Leaders in Lending
Leaders in Lending

Episode · 1 year ago

Lending During a Global Pandemic: Customers Bank’s Road to Success w/ Sam Sidhu

ABOUT THIS EPISODE

Customers Bank, with a revolutionary crossover between FinTech and traditional banking, is truly disrupting and innovating past the financial industry as we know it. One year later, we look back and ask, how did AI-enabled underwriting models perform in a time of uncertainty?


Sam Sidhu, Vice Chairman and Chief Operating Officer of Customers Bank joins us this week to discuss the bank’s enormous success, how they got there, and where they’re headed next.

What we talked about:

- Lending practices and consumer loan performance during the pandemic

- How AI credit decisioning models helped drive strategic growth

- Managing risk appropriately during the pandemic

- Leading with bravery during a period of societal and economic stress


Check out these resources we mentioned during the podcast:

- https://www.linkedin.com/in/ssidhu/

- https://www.customersbank.com/

To hear more from Leaders in Lending, check us out on Apple Podcasts, Spotify, or on our website.

Listening on a desktop & can’t see the links? Just search for Leaders in Lending in your favorite podcast player.

You are listening to leaders and lending from upstart, a podcast dedicated to helping consumer lenders grow their programs and improve their product offerings. Each week here, decision makers in the finance industry offer insights into the future of the lending industry, Best Practices around digital transformation and more. Let's get into the show. Hi and welcome to leaders in lending. I'm your host, Jeff Keltner. This week we're featuring my conversation with Sam Sidhu from customers bank. Sam is currently the vice chair and Chief Operating Officer Customers Bank, but he'll become the president and CEO effect of July one two thousand and twenty one. I've wanted to have SAM joined the podcast for a while now, because customers bank has been at the forefront of two trends I think are really important and consumer lending, the push into unsecured loans, including student loans, and the adoption of fintech partnerships. Sam Discusses why the Bank chose to invest in these areas and how they've been able to do so effectively launching and managing multiple fintech partnerships. We also discuss how consumer loans have fared from a credit performance point of view during the pandemic induced macroeconomic stress environment we've been experiencing. And Sam flip the rolls of it and ask me a couple questions about upstarts, work and AI for credit and topics like accuracy and fairness. It's a fun interactive conversation that I think will provide a lot of insights for everyone. This conversation was originally produced as a Webinar, so the formats a little bit differ front and we do refer to visuals a few times. You can find a link to the video of the session and the show notes if you'd like to see the visuals. And with that, let's see see the conversation. SAMP, thank you for joining me. I appreciate this. This should be a fun conversation. Absolutely thanks, Jeff. Looking forward to it. Yeah, well, let me just start by saying congratulations on your recent appointment. Is, I know, your vice share now but, as you know, CEO elect of customers bank. That's really exciting. Thank you so much. It's it's been what a year to start and career. Thanking. For those who don't know, it was I was in the board of Customers Bank right years and then join last January and end of January at six weeks in person with my management team before we went remote. Talk about a neck of the start up to a new job. Out of the frying pan into the fire, so to speak. Real we'll try by fire. For those of the audience who might be a little bit less familiar, can you give me just a little bit of background on Cuspers Bank, who you guys are, what you do the bank in general? Sure, so we're we are just over a ten year old start up bank that has now grown to eighteen billion and assets, and the way that we like to think about ourselves and to find ourselves, we're like a super community bank that has the established expertise of a typical community or regional bank, but with the modern off frames and platform of the war technology oriented company. So we're trying to design a bank of the future, but we're really at the intersection of banking and Fintech, but doing so as already one of the top hundred banks in the country. So we have a limit of scale from that perspective. Yeah, and you guys have been growing pretty rapidly. You say eighteen billion. In my mind I go back to when we first started talking, I think it was like gotten eight or nine and there was you guys are under the ten billion threshold. So Cangrat, see you have any what's been driving some of that growth. I know this wasn't on my questions list, but I'm curious because it is a kind of remarkable trajectory of growth. It's not common in the banking industry. Are Sure? No. Absolutely. We have community banking franchise in the northeast that's a branch light format with relationship based private banking for small medium sized businesses using the single wine of contact team model. We only have twelve branches, which is the same amount of that as when when we started our relationship together many years ago. We've gone up to fourteen and back down to twelves. We close twenty percent of our branches. Is What we'd like to say, just along with the industry, but clearly not that many from a scale perspective and the way that we've grown it. As we've hired, on the CNI side, entrepreneurs and CEOS of mortgage banking, CEO of lender finance, the CEEO fun finance, real state special cold lending, equipment finance, and really help those entrepreneurs have the autonomy but then also give them the support to build out their team. So we've had a combination of relationship based a C and I growth, but then also a tremendous mone of growth on our consumer portfolio, which really did not exist because we were not a branch based bank, with the help of up startings and partners. Yeah, yeah, it's true. I did want to remind you, real quicksand that you promised to ask me hard questions here, so I'm not just ask so feel free to interrupt. I think for the audiocely want to keep this is a kind of interactive dialog and, as you said, if you throw in some questions, will try and get to them throughout the presentation. We do have some time reserved at the end for that. One of the things that struck me about your strategy, Sam, has been the execution of Fintech Partnerships, and I'm curious how you think about that kind of build versus by in the the partnerships that you have created, because you've been at the forefront, I would say, of the banks I've worked with in terms of really leveraging that strategically. So I just love to understand your the thought process behind how you think about that as a part of the strategic mix at the bank. Sure, absolutely very good question and I think that, and one of the things that our currencyeo says, is that fintext are doing everything that banks should be doing, but aren't doing it right...

...of chosen not to do choosing to do so as such is difficult operationally, from a regulatory perspective, from an allocation accountal perspective. So we've always thought a Fintech of partnerships to allow us to advance into new markets and to new channels faster than we would otherwise be able to ourselves. And while the Bank of certainly has plans to become increasingly digital across our product portfolio, we also recognize their times when speed to market is critical, when the learnings are too costly or too much of an operational or bandwidth distraction and would be hindered by building rather than partner the one of the other things that we also taken this is customers bank specific approach and view is that we're not afraid, in fact we welcome an opportunity to be a first partner or a fast follow from similar towards our partnership with upstart comes with costs, but it comes to t renispouts of benefits. So, for example, we're working with it not to be named, the technology of partner today that we recently signed up earlier this year and where their first bank partner, and we're sitting in there as they are implementing us for a tech perspective, their documenting what they're on boarding and partnership and implementation processes for the next bank. Now, what does that get us? It gets US customization, it gets US something that looks and feels good for us to take. The cost us more time up front, but then we get something that feels more like a custom product. So there's all kinds of bushes and polls, but we approach it as we approach partnerships, as we're very open to partnerships. Yeah, I'd love your sense on how. You may know you're somewhat newer in a full time roll at the bank, but one of the things that's unique to me is your ability to execute, and I mean that both in terms of finding and onboarding a partner and then managing the relationships. I see banks that really fail at both. They have maybe the appetite for partnerships and then they can't get it through all the various committees and it gets mired and internal process and doesn't go anywhere. In similarly, I do see banks that are able to sign a partnership and then, you know what I came from the software iss we always called it shelfware. Right, it go, it's great, its signed it like it doesn't actually produce results for the business. And you guys have been effective at both bringing new partnerships live and making the meaningful parts of the bank and the business and I'd be curious what you think it is that you do differently or better or uniquely well in that kind of process internally at the Bank to enable you to do that. So I think it's something many of the the tendys probably are trying to do and struggling with the effectiveness that you guys have managed. Your thoughts on how you do that? What makes you different? I'd love to hear absolutely and before I talk about our strengths, that also talk about our weaknesses. We do exactly what you just subscribe. We have also made mistakes along the way where we've sure signed up for some very complicated software that's supposed to change our entire organization, and I equipal. I call it the equivalent of we received a CD ROM in the mail and we never hoopend it. Are inserted and install it and figured out to use. Everyone does things like that. Their key learns along the way. But I think what makes us different than the typical bank is we have, and we call our tech team the tech team, not it. We truly think about the strategic value of the partnerships and we've made sure that we're developing the right capabilities internally. That could be from a cultural perspective, it could be from an operations perspective, it could also just be from an Abi Capability Perspective to make sure that we have the muscle memory for these types of partnerships. And and started with some developers and then it evolved into a true sort of a tech organization. But really what really helped us was not a put our best foot forward and say this is we want to be. We were building a Fintech within our organization and as a result, with bank Globil and as a result we built a lot of these capabilities as a traditional commercial bank. Originally we would not have otherwise had a necessity to those. So we're grateful for that DNA that was put into our organization, call it five plus years ago. Yeah, I like the phrase muscle memory too, because I do think there's a degree to which the first is the hardest, and these are often in banks, untread paths, and it gets easier, and I think you guys have done a good job of breaking that near ground and then saying hey, now we know, like now we've learned, we got a little better at our process and our our team gets a little more comfortable. So I think that's a good way to think about it. I didn't ask now, of course I we want to talk about consumer lendings. I Apologize The audience not taking you on to get there, but I wanted to ask before you guys ended up being very large and in the PPP lending program throughout covid which you know, given your size the time, I think you were. What is it punched way, I could by above your weight class in terms of your what you did through PPP. Can Tell me about how you how you did that? What was it that would enabled you be successful in that and why that was important to you, because I think a lot of PPP banks were serving their existing customers right there, just going hey, I want to make this available to the banks already the businesses I serve. I think you quite a bit brought her to try and support the program holistically. I'd love to know why and then how you execute it on that sure and I think it we didn't go as intentional as it might seem looking backward, but we started a digital application process which, for a bank of our side, no one really a digital application process, and we stood one up within seventy two hours. And when we initially came up with the idea in the concept, but it was no different than filling out a form or type into form. It just it was not a dynamic term. But what we noticed in the process is we kept...

...getting daily, day by day, smaller and smaller loans. Whereas our average loan size was called three hundred, fiftyzero or five undred holes at the bank for customers, we started seeing loans as small as hundreds of dollars and we recognize that there was demand out there that was being unserved. We then took our typical be to be in this case, although many of that last be kind of felt like CEA's in the sense that you had a hundreds of dollars. I bet it does. Yeah, and and we set up in tech partnerships with the cabbages, the on decks, the lendios of the world, who had many of these direct relationships where folks that were being failed by banks because banks were either had a manual process whatever, were overwhelmed by trying to design a system to underwrite a program that normally you would stand up in two years, but this was an emergency pandemic program and yeah, and so we had a good combination of being small enough but big enough, and I think that allowed us to sit in the sweet soft spot and actually be able to pause, you said, punch way above our way. We did four a thousand loans over a proxim on just under four a thousand loans, eleven billion dollars of funds dispersed. I mean for a bank that was nine billion and as sets just a handful of years ago, eleven billion in funds dispersed for PPP is as quite an achievement it. CONGRATS and well done. That's a an impressive execution, I think. So I will switch now to consumer loan, since that's the thing we do and the thing that we work on together, but because, for the bank made a real decision a number of years ago to into a consumer loans in a pretty substantial way, not just in partnership with upstart, but I think broadly, and I'd love to to get your thoughts on that, because it's not something Mani banks do. I see most banks think consumer is mortgage and anything it's not a mortgage like I don't really touch it any scale. And and you guys chose a different paths. I'm curious why that was strategically something you wanted to end us more heavily in sure, absolutely very good question. And we had the bank and recognize because we were branched light. We suddenly the bank was acquired by the current management team. In two thousand and nine. It was two hundred million in assets and it grew organically to when our relationship start, that started a a billion. So, as you can imagine, twelve branches, two hundred million, twelve branches, eight billion. That clearly didn't come from the consumers. Of the deposits are not from the consumers. Yeah, thank Globio. We set up as an opportunity to raise more digital bank deposits and consumer process. We now wanted to match fund and we wanted to create a diversification to franchise and we felt that somewhere between ten and twenty percent was the minimum freshmold we wanted to get to. We knew we weren't smart enough to build it ourselves. To Your earlier question, Huh, we also knew that becoming extremely adept, you know, within a short period of time from a model perspective, would mean that we need to purchase a lot of data or build a lot of data ourselves, which means you lose a lot of money yourself to be able to create the right long so what we did was is we started purchasing loans, flow arrangements and referral arrangements with some of the top consumer lenders. We learned from them. They helped educate us, we help them, they helped us. We started with a lot, we narrowed to a few and then we leaned in with the best partners up start as an example. That really helped achieve our, you know, longer term goals. And then what started? There's a wholesale business has no involved into it, you know, direct franchise enhancing business and that's the way that we planned it and that pass that we've been on. It was a path. This time it was a was an intentional path, as supposed to your think that and you guys are in a number of categories. If consumer loans this point, right, what is how many different things? I know we do on secure together and we can talk a bit about that, but can you tell me about what your broader consumer portfolio looks like at this point? Sure, so, as you can imagine, we have a small residential, you know, portfolio. We also have a historical manufactured housing portfolio which is part of our consumer book. Those are more the like like I see business has with the bank. We but we have the the personal loans, we have student loan, Reef Nance and we're looking to, you know, add home improvement and a call the next rooms. All good categories of lending. I like that. And so let's talk about Covid, and that's the title of the Webinar Right. Like consumer lending, it forance to covid. I think when I was talking the banks, call it, three years ago, there would be a concern that was both, hey, this is the riskiest thing we could do right, like you're not. There's no house, there's no car, there's nothing to take back. This money is just it's not even like a student on that can survive bankruptcy. Like an unsecured consumer loan as the riskiest kind of loan in many ways that a bank can engage in, and there was nervousness about that. But then that nervousness was certainly enhanced by we're at a detail end of a pretty good period of years from a credit point of view. Is this a moment in which to engage and am I going to really, at the of the boom times in get in that's in this risky category and leave myself at risk during what is inevitably a too common terms of a downturn? Tell me how you guys were thinking about that particular risk at the time, because I know we started working together a number of years ago in the consumer space and that I'd love to understand the evolution of what you saw through the last couple of months, a year and a half or so of very unusual economic...

...circumstance. But certainly you know one that I think is could probably be described as a macroeconomic disruption of some real portion. Sure you know. I'll start with how we viewed when we entered into the business, which I would call the digital personal loan business, a couple of years ago, is that we felt that there was Alpha to be made. So we could. We felt that we could, but yes, there would be charge offs. Yes, we would, quote UNQUIE be writing off loans and losing money on some of those. Having said that, we felt that we were disproportionately be paid for that risk. So that was the, you know, intention that we had when we started the business. Once the pandemic hit, it wasn't too far into the pandemic where we started to say this is the opportunity for us to prove everyone wrong and to say that we were right. And we had some very tough conversations that you remember, very early on and the pandemic and there was a lot of their lot of parallels initially with hurricanes or natural disasters that you could view that we thought were a very important parallels. Thanks for building reserves, planning for a potential I would call them insurance reserves for a potential downturn and potential credit losses. But we didn't necessarily anticipate that. I would go that far now. None of us anticipated that the stimulus would be so large and would be so sustaining and continue that, and that's one of the things that I think has been a little bit of the while we had three caps on the feather. Now we have to because at the end of the day, credit of credit risk is lower today, to be completely frank, because of all US almostimulus flowing to the system, of the money fire payoffs happening sooner that we anticipated. But at the same time there was a six to nine month period of time where we felt our alpha or margin increased even more significantly than we're getting paid for prependom now we can. I know some of these answers, but were you actually increasing your kind of target returns and pricing on the loans for the Alpha? I will say for those who aren't a familiar as somebody who plays broadly in the industry, we saw a dramatic pull back from banks, from capital markets, just a high degree of nervousness on which, I think, to your point, was it was a massive opportunity if you believed in what you were doing. What does it warm buff and says when everybody else is nervous, get greeting and everybody was nervous and it was a moment, I think, where you could go and take advantage of that. How did you think about were you tightening credit boxes? Where you raising rates like? How did you think about managing the fact that it was a non zero risk that you would see deterioration and performance? And then we can talk about what we yet we actually end up seeing in the portfolio, but I'm curious how you thought about managing that increase level of risk, even if you were trying to take advantage of the opportunity. Yeah, so they're were they were competing the competing sort of decisions that we have. So one is messaging and investor concern and the second was is taking advantage of showing that we were not tourists as well to be a sort of active in the market. It's important to show that you're not going in and out. The same goes for a mortgage warehouse business. That's why we've hatched us a tremendous year, because we've been able to show those customers and to show the industry that we're willing to be there when good times and in tough times, and as such, we got rewarded in the good times past, well months, we did cut the credit box, which again is an output versus and inputs or in our overall relationship, and we raised it from the time, I think, prepandemic by about twenty twenty points, and that was more in a little bit of a to appease some of the concerns that were out there in the market, because not everyone can understand the analytics and the modeling that goes into thinking about this. But we and we paused all pool purposes, which we were still doing, I'm and we leaned in and I think that it served us well and it allowed us to acquire a lot more customers and and we've been ramping up since. I think we have slowed down to thirty to fifty million a month in the middle of last year and the year between fifty to seventy five a month, and we're about hundred million dollars a month or so in originations today. Yep, we're glad to be doing on a hundred million a month with you then. It's been great. So I guess we should back up, I forgot to do this earlier, and talk about the nature of the relationship. You know, we have with customers bank. We've obviously the partner together for a number of years. How do you think about how the partnership works? Maybe I'll give from up starts point of view how we think of how we work with banks. Broadly, we would love to just start with your perspective on how this partnership works for you. Yeah, it's been. It's been a great partnership for us. It's been a long term partner. Again, we were in early early bank partner of upstart, which has allowed us to have a nice strategic partnership, a Nice Two way partnership, and be and allow us to help upstart build their business but, importantly, allow upstart to help us build our consumer loan business. So it's been mutually beneficial from that perspective. What I would say is that in tough times you recognize who are your best partner, as your best friends, your best team members, and from a and the throes of the beginning to pandemic, when what's hard to remember those times right now when we really didn't know what was going on, we didn't know how long this is going to last, or we thought it was going to last eight weeks and we'd be through this and everything would be back to normal. We had, I think, a very good experience with upstart of from from a from being open and transparent,...

...from a servicing relationship, from a human relationship, on thinking about the customers at the end as opposed to just the dollars in a sense, and I think that we valued that a lot and that speaks to why a year, just over a year later, our partnership is growing in deepening. So I think that's a very important aspect of who you partner with and our relationship. I've always enjoyed the the mission alignment I think we have as well, about providing high end consumer experiences and focusing on the end consumers. That the goal which I think is been a true north for us. For those who are less familiar with upstart, we are an AI lending platform, so providing unlike many Fintex we are entirely partnered with banks and have been from the our earliest days, and provide kind of digital origination experience, including, probably the thing we're best known for is the application of Ai to credit underwriting and deeper analytics to find those borrowers who are more credit worthy than their credit score might indicating. I think we can. We'll talk about that in a minute, Samcause I think there's been a lot of question about is that really going to work, how does it work? Is it going to survive a downturn? And we have some data on that now as we've come through the pandemic. The other area we really apply machine learning and artificial intelligence to is the kind of simplification of the bar works experience and and how do we get through Ky se ID verification, the income verification, without asking for a lot of documents, and those things really end up making a huge difference in the consumer experience but importantly, in the economics of the program and the cost that you bear to actually process those loans. I think one of the reasons so many banks have not been in unsecured lending is because the costs are too high to justify the revenue. And when you can reduce those costs, you can make this really economical and we offer the ability not only to have the origination experience but also to drive a demand to that experience for our partners. So we're actually helping you guys source that hundred million a month and then servicing on the back end for partners who want so, and we've been doing all of that with customers bank. You guys were the first partner that was actually keeping loans on balance sheet with us, way back in the day, as opposed to programs that we're selling loans into the capital markets, and so we've evolved a lot together and are looking at now the second product we've entered, which is on a refy and eventually auto purchase financing, which I know we're talking about. How we get into that game together. So we've been excited to do that. And with that background, I did want to ask you really quickly one of the things I've been talking about Ai in credit underwriting for ten years now, almost to banks, and one of the questions that was hardest to answer for any banker was, hey, you show me some great data and it's all from like good times, and yeah, there's some like better differentiation and the credits better, but what happens when times are not so good? Is this going to deteriorate much more so than the thing I've watched through a number of cycles, like credit score. Did you have those concerns? And then how would you categorize the performance of those models through the current macroeconomic stress environment brought on by covid absolutely we had those concerns. Our investors have those extreme concerns because of the new business for us as well. And I would actually pose it back to you and I'll ask you some of the questions that I get asked, in fact that you have helped us answer, because I think you'll have but you'll be able to. We can talk a little bit about the overall portfolio and not just our direct relationship, and that'll help get the question that you're asking. One question that we could ask. Why do you need a thousand or fifteen hundred? However many vary. Isn't it really just fight go oh, and one or two others? And why do you need all these? And how heavily weighted are the thousands? One in the eleven, under fore, one, thix hundred and first variable. So we have something like sixteen hundred variables that are contributors to our model today, and it's really amazing that you find that there is very little power even I think you got to get over a hundred variables to see something like half of the explanatory power of our model. And then every little variable is not super important. There's you can take out anyone variable, including a credit score, and it wouldn't really change the outcome because there are, of the sixteen hundred many that are saying similar thing. They're related, but it's the the ones that are related at say slightly different things and understanding how that really reflects a difference of credit worthiness that gives you UPLIFTS. And I think to take advantage of this, I think you really need a combination of three things, and not many have put all three together. And that's the one six hundred. I think of the data like a big spreadsheet. Right one sixteen hundreds, like how many columns do I have? And one thousand six hundred columns is great, but then I need to make sense of that. I need a lot of rows because I need a lot of people who look very similar in one column of a similar credit score and look different in others to understand how to find that slightly lower credit score Barre who truly is credit worthy, and we know they're. They're the beginning insight we saw was in a subprime pool like Gif, twenty percent defaults, which sounds awful until you realize it means eighty percent of people paige, you back. Could you just find the eighty? And that's really where we started. And so you find that if you have those columns, you need a lot of rows. We've now, across all of our partners, originated over ten billion dollars in unsecure consumer loans, and so that's hundreds of thousands of rows of data, so to speak, in the spreadsheet. And then you can't use your old logistic regression. Goes to a...

...score card that prints out on a five page PDF. To take advantage of those things right, you can't say if this variable goes above x, you need really sophisticated algorithms and those algorithms require both the large number of columns in the large number of rows. So we found that it's really important that if you have those rows and those columns and can apply those techniques, then there's tremendous ability to actually find those relatively credit worthy, yet not yet high credit score borrowers and even to find those high credit score borrowers who actually represent a somewhat higher degree of Bresk. And so it really does take all the variables. You can take one out, but every one of them adds a little something to the model. And it's the sum of all those little somethings that ends up making a really tremendous difference and your understanding of the credit worthiness of a specific consumer. I think that we've gotten to understand that. We've gotten to see the benefits of that. Now, I think one of the things that we talked about in the banking business, both in the consumer side as well as with the commercial side of it, there's the gut, there's the relationship. There's no shaking someone's hand, looking at them in the knowing them in the community. That's really helps reduce preditres. So how do you think about that? These so the a digital relationship with the customer that no one from the bank as has meant. Yeah, I think it's a great question. The obviously our models are all trained on a performance of loans that didn't have that relationship and I think, particularly as you get into larger, different kinds of loans, of say mortgages, that becomes really crucial and I actually I love the model you guys are developing because I do think that a hybrid of the two will be valuable in the future, particularly less from a credit as point of view and more from a service point of view. But I do think you see, and we see this in pools of loans, that for customers with long standing relationships with a particular bank they perform better on a loan from that bank and they do want a generic long but there's elements of that that we see and will price with our bank partners. But I have a longstanding relationship. But I think when you can see it, it means you can also see the APPS and set it and so you can properly price and manage that risk. So I think there will be real value for banks that can cross sell their customers on multiple products and thereby take advantage of the lower risk that comes with a long term relationship understand how to price and quantify that lower risk. It's not just a hey, you're a customer, will give you fifty bips off, but you can really understand how much less risk is this customer who's paid off three loans with me than a new consumer. But the course is also real value for the bank and being able to bring a low friction, low cost experience. It can bring new customers into the bank because the great thing about that loan that's to a nonexisting customers. That's a new customer and you can sell them another long where they won't be a new customer and you can help them with other needs, and I think being able to do both is really important and we've certainly seen that, particularly in the small loans, on secure loans. Like people want fast, they want easy. They don't for the longest time. My CEO would go on to his bank, and I won't. It's a big bank, so I won't name it, and the CVA web and art to make them feel bad. But if you ends that I'd like and I'm secured loan, they would pull up an eight hundred number to schedule an appointment in the branch and he may have liked shaking somebody's hand, but in that moment he wanted to know how much he qualified for and they weren't giving him that information. So I think providing the best consumer experience does me meeting them where they are, which in this case may mean and their pajamas on the couch over here, and they want an answer then, and I think you can ultimately combine that with relationships and high touch service as it's needed, but not necessarily for everything, which is I think the default in many banks go down to Yep, you know, absolutely like the point you made about it's a little bit of self selection as well, right the fact, trying to find customers who want this journey for this channel as well. And he touched a little bit on the relationship and the cross selling and owning a relationship. And you know how I'm sure you could ask a lot of questions as opposed to just tucking that our experience. And when the when? When a bank partner comes to you and says, I'm in Pennsylvania New Jersey and I want I want to referral loans in Pennsylvania New Jersey and that's all I need? How do you think about the old branch bottle and the geographic model versus a national model and a digital branch? You know, type, type feel. Yeah, it's a good question. I see banks that go different ways and I'm always recommending the banks to think of a digital product as a way to build a national footprint. I will say there are still many banks that want to go digital, but they want to know that the customers are in a footprint where they can walk into the branch and talk to somebody if they want. I think often they feel like their ability to cross sell other types of products is related to everything else I've got as sold in the branch. So if I want to bring a new customer in and need to have them able to come of the branch to cross all but we really push him to think about a way to broaden. We can obviously restrict when we're doing referral flows, but we're helping you find new customers. We cannot. We can restrict that to the geographic footprint of our banks. Let's say I'm in these five states, can just get me lunch mirror and that's fine. But I find many of them are increasingly interested in using these digital experiences as a way to broaden their experience, to see what it's like to have a customer in a state they haven't been in and dip their toe in the water of moving towards a national digital experience as well as they're in personal experience. And then the other thing that's hiss. We do work with our banks that have more, you know, substantial existing branch footprints to say how do we bring this experience into the branch? How do we enable the branch employ to talk about this kind of product to the consumer...

...and then originate it in the branch, maybe on the consumers phone, but in consultation with that banker. We've had a lot of success with some of our partners driving adoption within their existing customer base through their existing branch network. It actually can work quite well. So we always want to serve your current customers, but think of this as a way to expand both your customer base and your geographical footprint, because there's a lot of opportunity and demand out there for that. Absolutely couldn't agree more. I'm so did I fully answer you know, your question with the reverse questions? I think so. The question I'd have for you is, do you think this is going to be a turning point moment? You now we cannot just say yeah, models performed well, but we can actually quantify a net might as well, while we're here, might as well throw some of these slides up and show the quantifications. I but this is I pulled this out of here, I think, analyst called DEXA. I'm sure you're familiar with this. And when we actually look at to quantify what you and I were talking about, the performance through the model, do you want to tell the audience here what this slide is showing. Samon that I'll give a little context on the experience we've had in more broadly, but would love you and walk through what she saw. Kind of performance through the cycle on this port or absolutely so what do you in the top line is the industry of consumer loans and consumer installment loans and goes on security, consumer loans and forbearance. Is Prior to looking at the date track and through the pandemic, and that's the red line. So you see that and he got up to it seems like approximately sixteen percent or so of loans and some sort of before barance. Now, if you look at a customers bank direct you can see our our increase was less sharp but obviously either the margin and the Delta was significant. If you also pulled out upstart from that, you would see that upstart and our relationship with upstart did even better than the Blue Line, which is a blended line go across our overall portfolio, and I think a lot of that has to do too with not only be underwriting but also, when I cus from earlier, which is the servious, service oriented nature up start services the loans that they help us. So for a referral perspective with yeah, I think that service and running the the referral and thor the deferral program sorry on the talent, was really important for context. It's the shape is remarkably similar. This is what we saw for the industry and across all of our lending partners. We have that and you saw this kind of increase, but a much more muted increase, and overall delinquencies, and this was this payment impairment for the audience is a is a combination of both people who are in a deferral program are people who are any number of days late on a loan. So it's the total impairment, whether they're just not paying or whether they entered deferral. And what's remarkable. So it's come back to normal. The industry is still slightly above normal, but as of the state end of last year. But the upstart portfolio is really back to where it was before, which is to say we saw a very small increased relative to industry and almost a complete return to normal. And then, as we talked about the AI models, this is one of my favorite charts, but it's really hard to read, but I think it explains why. If you looked at the gross numbers that the customers bank impairments were much lower than the upstart overall platform, and that's because, as we work together so and you guys don't take you have a limited risk appetite. We have other lenders who sell under the capital markets and don't retain and they're willing to originate loans that are riskier, as we perceive them, than you are. And this is a chart of you know how risky upstart perceived the loan in in terms of tears and the credit score. And what you can really see is now our bank set were limiting risk by the upstart risk prediction. Saw Not only better credit performance of good times, but this is impairment rates. When you were in here's one through four in the less risky category of loans, your appairments were much lower than you were if you were over here. And what upstart declared as the more risky loans. In a way that just wasn't true. If you were using only credit score to do that right, if you tried to limit your credit is by just looking at credit score, you didn't have the same kind of relationship where you were really limiting risk of impairment here versus what happened and this and this is why, because you guys are looking in the lower risk heres. Is Why you're portfolio had less impairment, the less losses and good times and less impairment during the current crisis. And so I think this date has been really quite stunning in some ways to see how much more predictive of risks and impairment to the portfolio the upstart model was. You can just look at the average column for credits for and the average row at the bottom for upstart tier and go well, if I have had to pick one of those to limit my risk, it's not hard to figure out if I want to. I want to use the columns or the rows. It's, I guess, the question I have for you coming out of that. I'll stop showing sounds. Do you think this is if that was a big concern? Okay, you've seen the models and I seen the accuracy metrics and good times, but what's it going to happen in bad times to that? Do you think coming through this experience will be a point when more banks become open to leveraging these technologies, because you've seen them through a cycle and you now have some evidence to look at, not just assumptions about how they'll perform, and I think so far the data is really compelling. Absolutely, and I think that this goes to the point I talked about. This is an opportunity for us, customers bank, to showcase of strength of our franchise. That's more the output, but the fact is we got data and the data is what makes this much stronger. Is, yes, the out the output is what allows people to feel more comfortable, but the fact that that we went through it makes the upstart model, as an example, that...

...much better. Yep, that's right. We certainly it's been a lot of time improving our models for how to adjust to and in a way that it's fun pressed like the pidity of change of the economic situation in this instance was so much greater. Normally you've got it takes months to have this happening here as a matter of days. But I think we learned a lot and I think will be even better position the next time we get through a cycle. But certainly the data to me seems indicate that if this was your concern as a bank, what's going to happen during a stress period? There's pretty strong, compelling data now that it's really not a major concern. So I'd like to turn over to audience questions in a minute, but before I do I just wanted to in by asking you you're taking over the helm of the bank. You guys have been really on the cutting edge of but of interesting stuff and some vintech partnerships and consider letting what's on the horizon. What are the next two or three years for customers bank under your direction look like? Sure, I think that we're a bank and transition and it's not necessarily because of leadership. It's also just partly because of maturity and growth. So we crossed ten billion for the first time just over a year ago with into the fourth quarter of two thousand and nineteen, and we had paused at Hunder ten billion for Durban release and their reasons really our bank, global ownership and investment. So I think that there's a resumption that wrote. There's a building out of a bunch of our businesses, but really it's it's thinking about the future of a bank, where banking is going. We're not burdened by legacy technology and a legacy branch that work which in some cases can to have some benefits, but really I think the last year has shown that they were trends that were already happening. They've been accelerated their getting momentum to banking, digital customer requisition, bank as a service. These are all things that were already a part of customers bank in a very small way, but we'll be leading in more heavily over the next couple of years and the way that one of the things that we need to do is focus on change management within the organization. As tech forward as we are, we might be better than ninety percent of the banks. That's not saying much to the non against the non banks. The tech companies sort of a lot of work from that perspective. But I think that we're looking to increase and lean into our consumer loan portfolio and build it into an overall, overall strong relationship with our consumers, both in the asset side as well as a liability side, as well as across south side, and I think that's taking what has proven to be a strong we led with the asset generation and now we're going to continue to try to create a strong customers not just through the life of the loan but through for life through digital means. I think that's going to be a very important aspect of how we approach not only are our consumer loan borrowers, but also, importantly, over all through the bank and try to create a Omnie channel digital experience that doesn't feel like a digital bank versus a branch bank, versus the Commercial Bank. And that's it's and I like that you talked about leading with the assets. It's one of the things I'm starting to hear more from banks I talk to, which is this question of can we leave with when in the traditional model has always been you sponsor a little league team, you bring in deposit accounts with relationships and then you and then you offer them loans as their customer. And I think this method of actually bringing people into the bank through revenue heating product. Frankly, it's better to start off with a loan. It is where the revenue comes from. But I think it's really interesting because I most banks I see are still hesitant to lean that way, but I think the world is shifting that way where if you can do it, why not? And it's great to have a partner WHO's pushing it the front of that. Absolutely have to because it's tough to acquire a deposit customer digitally. That what are you offering other than rates? So that's why you need to think about what does a customer need? How do I service with the customer needs? Then how do I grip get the overall relationship? Yep, perfect. Thanks for joining sale. I've got a bunch of questions coming in from the audience. That Jenny. I don't know if you want to ask, but I can pop on here. I've got one that came in that I'm actually kind interested in the context of this relationship question, which is you mentioned that you started out with some whole loan purchase programs, but you're now in an origination model, at least in terms of your upstart relationship. How did you think about how the importance of originations and originating in your name versus buying loans on the back end there's more of an asset allocation thing. Why do you think that's important to you? Yeah, so I think that one is a wholesale business and and one is a franchise enhancing business. So the wholesale business we were very open about. We were learning, we were purchasing, but you're a price taker versus a price maker, and that's really as simple as it was. And so they were transitory loans booked on someone else's paper. We own them, we made a premium servicing and it was truly an asset only relationship, and I think that's the transition that we needed to make as we continue to learn, build under models, build out the other partnerships to be able to figure out how do we build the best digital, first consumer bank within our commercial yeah, I like it. Let's see what we got here in the quick I got my questions pulled up. Out of out of the ten billion and originations. What is the average lone? Man? It's a great question. Sam. Do you know the average one amount and your portfolio? I'm sure it's going to paing it to me and slack if you don't. And I think between twelve and fifteen thousand. It's my as my guests at probably knows best that. I'm sure I does best. I think you're right. If between twelve and fifteen and the upstar platform is a whole, it's a little lower in and that's really a relationship of the broader risk profile that we have across all the lending partners that we have and the lower risk loans tend to have slightly larger loan sizes. You can imagine higher income consumers, higher presport consumer that the cubby portfolio is a little bit larger on an...

...average lone size basis than the upstart portfolio as a whole. But you can think of the unsecure consumer loans like as as three five years, between one and Fiftyzero. But typically you're seeing a ten to fifteen thousand dollar average lone size and the chunk of that being credit card refinancing, high interest and refinancing is a big is a big chunk of that. Let's see. Okay, we've got other COQUDS TO AI models. Replace human underwriting a hundred percent, but he thinks am a hundred percent. Definitely not a hundred percent. You. You can't even book a hundred percent the loan without without sometimes having to an intervention. So I think the way to think about the end model is you're helping. In some cases you're building a credit box, you're opening up the door based upon a box and you're trying to relate replace. As I mentioned before, a little bit of the gut of the relationship manager based on a lot more data than the relationship manager has when they're making that gut based decision. Yeah, and I'd say from upstar platform point of view, all the credit decisions are fully automated, so there is a complete replacement. From the risk analytics point of view, we're not saying, Hey, come in and tell me you think this person's better risk. There is still instances where, for fraud prevention, for verification, for other things, there will be human interaction and again we try our best to limit those because they do have and we find if we can go to a no human interaction model, we've convert roughly twice as many interested parties into loans. That's good for everybody, but we also don't want to do that at the detriment of preventing fraud. Maybe kept fraud below thirty bips across our history, across the platform. So balancing those two is really important and we did. That's not to say you can't call if you have a question, you want to talk to somebody, we're absolutely there to make that happen. But at the same time, as I said, a lot of people don't write, they just they want to get through it and the more we can not ask you to upload a pay stub or a w two or a bank statement to complete the process. The better off it is for the consumer, the lower cost it is for us and for the partner and generally, the better performing the loans will be. So we do find it that it works that way. Let's see, trying to look through my questions. Oh, here we go. During the pandemic, how did you monitor and assess the performance of your personal lump portfolio and how did you get confident going back and expanding originations? What was the cadence of the process by which you were looking at how listing was performing and getting comfortable, as you said, increasing the originations as we as you got a little bit farther in and said Hey, things are going well, let's start growing again. What did that look like? So there was a data element and a human element to that. So we, for example, with all of our will, we call sort of our service by other portfolios, we started evaluating them in the daily basis that we could, on a weekly basis at a minimum, we had weekly calls to each of our our services. We were gathering our own data and developing our own proprietory views. We were evaluating hurricanes and natural disasters and Puerto Rico and Katrina and trying to think about all of it, what history could help us to inform in addition to what the data, you know, was telling us. And some, I think, as I mentioned earlier, some of our partners really showed strength relative to others and we leaned in with with those partners. Yeah, yeah, that's great and I think we enjoyed the ongoing dialog and it was nice to have a good partner who was looking at the data and making rational decisions where I think some we're making fear based decisions, and I think that process worked well and could us to your team, I think, for being on top of it well, respecting of the data, understanding of it. So I've got two questions here related to fair lending, and this is probably if what's going to happen when the economy turns south is the number one question I get asked about a models, fair lending is probably number two and say I'm going to assume you'd rather I answer. I could set yes, that's I think whenever you look at the application of Aml to to any area, the question of fairness is central and it was central for us as we began developing models many years ago, and so we actually went and had a conversation with the consumer financial protection bureau before we started lending with any of our bank partners, on how should you think about fairness in the context of the models were building in the data were using. I will say we were now even up that we walked into the CFPBS enforcement office as opposed to their office of innovation, because we just we weren't sophisticated rericulated entities yet. But what what we came up with them was a process to really think through how should you evaluate fairness, understanding that the world as it exists is not totally fair. If you look at the distribution of credit scores among different classes of people, African Americans versus Caucasian Americans, they're not the same, and so if you're using even something as standards credits court, you're going to have a higher approval rate for White Americans and you will for African Americans or Hispanic Americans because they just don't have the same credits court distributions. It's a Kay, that's true. So we can't just compared as everybody being treated exactly the same. So we came up with a waterfall test mechanism that we built with in conjunction with the Bureau and Perform quarterly on the portfolio and provide results to the bureau. Of the result of that, in the end was the issuance by the Bureau of what they call a no action letter, which is a hey, we've looked at this,...

...it makes sense and we don't see any cause for concern. On specifically the topic of fairness and frankly, what we found is that in a world where we're in accuracy is high right, where we're turning down everybody below six hundred and eighty eighty five, ninety percent of who might be good borrowers, that when you can have a more accurate model, everybody can win. And that really means two things. One, when the sea a PB compared our results to what a traditional model might have done with similar risk levels on the same portfolio, they said that they found that for every demographic we could increase approval rates in lower interest rates. Right, so we're charging people last, we're proving people more than a traditional model across all classes. And then the question becomes are you is that impact being desperately felt by a protected class or not. In there, what you find is that this data can often offset traditional biases, things that are not evenly distributed today, and so we've not found any cause for concern and our work with the bureau and that's something we will continue to do. But I think it's an important question. It's not an easy question to answer, which is why we went right to the front of it. But we really believe very strongly that the uses of these techniques and alternative data points can help improve the fairness of the overall credit system because of how much unfairness and inequality exists in the system to day, and we think we're seeing that and the results of our testing our work with the bureau. So it's I don't think of that as a backfoot question. I think of that as something we really lean into. Is, frankly, why we got into the business in the first place. Can I just ask a follow up question? That is and I think that if you are the C Itpp, you're just generally a regulator. A static model seems easier to take, you know, no action. So how does a regulator, or how to the bank partner think about a regulator understanding and getting comfortable that dynamic one. Yeah, it's a great question. So I think what you have to do is move the level that you're thinking about the bottle at up a level, which is to say I'm not worried about the specific like credit score box, as much as how do I determine what that box should be? What's the process that the trains the model? Where is the data coming from? How are we assessing fairness? How are we assessing accuracy and how are we overseeing things that might go to production? And if those things are staying the same and I'm overseeing that process, then the output of that process should be good. In fact, as a model is trained, one of the benefits of having defined the test for fair lending is that we can run it on every version of the mop and go hey, we tested it under the old model, we've tested it under the new model and we still have good results. So we're comfortable going live, and that's why I don't know that, frankly, there's any other platforms doing that. But thinking about evaluating, overseeing the process level and the oversight that the criteria to launch the testing the training process. That's the core thing, I think, versus saying Hey, I want to I want to approve every change and Hyco score, and of course you guys do approve and dictate every change in credit score box. But I think that's where the thinking evolved at the regulatory side. Where the banks have to get comfortable to is saying I'm not don need to look at the code for every model change. I need to understand how it's being evaluated. If that evaluation process is changing, now that's a different issue. I want to see very clearly what's happening. But if you're using the same training and testing and evaluation method and the model gets a little bit smarter, I'm comfortable. That's still effectively the same model and it's just a little bit smarter version of it. And that's, I think, that the shift and thinking that has to happen right to effectively take advantage of these things. So we get a question is upstart provide the digital application that a customer would fill out or only provide the underwriting engine? And my answer is up to you. We on our partnership with customers bank. We provide the digital experience, we provide the flow of loans and the servicing and we have other partners that just want to consume the underwriting engine and do that through a programmatic interface. I think that's not as common and unsecured loans because, frankly, not a lot of people have a great experience for unsecured loans today. But it is available if that's how you'd want to consume it. Get Jeff. I have a follow up question that Bush. You know what is upstarts and he asked and how do you think about yeah, it's a great question. We measure MPs very carefully. Typically on originated borrowers soon after origination in our MPs hovers right around eighty. I don't know what our latest number is across all of our partners and frankly, our bank partners that are retaining a customers bank being exable typically have slightly higher inps has that are programs that are selling to the capital markets, because the number one thing that influences people's happiness is there great and because you guys are able to offer slightly better rates than those lenders that are selling our loans to hedge funds and others. Typically that results in higher customer satisfaction. But Eighty, I'm being told, is eighty one right now. I Never Grad Eighty one is a pretty high MPs and we monitor that weekly, daily, following the Trans because it's really important to us as a metric. Of is the experience where providing meeting the customers needs, and that's now we got into this business with the consumers are true north and this is one of the ways we make sure that we are staying true to that true north. And I just as a point of reference. I'm sort of many folks in the from the call know their own MPs has, but where would you say top tier banks are? Other I don't know. I don't want to make anybody feel bad say, but the JD power looks at the MPs for the the industry...

...as a whole. I want to say it's in the S or S. I know there are some on the lower end. That actually MPs for those who and is familiar, is net promoter score and one to ten. Would you recommend this product or service to a friend or colleague? And I think it's they don't call me the like eight to ten or eight to ten, or considered promoters seven hundred twenty five, or considered a neutral and form belower detractors, and you take your promoters and her detractors. So a negative one hundred is a possible score, not just as zero. And we do see some in the financial industry who go into the negatives where there are more people unhappy than our eight to ten is like. Got To be very people have been very happy and I think they're tell me customers banks is writer eighty one. So that's well above where I think anybody think. The only people in the industry financial industry that have an eighty or probably USA, who typically has a really high customer satisfaction score, and most of the rest are in the the teens to S. I think is pretty cample. I'd best top tier is considered five thousand hundred sixty. With that, you know, depends on how you measure it and who and what service, but it's eighty is quite high and looks a lot more like more two typical tech products in the financial end, the in the broad consumer industry then, than financial services. Well. So I guess people are asking if approval rates have gone up and if consumer demand has gone up in two thousand and twenty one, but we saw certainly a dip in consumer demand going through the pandemic in our minds. It's mostly recovered. I think you beliet a little bit by Simulus, but we have not seen a substantial slackening and demand from consumers and, frankly, the average approval rates going up. The approval rates depend a lot on the marketing mix we may send, like where people are coming from, but I will say on the same set of Bar Wers, every couple of months the model gets noticeably smarter. And whenever the model gets noticeably smarter, we can approve a few more of any given population of Barrowers and lower the rates for a good population more because there are still many good barrowers that we don't recognize as such. An every time you pull one or two losses that you can predict and not lend to, it gives you a handful of Barrowers that you thought were too risky that you could pull in and actually better understand it is credit worthy and and that happens for us every month, that we may choose to mail a slightly risky your group that we did last month and offset that from a gross approval rate point of view. But every month the model is getting smarter and I think Sam with a test it's maintaining its performance from credit and then we're not seeing, as it approves more people, a deterioration of the credit performance. It's just US really finding those properly credit worthy people more accurately than we did a couple months ago. Up Start Partners with banks and credit unions to help grow their consumer loan port folios and deliver a modern, all digital lending experience. As the average consumer becomes more digitally savvy, it only makes sense that their bank does too. Up Starts AI landing platform uses sophisticated machine learning models to more accurate really identify risk and approve more applicants than traditional credit models, which fraud rates near zero. Upstarts all digital experience reduces manual processing for banks and offers a simple and convenient experience for consumers. Whether you're looking to grow and enhance your existing personal and auto lending programs or you're just getting started, upstart can help. Upstart offers an into in solution that can help you find more credit worthy borrowers within your risk profile, with all digital underwriting, onboarding, loan closing and servicing. It's all possible with upstart in your corner. Learn more about finding new borrowers, enhancing your credit decisioning process and growing your business by visiting UPSTARTCOM Ford Banks. That's upstartcom forward banks. You've been listening to leaders and lending from upstart. Make sure you never miss an episode. Subscribe to leaders and lending in your favorite podcast player using apple podcast. Leave us a quick rating by tapping the number of stars you think the show deserves. Thanks for listening. Until next time. The views and opinions expressed by the host and guests on the leaders and lending podcast are their own and their participation in this podcast does not imply an endorsement of such views by their organization or themselves. The content provided is for informational purposes only and the discussion between the host and guests should not be taken as financial advice by companies or individuals.

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