Sept. 4, 2024

Small Steps, Big Gains: Scaling Success with AI in Credit Unions in 2024

Small Steps, Big Gains: Scaling Success with AI in Credit Unions in 2024
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Like many institutions, credit unions can't afford to be left behind in the race to adapt to the new AI-driven technological landscape. But successfully and responsibly leveraging AI goes beyond adopting AI solutions for the sake of checking off a box—it involves identifying opportunities to collaborate with seasoned partners who can help solve the problems that AI is equipped to solve.

This week’s episode features a conversation with Upstart Senior Account Managers Barry Roach and Drew Megrey, which originally took place on an episode of The CU Lab. Barry and Drew outline the crucial role of a strong digital and AI strategy in helping credit unions tackle issues like liquidity restraints and regulatory hurdles—and they explore how strategic AI adoption can help credit unions not just keep up, but lead the way.

Join us as we discuss:

  • The importance of transparency and education in forming successful partnerships between AI providers and credit unions
  • Starting small and involving all teams for successful scaling
  • The benefits of AI in underwriting, including better risk prediction and higher approval rates
  • How Upstart’s "Recognized Customer Personalization" feature helps credit unions identify potential borrowers more efficiently
WEBVTT

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You're listening to Leaders in Lending from Upstart, a podcast

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dedicated to helping consumer lenders grow their programs and improve

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their product offerings. Each week, here, decision makers in the

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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

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the show.

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Hello and welcome to Leaders in Lending. I'm your host,

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Drew Megory, and this week's episode is a special reairing

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of a conversation originally featured on America's Credit Unions podcast,

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The SeeU Lab, where Barry Roach and I dive into

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how credit unions can win. In twenty twenty four, we

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talk about how AI and fintech partnerships can help institutions

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tackle challenges such as liquidity constraints and keeping up with

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ongoing regulatory hurdles, to name a few. With that said,

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I hope you enjoy this week's show.

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Hello, and thank you for joining us for another episode

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of the CEU Lab. I'm modeling Crownfeld with America's Credit

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Union and I'll be your moderator.

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Today.

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I'm sitting down with Barry Roach and Drew Magrie, senior

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account managers at Upstart, and we're going to discuss how

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credit unions can win in twenty twenty four. Barry Drew,

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it's great speaking with you, and thank you so much

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for joining us today.

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Thanks having to me, great to be here. Great.

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Well, let's start with just a little more information about

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your roles at Upstart.

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Thanks Malan. I'm Barry Roach. I'm a senior account manager

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here at Upstart. I've been with uptur for about eighteen months,

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but prior to my time with Upstart, I was CEO

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of two different credit unis in California for about ten

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years and have about twenty years total in the credit

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union industry. So very familiar with the challenges that we

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have in credit unis and happy to be here to

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talk about that a little bit today. True.

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Yeah, thanks Barry. So I've been with Upstart, coming up

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on almost three years now, but prior to Upstart, I

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started my career in the financial service industry about fifteen

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sixteen years or so, where I actually started in the

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insurance business and then quickly transitioned into the regional banks

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where I worked in multiple areas that pertain to consumer

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lending in some form of a capacity. After about five

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or six years of doing that regional bank space thing,

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I wanted to get out and about and check out

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this credit union space that I heard so much about.

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And I was fortunate enough to lead the Ohio Teamsters

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credit Union for just shy of nine years as president

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and CEO before coming to Upstart to help build up

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the account management team's focus in partnering with credit unions.

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Going back to your initial ask of what does the

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account management function entail here at Upstart is we do

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have a dedicated team made up of prior executives both

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in credit unions and in banks, and you can kind

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of think of as our function as like an ongoing

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post sales support as this is not, of course the

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setate and forget a business. And what we really strive

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to do is own the executive relationship with our partners

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and almost act as if we're an extension of their

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organization to give this more of a partnership feel rather

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than just another vendor type of feel. And where this

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helps is because of course, to what Barry and I

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have already talked about as we've sat in those chairs

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and we have done the work of the people that

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we work with on a day over day basis, and

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this helps because our team is able to provide positive

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insights to their programs to assist in meeting strategic goals

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and objectives as part of our partnership. But they can

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also leverage our partnership to augment other key initiatives within

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their organization that they may be trying to fulfill as

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part of their business plans throughout the current state and

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in future years ahead.

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Great well as past credit union CEOs, you both have

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a very unique perspective on this, So could you speak

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about some of the challenges that credit unions are facing

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in today's environment?

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Sure, thank you, Madlin, So Drew and I speak to

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executives from across the country on a daily basis, and

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for the most part, there are less regional differences in

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terms of the challenges than there are sort of right

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across the country. Everyone has liquidity concerns, certainly maybe not

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as bad today as it was in early twenty twenty three.

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We're hearing less and less about concerns about liquidity and

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more about as the positive come back, as investments have

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run off and now looking for reinvestment opportunities, where's a

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good place to put that money you hold it or

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do you invest it in sort of higher yielding assets

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right now? And I mean we've seen in the learning

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space now yields as high as they've been in since

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before the Great Financial Crisis. So with that, that's great

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learn income coming in. Well, what about credit quality, because

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we have seen sort across the country certain degradation in

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credit really in all astic life and across the spectrum

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of risk, though not just subprime performing or underperforming as

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big maybe, but also for the prime space. We've seen

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through data from our partnership trained being, for example, a

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little bit of stress for all borrowards out there right

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now through anything you could add from what I've heard

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from some of my lending departments.

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Yeah, one thing to kind of touch off that whole

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credit risk and defaults rising, right, everybody knows that the

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personal savings rate continues to drop, defaults trying to rise

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across all asset classes. And we have this new thing

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as of December called CECIL and how to manage those

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methodologies at a really odd time, right, so being able

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to predict risk and look at what those ongoing trends

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are across all assets in comparison to what the defaults

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are doing I've heard a lot of chatter around the

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challenge of how to formulate an accurate cecil methodology, and

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as a result, informing those methodologies, it's taken a hit

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to some credit unions across the country from a net

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income perspective. So that's another one that I'll add around

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around credit risk for sure.

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And of course there's always the competitive risk, right, so

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all credit nis are trying to remain viable for their

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membership and to attract new members as well, and so

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you have to have nowadays not just a great brand

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footprint and a great experience when members are walking into branches,

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but digital footprint is very important as well in that

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digital experience. So, especially through Upstart, a lot of what

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we do is to help introduce those brand new borders

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who are now becoming members of credit unis with a nice,

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elegant digital experience when it first applied for loans through

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the Upstart platform. So that's just one example of those

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competitive stresses. But also now AI AI has become this

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new buzzword and now you know, boards are saying, well,

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tell me about your AI strategy. It's like, well, what

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is AI? You know, we have a lot of crediting

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executives are struggling with perhaps understanding not only what AI is,

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but not necessarily understanding how AI can help their business

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and help move their crediting forward in terms of a

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much better value proposition for their membership. One thing up

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there does do around AI is that is key in

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how we perform our underwritings. So we've been using our

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digital intelligence machine learning for years now and with AI

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and with training data, the more data and the more

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time you have, the more accurate both predictions can be.

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So both Drew and I have found I think that

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just providing that for our blending partners has been a

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great help for them in not just sort of knowing

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how ay I can help the business, but actually leveraging

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it and having a fancible impact on their business.

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Another thing I'll add to on a side of just

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AI and of course cost of funds and liquidity and

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all this fun stuff is the increasing regulatory environment is

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another challenge that I've heard too, and the cost associated

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with it too. Like you go through an NSU exam,

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seet PB exam, I don't know what the asset size

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of the listeners are. The multitude of different things that

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are needed to be done from a regulatory and compliance

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perspective have elevated in the past two three years to

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the point where you're having to add additional fte within

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your organization to adhere to those regulatory requirements. And that's

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been another real key challenge in the credit union space

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in the past few years.

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Yeah, I think those are some challenges that we've been

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hearing kind of across the board. But let's take in

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a little bit more and address AI and how that

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can really help in the face of some of these challenges.

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Yeah, I'll start here, and I'll preface that the Upstart

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crew did have some boots on the ground last week

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at acus CEO's conference in Key West, and the general consensus,

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outside of some of the stuff that we've already outlined,

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is really two things. Is credit unions, even though they're

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very widely known across the country, they continue to struggle

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with providing what their identity is and getting the word

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out within their communities of what is the value that

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credit unions possess. And then the second, as a result

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of that conversation, the credit union consolidation could be coming.

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We once had ten thousand credit unions in the country.

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Now down to five thousand. Don't quote me ONCT the

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exact number, but somewhere in that realm. And this is

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in large part due to the struggles to manage again

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those inatory requirements, the cost associated with that. You're competing

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with the Chase, the Wells, Spargos, the Bank of Americas,

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and as a result, some of that profitability is going away.

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So to your point about how AI can address some

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of these challenges already outlined, is I'm going to go

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through kind of like three key themes of things that

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we hear and things that we talk about here at Upstart,

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and one of those themes is going to be innovation innovation,

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and I'm going to start it around the thought of

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automation less human interaction. Consumers today do not want to

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talk to an individual and a branch as much as

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they would like to click some buttons on their phone,

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their tablet, their computer, what have you, and not have

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that human interaction and have that fully automated experience. To

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give you some numbers, for instance, just on the Upstart platform,

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of the borrowers that come through the top of our

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funnel and apply for a loan and get funded, ninety

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percent of those individuals are going through a fully automated

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experience and then fast forward from another thought process of innovation,

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it creates an elevated member experience. You want to serve

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your member base, you want to serve your net new

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members that you could be obtaining through partner channels or

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even within your own internal type of rails, of ways

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to promote products to your membership, and that elevated member

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experience giving them real time decisions whether they're good bad

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from the comfort of their own home. It allows that

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member experience to be elevated for them to come back

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to you for additional needs that they may have. Going

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back to the theme of credit risk or economic uncertainty, things

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could of course change month over month based on what

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we're seeing in some of the data, but it's been

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proven that the use of AI for decisioning loans particularly

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that's our general scope of what we do here at upstart,

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is it is a better predictor of default. It's a

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better predictor of risk in comparison to using traditional underwriting

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methods that maybe wouldn't allow for an approval of a

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member on your internal policy and procedure. I'll give some

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some statistics here too is for Upstart particularly, our model

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is about three times better at separating risk between the

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highest and lowest Fyco bands, which again goes back to

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being able to say yes to more borrowers. And an

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example of that is someone that has a six forty

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FICO grade may qualify for some form of loan within

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your institution, but the actual probability of that individual of

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defaulting may only be let's say fifty basis points. So

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being able to price that accurately and predict that risk

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accurately allows you to play in that lower tier of

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Fyco borrowers within your organization. And then the last kind

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of key theme that I'll address is is competition and cost.

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I talked a little bit already about the competition in

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comparison to the larger banks, but you're also competing with

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that potential credit union consolidation revolution. You're competing with the

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ten billion plus credit unions or the top twenty five

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that are able to reach a broader range of members

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and build their businesses, and you're only able to adhere

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to your existing field of membership, which might be smaller

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in nature. So using AI under multiple platforms, not just

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in lending, can allow your organization to really be one

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with the times and better compete across the financial service ecosystem.

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Hey there, former host Jeff Kelner here to let you

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know about an exciting opportunity to strengthen your understanding of

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artificial intelligence and financial services. If you want to better

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slash AI Certification. Thanks, and now back to the show.

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To add to what through was saying, we just entered

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a new feed thure within ubserve. We call it recognized

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Customer Personalization the fancy long term. Basically, all it means

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is it's a method for upsearch to identify borrowers on

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our platform who belong to our partner credit unions right

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at the beginning of the application, so we can drive

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those applications to our lending partners in a much more

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efficient and faster way. And it's increasing the cross sell

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now for those members and bring a better relationship for

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that crediting member. So that's a new feature that's coming

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in and this kind of illustrates a lot of the

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innovation that Upstart is doing. We're not just an AI

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lending company. We're constantly trying to find ways so we

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can better support our lending partners and new lending partners

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coming on board all the time.

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Yeah, I mean, just that line about being able to

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say yes to more borrowers, I think that's crucial to

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the credit unions that you're working with. Being able to

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better serve their members is really critical. So well as

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you know the credit union space, it's really collaborative. Peers

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are learning directly from one another. Do you have some

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examples of partners that you're working with who are really

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successfully addressing these challenges.

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I can say that I've got a couple of newer

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lending partners who came to ups are not just looking

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for ways that they can improve their lending capability and

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certainly add some good quality high yielding loans in their books,

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but they're also looking for how can I expand my membership?

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So field and membership is different amongst all credit ings,

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and some are more successful at leveraging. They're larger charters,

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they're larger field of membership than others. What ups are

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can do is actually almost on a turn can debate

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to provide new members for those creditings that are coming

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in markets that maybe they're not they're not a lot

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of active in so my old crediting and others I've

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spoken to, for the most part, those marketing activities are

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centered around their market where there's a brand footprint. However,

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they may have other need the other states of other

283
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areas of the country where they have the ability to

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onboard new members but just haven't really realized an effective

285
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marketing spend in those markets. And I'll start confind borrowers

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in those markets, deliver them to these creditings as new members,

287
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and now it gives you an app back to be

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able to get that second and third product service from

289
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that brand new member and really establishing strength in that

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relationship from there.

291
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Yeah, I'll give a more seasoned example without naming names,

292
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but we have a partner about two and a half

293
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billion or so in assets that's been leveraging our platform

294
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for about two years now. Of course, their CFO has

295
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that l word of liquidity being top of mind and

296
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almost all of twenty twenty three, but coming into twenty

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twenty four, without giving exact dollar amounts, they increased their

298
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monthly capital with us to of course drive the higher

299
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yields right with it being a performing asset within expectations,

300
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they were able to utilize the higher yielding asset to

301
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augment their high cost of funds to retain their share

302
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accounts and their certificates, a deposit that we're starting to

303
00:16:06.480 --> 00:16:08.960
run off in the first quarter of this year. So

304
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they're with leveraging our program with increased capital in the

305
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twenty twenty four This also allows to Bury's point of

306
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how our program works, allows them to originate more net

307
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new members in growing their member base, and then they're

308
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doing a very very good job on the back end

309
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of providing cross sell opportunities. And some metrics here again

310
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is they're seeing roughly a twelve to fifteen orsh or

311
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so percent conversion rate on secondary products outside of just

312
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the unsecured personnel that they're obtaining from upstart and of

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course the opening of the share account, and they've been

314
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seeing success on that across multiple different assets, not just

315
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credit cards and autos, but they've seen some helock, they've

316
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seen some deposit growth in cross sell too, So they're

317
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doing very successful and of course increased capital, using that

318
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yield to offset their cost of funds and then getting

319
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that net new member and expanding that net new member

320
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experience and being able to deliver multiple product across the

321
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product offerings. Right.

322
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So, you know, as Drew says, we are an extension

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of the leadership team. We're not just dealing with the

324
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lending folks in credit unions or finance folks. We're also

325
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dealing with the marketing people and think about the opportunities

326
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to provide for marketing. You can ab test all kinds

327
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of different ways while onboarding these new members. You can

328
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see what works and what doesn't. You can throw out

329
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what doesn't even try and do more of what is

330
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working and sort of layer on other marketing treatments and

331
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elements from there. There's lots of different ways of measuring this.

332
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We sit with marketing people all the time and sort

333
00:17:34.319 --> 00:17:37.839
of brainstorm ways that they can improve cross sell or

334
00:17:37.920 --> 00:17:40.359
reach out to these brand new members that they're that

335
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they're getting from Upstart.

336
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Yeah, and on that, like I would I would even

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add outside of just Upstart or lending in general, is

338
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if you're looking to utilize AI in any realm of

339
00:17:51.839 --> 00:17:54.720
your business, like, find that partner that is able to

340
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adhere to your goals and objectives across all different functions

341
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within your organization and is an extension of your organization

342
00:18:02.440 --> 00:18:05.640
to provide those insights and be the industry leader in

343
00:18:05.799 --> 00:18:08.359
letting you know what's going on within their company so

344
00:18:08.400 --> 00:18:11.119
you can better speak to your partnership when you're sitting

345
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in front of regulators and so on and so forth. Yeah.

346
00:18:14.079 --> 00:18:16.599
So I mean Upstart is partnering with more than one

347
00:18:16.680 --> 00:18:19.119
hundred credit unions and banks. Now, so what are some

348
00:18:19.160 --> 00:18:21.400
of the key tips that you have for success when

349
00:18:21.440 --> 00:18:24.039
you're partnering with financial institutions.

350
00:18:24.559 --> 00:18:26.799
I can say that my former credit uni was also

351
00:18:26.839 --> 00:18:29.240
an out there partner, so I had seen it from

352
00:18:29.519 --> 00:18:33.440
the implementation side, from the crediting perspective, and now coming

353
00:18:33.440 --> 00:18:36.799
into off starting and delivering it. This gives me a

354
00:18:36.839 --> 00:18:41.000
holistic view of how effectively implement a program like this.

355
00:18:41.200 --> 00:18:44.480
But I think the biggest learning that I've had is

356
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that we try and encourage our lending partners to start

357
00:18:47.440 --> 00:18:50.880
small and really let's get the pipe built. Let's run

358
00:18:50.920 --> 00:18:53.000
a little bit of water through the pipe. Let's make

359
00:18:53.039 --> 00:18:56.440
sure that from a reporting standpoint, everything is working efficiently

360
00:18:56.480 --> 00:18:58.880
on the back end, how that new membership is on

361
00:18:58.960 --> 00:19:02.599
board on your for the accounting is looked after, the

362
00:19:02.640 --> 00:19:05.559
compliance and regulatory aspects are looked after from the risk

363
00:19:05.599 --> 00:19:08.440
folks within the credit union. And let's get a few

364
00:19:08.480 --> 00:19:11.039
loans under your books and let's see how they perform

365
00:19:11.160 --> 00:19:15.559
early and really understand how that flow of information is

366
00:19:15.599 --> 00:19:17.400
coming through and how we can be efficient on the

367
00:19:17.400 --> 00:19:19.400
back end so that it doesn't become a burden on

368
00:19:19.440 --> 00:19:21.880
the operations folks when you're bringing in all these brand

369
00:19:21.920 --> 00:19:25.880
new members. But from there, once you realize that working

370
00:19:25.920 --> 00:19:29.240
pretty well, it's working efficiently, let's scale it. The nice

371
00:19:29.279 --> 00:19:32.279
thing with our program is there's a lot of configurability

372
00:19:32.920 --> 00:19:36.599
options available for the crediting so they can expand their

373
00:19:36.599 --> 00:19:39.480
credit box, that can shrink it as their business needs changed.

374
00:19:39.759 --> 00:19:42.400
You can raise or lower the volume as needed for

375
00:19:42.480 --> 00:19:46.240
your program. Your net return is something that you are

376
00:19:46.319 --> 00:19:49.440
providing to us as opposed to outstart saying that we

377
00:19:49.559 --> 00:19:52.640
will provide that return. You're seeing what your net return

378
00:19:53.000 --> 00:19:56.480
options are necessary for your business, and then we help

379
00:19:56.559 --> 00:20:00.160
to deliver a portfolio that will meet those that is subjective. Well,

380
00:20:00.319 --> 00:20:02.680
that was kind of my biggest learning, I think, from

381
00:20:02.759 --> 00:20:05.279
both sides of the desk. With the accent relationship.

382
00:20:05.880 --> 00:20:08.480
Yeah, I can't say that I was partnered with Upstart

383
00:20:08.519 --> 00:20:10.720
at my prior credit union. But one thing I will

384
00:20:10.759 --> 00:20:13.359
add is, even from the early onset of the discussion

385
00:20:13.680 --> 00:20:18.039
with partnering, it's important to get executive buy in, not

386
00:20:18.359 --> 00:20:21.559
just the lending folks. It's imperative to get board buy in.

387
00:20:22.160 --> 00:20:24.480
And then once you do go forward with some form

388
00:20:24.519 --> 00:20:28.440
of AI driven partnership, bring all the teams into it

389
00:20:28.480 --> 00:20:31.240
as well, look at credit risk committee, bring in the

390
00:20:31.440 --> 00:20:33.559
legal compliance, so on and so forth. And even though

391
00:20:33.559 --> 00:20:35.960
they're not touching it every single day in some capacity,

392
00:20:35.960 --> 00:20:38.880
at least they have a general sense of what is

393
00:20:38.920 --> 00:20:41.079
being done. So when you get to that portion of

394
00:20:41.400 --> 00:20:44.160
what Barry was talking about of scaling, everybody within your

395
00:20:44.240 --> 00:20:47.799
organization is comfortable with the partnership, is comfortable with the

396
00:20:47.839 --> 00:20:50.839
potential to scale, and then being able to monitor on

397
00:20:50.880 --> 00:20:52.799
the back end as things have increased.

398
00:20:53.559 --> 00:20:56.359
Yeah, including the board, right, Drew. I mean we've actually

399
00:20:56.400 --> 00:20:59.000
spoken to board members in the past, We've had credit

400
00:20:59.079 --> 00:21:01.240
unis and by this in board meetings so that we

401
00:21:01.279 --> 00:21:04.440
can help to explain the merit of the program, the

402
00:21:04.440 --> 00:21:06.680
bafans of the program, and some of the risks of

403
00:21:06.720 --> 00:21:08.359
the program. I mean, I think we need to be

404
00:21:08.400 --> 00:21:11.920
fully frank parented to all elements of the program that

405
00:21:12.359 --> 00:21:15.720
hopefully will become successful for the crediting and if there

406
00:21:15.799 --> 00:21:18.720
are success measures that may not be met, how it

407
00:21:18.799 --> 00:21:21.440
is that up there can help to get the program

408
00:21:21.640 --> 00:21:25.559
back on track because we may enter into a partnership

409
00:21:25.559 --> 00:21:29.079
with a certain expectation and if the explication is met.

410
00:21:29.160 --> 00:21:31.440
I mean, this is where really where Drew and I

411
00:21:31.480 --> 00:21:33.799
were making our money, because we are the ones who

412
00:21:33.839 --> 00:21:36.880
are coming in to help with our crediting partners and

413
00:21:37.000 --> 00:21:39.400
explain what's happening with the program and to make sure

414
00:21:39.480 --> 00:21:43.079
that we have the tools available in order to make

415
00:21:43.119 --> 00:21:44.720
it as successful as possible for them.

416
00:21:45.279 --> 00:21:47.160
Yeah. I would add to like when you fast forward

417
00:21:47.200 --> 00:21:51.000
and you're partnered with any type of partnership vendor, like

418
00:21:51.319 --> 00:21:53.319
make sure you stay updated on what's going on too.

419
00:21:53.400 --> 00:21:57.160
From an education perspective. This wave of AI has evolved

420
00:21:57.279 --> 00:21:59.559
over the past six months more than it has in

421
00:21:59.599 --> 00:22:04.400
the past two years. Businesses, as does the credit union

422
00:22:04.599 --> 00:22:07.920
listeners here like you have to pivot your organization to

423
00:22:07.960 --> 00:22:10.519
meet specific goals and objectives. Your partners are going to

424
00:22:10.519 --> 00:22:12.200
do the same thing. So as much as you know

425
00:22:12.279 --> 00:22:16.400
about your partners when leveraging AI, the better suited you

426
00:22:16.400 --> 00:22:19.480
will be when there are pivots within the organization to

427
00:22:19.559 --> 00:22:22.960
make more accurate decisions of how you want to leverage

428
00:22:22.960 --> 00:22:24.759
your partner in future years.

429
00:22:25.000 --> 00:22:27.440
Yeah, you couldn't be more right about that. The advances

430
00:22:27.440 --> 00:22:28.799
that we're going to see in the next couple of

431
00:22:28.839 --> 00:22:32.039
years were moving so much faster than we were even ten, fifteen,

432
00:22:32.480 --> 00:22:36.680
fifty years ago. Yeah, before we end today, any final

433
00:22:36.680 --> 00:22:40.359
words of advice to our audience, just to really summarize

434
00:22:40.359 --> 00:22:42.960
that how to win in twenty twenty four concept.

435
00:22:43.240 --> 00:22:46.880
So I'll say with AI. Upstart has an animule meeting

436
00:22:47.000 --> 00:22:49.839
where we bring our any partners together and we network

437
00:22:49.880 --> 00:22:52.960
and we talk about advances in the industry and in

438
00:22:53.039 --> 00:22:55.319
AI and so on. And we have a speaker come

439
00:22:55.359 --> 00:23:00.119
in to our conference last year and you spoke about AIS,

440
00:23:00.119 --> 00:23:04.480
not necessarily how you're using AI, it's really making sure

441
00:23:04.519 --> 00:23:08.119
that you're being ahead of this because your competitor may

442
00:23:08.200 --> 00:23:10.359
already be down the road in using the AI and

443
00:23:10.359 --> 00:23:13.440
you don't necessarily know. So it's almost like for those

444
00:23:13.480 --> 00:23:15.039
of you who are around in the nineties and the

445
00:23:15.039 --> 00:23:18.200
Internet came on and a lot of people really struggled, Well,

446
00:23:18.319 --> 00:23:20.319
the Internet, this is great, but how are we going

447
00:23:20.319 --> 00:23:22.440
to use this? What's the business used for this? And

448
00:23:22.960 --> 00:23:25.599
I think we've all learned that now that in the

449
00:23:25.680 --> 00:23:28.400
twenty twenty is that that connectedness and the on demand

450
00:23:28.440 --> 00:23:31.160
and the ability to transact business and to connect with

451
00:23:31.240 --> 00:23:32.680
others is if we.

452
00:23:32.559 --> 00:23:34.680
Didn't have it, we couldn't do the things we're doing

453
00:23:34.759 --> 00:23:37.359
right now. And I think AI is going to have

454
00:23:38.039 --> 00:23:40.920
that much an effect, possibly even more, because it's going

455
00:23:40.960 --> 00:23:43.400
to make those day to day pats so much more

456
00:23:43.400 --> 00:23:46.480
efficient and those decisions that have to be made and

457
00:23:46.599 --> 00:23:48.839
in upstart S case, we're talking about under a decision.

458
00:23:49.240 --> 00:23:51.599
It will be using more and more data and get

459
00:23:51.680 --> 00:23:56.000
into a more granular site way of decision making and

460
00:23:56.839 --> 00:23:58.839
you don't have to jump in with both feet on this.

461
00:23:58.920 --> 00:24:01.519
I mean, I think this is where Upstart, having been

462
00:24:01.559 --> 00:24:04.200
in this business for over a decade, and having a

463
00:24:04.200 --> 00:24:06.759
lot of training data and a lot of experience with.

464
00:24:06.680 --> 00:24:11.000
This is a good introduction for AI into creditings who

465
00:24:11.079 --> 00:24:13.200
may not even know where to start. This is not

466
00:24:13.400 --> 00:24:16.000
chat GPP, not where you ask a question and we

467
00:24:16.039 --> 00:24:19.160
will give an answer to this impactful business use case

468
00:24:19.599 --> 00:24:22.440
where we are you liedes and machine learning and artificial

469
00:24:22.440 --> 00:24:26.400
intelligence to provide better decision making for you. And as

470
00:24:26.599 --> 00:24:29.880
Upstart goes out and talks to prospective credit unions about this,

471
00:24:30.160 --> 00:24:32.640
I think that's been very appealing for them, even more

472
00:24:32.680 --> 00:24:35.839
so now because AI has become such a prevalent topic,

473
00:24:36.000 --> 00:24:37.640
not just in business but in society.

474
00:24:38.359 --> 00:24:40.519
Now, that's good. I'll expand a little bit off of

475
00:24:40.559 --> 00:24:43.920
that and kind of close out here with the reoccurring

476
00:24:43.960 --> 00:24:46.960
theme of our conversation today has been partnering with the

477
00:24:47.039 --> 00:24:49.799
right partner that can help your organization stay ahead of

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00:24:49.839 --> 00:24:53.279
the curve and actually lead the conversation within your credit

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union when it comes to the impact of AI. So

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I'm going to make a quick plug here to the listeners.

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00:24:58.079 --> 00:25:02.359
Upstart has released an AI certification and financial services program

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00:25:02.359 --> 00:25:04.960
back on May first. This is a first of its

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00:25:05.039 --> 00:25:09.440
kind AI certification program for executives in the financial service industry,

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00:25:09.880 --> 00:25:12.559
and you can think of this course as an online

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00:25:12.599 --> 00:25:16.480
master style class being led by upstarts, executives and experts

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00:25:16.480 --> 00:25:19.880
within each field. The program is currently opened and relevant

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00:25:19.920 --> 00:25:22.640
to anyone within the industry looking to get smarter and

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more informed on AI and how, where and why it

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applied to the credit union industry. For now, we are

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00:25:28.079 --> 00:25:30.720
providing this for free. I've had the privilege of taking

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00:25:30.720 --> 00:25:33.599
the course. It's an exceptional opportunity to learn about AI

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00:25:33.680 --> 00:25:36.519
from a broader sense on how it's leveraged in lending

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00:25:36.559 --> 00:25:40.440
to further advanced ones knowledge for personal development and professional growth.

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00:25:40.640 --> 00:25:42.759
If you're interested, we'd love for you to register at

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00:25:42.799 --> 00:25:46.160
upstart dot com forward Slash AI hyphen Certification.

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00:25:46.759 --> 00:25:49.079
Yeah. I think that's a really useful course for folks

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00:25:49.160 --> 00:25:50.599
to look into. We'll make sure to put a link

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00:25:50.599 --> 00:25:53.039
to that in our show notes as well. Well, Barry Drew,

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00:25:53.160 --> 00:25:54.960
we covered a lot today. I just want to thank

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00:25:55.000 --> 00:25:57.480
you both so much for joining us to share your insights.

501
00:25:57.920 --> 00:25:58.960
Thank you, it's been a pleasure.

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00:25:59.240 --> 00:26:00.759
Thank you. Malin appreciates the time.

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00:26:01.160 --> 00:26:03.279
Yeah, and thank you to everyone for listening. And if

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00:26:03.319 --> 00:26:06.200
you're interested in learning more, you can check out resources

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00:26:06.240 --> 00:26:10.119
at www dot NAFQ dot org forward slash Upstart have

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00:26:10.160 --> 00:26:11.240
a great day everyone.

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00:26:11.680 --> 00:26:14.799
Upstart partners with banks and credit unions to grow households

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00:26:14.839 --> 00:26:18.559
and expand consumer lending through its leading AI lending platform.

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00:26:18.799 --> 00:26:22.160
Upstart powered banks and credit unions leverage AI to offer

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00:26:22.240 --> 00:26:26.119
higher approval rates and experience lower loss rates while simultaneously

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00:26:26.160 --> 00:26:30.079
delivering the exceptional digital first lending experience that consumers demand.

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00:26:30.599 --> 00:26:33.400
Whether you're looking to grow and enhance your existing personal

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00:26:33.400 --> 00:26:37.240
and auto lending programs or you're just getting started, Upstart

514
00:26:37.240 --> 00:26:40.480
can help. Upstart offers an end to end solution that

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00:26:40.559 --> 00:26:43.400
can help you find more credit worthy borrowers within your

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00:26:43.480 --> 00:26:48.880
risk profile with all digital underwriting, verification, loan closing, and servicing.

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00:26:49.319 --> 00:26:52.279
It's all possible with Upstart in your corner. Learn more

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00:26:52.319 --> 00:26:56.160
about finding new borrowers, enhancing your credit decisioning process, and

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00:26:56.200 --> 00:26:59.920
growing your business by visiting upstart dot com slash lenders.

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00:27:00.359 --> 00:27:04.640
That's upstart dot com slash slenders