Prime. I guess absolutely that's

412
00:27:52.400 --> 00:27:56.839
our big it's it's you know ore
when we think of technology investments that we

413
00:27:56.920 --> 00:28:00.279
have, right, you can't do
everything, but you can do some thing's

414
00:28:00.519 --> 00:28:03.559
right. You know, you can
do you can do what's right. And

415
00:28:03.799 --> 00:28:06.920
you know, one of the ways
that we decide that, you know,

416
00:28:06.960 --> 00:28:10.559
what we're going to invest in is
kind of the is the mantra for one

417
00:28:10.599 --> 00:28:14.279
day sooner. You know, is
this going to help our customers board their

418
00:28:14.359 --> 00:28:17.519
loan one day sooner? Is the
application process going to go one day sooner?

419
00:28:17.559 --> 00:28:21.240
How is this technology going to help
get something done one day sooner?

420
00:28:21.319 --> 00:28:23.680
So that's that's really what we have. It makes me think of the fun

421
00:28:23.799 --> 00:28:26.960
one day more when you say that
over and over from La Miss you need

422
00:28:27.119 --> 00:28:32.759
you need a theme song for one
days, but that would probably fly.

423
00:28:33.000 --> 00:28:37.039
I's just probably just like, Yeah, I'm a musicals guy, so I

424
00:28:37.079 --> 00:28:40.079
got like one day anyway. I
can't say I liked it. I liked

425
00:28:40.079 --> 00:28:41.880
it. Yeah, we got to
find a way to get the one day

426
00:28:41.920 --> 00:28:45.200
sooner is a that's a great month. I love it. It is.

427
00:28:45.279 --> 00:28:48.599
Yeah, it is amazingly powerful when
you can accelerate the timeline to value for

428
00:28:48.640 --> 00:28:52.720
your customer. How much day that
can improve your conversions, You're you're pulled

429
00:28:52.720 --> 00:28:57.119
through your your overall business and satisfaction
with the customers that you have. Absolutely

430
00:28:59.200 --> 00:29:02.880
um. One of the questions is
he, I mean, the chat based

431
00:29:02.880 --> 00:29:07.039
interaction is interesting in the I mean, even more recent than the banking issues

432
00:29:07.039 --> 00:29:11.920
and interest rate risk kedging and in
management is this concept of generative AI andarts

433
00:29:11.960 --> 00:29:15.000
that can kind of behave in a
human like way? Is that something you've

434
00:29:15.000 --> 00:29:18.440
looked at it all are still like
I'm also you know, I went into

435
00:29:18.519 --> 00:29:21.559
like change right and to like,
I've got an extra thousand dollars, how

436
00:29:21.559 --> 00:29:25.279
should I invest from my retirement?
It'll do a pretty good job breaking down

437
00:29:25.599 --> 00:29:29.720
roth iras and iras in four oh
one ks and in different investment options and

438
00:29:29.759 --> 00:29:33.279
where you should start and whatnot and
sending these accounts and the CDs and um.

439
00:29:33.920 --> 00:29:37.519
But have you thought about any ways
to like take their first round of

440
00:29:37.599 --> 00:29:41.400
questions that can be automated or is
it still all that's still like a we're

441
00:29:41.640 --> 00:29:45.000
we're committed to any human human interaction
with the Night Channel. M One thing

442
00:29:45.079 --> 00:29:52.279
that and this is what I've actually
loved about is that we're not I guess

443
00:29:52.359 --> 00:29:53.680
what we would say, Hey,
we're not a sales culture. That the

444
00:29:53.680 --> 00:29:57.799
purpose of this channel isn't to sell
it our customer or something, right,

445
00:29:57.799 --> 00:30:02.599
it's it's to provide CERTA said.
We really believe that service first leads to

446
00:30:02.720 --> 00:30:07.200
more business, so we have a
very service based culture. It's actually really

447
00:30:07.240 --> 00:30:11.319
interesting. Back when Ray Davis started
started the bank, Well had taken over

448
00:30:11.359 --> 00:30:17.680
as the CEO. He dubbed all
of our branches then you know stores,

449
00:30:17.799 --> 00:30:21.319
right, and this store experience was
really based off Nordstrom, and we would

450
00:30:21.359 --> 00:30:25.319
hire not bankers, but we would
hire people who worked at Nordstrom, people

451
00:30:25.319 --> 00:30:27.599
who worked at Starbucks, people who
delivered you know, service. And this

452
00:30:27.680 --> 00:30:32.200
was in our in our front of
the house with within our branches or what

453
00:30:32.240 --> 00:30:36.680
we had then called stores. And
so how did we you know, what

454
00:30:36.720 --> 00:30:41.200
we want to do is translate that
experience into a digital experience. And some

455
00:30:41.279 --> 00:30:42.640
of the stories that come out of
this, you know, for the Unqua

456
00:30:42.720 --> 00:30:49.079
Go too, is being able to
do follow ups with your customers when they

457
00:30:49.119 --> 00:30:52.319
say, hey, I'm trying to
finance a wedding, Okay, great,

458
00:30:52.359 --> 00:30:53.319
Not only will we do that,
but you know, we send you the

459
00:30:53.319 --> 00:30:56.880
handwritten car. There's certain touches that
we follow up with, you know,

460
00:30:57.119 --> 00:31:00.799
help them, put them in touch
with a floorist that we might also bank

461
00:31:00.839 --> 00:31:04.279
as well, you know, really
expand on that network. And we think

462
00:31:04.319 --> 00:31:10.839
that giving one empowering our associates to
have that human interaction with our customers goes

463
00:31:10.880 --> 00:31:14.920
a lot further than to be able
to kind of constantly offer you know,

464
00:31:15.119 --> 00:31:18.119
basically mining a conversation for sales opportunities
that you know, we're kind of going

465
00:31:18.160 --> 00:31:22.960
the different direction. We're minding these
conversations for service opportunities, which you know

466
00:31:23.000 --> 00:31:29.359
hopefully then leads to good graces in
getting more business and preferring friends and kind

467
00:31:29.359 --> 00:31:32.559
of having this net promoter score in
one way or another. But we want

468
00:31:32.559 --> 00:31:37.279
to just really be satisfied with the
service that we're giving, so very very

469
00:31:37.440 --> 00:31:41.200
kind of hardlined with you know,
the AI isn't meant to do sales right

470
00:31:41.200 --> 00:31:48.000
where you might have something like a
different chatbots. I will name industry names,

471
00:31:48.000 --> 00:31:51.000
but you know, it's certain things
that don't necessarily work. They're just

472
00:31:51.039 --> 00:31:53.000
trying to get you through a queue. They're trying to take you know,

473
00:31:53.839 --> 00:31:59.240
volume out of the call centers.
You know, we're actually just trying to

474
00:31:59.279 --> 00:32:05.079
translate our in store, our in
branch experience to a digital channel. Iceland

475
00:32:05.119 --> 00:32:07.680
and I want to kind of strange
that we're getting to the end of our

476
00:32:07.720 --> 00:32:10.200
time and I'm going to ask this
question, but you said you're probably manager

477
00:32:10.279 --> 00:32:14.319
for scored lending. How do you
guys define scored lending? What does that?

478
00:32:14.359 --> 00:32:16.519
I mean? I feel like all
lending should be scored right, Well,

479
00:32:16.640 --> 00:32:22.839
I think so we're yeah, so
well, we I think through our

480
00:32:22.359 --> 00:32:27.759
loan channels, right, we do
do a lot of larger commercial deals that

481
00:32:27.799 --> 00:32:30.640
need to go through custom underwriting.
So scored lending, what we define a

482
00:32:30.720 --> 00:32:37.480
scored lending is within a parameter set
loan amount, collateral risk that can go

483
00:32:37.640 --> 00:32:44.759
through a scoring model that can basically
kick out a approval based on amount of

484
00:32:44.759 --> 00:32:49.200
factors and then from there help expedite
that funding. So typically right now we're

485
00:32:49.200 --> 00:32:52.480
doing three million and under for business, and all of our consumer lending is

486
00:32:52.599 --> 00:32:55.480
scored for the most part, unless
there needs to be some type of custom

487
00:32:55.559 --> 00:33:01.200
underwriting. So it's really based on
own amount and risk for the most part

488
00:33:01.440 --> 00:33:06.680
of the different products that we have. And so you know this is this

489
00:33:06.759 --> 00:33:10.559
is pretty I wouldn't say newer for
organizations, but a lot of organizations that

490
00:33:10.799 --> 00:33:15.559
are still out there at a regional
bank level, you know, they will

491
00:33:15.759 --> 00:33:19.200
do the custom underwriting. They'll they'll
go through you know, you'll apply for

492
00:33:19.240 --> 00:33:22.079
a loan and it will go through
underwriters, you know, some type of

493
00:33:22.119 --> 00:33:24.759
credit underwriting center. They'll take a
paper application, they'll go through your financials

494
00:33:24.759 --> 00:33:29.519
and they'll do an approval that way
opposed to one day sooner, right or

495
00:33:29.559 --> 00:33:31.359
something of a scored lending channel to
be able to get that approval, get

496
00:33:31.359 --> 00:33:36.599
the documents process and move forward.
And when it comes to human digital even

497
00:33:36.680 --> 00:33:40.599
even with our scored lending channel,
right, we still have human interaction where

498
00:33:42.160 --> 00:33:45.519
if we could kind of get down
some of these manual reviews, whether they

499
00:33:45.599 --> 00:33:51.319
be for fraud or incomplete applications or
certain things I don't quite date a credit

500
00:33:51.319 --> 00:33:54.799
box, and we could identify and
eliminate those human touches, we could start

501
00:33:55.160 --> 00:33:59.759
really getting one day sooner to funding
for our customers too. So even within

502
00:33:59.839 --> 00:34:02.440
us score channel, there is human
interaction and um, you know, the

503
00:34:02.480 --> 00:34:07.799
onus with as a product manager is
to you know, really help drive you

504
00:34:07.839 --> 00:34:10.400
know a one day sooner or approach
on what are we doing and you know,

505
00:34:10.440 --> 00:34:15.920
how can we get this done in
a more streamlined fashion? And fraud

506
00:34:15.039 --> 00:34:17.840
fraud check is a big big piece
of that too, right, Yeah,

507
00:34:17.880 --> 00:34:21.880
for sure, One thing I I
would do want to dig in on is

508
00:34:22.239 --> 00:34:24.000
the idea of when you say scoring, I love it. But there's also

509
00:34:24.039 --> 00:34:29.679
this current debate about alternative scoring approaches
all right, data used in scoring.

510
00:34:30.000 --> 00:34:34.559
What's your take on the opportunities and
risks associated with you know, going beyond

511
00:34:34.639 --> 00:34:37.559
the traditional you know. Yeah,
I mean when I look at even most

512
00:34:37.559 --> 00:34:42.199
scoring mechanisms by banks, there's you
know, for consumer loans, there's a

513
00:34:42.199 --> 00:34:45.880
handful of variables that's related maybe to
equity in the in the house or an

514
00:34:45.880 --> 00:34:49.719
auto loan, and that it's like
credit score ten or fifteen things coming off

515
00:34:49.719 --> 00:34:52.480
the credit file, and it's it's
a pretty straightforward set of pretty traditional metrics

516
00:34:52.480 --> 00:34:57.400
that are used to relations. There's
a whole you know, sets of data

517
00:34:57.440 --> 00:35:00.079
that are non traditional that are right
being used by I'm curious how you think

518
00:35:00.119 --> 00:35:04.960
about you know, you know,
moving forward. When you're in that automated

519
00:35:04.960 --> 00:35:07.440
scoring mechanism, all of a sudden, the question becomes what other kinds of

520
00:35:07.519 --> 00:35:12.760
data or absolutely it could we use
to make better determinations? Right as that

521
00:35:12.880 --> 00:35:14.719
in that journey, what do you
what do you think the future looks like?

522
00:35:15.039 --> 00:35:16.800
Yeah? Absolutely, so there's you
know, is this telling the whole

523
00:35:16.800 --> 00:35:20.360
story of the customer's ability to repay? Right? You know? Is this

524
00:35:20.480 --> 00:35:22.519
the best method? Or are there
are some of the scoring models, some

525
00:35:22.559 --> 00:35:28.960
of the larger you know, phycou
you know, uh advantage of some of

526
00:35:28.960 --> 00:35:31.440
these models that are out of the
box, you know, are they really

527
00:35:31.480 --> 00:35:36.480
doing the best to mitigate risk,
right, and it all comes down to

528
00:35:36.480 --> 00:35:39.239
the risk of the portfolio from a
bank side. And so right now,

529
00:35:39.280 --> 00:35:45.239
I mean these traditional models, their
advantage is that they have results recorded,

530
00:35:45.320 --> 00:35:50.079
right, I mean they there is
revault of yeah, exactly, default rates,

531
00:35:50.119 --> 00:35:52.159
certain things like that that that have
worked in the past, um,

532
00:35:52.320 --> 00:35:57.000
but that is starting to turn,
right, These alternative credit models are starting

533
00:35:57.000 --> 00:36:00.480
to say, hey, not only
are we seeing lower de fault rates,

534
00:36:00.519 --> 00:36:04.119
but we're being able to approve more
barrowards within you know that these models would

535
00:36:04.159 --> 00:36:07.400
have declined. Yeah. One huge
thing that I think that's kind of a

536
00:36:07.440 --> 00:36:12.960
really big focus for us too as
an organization are these special purpose credit programs.

537
00:36:13.280 --> 00:36:15.679
So you know, we want to
be making sure we're lending to communities

538
00:36:16.079 --> 00:36:23.559
that these traditional scoring models wouldn't necessarily
approve, right, So how can we

539
00:36:23.599 --> 00:36:28.719
do that? How can we do
more lending investing in minorities, you know,

540
00:36:28.760 --> 00:36:31.840
women owned businesses, black owned businesses, certain things like that where you

541
00:36:31.840 --> 00:36:36.760
know, hey, they weren't getting
qualified through these traditional scoring models. But

542
00:36:36.840 --> 00:36:38.119
you know what, we're going to
be using alternateive scoring models that will help

543
00:36:38.159 --> 00:36:43.519
them with our special purpose credit programs
opposed to you know, just lowering the

544
00:36:43.599 --> 00:36:49.920
score for some of these loan applicants
versus you know, keeping them versus like

545
00:36:49.960 --> 00:36:52.440
if they you know, if they
didn't meet these types of the boxes that

546
00:36:52.480 --> 00:36:55.719
we've met. So for me,
top of mind for alternative scoring models,

547
00:36:55.719 --> 00:37:00.559
I think there's a great advantage to
be helping with the special purpose credit programs

548
00:37:00.119 --> 00:37:06.920
that are out there. And also
I think just the more that we're able

549
00:37:07.000 --> 00:37:10.840
to prove these models and there you
know their efficiencies, you know, to

550
00:37:12.280 --> 00:37:15.719
mitigating default rates, the stronger it's
going to be in the corner too.

551
00:37:15.480 --> 00:37:20.119
Excellent. Well, I think that's
most of the questions I have for you,

552
00:37:20.199 --> 00:37:22.519
but I appreciate it has been a
great conversation. I do have three

553
00:37:22.599 --> 00:37:24.960
questions I like to ask everybody at
the end of the podcast, so absolutely

554
00:37:25.000 --> 00:37:29.639
I and we can we can jump
to those ready. First, what's the

555
00:37:29.679 --> 00:37:32.519
best piece of career advice you've ever
gotten? Well, I'll just go through

556
00:37:32.840 --> 00:37:38.280
what my journey has brought me to
is that, you know it always try

557
00:37:38.360 --> 00:37:44.400
to be building on your past experiences, so you know, be mindful of

558
00:37:44.440 --> 00:37:49.719
your career approach. I think that
some people or some associates easy to kind

559
00:37:49.760 --> 00:37:53.800
of just accept the faith that they're
at within the organization. But if you're

560
00:37:53.800 --> 00:37:58.719
intentional about your career path and working
with the manager to get you there,

561
00:37:58.760 --> 00:38:00.440
I think that's um. You know. One of the steps that I would

562
00:38:00.480 --> 00:38:04.719
take is always trying to build upon
your past experiences for your new role,

563
00:38:06.280 --> 00:38:10.920
and also look outside of your organization
for not new opportunities, but to see

564
00:38:10.920 --> 00:38:14.960
what your organization is doing, because
I think oftentimes too when you're an organization,

565
00:38:15.000 --> 00:38:19.239
I've been with a bank for eleven
years, but if I wasn't curious,

566
00:38:19.400 --> 00:38:22.360
you know, staying curious and looking
at what other organizations are doing,

567
00:38:22.639 --> 00:38:25.639
you know, what roles are they
implementing and bringing that back to our organization

568
00:38:25.679 --> 00:38:30.519
as well. I think that helps
kind of diversify the ideas that you can

569
00:38:30.559 --> 00:38:35.880
bring to your organization as well.
Love it. Second question I got is

570
00:38:36.079 --> 00:38:39.559
what's the best advice about the you
know, retail consumer banking industry in general

571
00:38:39.599 --> 00:38:46.360
that you've gotten or give. I
would say, if you're a consumer right

572
00:38:46.400 --> 00:38:50.880
now, you know, looking around, I think you're in a really good

573
00:38:50.880 --> 00:38:52.599
place. I think with the fintech
industry that's happening. I mean, you're

574
00:38:52.639 --> 00:38:57.320
getting options and just like anything that
they would say, like if hey,

575
00:38:57.360 --> 00:38:59.519
if you're going to shop for a
mortgage, you know, make sure you're

576
00:38:59.519 --> 00:39:01.559
shopping for more debate. Same thing
as as a consumer, you know,

577
00:39:01.559 --> 00:39:06.360
if you're you have a lot more
options to you than you did previously,

578
00:39:07.239 --> 00:39:10.360
and there are companies who are fighting
to provide that service. So you know,

579
00:39:10.960 --> 00:39:15.119
although it might be hard to switch
your checking account from the institution you

580
00:39:15.159 --> 00:39:17.039
have now, it might be worth
doing so if you haven't looked around in

581
00:39:17.079 --> 00:39:22.039
a while, because there are companies
that are willing to kind of go above

582
00:39:22.079 --> 00:39:25.079
and beyond to kind of break down
some of those barriers that they have from

583
00:39:25.679 --> 00:39:29.159
uh, you know, the banking
industry. You know that could really provide

584
00:39:29.199 --> 00:39:31.679
exceptional service. And you know,
make sure that you're you know, you

585
00:39:31.719 --> 00:39:36.599
are valuable as a consumer in this
space. I will I will tell you

586
00:39:36.599 --> 00:39:39.960
that much right now. All right, that's great and fast. One is

587
00:39:40.000 --> 00:39:46.719
what's one bold prediction for the future. I would say that, you know

588
00:39:47.199 --> 00:39:52.159
one bold prediction for the future that
would really be for me. I think

589
00:39:52.159 --> 00:39:57.960
that we're starting to see one thing
that's a popular belief within this current industry

590
00:39:58.039 --> 00:40:01.280
right now is who your competitors are
as a bank between your asset size and

591
00:40:01.320 --> 00:40:05.440
I see this all the time where
it's Hey, you're a fifty billion dollar

592
00:40:05.519 --> 00:40:07.960
bank. Well here's you know,
let's compare you to other fifty billion dollar

593
00:40:08.039 --> 00:40:12.320
banks are less because these are your
competitors. And I think that there's a

594
00:40:12.320 --> 00:40:16.679
digital landscape that's happening right now where
you know, we are competing with bigger

595
00:40:16.679 --> 00:40:20.920
banks, we are competing with FinTechs, and we're not just within a asset

596
00:40:20.960 --> 00:40:24.039
class of who our competitors are.
And so I think the competition within the

597
00:40:24.119 --> 00:40:30.079
organizations of the products that you're offering, you know, really needs to broaden

598
00:40:30.159 --> 00:40:34.880
that scope because it's not anymore of
just who's in your footprint and who's in

599
00:40:34.880 --> 00:40:37.199
your asset size. I mean,
it really is the ability through this digital

600
00:40:37.280 --> 00:40:40.800
channel to be able to shop around
as a consumer. And if you're not

601
00:40:40.960 --> 00:40:46.159
capturing that and you're you know,
if you're thinking that, you know,

602
00:40:46.199 --> 00:40:49.440
you're kind of safe with who your
competitors are, and you're going to price

603
00:40:49.480 --> 00:40:52.719
similar to your competitors based off asset
size, I think that that's going to

604
00:40:52.800 --> 00:40:57.840
be a detriment to your organization.
Definitely interesting, very true that we you

605
00:40:57.840 --> 00:41:00.800
could think of your competitors an equity
investor point of view, maybe here competitors

606
00:41:00.840 --> 00:41:05.639
or banks your size. That might
be who wants to fund the company,

607
00:41:05.639 --> 00:41:10.079
where you'll be compared when you do
your earnings call when trying to find which

608
00:41:10.360 --> 00:41:14.719
which depositive product I want or where
I will write where I want to invest

609
00:41:14.800 --> 00:41:19.360
my money? That they couldn't tell
you. I bet most conseritors couldn't tell

610
00:41:19.400 --> 00:41:21.599
you that the asset size of the
bank they were, But there's just not

611
00:41:21.719 --> 00:41:24.920
irrelevant constit They're they're comparing you guests
across a lot of different competitors, right

612
00:41:25.000 --> 00:41:29.280
and you know, we're we're relying
on third parties to help kind of provide

613
00:41:29.280 --> 00:41:31.519
some of that data, and they
always try to bucket you in these these

614
00:41:32.000 --> 00:41:36.440
competitors based on your assets size,
and it's it's you know, for them.

615
00:41:36.480 --> 00:41:38.400
I think what you know, the
institutions need to do, and even

616
00:41:38.440 --> 00:41:44.960
those who help provide you know,
pricing analytics or other other opportunities, they

617
00:41:44.960 --> 00:41:47.840
need to really kind of start rethinking
what that competitor pool starts looking like for

618
00:41:47.960 --> 00:41:53.079
organizations because that landscape is changing drastically. Excellent. I think it's a fabulous

619
00:41:53.159 --> 00:41:57.280
point and a great place to leave
it. Then again, thanks for making

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00:41:57.360 --> 00:42:00.039
time and joining us. This was
a very fun conversation. I appreciate it.

621
00:42:00.519 --> 00:42:05.320
Thanks stuff. Upstart partners with banks
and credit unions to help grow their

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00:42:05.320 --> 00:42:09.480
consumer loan portfolios and deliver a modern, all digital lending experience. As the

623
00:42:09.519 --> 00:42:15.320
average consumer becomes more digitally savvy,
it only makes sense that their bank does

624
00:42:15.360 --> 00:42:21.920
too. Upstarts AI lending platform uses
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risk and approve more applicants than traditional
credit models. With fraud rates near zero,

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upstarts all digital experience reduces manual processing
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00:42:32.480 --> 00:42:37.840
convenient experience for consumers. Whether you're
looking to grow and enhance your existing personal

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and auto lending programs or you're just
getting started, Upstart can help. Upstart

629
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offers an end to end solution that
can help you find more credit worthy borrowers

630
00:42:47.239 --> 00:42:52.400
within your risk profile. With all
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631
00:42:52.440 --> 00:42:58.360
and servicing, It's all possible with
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finding new borrowers in hand, seeing
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business by visiting upstart dot com slash
foward dash banks. That's upstart dot com

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635
00:43:13.599 --> 00:43:16.280
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