Data Is The New Oil: What’s Next In Banking

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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 Tim
Schangel. He works on data and analytics

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at Choice one Bank and as part
of the American Bankers Associations Merging Leaders Council.

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And we really you know, Tim
has been in the tech world for

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a while, has a CS degree, and we really dove into the technology

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a little deep, talking about chat, gpt AI, some of the new

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things and where they might fit into
the banking environment and also where they don't

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fit, how you combine AI and
human resources and human touches. I think

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importantly Tim's perspective that sometimes we overestimate
what to expect from a technology in the

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short term, but underestimate in that
medium term what maybe a ten year time

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horizon. While things may not change
dramatically in the next two years or the

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next ten the banking environment might be
unrecognizable and so really interesting conversation. And

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the last bit we delve into his
background going to seminary studying theology and how

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that impacts the way he thinks about
banking. It's a really interesting conversation that

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ranges a lot of topics, but
deep on the tech this week. Please

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enjoy my conversation with Tim. Tim, Welcome to the podcast. Thanks for

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making the time to join us today. Yeah, thank you, thank you

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for having me. Excited to talk
here. A little bit of a body

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innovation. Just right before this call, I was chatting with chat gpt,

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so definitely into it. What did
what did chat GPT tell you? Buddy

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of mine called me. It's like
I had a business idea for you financial

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services chat GPT go. I was
like, all right, man, I

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feel like everybody's trying to get the
chat GPT of X. Yeah. No,

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I was just kind of testing it
and I said, I said,

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rate letter for me to give to
my employer that I changed bank accounts.

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And that's all I said to it
because I wanted to see what kind of

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what it did. And it gave
a perfect form letter and said like insert

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your name here, insert your new
bank's name here, your account number,

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your routing number. And so then
of course I had to follow up with

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it, and I asked it,
well, where else should I change my

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bank account information? And that rattled
off the next like three or four things

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and gave me template letters for all
those, and so it's pretty It was

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funny. I saw this Twitter post
or something somewhere somebody said, you know,

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chat GPT is great and all,
but I'll never be used in medicine.

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And the next thing I saw were
two doctors, and one I said,

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well, whenever I get denied insurance
coverage for a treatment, I go

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to chat GPT and tell it,
you know, write me a letter to

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United Healthcare justifying. You know.
It spits out a perfect letter. And

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then I talked to a buddy mine. It's like, oh man, I

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use it all the time to write
reference letters, because I wouldn't write these

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nice reference letters. But I can
go and say, write a reference letter

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from the head whatever position, at
this position, and for a nurse with

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this name and these you know,
she's cheerful and on time and effect whatever

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professional. Give a couple of adjectives, and that it pops out this perfect

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layers, Like what would have been
hours with work is now five minutes of

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putting in and it's still small.
Cousin. They edited it a little bit,

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but I was like, yeah,
right there, I can't never work

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in medicine. I went, well, I mean it's not doing diagnosies.

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I great, but like that's doing
a pretty good job exactly, you're actually

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changing your bank or was that just
the test game. No, No,

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that was just a complete test just
to see how how close they could get

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it. So, I mean,
but even like writing emails like okay,

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I want to announce this new feature
coming out, I throw it in chat

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GPT first and five drafts later,
I have one that's perfect that to get

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that initial draft that sometimes the hardest
thing to do. Yeah. I actually

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saw somebody who's built a I forget
the name of it, but it's like

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a Chrome plug in that uses Chat
JPT. It kind of embedds it in

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the Gmail composed experience, so you
can be in Gmail. Well you can

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plug like a grammarly plug in will
come in and make you sound that our

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our it T T team will let
us use that, and we'll let us

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use this. But you could give
it a few prompts in it will pop

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a right in the Gmail so you
don't have to have two witness open.

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It just kind of like uses it
to kind of throw stuff right right into

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the email body for you. It
sounds pretty fun. Oh that's awesome.

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Yeah, I mean, I gotta
find that one. So when we talked

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to earlier time, you use this
really interesting phase that I wanted you to

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explain it, which was innovation to
scale and to time, And I thought

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that was an interesting description of innovation
or ways you think about innovation and access

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along way. So talk to a
little bit about what you mean by innovation

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to scale and innovation to time.
Yeah, So innovation to scale, like

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especially when we think about like small
community banks like Choice one. I mean

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we have thirty four locations. There's
a lot of banks smaller than us,

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and there's a whole lot better,
a whole lot bigger than us. One

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big thing is they with all of
like cat GPT and artificial intelligence and all

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the information we have. One of
the big kind of pushes as well,

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you have to have a customized experience
for all of your customers, and there's

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a lot of different ways to do
that. But sometimes they call it like

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niche banking. But when we think
about like our geographic area with niche banking,

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and like, let's say we wanted
to do something for dentists, Well,

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we only have a limited geography and
there's only so many dentists that can

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bank in that geographical area. So
then you have to kind of weigh it,

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and it's like, Okay, do
you really want to create a special

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product and special user interface for a
niche market when the maximum number of people

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you can get is one hundred people? And I'm just throwing those numbers out

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that probably isn't correct for dentists in
our area. But it's still one of

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those where it's like, Okay,
with scale, it's like if you're launching

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stuffing nationally, it's very different than
if you're a community bank that's trying to

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reach a geographic area. Interesting,
that's the innovation to scale. How about

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time? How do you think about
that question? Yeah? And then the

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time it's interesting because you innovation happens
in the next five years, there's not

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going to be really that much that
changes. I mean, there'll be new

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products on the market, you know, there'll be early adopters that are doing

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really exciting things, and some of
them will fail. There'll be other people

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that have literally not changed at all
in the next five years and it will

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still be acceptable. But then if
we go ten years out and we look

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backwards, it'll be like, oh, my gosh, everything has changed in

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the last ten years. And I
think about my own career in banking.

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I started about ten years ago,
and you very much saw that. I

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mean, when I started ten years
ago, there were still the number of

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banks that didn't have mobile banking yet, it didn't have mobile deposit. Mobile

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deposit was still questionable whether or not
the everything was laid out in the best

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way possible to prevent fraud. There
was no type of mobile wallet. And

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that's only ten years ago. And
I think with innovation, we have to

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kind of keep in mind that there's
gonna be a whole lot that changes.

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We just don't feel it changing.
So you have to kind of look at

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that ten years out and then remember
that, like five years from now,

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it's okay, You're gonna have plenty
of time to help on. Yeah,

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it's interesting. I think it's a
quote by Roy Amara who said something along

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lines if we tend to overestimate the
impact of technology and the short term and

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underestimate it in the long term.
I think it's kind of about the five

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the ten years we see chatting team. We expect next week, I'm gonna

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be chatting on my banking website with
an AI thing and it's gonna be great,

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and then it doesn't. Kind of
go, oh, this thing never

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worked out. It's like, well, in ten years, you may not

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recognize anything about the experience, but
in you know, in two weeks and

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in a year that those things take
a little time to percolate, so we

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tend to we tend to not notice
it or expect it to be instantaneous,

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and it's actually faster than you might
have thought in the long term, but

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in the short term it just never
quite lives up to expectations. I think

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there's a lot of that going around
exactly, and quite often there's this kind

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of fear that oh, I'm going
to miss out, Like this is moving

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so fast, I'm gonna miss out
on it. But just the same way

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that customers are so slow to move, there will be some customers that are

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earlier ops. But overall, it's
a lot of work to change a bank

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account. It's a lot of work
just to convince them to change their morning

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routine and to hop on a peloton
instead of happening on a treadmill. And

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eventually they do, but they have
to kind of ramp up and scale just

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the same way that we do.
Yeah. The other thing that occurs to

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me is the kind of the Gartner
version of this, the hype cycle.

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Yeah, I'm sure you're familiar with
the hypes you can kind of. I

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think it's it's related to this kind
of you know, short term overestimation long

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term because the short term overestimation is
that hype peak whatever, they call it,

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the peak of whatever, and then
they've got the trough of disillusionment,

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which is where the real work is
being done to build the long term lasting

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that kind of longer term vision.
One of the things you how do you

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think about sustaining because there's this kind
of like the AH as a flash in

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a pan and it's not going to
be it just didn't do what I wanted

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in six months, and yet it's
really the people investing in building it in

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the right ways over the next six
seven years that are going to reap the

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rewards on that timescale. How do
you think about the like what you do

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to optimize your ability to really see
those things and then continue in, you

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know, iterating on and investing in
the important areas of technology over time so

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you can you can actually be the
ones developing the new thing over the ten

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year horizon that maybe doesn't come into
Yeah. I think the big part with

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that is to kind of keep your
eyes focused on that ten year or to

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kind of know what's happening ten years
from now and kind of know, Okay,

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where the trends going, what should
we have our eyes on. Like

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I think of ten years ago,
like sending you around a table and talking

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about mobile design, like anything that
we're going to invest in, we're going

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to make sure it has mobile design, is going to be compatible with phones.

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And ten years ago, like we
had phones, but there was a

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question of should should a website even
be mobile responsive or should we just go

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straight to the app? And we
kind of made an executive decision like no,

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everything going forward is going to be
mobile responsive. You're going to have

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to get zone on the phone.
And I think making those type of decisions

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so they they're kind of the smaller
the decisions that have a big impact on

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the kind of overall direction then along
with you know, looking to see when

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those kind of smaller changes kind of
reach fruition. You know. I think

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of like the Microsoft Power Apps platform
with power BI and a lot of the

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kind of no code automated, you
know, type of things that have been

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promised for the last twenty years.
I think has finally reached a point of

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maturity where you can start using them
in production. And I think that's the

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kind of an area of excitement.
You said two things to me there that

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I want to dig into. One
is kind of like what these tenure trends

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are You talk about power tools being
on the lipic if I want to take

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a step back. You talked about
these small decisions that end up having a

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big impact, and that was really
interesting to me. Jeff bezos Wants described

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them as like thinking about you know, one way doors versus two way doors,

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right, and like move quickly through
the two way door and slowly through

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a decision that can't be undone or
reverse it. And I think in tech

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often it's things like data architecture where
you can build code quickly and replace it.

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But if you architect the data wrong, well God help you. But

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replacing that fixing that adding the feature
that wasn't that the data infrastructure didn't support

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becomes nigh impossible two years down the
road because stuff gets built on top.

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And I guess my question is,
how do you think about what the small

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decisions that have a big impact are
though you want to be careful about or

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get right or thoughtful about, versus
the small decisions that are like easy to

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change and not a big deal and
you should just make them with little information

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and move quickly as opposed to trying
to get them right. Because it seems

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really important to understand the difference between
the big, the big decisions that make

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you know, maybe small in the
moment but make a big difference on the

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road, and the small on the
moment that are like easy to fix and

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don't worry about this, just go
and try a bunch of stuff. They

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feel like very different. How do
you how do you think about discerning what

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you're looking at? Yeah, so
I mean like big decisions. I mean

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you're always going to look at like
okay, cost availability and struggle with the

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contract to whole bunch and get tied
up with lawyers, and so I mean

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like, like big decisions are always
going to be big decisions. But then

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I think it's there's other kind of
small, varying factors they can kind of

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plug into there. So whether it's
like, Okay, does this new application

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have an API? Like we have
no plans to use an API, but

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can I get my data out of
it? And it's those type of decisions

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where you have A, B and
C products that you're evaluating, and if

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all of them are kind of equal, but this one has a really good

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API that you have no intention of
using, but maybe someday you will,

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it's an easier decision to go with
that product. And I think it's like

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artificial intelligence will be another one where
it's like, Okay, does this new

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product can it integrate with have an
API that will allow it to integrate with

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chat GPT or something similar to it. We haven't kind of went down that

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road yet, but I think very
quickly will get there if it, especially

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if chat GPT continues the way it
is going. Yeah, well, yeah,

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well we'll talk about chat TB too
many. I think your answer is

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so interesting because it highlights this like
import of the ability to do things I

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don't yet need or want to do, but kind of the optionality of having

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that capability if in what I would
want to because so often like it's the

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thing you didn't need two years ago, that you didn't optimize for and then

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and two years ago, and oh
the lack of that thing is killing my

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ability to do the next thing I
want to do. And what if I

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put myself in this corner and as
fascinating to think about as things you're not,

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I'm making a decision based on the
future. I don't even use you

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do that. You're kind of future
proofing if you will your your thought process,

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which I think is a really interesting
mental construct. Right well, and

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like people do it all the time. I mean, I mean they go

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to buy a car, and till
newlywed's going to buy a car, Well,

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maybe I shouldn't buy the sports car
because we just got married and we're

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gonna have kids soon. I don't
know when we're gonna have kids. Maybe

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we'll have kids, maybe we won't
have kids. But let's go with a

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Sudan this car I got sports car, and then upgrade. That's what I

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would be my advice. You get
to take it, take it while you

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can have. You is a long
time do you go back the other way?

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So just trader in when it's time
and enjoy it while you can.

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It's my regret. I think I
went with a Preuss instead of the sports

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car. That was definitely not the
same kind of enjoyment for the first few

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years before we had the kids.
Small stakes, they are small mistakes.

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What it is? What do you
see as that you know you talked,

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We talked about chat, GPT,
talked about kind of the Microsoft power Tools

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power BI What are the big if
you think the big waves are the big

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trends, the thing you say,
hey, we've got to be this is

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going to be a thing over this
time horizon. The question is how do

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we take advantage of it, What
do we do about it, how do

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we work with it? What are
the ones you've got your eye on?

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What are the things you're saying,
Hey, this is the stuff that's really

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interesting. Obviously you've got AI in
particularly generative AI and in large language models

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with chat, GPT and GPT three
on the list. Anything else that goes

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into that kind of bucket. Yeah, I would say all the kind of

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no code low code solutions. So
whether it's power apps or like Jecutary's workflow

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or I mean, there's so many
on the market right now. That allows

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someone to kind of somewhat quickly develop
kind of their own custom program with with

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fairly little programming experience. I mean, it still takes a lot of work,

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and it will get better in the
future, you know. But I

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think that's one area that you'll see
a lot of kind of investment in.

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And finally, the automation of the
manual Excel spreadsheets that a lot of people

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are using. Yeah. I once
heard somebody describe, as you know,

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in the in the sort of committee, like why do I get a great

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business idea? They go, if
you want to be to b SaaS business

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idea, just find anything that's done
in a spreadsheet and then build an app

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that does it better. Yea.
And that's like going to build, build,

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build a billion dollar business on that. And there are a lot of

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businesses that are essentially really complicated Excel
sheets turned into an app. But the

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no code loco and I've not heard
that before. That's I mean, I'm

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familiar with it. Are you seeing
a lot of development and interest in that

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space? It's a really I think
it's a fascinating space to open up the

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creative power. If you think back
to the origins of the Internet and hackers,

258
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they were really builders who wanted to
build stuff, and it was like

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it was behind this technical wall of
stuff you had to learn to be able

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to build in that environment. And
the no code is kind of going,

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Hey, if you're a builder but
don't don't know the sophisticated languages and the

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kind of technical background, you can
still build interesting stuff, which I think

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is a really fascinating unlocking of the
power of compute for a user who never

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learned the secret language of you know, c Sharp or Swift or Java or

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whatever you pick your language of choice. Python. What are you seeing done

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with that that's interesting to you?
Yeah? Really, I see the exact

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same things that I was doing twenty
five years ago. And micros opt to

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access Yeah, I mean, just
to be completely frank and honest, but

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it's one of those where micros opt
to Access was. I mean, there

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are ways to roll it out across
the network, but really power apps is

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kind of the embodiment of that of
like, Okay, you have all this

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data, We're going to put a
pretty interface on top of it and allow

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you to work with it. Then
of course, I mean, you can

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plug in with different APIs and you
know, they made it a whole lot

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better, But at the end of
the day, it's really take those kind

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of like database oriented data, you
know, crunching type of tools and making

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a beautiful way to view it and
process that and work with that data.

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Yeah, you've said one of the
I think one of the through lines of

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my conversations has been the increasing import
of data. And you know, I've

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had this ongoing debate like if data
is the new oil, and I actually

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I'm curious to take I'll give you
my perspective, and I'm kind of curious

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your reaction, which is like,
I hear this data is the new oil,

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and I kind of think it's a
totally wrong analogy because oil is something

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that's like rare, only a couple
of people have it, and it's mostly

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just having it that's valuable, and
I kind of feel like data is the

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opposite. Data is like everywhere,
everybody's got tons of it, and it's

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not the having of it that's important. It's the being able to make use

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of it in some important way that
is the key differentiator. So I kind

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of think it's like well and someway, it's kind of more like sand it's

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everywhere. But it's like the turning
it into silicon and chips. It's like,

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that's the part that's really magical.
It's not the like I've got the

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sand, like everyone's got sand.
It's not a big deal oils. More

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like you got it. It's good
and like wow, So I know what

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you're taking is but I feel like
there's this unlocking the power of data to

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do things in a better way that
is a part of whatever the tools are,

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there's a part of the way of
the future that is really important for

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people to be investing in and getting
right. Yeah, I really like that

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analogy. Yeah that you gave it. I think I definitely agree with it

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and resonate with it. The whole
idea of data being the new oil,

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I definitely don't think I agree with
it. I think it does take a

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lot of it's really the processing of
it, and that's really I mean,

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what you know chat GPT is doing
is it's processing these huge amounts of data.

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I mean I will read different articles
and stuff and they talk about like,

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oh, yeah, you need a
mine your data to get the best

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financial decision for your customer. It's
like, well, probably at least a

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third of my customers the best financial
decision they can do is to balance their

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checkbooks. It's like, I don't
really need a big day to tell me

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that. And I think of Adam
Greenland, who's our CFO and spend a

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bunch of time processing all these reports
and identifying different customers. I gave him

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like a top ten list and because
I bet it's these ten, and sure

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enough, that's exactly who it was. Because he was so familiar with the

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data. I think sometimes we lose
sight of just the human that's able to

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process the data on their own,
and then we need to figure out ways

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to process the data in a way
that the human can still be involved in

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it. At the end of the
day, it's a very human centric problem

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as opposed to a problem we're just
going to push over to the machine and

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00:19:37.640 --> 00:19:44.759
have them solve it. Hey,
Sarah buch Here, VP of Consumer Lending

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00:19:44.759 --> 00:19:48.680
at First Federal Bank of Kansas City. A few years back, our executive

319
00:19:48.680 --> 00:19:52.119
team knew we needed to grow our
unsecured personal loan portfolio, so we turned

320
00:19:52.119 --> 00:19:56.640
to Upstart. Three years later,
I am proud to share that we've scaled

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00:19:56.640 --> 00:20:00.720
our loan volume target from five hundred
thousand a month to twelve million a month

322
00:20:00.839 --> 00:20:03.480
and acquired over a thousand new customers. If you want to hear more about

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00:20:03.519 --> 00:20:07.960
our partnership, check out the full
case study on upstart dot Com forward slash

324
00:20:08.079 --> 00:20:15.039
Lenders. Once again, that's Upstart
dot Com Forward slash Lenders. All right,

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00:20:15.559 --> 00:20:18.519
let's get back to the show.
We've talked a lot about chat GPT.

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Are you are you guys deploying any
kind of generative AI be it you

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have any specific use cases for where
you see that's kind of the large language

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model version that's text based, and
of course the other big generative AI space

329
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right now is its image base.
Are you guys looking at any use of

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utilization of any of those tools in
any specific ways or more just kind of

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tinkering and playing at this point,
not in a very formal way. A

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lot of the reasons, you know, we don't want to put a bunch

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of data in there and then have
it be I don't know if there's quite

334
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a business structure around it. That's
all. We'll plus all the audit inspections,

335
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but we're definitely using it for the
things that we would google, you

336
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know, so we would be like
you might Google, like a good email,

337
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descend to so and so for X, Y and Z. Instead put

338
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that in a chat GPT and it
gives you the full letter without any advertising

339
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or pop ups or fear that you're
going to click on the wrong link.

340
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How do you think about what the
line of that is? Because the thing

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I worry about for chat GPT,
and I've told my kids is because now

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I don't think my kids have done
it, but I don't know, but

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I know their friends have where there's
like they're they're putting homework prompts into chat

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CHPT and getting out and they're like, oh, we ddit it before,

345
00:21:30.119 --> 00:21:33.440
Yeah, but didn't right most.
But the interesting thing is it's it's like

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a very good writer, yeah,
but it's not always a good fact checker,

347
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which is to say, sometimes it
writes stuff confidently and well, but

348
00:21:41.960 --> 00:21:45.920
it's wrong and you're right. That's
something like write me a letter to a

349
00:21:45.920 --> 00:21:51.039
customer who X that that tells them
about why you can change the factual and

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accuracies if you ask it, like, you know, at a six year

351
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at a six percent annual rate of
return, how long does it take to

352
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double my money? I don't know
that I trust it to like get that

353
00:22:00.720 --> 00:22:03.839
answer. I got factual stuff is
not there, So I'm curious how you

354
00:22:03.839 --> 00:22:06.640
think about I think that's one of
the reason whole it's never gonna touch finance

355
00:22:06.680 --> 00:22:08.200
because it's wrong about stuff. But
that's very different than like, write me

356
00:22:08.200 --> 00:22:11.799
a letter to a customer in a
you know, in a disaster area that

357
00:22:11.839 --> 00:22:15.119
needs forbearance on their loan to you
know, and that you can imagine that

358
00:22:15.400 --> 00:22:18.799
actually writing a really good thing.
Can you do you have any heuristics for

359
00:22:18.880 --> 00:22:22.519
how you think about the kinds of
problems you would think this is a good

360
00:22:22.519 --> 00:22:25.119
fit to help you solve and those
that you go, h, I'm not.

361
00:22:25.160 --> 00:22:27.200
I don't want to trust a language
model to do the math for me

362
00:22:27.240 --> 00:22:30.240
because it doesn't do very good maths
sometimes. Yeah. Well, I mean

363
00:22:30.920 --> 00:22:34.160
the bank already has, you know, things that can calculate all of those

364
00:22:34.880 --> 00:22:38.039
items. Yeah. Yeah, So, I mean we really don't need another

365
00:22:38.079 --> 00:22:42.720
tool to calculate the financial information for
us. We already have tools that can

366
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do that. Where we struggle is
is is taking those those answers, those

367
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financial and actually get them in a
way that our customers are willing to view

368
00:22:53.160 --> 00:22:56.559
them and see them and listen to
us. Yeah. So I think that's

369
00:22:56.599 --> 00:23:02.119
where chat GPT comes in is here's
my bullet points, here's the financial data.

370
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Write a good message you know that
appeals to a gen Z audience.

371
00:23:07.640 --> 00:23:12.160
Facebook post, Yeah, yeah,
using the prompt to change like we talk

372
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about like the personalization of the message
and the content and emojis in it to

373
00:23:17.000 --> 00:23:21.000
can you know what emoticate? I
don't speak that way, but you know

374
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the young kids do, and so
if you want to reach them on a

375
00:23:22.920 --> 00:23:26.240
level that's really interesting. Can I
tell you my favorite chat GPT instance here

376
00:23:26.240 --> 00:23:30.079
that the funny story about math?
And so there was an instance of chat

377
00:23:30.160 --> 00:23:33.279
GPT and somebody said what is five
plus two and said five plus two a

378
00:23:33.359 --> 00:23:37.359
seven? Says my wife says five
plus two is eight and says your wife

379
00:23:37.400 --> 00:23:40.519
is incorrect five plus two a seven. And then the person says, my

380
00:23:40.599 --> 00:23:44.720
wife is never wrong, and chat
with your wife is correct plus to his

381
00:23:44.799 --> 00:23:48.079
eight. A very smart tool.
It's smarter than I gave it credit for.

382
00:23:48.279 --> 00:23:52.880
But you know, um, you
got to be careful when my wife

383
00:23:52.880 --> 00:23:56.200
actually has taken a couple of college
classes and she has to write papers and

384
00:23:56.559 --> 00:24:00.599
she's using chat GPT in a number
of different ways. So show right out

385
00:24:00.640 --> 00:24:03.640
of prompt and it's way too long, and have chat JPC helper summarize it

386
00:24:03.720 --> 00:24:08.480
and other times helper kind of stretch
out bullet points into a well written essays.

387
00:24:08.519 --> 00:24:12.279
So well, yeah, I think
that's the you know, people think

388
00:24:12.680 --> 00:24:17.559
chat GPT will replace lots of jobs. It will replace some these kinds of

389
00:24:17.960 --> 00:24:21.559
chat particular but large language models.
But I do think the interesting thing is

390
00:24:21.599 --> 00:24:23.039
like how do you get good at
using it? As people said the same

391
00:24:23.039 --> 00:24:26.960
thing about computers and every technology that's
long and calculators, and they did replace

392
00:24:27.000 --> 00:24:30.960
certain jobs, but it was a
people who were effective at using the tool,

393
00:24:30.960 --> 00:24:33.200
who could use Excel well, that
were able to take the most And

394
00:24:33.240 --> 00:24:37.200
so the skill of like how do
I get good at writing a prompt or

395
00:24:37.240 --> 00:24:40.599
figuring out? Hey, chat GPT
can help me generate a bunch of ideas,

396
00:24:40.599 --> 00:24:42.119
but then I've got to take them
and do X or I want to

397
00:24:42.200 --> 00:24:45.920
use it to expand on this point
that I'm kind of stuck on my writing

398
00:24:45.119 --> 00:24:48.680
or structure a thing. But it's
it's not replacing me, it's letting me.

399
00:24:49.039 --> 00:24:52.000
You know, what's the old job
quote A bicycle for the mind.

400
00:24:52.039 --> 00:24:55.279
It's it's helping me accelerate my productivity, and I've gotten good at using it

401
00:24:55.319 --> 00:24:57.000
as a tool. I think that's
going to be an amazing skill to develop

402
00:24:57.000 --> 00:25:00.200
over an imp. And I don't
think it's going to happen overnight. I

403
00:25:00.200 --> 00:25:02.960
mean, like we said before,
I mean this technology takes a long time.

404
00:25:03.079 --> 00:25:06.880
So even if it was ten times
as good as what it is now,

405
00:25:07.799 --> 00:25:11.400
writers are still going to write for
probably at least for our generation,

406
00:25:11.440 --> 00:25:15.480
if not many more to come.
You know, it's it's not gonna be

407
00:25:15.519 --> 00:25:18.759
a like, Okay, we're gonna
fire everyone and replace you a chat GPT.

408
00:25:18.960 --> 00:25:22.200
It's going to be more kind of
bi attrition and you're gonna increase your

409
00:25:22.200 --> 00:25:26.240
workflow. You're gonna be able to
crank out twice as many papers as what

410
00:25:26.240 --> 00:25:27.839
you could before. I did hear
it right, it's a pretty good Seinfeld

411
00:25:27.839 --> 00:25:30.240
episode if you ask for that.
That's like it's a lot of content.

412
00:25:32.440 --> 00:25:37.119
Yeah, George walks into a restaurant. I could figure out what to do.

413
00:25:37.640 --> 00:25:41.839
I wanted to end. We normally
I start this podcast by asking people

414
00:25:41.880 --> 00:25:45.119
about their path into banking, and
we kind of jumped right into we're too

415
00:25:45.160 --> 00:25:48.920
excited about chat GPT whatever. We
would jump right in. But you've had

416
00:25:48.960 --> 00:25:53.960
a particularly interesting path I think into
the into the banking space in one that

417
00:25:55.000 --> 00:25:57.240
I think really highlights the human element
that you're you're talking about with these technologies.

418
00:25:57.240 --> 00:26:00.240
Tell me a little bit about about
how you got your excited. It's

419
00:26:00.480 --> 00:26:06.400
it's a fascinating story. Yeah.
So I I have a undergraduate from a

420
00:26:06.519 --> 00:26:11.039
Quintas College in Grand Rapids in computer
science. You know, so I have

421
00:26:11.119 --> 00:26:15.839
a tech background and worked in tech
for many many years. And then from

422
00:26:15.880 --> 00:26:18.839
there I went on I got my
Master of Arts and Theological Study from Asbury

423
00:26:18.920 --> 00:26:23.240
Theological Seminary. So all I was
down there is working on all their websites

424
00:26:23.240 --> 00:26:29.240
and varying into the tech space,
but reading in depth philosophy, fee and

425
00:26:29.400 --> 00:26:36.680
theology and really enjoyed it. And
then kind of came back home to Michigan

426
00:26:36.720 --> 00:26:41.480
and ended up at Choice One.
So Kelly Pots who I is from the

427
00:26:41.559 --> 00:26:45.720
same small town and grew up with
my parents and I kind of new Choice

428
00:26:45.720 --> 00:26:51.519
one is the small hometown bank in
the small town of Sparta, and end

429
00:26:51.640 --> 00:26:56.319
up working in their customer service center
about ten years ago. So let me

430
00:26:56.359 --> 00:26:59.880
just ask one question about that,
which is, what do you take for

431
00:27:00.200 --> 00:27:03.400
your you know, theological training from
seminary that's applicable to the banking space.

432
00:27:03.519 --> 00:27:07.839
It's such a different area of study
of being in the technology side of banking.

433
00:27:07.880 --> 00:27:11.519
I can imagine what the CS degree
brings, but you know what perspective

434
00:27:11.640 --> 00:27:15.000
or different point of view do you
bring from that theological studies into the work

435
00:27:15.000 --> 00:27:18.359
you do today. I mean,
there's so much. I mean, I

436
00:27:18.400 --> 00:27:21.079
could talk for hours on it,
but I think that if I had to

437
00:27:21.200 --> 00:27:23.920
focus on one thing, it would
be that, I mean, we're all

438
00:27:23.920 --> 00:27:29.480
people, I mean, and people
are interesting creatures. I mean, we

439
00:27:29.559 --> 00:27:33.279
have we make all kinds of mistakes, but then we also do all kinds

440
00:27:33.319 --> 00:27:37.359
of good things. And I think
it's, you know, one of those

441
00:27:37.400 --> 00:27:40.519
that when we look at the numbers, we sometimes you have to remember like,

442
00:27:40.559 --> 00:27:44.759
Okay, these are people behind this
data. And once we do that,

443
00:27:44.799 --> 00:27:49.519
we can approach them better and we
can turn around financial lives and it

444
00:27:49.559 --> 00:27:53.079
makes everything just a little bit easier. I love that. Do you have

445
00:27:53.079 --> 00:27:57.759
any tips on how you help the
organization to I mean, it's it's one

446
00:27:57.759 --> 00:28:00.839
of the things I worry about when
I ended up coming from the technology space

447
00:28:00.839 --> 00:28:06.160
into financial services is with how numbers
oriented. It is, mean, loans

448
00:28:06.200 --> 00:28:11.200
deposits, ratios, right interest rates, deltas, spread your nettedge whatever you

449
00:28:11.240 --> 00:28:15.839
can get in this world where you
lose sight of the human beings behind the

450
00:28:15.880 --> 00:28:18.720
numbers and you optimize the business.
You've got knowledge. And there's a great

451
00:28:18.799 --> 00:28:22.400
article about someone at the credit card
Visit, a large credit card credit card

452
00:28:22.440 --> 00:28:26.160
bank, who felt, I got
a couple of years in it was like

453
00:28:26.160 --> 00:28:29.039
a McKenzie project for them, and
they were dialing the numbers to optimize and

454
00:28:29.039 --> 00:28:32.599
they were really getting people in debt
that they couldn't repay and like, and

455
00:28:32.720 --> 00:28:36.880
you lose sight of the impact of
those decisions on that people, particularly as

456
00:28:36.880 --> 00:28:40.839
you get removed from being a frontline
employee, right. And I love that

457
00:28:40.880 --> 00:28:44.200
perspective, but I'm curious if you
have any advice on how you help the

458
00:28:44.279 --> 00:28:48.920
organization or the people who have less
customer facing experience kind of maintain front and

459
00:28:48.920 --> 00:28:52.799
center that perspective of the human nature
of the products and the people that we're

460
00:28:52.799 --> 00:28:56.079
serving and the import of these decisions
on my livesty. I feel like for

461
00:28:56.119 --> 00:28:59.640
me, I've always worried about losing
sight of that and optimizing something that made

462
00:28:59.640 --> 00:29:02.079
the business look great and then you
woke up on more Oh my god.

463
00:29:02.119 --> 00:29:04.200
I've been like I've been hurting people
about making this decision in a way that

464
00:29:04.200 --> 00:29:07.640
I shouldn't have and I didn't even
realize it. Yeah, I think back

465
00:29:07.680 --> 00:29:12.680
to it was right before one of
the first panel discussions it was ever on,

466
00:29:12.839 --> 00:29:15.400
and I was talking with my uncle, you know, Keith Brophy,

467
00:29:15.559 --> 00:29:18.440
and he was I kind of asking
him like, hey, do you have

468
00:29:18.480 --> 00:29:22.200
any advice you know, like for
when I sat on this panel discussion.

469
00:29:22.559 --> 00:29:25.960
He's like, Tim, like,
you can memorize as many facts and figures

470
00:29:26.000 --> 00:29:27.839
as you want. You can talk
about all the statistics, but what people

471
00:29:27.880 --> 00:29:30.240
are going to remember at the end
of the day is the stories you share.

472
00:29:30.839 --> 00:29:34.599
So he goes the more that you
can tie whatever big point you want

473
00:29:34.599 --> 00:29:40.640
to get across and tie that to
a story that's gonna help stick in people's

474
00:29:40.680 --> 00:29:45.039
minds. And I think we can
do the same thing at the banks that

475
00:29:45.079 --> 00:29:48.119
we work at, where it's like, Okay, if we want to try

476
00:29:48.160 --> 00:29:51.880
to do this and improve financial lives
this way, well, let's share ways

477
00:29:51.960 --> 00:29:56.880
where we actually improve financial lives.
Let's share kind of our wins and successes

478
00:29:56.880 --> 00:30:02.599
on a very kind of human personal
level as opposed to just we increased X

479
00:30:02.640 --> 00:30:06.480
by ten percent. Interesting, Yeah, the story is thing really resonates with

480
00:30:06.519 --> 00:30:10.799
me because I do think we are
at the core storytelling creature. We remember

481
00:30:10.839 --> 00:30:15.200
things that way, and so I
often love in um in my slides,

482
00:30:15.400 --> 00:30:18.519
like having single visuals that tie to
stories as opposed to fifteen bullet points,

483
00:30:18.519 --> 00:30:22.200
because if you'll people remember one thing, like tell them the story with a

484
00:30:22.279 --> 00:30:26.119
visual, they remember and they're more
likely to like take that message home and

485
00:30:26.200 --> 00:30:29.680
resonate and remember it than like this
was a slide with six bullet points each

486
00:30:29.680 --> 00:30:33.440
with twenty words. I have no
deal with that slide where I've forgotten,

487
00:30:33.440 --> 00:30:37.599
but like a good story and a
visual to stick in the brain and they

488
00:30:37.599 --> 00:30:41.519
can change your perspective and change your
behavior. All right, Tim, I

489
00:30:41.559 --> 00:30:44.480
got three questions I ask everybody at
the end of this podcast, and unfortunately

490
00:30:44.519 --> 00:30:47.240
my clocks is about thirty minutes are
gone, so it's it's time for us

491
00:30:47.279 --> 00:30:51.279
to drive through them. Um,
and those are first. What's the best

492
00:30:51.279 --> 00:30:56.039
piece of career advice you've ever gotten? Probably the best piece of career advice?

493
00:30:56.759 --> 00:31:00.400
Yeah, really, just try your
best And I got that from both

494
00:31:00.400 --> 00:31:06.279
of my parents of just give forth
your best effort and uh and try your

495
00:31:06.279 --> 00:31:11.440
hardest. How did they impart as
a as a father of children teenagers in

496
00:31:11.480 --> 00:31:15.000
the less, how did they convince
you of the truth of the wisdom of

497
00:31:15.000 --> 00:31:19.119
that perspective at a younger age.
Yeah, really, it's just through practice,

498
00:31:19.200 --> 00:31:22.880
you know. So my mom is
a township treasurer, so really into

499
00:31:22.920 --> 00:31:29.319
the numbers and everything, but very
much into uh, serving her community in

500
00:31:29.319 --> 00:31:33.319
that sense of civic duty. My
dad's a number of different jobs and uh,

501
00:31:33.359 --> 00:31:40.240
you know, from everything from a
plant manager at a large international shoe

502
00:31:40.279 --> 00:31:45.599
factory to h Now he's currently a
living statue. Yea, So he's internationally

503
00:31:45.640 --> 00:31:52.279
renowned living statue, goes around travels
the world in living statue competitions. But

504
00:31:53.359 --> 00:31:56.759
I didn't know that we're living statue. You can be a competitive living statue.

505
00:31:57.039 --> 00:32:00.480
Oh yeah, yeah, yeah,
he does it. It's really big

506
00:32:00.480 --> 00:32:05.799
in Europe, but I mean he
does it and Mackinaw City and kind of

507
00:32:05.799 --> 00:32:08.519
all over. But he uh,
just seeing the passion that he has for

508
00:32:08.599 --> 00:32:13.519
that and kind of any job that
he's ever had, he has passion forward

509
00:32:13.559 --> 00:32:15.480
and just drives his best at it. So put your best foot forward,

510
00:32:15.920 --> 00:32:20.480
love it. Second question, what's
the best piece of advice you've gotten about

511
00:32:20.480 --> 00:32:23.640
the consumer banking or consumer lending industry
as a whole. Yeah, I think

512
00:32:23.680 --> 00:32:28.640
going back to what my you know, uncle said about telling a story.

513
00:32:28.559 --> 00:32:31.400
You know, that's really helped me. So trying to find other people's stories,

514
00:32:31.400 --> 00:32:35.920
trying to put a story to whatever, you know, trying to do,

515
00:32:36.960 --> 00:32:38.640
put a story behind whatever you're trying
to do. All right? And

516
00:32:39.240 --> 00:32:42.880
final question, what's one bold prediction? If I feel like we've cared a

517
00:32:42.880 --> 00:32:45.559
lot of ground for bold predictions,
but I always like one bold prediction and

518
00:32:45.599 --> 00:32:47.160
we can bring you back and hold
your feet to the fire. So give

519
00:32:47.200 --> 00:32:51.839
me one bold prediction for the future. Yeah, if I had to do

520
00:32:51.960 --> 00:32:55.960
one bold one, I would say
within ten years. So it's a longer

521
00:32:57.400 --> 00:33:01.480
timeline, but within ten years there'll
be much more virtual reality, especially in

522
00:33:01.519 --> 00:33:07.240
a business environment. You're a virtual
reality okay, ten years virtual? Have

523
00:33:07.240 --> 00:33:10.839
you have you played with the meta
whatever, the quest whatever they call it,

524
00:33:10.880 --> 00:33:14.640
pro and all the different sides.
Have you have you used them and

525
00:33:14.640 --> 00:33:16.759
you found what are the most compelling
use cases you found for how they're being

526
00:33:16.799 --> 00:33:20.400
utilized to day or what do you
see that being used for. Yeah?

527
00:33:20.519 --> 00:33:22.799
I don't actually use my Oculus two
nearly as much as I used to because

528
00:33:22.880 --> 00:33:29.279
my son, he was eleven soon
to be twelve next Wednesday, is constantly

529
00:33:29.279 --> 00:33:32.160
on Guerrilla Tag, so he's swinging
his arms all around him in a virtual

530
00:33:32.200 --> 00:33:37.279
world, enjoying it. But for
me, the biggest use case I saw

531
00:33:37.319 --> 00:33:40.160
where I was in the light bulb
went off is I put on the I

532
00:33:40.200 --> 00:33:44.039
had my laptop in front of me, and I put on the headset,

533
00:33:44.680 --> 00:33:51.200
and all of a sudden, I
had a huge, like forty foot computer

534
00:33:51.279 --> 00:33:53.440
screen. And at that point I
kind of realized, like, Okay,

535
00:33:53.519 --> 00:33:57.119
this is this is how it will
change, is once you get into the

536
00:33:57.200 --> 00:34:01.279
business world and you have like an
augmented reality environment where instead of having a

537
00:34:01.319 --> 00:34:06.960
computer monitor, you have five different
computer monitors whatever size you want, and

538
00:34:07.160 --> 00:34:09.800
all the visualizations around you. I've
heard that use case. I've heard that

539
00:34:09.840 --> 00:34:15.039
the virtual reality meetings for people who
aren't there are actually very compelling. The

540
00:34:15.079 --> 00:34:19.440
integration. I think Microsoft Teams has
some integrations with the latest Oculus release,

541
00:34:19.519 --> 00:34:22.920
and they're supposed to be pretty compelling. I've not tried them myself, but

542
00:34:22.960 --> 00:34:27.000
I do hear that. Yeah,
all right, so bold prediction on VR

543
00:34:27.000 --> 00:34:28.920
in the future, But you gave
me a ten year time horizon, so

544
00:34:28.920 --> 00:34:30.159
I don't know if this podcast will
be I don't know if podcasts will be

545
00:34:30.239 --> 00:34:35.000
round. This podcast will be round
ten years. Maybe you'll find an interim

546
00:34:35.039 --> 00:34:37.440
period before ten years to check in
on how that one's doing. But Tim,

547
00:34:37.480 --> 00:34:40.000
thanks so much for joining me today. I appreciate all your perspectives.

548
00:34:40.039 --> 00:34:45.559
This is a lot of fun.
Yeah, thank you. Up Start partners

549
00:34:45.559 --> 00:34:49.960
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grow their consumer loan portfolios and deliver a

550
00:34:50.000 --> 00:34:54.599
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551
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552
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555
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556
00:35:22.480 --> 00:35:28.480
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557
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559
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560
00:35:42.840 --> 00:35:47.119
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561
00:35:47.280 --> 00:35:53.039
dash banks. That's upstart dot com
slash four dash banks. You've been listening

562
00:35:53.039 --> 00:35:57.920
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563
00:35:58.000 --> 00:36:01.440
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564
00:36:01.480 --> 00:36:05.840
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565
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