Leaders in Lending
Leaders in Lending

Episode 46 · 7 months ago

The Steady Adoption of AI & Machine Learning in Credit & Banking

ABOUT THIS EPISODE

The more banks lend, the better they do and the broader their customer base becomes. 

With AI & ML, banks can lend to a larger set of customers — those who are perceived as high risk — with a greater level of certainty that there won't be undue losses. 

Despite this, many banks and regulators remain uneasy about the outcomes. 

Tom Faughnan , EVP & Director of Consumer Lending at Associated Bank , is bullish on the potential of AI & ML. In this episode, he shares what needs to happen for regulators to give fintechs the green light. 

We discuss:

- The opportunities and hurdles of AI & ML in credit decisioning

- How to find the right fintech partner in the space

- Aligning internal parties across business lines during the vendor management process

- Navigating the mortgage space as rates rise 

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 on your favorite podcast player.

The more we lend, the better we can do, and then water our customer base becomes MMM. So where you have traditionally unbanked, unwin markets, that's where the opportunity is. You're 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. In more let's get into the show. Welcome to leaders and lending. I'm your host, Jeff Keltner. This week's episode features a conversation with Tom Fond and the director of consumer lending and Associated Bank. Associated Bank is a thirty five billion dollar bank based in Wisconsin that serves the Greater Midwest area. Tom And I really dove right into the topic of machine learning and AI, both where the opportunities are to apply it to banking and, more specifically, to lending, but also how you think about managing the risks, both regulatory risks and uncertainty, and internal stakeholders that might need to sign off. Credit Committees, compliance committees, thunder management. A great discussion on I think, a very important topic. We do have a little bit into Fintech Partnerships, how you invest in that area, both finding the right partners to work with, managing the risk of the partners, particularly enterprise risk, which Tom was interested in, but also how you manage a little bit the internal stakeholders and develop a process around really becoming effective at Fentech partnerships. Tom talked about their decision to buy and and direct auto business and get into that space to augment their mortgage space and specifically what what was like to do that in a virtual world as opposed to in personal world, which is a little more common for that sort of thing, and he gave us a couple really interesting thoughts on what it takes to earn customer loyalty and in the modern worlds. I thought those were really interesting and ended with a little bit of old school advice, so I have to listen to the end for that, but please enjoy this conversation with Tom Fonham, the director of consumer lending an associated bank. Tom, thanks so much for joining us today. I appreciate you're making the time to join us on the PODCAST. Glad to be here. You know, I was really interested in your perspective, because we're talking a little bit about and you said one of the one of the main areas you like to discusses aimchine learning and credit and banking, and, like I wore my heart with this statement. So would love to get your take on kind of where we're at in the state of the industry and where you think the opportunities are. Maybe the risks are the things holding you back from applying it more broadly. So I think we are farther ahead in creating a machine learning environment, particularly when it comes to credit decisioning, and I will say that's predominantly on the origination side, but also could apply to lost medigation efforts and techniques as well, and and the benefits of those are multi faceted. But I think what hasn't happened yet is banks and regulators have not yet gotten completely comfortable with the outcomes right and and frankly, it's new enough that there are a lot of outcomes out there to test. But I think that you know, realistically, is what the consumer...

...wants, it's what the banks want and it's what you know really what's going to drive the industry going forward. So we've got to figure out a way to come to grips with how it works. You know how it's going to work because, frankly, regulators are used to testing models right and the models are static and they can look at it and they can test it, look at the outcomes and decide up that one's just fine. Where you're talking about a machine learning environment, it's a constantly changing environment. So how do you ensure that with that change comes predictive results that satisfy the fair lending requirements, as an example as it where do you see, before we get into the like, how we address some of those concerns? Where do you see the biggest opportunities, like what's the value add to the institution? I think sometimes we get we get caught up in the like how do I get through the regulatory rigmarole and we forget a little bit about like why we want to do this in the first place and what the value add to the business now we want. I mean banks make money off loans. That's no secret, but the other thing is that the more we lend, the better we can do, and then water our customer base becomes so where you have traditionally unbanked unlent markets that's where the opportunity is. If you can show me a way that I can with some certainty be able to lend in those markets and make money and not suffer undue busses. I've created new customers, I've had additional relationships I can open up. So it really is an opportunity for us. We just need to be able to get there. And do you have any thoughts on what what helps bridge that gap? To your point, and I think there's like the changing nature of the models. I think that when any aiml there's like a complexity of the model that's a little more sophisticated that is harder for people to kind of wrap their mind around. Well, if these three things were different for this borrow or something, how do you think we kind of get regulators and and I think that just regular credit committees, banks, as it's a twoitions, more comfortable with these kinds of approaches that can have those benefits. Yeah, I think part of it is going to be time right to prove the model out, prove that the changing MODELC and work. I think the other thing is, you know, we're bringing new customers into the organization. That's going to create a value proposition as well. And then, you know, last of all, I think that you know, when we model it and look at it and and have an acceptable loss rate and we find that that acceptable loss rate throughout the cycle, right. That's the other thing. You know, machine learning is relatively new and has an experienced that kind of downturns that we saw after two thousand and ten. There's models that have been used to mimic that, but frankly, you know, in the real world environment we haven't seen it proved out through a down cycle. So some of that gets back to what I said in the beginning, which is time. Do you think the main covid has been this interesting kind of down cycle? It looked from certain macro indicator, let's take unemployment as an example, that we were in a really bad place right, particularly middle last year. It looked it look pretty scary, and then you had this opposite thing where, you know, for whatever reasons, government stimulus or others,...

...realize credit losses have it really you know, haven't really seen the same kind of increase in risk or loss that you might have expected given what some of the macro indicators were telling you. How do you think about how much covid in the experience kind of gives you some perspective on how these models were performed during, you know, a less benign credit environment than, you know, the most of the time they've been around. You know, it's funny because when you look at certain aspects of the pandemic impact and you look at, for example, unemployment and the initial spike and unemployment and then you've had kind of the retrenchment or back to basically precovid levels, you know, what did that look like? Well, I think that, you know, the fact that government stimulus was really so broad based that it really prevented because, you think, Gut stimus includes forbearance and include so. So basically, people are getting uppermental income and not being obligated, not being forced to meet their credit obligations, you know, through the forbearance process, which, by the way, was all together needed to get through this, but it really did create an artificial barrier that otherwise would have resulted in kind of a catastrophe, you know, economic impacting credit losses. So, you know, I think it really was because of the steps that were taken by the government, it did really mask what could have been a really horrendous and we're you know, we're not out of it yet. I mean we're starting to see inflation peak pick up again. We're starting to see how the factors that could lead. Now can we manage our way out of this process? Hopefully we can, I mean, but I think we're well prepared to manage through the process with what we've got already. But those are some of the things that need to happen to get us through the cycle, to have a proof point to be able to say, see, it does work. Yeah, I think that's I think it's right and I think there's certain signals we saw during the the crisis, for instance, you know models predictive power about maybe entrance into forbearance and recovery from forbearance that they gave you. You know, it'll least something closer to a proxy for what loss s acceleration might have looked like absent government stimulus and in four barance programs at things. So I feel like at least we've got a few more data points about the the survivability these models through economic downturn then we did, you know, pre this experience, but you're red it was. It's been a very interesting I think we're going to see some sort of a version at least to the mean here, because the stimils it's kept you up not just a neutral environment, but like really benign environment, right freely, exactly. YEA, and I want to ask Oh, go ahead. The other thing about the models is it uses non traditional metrics to help inform credit decisions, and that's something that the industry and regulators are not used to relying on. And and you know, how does it work? What are the outcomes? And again, that's a time based right. We're going to see what that looks like over time. But it also opens up greater opportunities to provide credit to traditionally unbanked unlent markets, and and you know that...

...that's an important attribute that you know can't be overlooped as well. I think that's right. I think it's it's interesting when you talk to regulators about this area, that there's the kind of the fair lending laws, but at the end of the day, I mean the thing that always I remember is that many more Americans are credit worthy been are traditionally prime type credit. You could just in any pool of high risk loans. The majority of people still pay back right, which is to say many of them were good credit risks, and any model that can help you serve that population is going to help. I mean that the populations that are traditionally underserved are going to be more aided by that kind of increase and accuracy than others. So I think it could be helpful to keep in mind that objective of saying, Hey, we need to apply the fair lending laws and we want to make sure we're falling them, but let's also can mind the objective of like increasing the population that we can serve and taking people who are unservable before and bringing them into a more traditional financial product, which is which would really value, which now, that only helps the community, it helps the financial institution build households, build families, right, and so I think it's a win win all around. It's just a matter of if it's a very new paradigm and you know, how do we feel about that? How the we accountable with that? Yeah, and I as you said, sometimes it just takes time. I know one of the other things that takes to build these kinds of models is kind of expertise that often doesn't exist in banks, which leads to this kind of you know, partnership with new or technology or Fintech type companies. How do you think about, you know, navigating the question of not just a model, let's say, but how do I find a good partner that I can rely on to be a partner in the space? How do you think about Fintech integration to the bank? It's, I think, is a huge topic and an interesting just its area. It is and is somebody who's looked at a lot of fintech providers. There's a lot of great ideas out there. There's a lot of great, you know, alternatives, but which ones work? which ones, because most fintext are still early stage, typically, maybe unprofitable, maybe VC funded right, and which ones of those are going to survive into a production environment, create a profitable business and be able to continue to move on, because you don't want to get halfway down the process, make a significant investment in a Fintech and then have the Fintech away right because because now you've want that investment, you're now behind you know, what can potentially be other peer groups that you're relying on and you want to take market Scheff them. So it it's a very chart and I would also say that we're getting better. But the traditional vendor management process in most organizations wasn't designed to be able to look at and unprofitable business and say, yeah, I want I want to leverage that unprofitable business. I want to use that vendor and make sure, you know, make some pretty big investments in my own there. Yeah, it's interesting because I hear a lot of banks or credit US talk to me about analyzing the capacity of a Fintech to serve a compliance program but your point about the operational risk of how survivable is that business as an...

...entity to continue working with? It's a really interesting one and it is probably pretty hard to think about in the context of an UNPROFITABISM. And most models will go cash burn rate equals out of business and x months, which is you know, a traditional banking model will go that it's not a good frol lend money to them. Yeah, so how do you how do you bridge that divide? If you found any secrets to how you think about finding companies you're comfortable with it, or maybe pray, I mean the obviously some of them gets a profitability and growth and number, but are there metrics you look at that get you more or less comfortable with investing in a FANTAC to baby. Is that probable? States of all, I think you need to have a good and understanding than the medical group. I mean they really need to understand the landscape, the true benefits that the attributes of the of the Fintech and bring to your organization. And then you've got to be able to say, okay, well, what you got to have the understanding from the Fintech what is your path to profitable? Tell us what Your Business Plan looks like, you know, because nobody's going to get in here. You know some exit strategies are yeah, we just want to get bought right and typically you don't hear that. Typically it is how do I become profitable, and what's my investment and typically it's future rounds of additional investment. And you know there are you look at the list of investors who are, you know, involved in the company and you look at their track record and you say, you know what, okay, this is probably one that, you know, I can take a significant amount of risk with because I think that they've got a good product, a good track record, a good investment community behind them and they're probably going to be one of the ones that does make it. Yeah, I can say like you may not exit strategies one thing, but usually companies like to buy companies they find that have a path to profitability to so absolute ever, your strategy is right, it kind of need a path to making money in your business or you got a fundamental problem. Right. Yeah, exactly, right. Well, and I think that you know, with that there can be okay, what is you know, maybe there's a play for the technology being used that goes beyond what is currently being youthful, right, and if you can find any youth case the technology that can up pull up a whole new set of doors. Yeah, yeah, how do you think about helping the vendor management process internal to the institution get improve? This is a I'll say I see a lot of my conversations with with banks and credit unions that they see the value in partnering with, you know, different kinds of organizations they have in the past for the future of the into organization. But the muscle around, how do I get good at diligence saying from you know, not just operation at risk, but maybe it's a credit policies, maybe it's, you know, regulatory risk, other things. How do I get the various stakeholders inside into a process where we can actually execute and test our way into successful folks. Feels like a critical capability for institutions to build, quite frankly, if they want to be good in the space. And I'm curious how you think about building that organizational muscle, because it's runs a little bit counter in some ways to the history of what those groups are meant to do inside the bank, which is prevent risk and slow things down a little bit it. You're absolutely right, and it does. I mean I talked about the vendom management piece before. That's certainly a key partner,...

...but so is, you know, in a lending environment, so is our credit risk partners. They've got to have a clear understanding. And then your Ip partners, right, so they're the ones that, you know, have probably the best, deepest understanding of what the technology is and what the roadmap to that technology looks like in the future from their perspective. So you need all of those parties, plus the business line, to be in a situation, in a situation where you can sit in room and talk about it, not be afraid to, you know, talk candidly about it, but understand that you know what are the benefits. So sometimes the risks have talked about a lot, the potential benefits don't, and you need to make sure that it's a balance conversation. That way and you know, find a way, and it's not always a pure technology play out of the box, but it may be. Okay, you know, vendor, if you do X, Y and Z, I can see a way that we can use your technology, but I need these risk amit against to be in placement for us to do that. That's interesting, coming back with a really a here's what we need to get comfortable. Imagine any FINTEX would would appreciate the clarity that that provides versus the kind of like, you know, sometimes we just couldn't get it through the committee. Is it's not helpful to the like hey, what's a place where you're going to be comfortable doing this sort of thing? Well, because typically if you give that answer, you're going to get a constructive response, right one that you may actually be able to work with. And beyond that, from a Fintech perspective, I've got a partner WHO's now able to help me build a product that maybe more salable in the general marketplace. So you know, it can typically be a one win. Yeah, and have you. Do you have any structure for how or thoughts on how you engage those partners or when you engage? Your point about making sure value, not just risk, is display, I think it's really good because so so many times I think if it kind of like my lawyer might hope my GC doesn't listen to this fee. Like so often lawyers feel like their job is not they feel like they're it feels like they're coming into like review at the last minute, tell you all the risks and kind of say no. And really I think the best ones are there to say, how do we understand the risks, find ways to limit them and kind of partner with you to help you achieve the value that you see while limiting the possible downsides? Well, that's right. How you think about creating that relationship with other different right? So that's the difference truly between risk mitigation risk avoidance, right. Yeah, so it's easy to avoid the ask. You just say no all the time, do Yeh, but but typically you wind up aging out of the market if you do that, if you start to figure out ways to mitigate the risk of the new tool that you're looking at and you understand what the what the benefit is. Two features and benefits that to are you should be able to manage a way out and you do it by developing relationships with the peers that you need at the table right, and those relationships need to be candid right, and that you're not saying you want to just be a somebody be your buddy. So they say yes, because you want to make sure you vet all all the risks, you understand the risk, you've mitigated the risk and then you stand back and go, okay, is my residual risk at and the reward adequate based on what we identify as the inherent risk?...

Yeah, that always love those concepts from our we go through our same compliance reviews and kind of like the inherent risk, admit against the and you can be pretty creative. And so we yourmit against size of a program for instance, or where you're deploying at acknowledge of the things that can limit the risk. You know what's the remaining risk down to a pretty manageable thing, even if the inherent risk is it harder to eliminate or reduced. And quite candidly, that's where you know things like creating a buybox. It says, okay, here's much hold, much risk I'm willing to take in the space right and and it typically it's balance, heat space or something like that. Okay, I think this products got value. I think we've mitigated the risk to a point where I'm willing to go this far. Then we get the experience and we see, okay, do we want to go farther? Our Room more called stable. Now have we been through some reviews that give us more certainty around this, this product or process? That's another great point, is the leverage of time to get the to understand and mitigate the risks. Actually say, Hey, we launched small, not that, because I often here. Will I will, we can only do this and it's not worth the effort. You'll this isn't the end result. This is where we start and how we build up the comfort in the history title bigger and and so you've that idea of that. You know, keeping it small to start as a risk it again, versus having to boil the ocean as we solve all the problems just to get a new product urnsue out the doors. It's a as a really interesting approach. Exactly. Yep. Now, I understand you took an interesting growth approach during the pandemic or diversification and actually acquired a new business. Tell me a little bit about you know, what drove that decision and what it's like to go through a transaction like that when we're all, you know, meeting virtually and in person. Yeah, so we are. The organization that I work with, Associated Bank, is a thirty five billion dollar Midwest Base Bank. We have a very heavy and we're very good at mortgages, but I think also became a very large horseman of our Balancy and we were looking for strategies to keep that mortgage business going and robust, but to diversify at the same time. Now put up a bouncy yeah. Right. So we looked at several other business lines and one of the business sides wot that was indirect auto. And you know, during the pandemic I made a contact in the in direct auto who I known for years. We rekindled our discussions and, frankly, he was in a position where he and and team were ready to make a move and we were able to negotiate the move over and negotiate some of the technology to come with it and stand up and indirect auto business in seven months. It's a great season team. We are, frankly, and footprint states. That will be in footprint states and the second quarter of next year. But we took their existing footprint and we just, you know, stood that up on our software with their team and, frankly, did it in record time and and we're very pleased with the results and very excited about the prospects for the next couple of years. It's fascinating to me because I hear so many banks skeptical of indirect auto or concerned about the...

...lack of like real customer relationships they build, the thinning of the margins. I've talked to several that have like basically run off their portfolios instead. I'm out of this game. I'm not originating. I'm going to either sell or just run off the portfolio. So I'm curious what was about that business that made that and appealing, you know, thing to for you guys to use to diversify the balance sheet away from a very mortgage heavy basis. Yeah, so I think you know, if you think about the mortgage base it's a traditionally, especially though we do it, or a prime lender, right, we don't do subprime. We don't give me your prime. We look at that and we say, okay, well, mortgages are great. We do it really, really well, but it is a low margin, long duration business. Right. It is excited us. If you're going to diversify. You know, if you think about auto, it is probably the second leading asset class for most consumers and it is shorter duration. It is higher yield, even though the yield may not be, you know, the the the the highest in in your portfolio, but it is a creative to our yield and that's important and we could do it with a group that knows it really well. It has a lot of great contacts in the industry. So I think all of those reasons, we're very good reasons for us to take that step into verse five, using the indirect on the space, and our mix of indirect auto is predominantly in the use space. We do an amount a new new business as well, but new car business, but we do a lot of use bit used car business, and that you typically comes a little bit higher yield. Yeah, that's that is that is fascinating that that you find a track gets. It all depends on your perspective. If you're coming from a high yield business, it looks it looks thin and if you're coming from the more the prime mortgage business, right, yeah, it's head in the other direction. Exagon. That was fascinating for me and I didn't ask. Is it mean, since your primary space is mortgage, what do you see happening in that space, particularly, as you know, rates rise? You know, we talked about broadening access or things like aim L and, and that's going to kind of fight the other way right, where we're going to be narrowing the box release a population we can serve. As rates rise, what do you see happening and how are you guys thinking about adjusting to the reality as these things kind of coming to and a reality? Yes, so, I mean obviously, as rates rise, we finance transaction opportunities go away. So you have left with a smaller market that is focused on purchase money. So that's that's existing homes, that's new construction and really and it's multi family obviously. But I think if you think about the first two of those categories, there are critical categories that, as you had continue to have home price appreciation, which may be slowing but continues to appreciate. If you have, you know, slower wage growth and the home price appreciation, the affordability gap widens. So how do you now serve for those gaps and people who want to all know, home? You've got to come up with creative ways to do that and typically you know that maybe you know, additional asset support. So it may be through grants, maybe to high AL TV products.

You've got to look at the afford not only the affordability, but you got to look at it from a different perspective. How are we going to go about doing that? How do we find the Barrows? What differentiates us in a market that's already overcrowded with refy lenders that now have to figure out a way to keep their business going? And how does that competition look? WHO's rational, who's not rational? So all of that will, you know, kind of work out over time, but it does create some unique challenges that we haven't had to face in quite a while. Yeah, it's been a while since we've been talking about this, this kind of environment coming our way and certainly some of the newer tech enable particularly the refly oriented lenders, I think are in for a you know, as you said, that refly business is going to get it's going to get pretty thin, I'm pretty pretty tough to execute. His rates go up, so that's going to put a lot of stress on everybody. Yeah, exactly, exactly, and I think. I do think that, you know, the lenders that do it well and have good, deep relationships and the purchase money space will continue to do well. I do think that, you know, one of the things that technology is helping us with is get from application of closing a heck of a lot quicker, using the same degree of certainty of, you know, authenticated information, whether that's aspects, whether it's abilities, whether it's income and employment. If you can get there sooner, you get a lot more nimble. It also, if you think about it, a sixty day or forty five day pipeline takes a lot of people to manage. If you now have a ten or fifteen day pipeline, that's a lot less management that goes into the process. So if you can do that routinely right for the majority of your population, that's going to be, you know, a distinct advantage in the world that we're going to live in going forward. Is that an are you guys are making investments? I'll say it's. It's maybe for us the place that we kind of underappreciated the value not just of being smarter about whose credit worthy and not, but of how quickly you can get to a hey, I'm confident in this application. We don't need to put a more hurtles in this bar wers. We let's get them, let's get them originated and shrink that time and it feels like to me in the industry a somewhat underappreciated part of what the technology platform needs to do is not just digitize what we're doing but really optimize the efficiency of that. You know that that whole end and process and removing the friction of the effort from quired of the borrower. Well and even where, and we've got some partners in that space that helps us with that technology. But even those spaces have, like you know, thirty five to fifty percent success rates because typically providers of the information haven't participated in that robust it right. So if I don't have a payroll company that's doing business with my vendor, well that's not going to be a hit for me. I'm going to have to go back at you with the usual way, which is going to go back and Yep, the other part of the process that needs a lot more attention is valuation. So evaluation, I think, if you were to ask most lenders, over the course of the last year,...

...has become one of the biggest challenges in trying to, you know, generate addequate term times, and that's for, you know, both our mortgage business in Er Home Equity Business and and you know, we think those are great opportunities for the future, but we need to be able to come up with a better method to do it, because the appraisal process is still about the same as it was years ago and it does use technology, but it takes far too long to come to evaluation determination Shin. That's acceptable and we're willing to go with so that's the part that we're working on as well. How much of these solutions do you think our technology, and how much of them are process things that you need to change or fix or rethink, whether it's a policy or a process, versus like just the application of technology to the absolutely both. It's going to be bold be because where you're looking at technical at regulations and policies that require a lot of manual work to come up with a result. Well, if you don't allow for technology and your policy, then you know you're never, never going to get there. So the policies got to come first, but the policy is going to be informed of the technology and you've got to be comfortable with the technology in order to change your policy. Yeah, it's a great point. I see some things like we're going to ply the technology and like if you don't have a policy that's going to accept just Avm as a simple example for certain kinds of transactions, you go technology can't fix that. You got to have the two acting of coordination. Again, how do you wear your risk met against? Like, I'm not going to do that for everything, but are there places where we can well do it right. So the more room I have on value, let's say value determination misses right. So sixty percent loan to value is opposed to a ninety five percent on the value. You know what, maybe I can afford in that space. I can't. I can't afford. I got to do a full praises. So that makes better use of the resources in the field to because you're only getting in on that. You know, one segment of the population. You put your applying those resources where they are. I making the biggest risk difference to the calculation for the institution. Exactly right. Yes, love it. Well, you know, I've gone through most of the questions I had. I had for you. Are there topics or areas you wanted to dive into that that I forgot to ask about today? You know, I don't think so. I think you know customer loyalty and customer so so we talked about Ai, we've talked about machine learning. At the end of the day, the person on the other end of the transactions a person. It's a consumer and you've got to find a way not only to use technology effectively to create a great customer relationship and a great customer experience, but you've also also got to be able to support that when a customer says I need is zero option right, I want to talk to somebody, and you know, chat bots are kind of in their infancy. I will tell you the chat bots of typically been we've struggled to effectively use chat bots because they are interpret the question the right way. So then the consumer becomes frustrated. So I think there's some more to be done there, but you've got to be able to provide a zero option for your consumer and one that's effective. So chat box for okay, but they got to understand the question.

I thought chat bots were such a fascinating place for financial institutions to a play apply. Am I to start or ML AI, because it's like it's like a really hard problem. It's like natural language processing plus like a nearly infinite problem space for things you can do, and I kind of always looked at it compared to like, let's say, a risk onder writing bottle with like really clear inputs, really clear outputs, right, you know, really great train to go away. That's like a tailor made problem for ML team. Then you go like somebody types in a question. You got to figure out what to do. Like that's like it's like nearly the hardest problem. From an M Al Tidy it seemed to be the where we went first. So that was always a fascinating development to me that they like, I think this is going to be harder than you think. To Really Act. I mean like maybe skipping the Ivr and like an Ivy are equivalent of like here's spoil things are chapots, one thing, but ask me a question, I'll give you an answer. This. It's a it is. But but the other thing is, how many people, if you talked to that go through an IV Arego? It's by the time you get to where your question is in the Ivre, it's forget it. That in twenty minutes. I I've frustrated. Yeah, so I do think it's an evolution in technology that needs to take place. But you're right, it's a big it's a big left. It is a big and I love your point that like it needs to be easy to I find this a technology is so great at simplifying transactional things. But then please don't make me go through a big Ivr or twenty stages in a chappot to go. I got a question. I need to talk to a human being. Can I want to check my balance? Yeah, I want to make a pain. I know how to make a payment on your website. I didn't call them. I will talk to somebody, and making that seamless and quick and easy I think is really valuable because in those moments when you need it, you really value making that accessible and fast. Yep, a great great all right, Tom Well, I've got three questions I ask everybody at the end of the podcast. So I'm I'm a fire match and we'll see what you got. Sure. My first question is what's the best piece of career advice you've ever gotten? Work harder than everybody else. Work harder than now. That's like an old school answer. People to like to just hear that answer. Give that answer anymore, but just work harder than everybody else. Smartlan everybody else. Yep, be the last. I am you're right, a very old school right and and not always popular with with the current environment. But work hard. I sometimes tell my kid this. It doesn't take doesn't take talent to work hard. Let's put the front in. Nobody can take that away from you. Well, frankly, look at the look at the football games. It took place over the weekend. There was a lot of harder work there that led to that. So yeah, there's a lot of hard work behind that. All right, work harder than everybody else. I like it. First piece of advice. Second, what's the best piece of advice you've gotten around consumer lending or consumer banking? Don't forget about the person at the other end of the transaction. HMM. Right, Ben, because if you put yourself in their shoes, not that you're going to make bad decisions, but you're going to be much more empathetic to what they're going through and be much better able to communicate your decision. And why I love that. I see putting the putting the customer first...

...and kind of understanding the perspective so valuable in any business, but but particular, I think, in a finance business, where it's easy to to lose the people in the numbers, if you will, exactly forget it. We'reget about what's really here for. So last question for you. What's one bold prediction about the future? Well, I would say bold prediction. Banks are going to get better at this, but they're not going to be the only ones in this base. Who's going to be in a space out than the banks? They could be bank regulated fintax. I think that there are there. There are a lot and more of those now. Yeah, and and are you know, frank, there they're going out there, they're getting smart. You know they're doing it tactically, but I think what's going to happen is they're going to get refined a little bit, which is probably good. Right. They got to be subject to the same level of regulation, but to make sure they do the right things. But at the end of the day they're very nimble and they're thinking outside the box, and that's what we've got to do in order to make sure over there. You think banks are going to figure out how to be as fast as the FENTTEX? I like it after or maybe not as fast as the ones are the move past and break things crowd. Maybe we don't be quite that fast to break things. Maybe that's a good objective. Exactly exactly now. All right, I like that good way in the podcast Tom thanks again for make the time. This was a fasting discussion. I appreciate your making the time for it. Thanks you. If I appreciate upstart 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 accurately identify risk and approve more applicants than traditional credit models. With 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 lenning programs or you're just getting started, upstart can help. Upstart offers an into end solution that can help you find more credit worthy borrowers within your risk profile, with all digital underwriting, on boarding, 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 FOR DASH banks. That's UPSTARTCOM FORWARD DASH 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 as 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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