Dec. 11, 2024
Evolving the Playbook: Tech, AI, and Customer-Centric Lending
In banking, yesterday’s touchdowns don’t win today’s games. A great product is just the start — constant evolution is key to meeting ever-changing customer needs.
In today’s episode, host Matt Snow sits down with Rhett Roberts, CEO and Co-Founder of LoanPro, for an in-depth look at the modern financial landscape. Rhett shares key insights from the recent Money 2020 event in Las Vegas, covering everything from AI’s growing role in financial services to the critical shift toward customer-centric lending. Together, they explore how small lenders can embrace tech modernization, the importance of proactive customer service, and the far-reaching effects of regulatory changes on the industry.
Join us as we discuss:
- Why small lenders should prioritize exceptional, cost-effective customer experiences over geographical reach.
- How AI and generative tech are transforming financial services, enhancing efficiency and compliance beyond traditional CRMs.
- The urgent need for financial institutions to modernize their tech to meet customer expectations and leverage open banking.
WEBVTT
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You are listening to Leaders in Lending from Upstart, a
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podcast dedicated to helping consumer lenders grow their programs and
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improve their product offerings. Each week, here, decision makers in
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the finance industry offer insights into the future of the
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lending industry, best practices around digital transformation, and more. Let's
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get into the show.
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Welcome to another episode of Leaders in Lending. I'm your
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host this episode, Matt Snow, joined by HTT Robert, CEO
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and co founder of loan pro Rett Thanks for joining.
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Me, Matt, Thanks for having me.
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Yeah, yeah, good to catch up and I know we're
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in similar industries. A lot we could cover here. I'm
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really curious knowing that you were just at Money twenty
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twenty and maybe give a little bit of an update
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on what you came away learning from there. What were
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the topics, what did people care about, and kind of
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questions you got there.
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Yeah, it's great event. So last week in Las Vegas
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was another year of Money twenty time and it was
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wild as always, right, there's just so many people in town,
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very very efficient. I brought a little bit of an
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army of my team down and we held hundreds, plural
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hundreds of meetings and they were with a lot of
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great individuals and helped progress many deals and opportunities. So
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we love that it's a very efficient time to go
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through and meet with folks, and I think others of
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view it the same way. There's a couple of themes
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that came out. Had the opportunity one of the sessions
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that I was speaking on stage with, and there was
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other things kind of going around the halls and talking
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to different people and seeing different themes.
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But there was a few things.
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Obviously, there was some talk of AI, and that's to
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be expected. It was one of the themes of conversation
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about What was interesting is there was sort of two camps,
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right There was a camp that AI is under hyped,
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in a different camp that it's being overhyped. So it's
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very interesting to see both of that and see what's
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going to happen with AI. And generally there's consensus on
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the strategies of employing AI within an organization of how
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do you do that right? Take over repeatable tasks, so
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lots of things around regulation, lots of things around some
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optimization and then sort of move up the value stream.
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And so we're seeing that there was talk a lot
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about like evolution of payments. Payments was a big topic
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as well, in particular as payments have got faster and faster,
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lots of things around fraud, and the two that we
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might not expect is there was a considerable amount of
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conversation about winning the customer. And so in the panel
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or the discussion that I led, we had a couple
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of folks come up on stage. We talked about the
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lending and financial services, the history of how a financial
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institution gauges and what's the hook to catch the customer.
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And we've seen a few hooks over the years. They
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could be like if you get the deposit account, that
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turns into the relationship builder, and then that brings over
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the accounts that the various lending products, and that's how
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it used to be looked at in the past, but
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it's sort of flipped on its head that now the
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hooks are looking to be much more bespoke and custom
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lending products are the hook to get to win the customer,
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and there's lots of studies that show once you capture
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them on a unique lending product, then you can increase deposits.
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So that works for our friends at the various depositories,
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and another topic about issuing innovation. So I think on
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a credit card, lots of stuff has happened over the
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last decade or so on. We could talk to quite
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a few of them actually on innovation on the acquiring side.
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Some pretty cool stuff really and one of the big
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conversation points that we bring to the table at Loan
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Pro but others we had conversations with as well. The
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focus that we're doing on issuing innovation and these something
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we call transaction level credit, this idea of these unique
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lending products within the credit card itself. So a couple
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of topics, but it was a great event. We're happy
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we went great.
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Sounds like you had a very productive event. I know
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a lot can happen there. You covered a lot of
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topics there. I'm not even sure where to go to
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start from all of those. But you know, we don't
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usually get through a podcast without talking about AI. You
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may have been the earliest to mention it, maybe eighty
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seconds in. And I have heard a lot on the
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overhype side, But I'm curious on the under hype side,
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what's the camp there, Like, what's the viewpoint? Are there
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certain use cases or things where maybe we're not focused
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enough or not taking advantage of some of this Technology's
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what's the contrarian view on the underhepe. Yeah, it's a great.
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Question, you know. So there it's I think everybody's read
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the ecosystem in a fairly similar way, right, lots of
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excitement in the earliest days of well, I can't even
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call them the earliest days. There's been some vocabulary changes
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of what AI definition is over time as well. But
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let's go back just a couple of years. Lots of
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excitement about generative AI in particular, and then it's sort
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of like HM fizzled for a little bit of maybe
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it's a little early think of playing with chat, GPT
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or other tools that you played with. They call it
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hallucinating where it'll just like make stuff up basically, and
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so that's kind of dampered some of the excitement. But
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what I started to see this view and this conversation,
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multiple conversations I was part of, is think of playing
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with chat GPT, and it's generally correct on the structure,
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Like you asked, ask it whatever question, and it gives
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you a very thoughtful structure back in the answer. Now
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we're just working on the actual content inside of that structure.
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But the structure by itself is extremely useful. So you know,
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give me a template form that blah blah blah, and
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it gives you one and now you know what should
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you should answer. And so as long as you're not
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in a world of like a copy and paste, but
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if you're operating in a world of like, oh, let
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me accelerate design. So we've done some really interesting things.
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Had some conversations about helping our customers using some different
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tools on writing rules within our platform around compliance, or
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in helping them build eachtmail templates or maybe even queries
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into the data sets, and this just speeds things up
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for them quite a bit. So on the under hyped,
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which is maybe what you were referring to as what's
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that talk track, it's usually coming from an organization who
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keeping some of the conversations anonymous. Yet it's an organization
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who's already employed it and it was much more successful
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than they thought. There's some costs takeout, but there's also
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just a huge amount of efficiencies within how fast they
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can get provide customer support or how consistent they can
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provide the right answers. Back to the folks that they're
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engaging with and we even see some folks using generative
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AI to start eroting what used to be viewed as
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a very sticky product like a salesforce and other things.
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They're using generative AI to actually build some of those
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tools within their own orgs. So there's a bit of
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that conversation as well. So it is interesting how it's
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a barbell, right. It's like, hey, it's way over hyped, like,
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don't worry about it, it's just a new label for
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machine learning. And then there's the opposite end of like, no,
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this is like a game changer and we're not giving
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it enough attention.
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I like the way decompose that in the structure and
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the contents helped me frame where I've seen the successes too,
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and I think, like I said, the automation efficiencies, those
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things can be huge wins. I saw maybe it was
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in Google's earnings or a press release recently they said
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twenty five or thirty percent of their code is now
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AI generated or enabled. So those things that speed up
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the monotonous, more mundane task. I think huge opportunities exist there.
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And it's particularly interesting and financial services. Financial services have
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a reputation to be slow to adopt to new technologies,
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in part because of the increased scrutiny of regulation, and
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we'll call them layers of regulation for the audience. When
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I was in elementary school, it's probably for most of us,
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the way they did classes, the way that they were
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presented with an overhead projector. Did you have those, Matt, Yeah?
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Did I remember the marketing though.
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I actually bought an overhead projector like two years ago
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at a garage cell for one dollar, and my kids like,
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what is this thing? I was like, Oh, let's get
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there at any rate. I like this visual of an
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overhead projector and then you put the paper on and
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if you do multiple layers there you get some version
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of a Venn diagram being projected up on the wall.
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And I like that visual because we see a lot
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of the regulations changing, right, and a regulator has they
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have a consistent objective whether they're trying to achieve, but
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depending on a whole bunch of factors, including who is
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the human, is the strategy working or not? Both a
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proactive and a reactive strategies to what's happening in the marketplaces,
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the tactics of how they go about and trying to
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achieve the consistent objective changes, and so that means rules
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change and they adjust and so forth. And so if
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you think of the each one, each rule as a
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different layer of this overhead projector this then gives you
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like a tapestry of the climate that we're oper reading in.
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And one of the reasons that financial services have been
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a little bit slow to adapt of using new technology
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is because it's sort of like a checkerboard of compliance.
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There's like all over the place, if that's a geography checkerboard,
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if it's where your license is at, and so forth,
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and so it gets complicated. And what we're finding is
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some opportunities with the generative AI is it can help
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make sure there's more consistency in how engagements work. And
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that's a lot of the things that get audited. Think
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of when an examiner comes into a depository for their
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annual examination, they want to get a sample set of
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show me so many of these kinds of things, right,
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show many loans and deposits, these kinds of transactions, and
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to show me basically that you're coloring within the lines
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of the sample set that they select, and having a
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tool that will always color within the lines is proving
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to be exceptionally valuable from a compliance side of things,
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but also from a consistency side. Think of like a
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favorite fast food restaurant, go to McDonald's, right, one of
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their keys of success is consistency, and so getting some
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financial services regularly have a consistency, and that these tools
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are helping unlock.
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That, Yeah, I couldn't agree more. I know we could
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go pretty deep on that side as well. I think
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you spoke recently with our chief risk officer, Andy Delgado
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at a conference recently, and I don't know when this
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will air, but you know we talked earlier. It's it's
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election day here in the US, so that regulatory environment
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could get a lot more complex in we don't know
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in which direction yet still, so maybe we can do
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a follow up afterwards and see what happens, but it'll
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be fascinating.
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Rights. So, I've got a lot of friends, know a
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ton of folks in the regulatory space, and I think
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it's important to highlight that the objectives of the regulators
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seem to be very consistent. They're trying to achieve, but
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achieve like you know, if it's a certain inflation or
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to manage what the inflation rate is soundness that safety
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and soundness like there's like consistency in the objective, but
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the strategy about how to achieve that objective seems like
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it's there's a high probability it will change based off
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of what this regulation or excuse me, based off what
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happens with the election, because there's two fairly opposing perspectives.
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If that's going to be things around how a partner
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make model works, if that's things around like the concentration
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in big banks versus community banks, if you know, and
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you can go on and on, but there seems to
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be some strategy differences about how do you go about
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achieving an agreed upon objective?
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Yeah, and I want to use this maybe to pivot
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back to one of your money twenty twenty topics because
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with the open banking regulation and perspectives that are coming
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out now, it's really changed the way I've thought about,
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you know, winning the customer as you said it, or
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like what what does it take to win a customer?
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Especially in financial services? So maybe I don't know, you
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can use open banking if you want to jump into that,
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or were there other things when you think about winning
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the customer, like who differentiates, how do financial services companies
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win or who's going to be the succeed or twenty
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thirty forty years now.
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Is a great question. So Open Banking has done something
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that's pretty interesting. Obviously, the recent rule final rules, they
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always call them final, but there seems to be multiple
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versions of final. So Final Rules of ten thirty three
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about basically unlocking who owns the consumer data and how
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portable is that consumer data. And with this portability, it
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