Myra Thomas
Good day My name is Myra Thomas and I’m editor of Bank Automation News. Recently I had the pleasure of speaking with Jimmy Lenz director of the Master of Engineering and financial technology and Master of Engineering and society, cybersecurity. And Franken Irene Salerno Visiting Professor of financial economics at Duke University’s Pratt School of Engineering in the masters of engineering programs in FinTech and cyber security, he started his career as an equity and derivatives trader over 25 years ago, Jimmy found he reveled in fast moving atmospheres that required both strategic thought and the ability to take immediate action. Jimmy was an early adopter of electronic trading and leg later algorithmic trading solutions. His success propelled him into a number of senior management roles in the finance in the financial community, including leading nysc broker dealer with foreign and domestic operations chief risk officer and chief credit officer at a top three broker dealer and the head of predictive analytics for one of the largest wealth management firms in the US. Jimmy holds an undergraduate degree from the University of South Carolina Masters of Science in finance from Washington University in St. Louis, and doctor of business administrative administration finance from Washington University’s Olin Business School. Recently, we got a chance to talk about the unique partnership between Duke University’s Pratt School of Engineering and the Federal Deposit Insurance Corporation. The FDIC recently announced that strategic partnership to support their technological innovation in the banking and financial services sector. Our organization bank automation news recently had the chance to speak with solten manchi. The FDIC is first Chief Innovation Officer pointed earlier this year. And he noted and I quote, this exciting collaboration with Duke will amplify our efforts to drive innovation in the banking ecosystem. And within the FDIC, we share common interests to better understand the opportunities and the risks of new technologies, and to build a first of its kind strategic innovation program. Welcome, Jimmy, I really appreciate you taking time out of your busy schedule to speak with me today.Jimmy Lenz
Absolutely. Thank you very much for having me today. This is this is always exciting to talk to people.Myra Thomas
Yes. So you know, I guess the best place to start is what exactly is a master in masters in FinTech?Jimmy Lenz
Sure, great question. By the way, as a opener, the Master of Engineering in financial technology is almost one of a kind. There are only two engineering schools in the United States that offer a graduate degree like this. There are I know, several, several engineering schools that are trying. And so what we are doing is we’re providing students with a background and these are mainly students with quantitative undergraduate degrees, some are coming from industry, that was some industry experience. But with a little bit of a quantitative background, in all cases, the tools necessary to move into FinTech. And when I say move into FinTech, I mean, both the the the traditional FinTech companies, your alley pays your rocket mortgages, your places like that, as well as traditional firms that are kind of starting to to maybe move a little bit in that direction. You see some of the large banks and things like making large acquisitions, and we’re trying to build things internally. Well, that’s what we’re, we’re training students to do is to move into those roles.Myra Thomas
Sure, sure. So talk to me a little bit about how engineering fits into FinTech. Yeah,Jimmy Lenz
great question. I was so hoping you I asked that. So I previously have taught in business schools. And one of the things that I noticed about business schools, and hey, I can throw rocks because my graduate and doctorate are both from business schools. So I feel I can throw rocks a little bit. The the business schools are great. They tend to teach in a very theoretical manner. engineering schools teach in a very applied manner, right? engineers build things, they build bridges, they build buildings, they build software. And and for FinTech, this is something that is very applied. This isn’t a theoretical realm. People are hiring students to build things to create new things to develop new ideas into into products that can be used services that can be used. And so that’s why engineering I think, the the fifth in engineering is just perfect. When I have the opportunity to go to to go to Duke in any engineering school. It I just jumped at it because I knew this is where this is where FinTech really belonged.Myra Thomas
Sure, sure. And so, you know, looking at this new partnership with the FDIC, you know, it’s all and you know, Sultans, new role. It’s all revolving around innovation. But what does innovation really mean in the banking system? I mean, term.

Jimmy Lenz
sold sounds great by the way in, in that new role and kind of the way he thinks about it. But I think of you know FinTech in general, FinTech, I’ll give you an analogy here FinTech is to banking, what Google is to the internet. Not only is it a portal, but it’s a it’s a user designed experience. And so this is a this is a very different way for for banks to start thinking about things because in the past, banks have been kind of like a supermarket, you walk in, and you take what’s on the shelf. Well, FinTech has turned things around 180 degrees. Right now you go in and you design the user experience that you want, you interact like you want, usually on a mobile device. So think of Rocket Mortgage, why is Rocket Mortgage making over 50% of the loans in America today, because you can do it on your phone, and you do it when you want and how you want, you don’t go into an office, you don’t meet with a loan officer, you don’t carry in member bazillions of papers and all that you don’t do any of those things, right. It’s a user design experience. And people have gotten used to that people have gotten used to that, from the way they interact on the internet, the way they buy things, the way they do everything. And so why should banking be any different? Well, it’s not, of course, people are taking that and and running with it. And so those companies that are becoming most successful, are those companies that can allow users to define what their experience is going to be there no longer, you know, the the grocery store.

Myra Thomas
Jimmy Okay, well, I’m sorry about that he dropped, he dropped off for a second there. So you know, what role can automation play in this whole process? You know, what sort of technologies do you see rolling out, that can facilitate this innovation and banking,

Jimmy Lenz
there are a number of things that we’re already seeing happening. So automation is being used in a lot of different ways. And it’s being used both by FinTech companies and by traditional companies are starting to embrace more and more automation. In the past, banking has relied on people and when there was a problem, they brought more people in, well, now FinTech companies have started up. And they’ve one of the one of the advantages they have is they automate a lot, they automate a lot of processes. Now, there are a couple of advantages to doing this. And, you know, people see automation in a couple of different ways. A lot of people see it as eliminating jobs or just for efficiencies. But automation is actually a opens up a lot of a lot of new roles. And it’s also a really nice risk mitigant. The the regulator’s very rightly have said, we want to see more automation, we want to see more repeatable processes, we want to see things that happen in an automated fashion. And I think that’s exactly the right tack to take, what soltana is doing and what he is exploring, I think, is partially automation. And partially some of the new technologies that we see actually in finance, and you know, things like blockchain and some of the digital currencies and some of those kinds of things that are being embraced, which are also elements of this automated, you know, the this increase in automation that we’re seeing. Sure. Now, the

Myra Thomas
funny thing is, you know, you’re talking about this partnership, and we’re, you know, talking, when I reporter talk to solten, you know, getting the idea that the FDIC is looking at looking at itself as being the teacher being the initiator of automation, cutting edge automation in an innovation in the banking system. Whereas, you know, traditionally, the FDIC has been seen as a stop gap or a lifesaver to the banks or, you know, in other federal, you know, regulatory bodies, financial regulatory bodies are seen as adversaries, oftentimes, to financial institutions. So having the FDIC sort of come out, saying, you know, here’s our role, you know, sort of leading innovation seems kind of strange, correct. I mean, you know, do you get the sense that, you know, banks are going to buy into this process?

Jimmy Lenz
It does seem kind of strange, who will admit that, I think there have been a lot of role changes since the financial crisis. And where the FDIC has been seen as a stop gap. I think they’ve been seen as a little bit more of a partner than maybe some of the other regulatory agencies. And so I think there is at this point, some, I think they are there more banks are going to be more open to this kind of thing. The other thing about this is is they are the FDIC, they are the Federal Deposit Insurance Corporation, as an insurer, this will also help them right. So more automation, the quicker they can get information, the quicker they can help a bank that might be in distress, the fact that they see behind The curtain is everywhere, there are a set there amassing a lot of information, a lot of data, a lot of very dynamic data, or they at least they can have a lot of dynamic data. They may know a bank has a problem before the bank does. And they can step in a little bit quicker, I think in their role at ensure the fact that they’re pushing automation, the fact that they’re pushing innovation, I think that is it helps both them and their banking partners. And I think the banking partners will see that I really do believe that they’re the the part that the FDIC plays in the banking system allows them kind of a little bit more leeway than say if it was one of the other other regulators. Sure, sure.

Myra Thomas
So give me the skinny on, you know, what actually is happening with Duke and the FDIC? Well,

Jimmy Lenz
we, um, wow, I it’s, um, I think we were all amazed at how fast we hit the ground running. So we, we announced the partnership, and we, we, that was in the late spring. Within a month, they had already basically formulated a couple of internships they wanted our students to work on the the the issue that we had this year was we actually had a lot more internship offers for students and we had students for internships. But we ended up working with the FDIC on three different internships. So they deck it up that fast, they already have people assigned to it from the FDIC, we work with them to articulate the questions a little bit. And the students have been reporting out almost, I guess, reporting out weekly, to the the sponsors at the FDIC teams of students that are working on these problems. One of the problems, I know has been adjusted a little bit because it had so much interest within the FDIC, that they they met with some of that the heads of various departments, because of the early findings. So we hit the ground running really quickly, the students will continue to work on these internship projects, for the, you know, kind of the remainder of the summer it through through the end of July. And then I think in the in the fall, we have a couple of more things that are that are on on on deck right now to be initiated. I see this as an ongoing, I think we will continue to the FDIC will continue to work with us on all types of new projects and initiatives. So we a couple of our projects are more based on the legacy upgrading some of the legacy, and some of them are based on emerging technologies. So it’s they’re using us kind of across the board.

Myra Thomas
So you’re talking about obviously, legacy systems for the FDIC itself, I would assume, right?

Jimmy Lenz
these are these are, I would say, yes, legacy systems and kind of some of the just the things that banks are going to be saddled with for a long time. So different ways to think about them different approaches to take to to move things forward. And so we’re looking at some very, very data centric approaches to, you know, to answer certain questions and to move things and maybe a little bit direction, a different direction.

Myra Thomas
Yeah, I’m always amazed to when I talk to bankers, and I’ve talked to a lot of bankers, even big, you know, global banks, that when you get behind the scenes, you pull back the curtain, that there’s still a lot of manual processes that exist, you know, batch systems and whatever else that they’re doing behind the scenes that you would just be perplexed by. So, you know, automation efforts coming from the FDIC, you know, to push this seems like a, you know, really timely thing. But do you think there any sort of specific challenges within the banking world that the FDIC specifically wants to address?

Jimmy Lenz
I think there are a lot of there. I mean, salthill, you’ve met him, you’ve talked to him, he, he has a plate that, you know, just gigantic, so he’s always thinking about a lot of different things that, by the way, he’s an engineer, too. So he thinks about things and, and are really, really large way. And so I think there are a lot of legacy things that they’re looking at, they also have to be very, very cautious. And I know they are very, very cognizant of the difference. As you mentioned, you talk to all kinds of bankers, you know, global banks, but there’s also these 5000 community banks that they deal with that have very, very different resources and resource constraints and things like that. And so they’re really trying to think I think across the constituency, and one of the things that they’ve kind of tasked us to do is to think across that constituency, so that we can you know, it basically improve the improve things for all of their, of all of their their clients. rather than, you know, just the global banks, or just maybe the Super Regionals or they’re really, really trying to look across the platform, which of course is much harder because of the different constraints that different banks have.

Myra Thomas
Sure. I mean, yeah, like you say, I mean, I recently spoke with a relatively large community develop, well, relatively small, forgive me, community development, financial institution, and I know that the Biden agenda is pushing, you know, trying to figure out how to aid these institutions. And I guess today for financial institutions, that really means automation, you know, whether it’s, you know, loan turnover time, loan turn, you know, turn rates, or whatever it might be automation is the key to all of this. And looking at, I guess, the next stage, you know, artificial intelligence, obviously, is, you know, the thing that banks are talking about now, and deploying automation, automation related to AI. And, obviously, the unintended consequence of this is possible bias. And I know that the FDIC is very much interested in figuring out how to shepherd these integrations without, you know, that unintended bias being a part of it. But I’m also interested in add banks, but I’m also interested in how the FDIC sees utilizing AI within their own organization is that something that you guys will be addressing,

Jimmy Lenz
we are addressing some aspects of AI and machine learning within the within the the larger ecosystem, not within the FDIC, but within their constituent banks. And we are looking at that, in fact, we’ve been contacted by another regulator, to help them with with bias with identifying certain kinds of bias, and, you know, making the making them, making them aware of different different sorts of approaches and things like that. So there are, that’s something that’s very top of mind, we think with with everyone, it’s one of the, I would say it’s one of the unseen or unforeseen consequences of a proliferation of AI and machine learning tools is right now, machine learning tools are very accessible. But having the being able to use them, and understanding what the outputs are, are two very different things. And I do worry about that a little bit. soltana and I have talked about this at length

Jimmy Lenz
that while machine learning tools are out there, understanding what goes in, and what comes out is really important. And that’s that’s one of the things that I spent a fair amount of time actually teaching machine learning in, in FinTech, like I’ll be teaching it this semester I’m in and I spent a fair amount of time on on bias in you know, in different kinds of machine learning applications, things like that, and how to how to detect it, how to how to look for it, how to be very overt about about those kinds of things. And so I think, I think you bring up a great point, and I don’t think it can be brought up enough. I do worry about that, though, with this proliferation of tools. People that are not trained, and are not don’t understand, you know, some of the impacts of what they’re doing, as well as maybe they they could, I think it really calls for experts who understand econometrics and understand statistics, understand, you know, how these these different algorithms work, because otherwise you do you do end up with these things. And I really do believe that a lot of the bias that we see, and there have been some really, really bad cases of it, right, some of the bias that we’ve seen, it’s unintentional, I really think it’s, it’s because in a lot of cases, the folks that are that are, that are putting these together are just not as you know, don’t have as much experience as they might, in you know, in these areas know what to look for and know how to measure for these kinds of things. I don’t think people overtly go out and say, I’m going to do something bad. I think they just don’t know.

Myra Thomas
So talk to me a little bit about this, because I got into arguments with people about this trying to explain it to now now I’ve got a teacher here. very educated teacher. The

Jimmy Lenz
the idea of bias of sometimes that we have what’s called omitted variable bias. So you you may have, you may be putting together a machine learning algorithm to for anything, it could be. It could be for credit decisioning or it could be for you know, the flavor of popsicles people like doesn’t really matter. And you’re you’re putting you’re bringing in all of these variables, all these features that you want to include and you want to test to see do these have a statistical significance? Well, if you don’t even consider something this omitted variable bias if something was never a consideration, you may bias your results. And not even not even understand that there was something you should have included that you didn’t, you know, those kinds of things now can we test

Unknown Speaker
for that

Jimmy Lenz
we can test for some of those kinds of things, not all of them, but we can can test for some of them. But only if you’re aware of the fact that you can do that. You know, sometimes I tell students, if you’re, if you’re, you know, results look too good, be very suspect. There’s probably something wrong. I know that you’re not smart students, but be very suspect when your results are better than you expect. And sometimes people don’t people aren’t suspect. And so I think those kinds of things occur, as I said, I don’t think most people go out with the intention of you know, I’m, I want to do something wrong, I think they just don’t know.

Myra Thomas
Right, right. Explain to our audience the difference between AI and machine learning,

Jimmy Lenz
no, machine learning is a school under the AI umbrella. So it’s part of the the big AI umbrella. So artificial intelligence is, is rather large machine learning is part of that. And machine learning,

Jimmy Lenz
What we do is we use that to detect different kinds of patterns in data that wouldn’t be detected otherwise. And they and we use a lot of different algorithms to do this. So, you know, we may test if we’re, if we’re doing something, not only a bunch of different variables, but a bunch of different algorithms that we use, that are used that are really useful for different kinds of purposes, their regression algorithms, and there are clustering algorithms, there’s all kinds of things that are out there, that we use to detect certain patterns and, and to forecast things. Because at the end of the day, almost all of these are used for forecasting purposes, sometimes for categorization and things like that. But usually,

we’re going to even use those for some kind of forecasting purposes. And they tend to be a because of the the nature of machine learning, they tend to be very, very, they can’t be very accurate, in in doing this kind of thing. But we’re using them typically for those kinds of purposes, but there’s not, you know, the one thing that, you know, I want people to to make sure people understand is, when we talk about machine learning, it’s not like there’s a machine learning algorithm, there are hundreds of these, there are new ones being developed all the time. And every time you you tweak, one, you just created a new one. And we do that all the time. In fact, that’s what I teach students how to do is this now you can adjust the algorithms, you know, once they learn the kind of the math behind them. So yeah, those those kinds of things occur.

Myra Thomas
What do you think is the best application of artificial intelligence for a bank or financials to have? Or for FinTech? What do you see as some of the better applications of AI?

Jimmy Lenz
Yeah, I think there are a number, one of the things that I’ve always kind of been a fan of is giving customers back their own data. And so think of think about it this way, if you’re a small business, and you’re using a bank, and the bank doesn’t really matter, that bank has seen all of your cash flows. Not only are they seeing all the cash flows, they’re seeing the times that the cash flows come in both time as far as chronological time, in business cycles, macro economic cycles, things like that, such that and they also see all of a lot of your competitors, in similar industries. And so they are seeing a lot of different things. What if the bank could use that and give it back to you and say, Hey, we notice that you know, in a certain business cycle, you are probably going to need, you’re probably going to ramp up your production. And so you may need a larger line of credit, before they actually need it. What if you could do things like that, basically give people back their own data, because this is data that it might be hard for them to analyze? We were talking about, you know, using machine learning and computational power and things like that. Well, banks have a lot of that. What if you could do that for an individual to? What if you could, what if you gave them back their own data in a really consumable form? That said, Hey, it looks like, you know, this is happening, this might happen. And and maybe it’s, it’s a little bit like, when you go to Amazon, you buy a book, and they said, people who buy this book, also like these three, and you look at the other three, and you’re like, wow, that other one looks pretty good. Um, there’s there, there’s a real value to that. I mean, sure, Amazon’s trying to sell you another book. But they’re sifting through all of this data that you could never do yourself. They can also see across this large spectrum of things that are occurring, that you can’t do. So I love the idea of giving you back your own data in a really consumable form. Maybe it sells you more services, maybe it just tells you something about your business. Maybe they tell you hey, if you’re a coffee shop in, you know, Seattle, and it’s a sunny day, you know, expect your business to be off 10% I don’t know you know, there are all kinds of things like that. That they can see. But as a you know, as a small business owner or medium sized business owner, you may not be aware of.

Myra Thomas
Sure. So, you know, if the FDIC is championing, you know, innovation within their own organization, as well, as, you know, trying to promote it, financial institutions in the US, they turned to do so why university? Why do they turn to you? Why do they turn to your students?

Jimmy Lenz
I think there are a couple of reasons. One, because these, the students that they’re dealing with in a lot of cases are very similar what you would hire if you hired one of the, you know, big consulting firms, right, they’re usually fairly early in their career people that would show up, but they’re in the process of learning the very latest techniques. So you mentioned machine learning and artificial intelligence, they’re just learning the latest techniques right now. So they’re going to be very, very on, you know, the newest technologies and things along those lines. They are also I think, in a mode, and I love this about students, one of the things I love about working with students, is they’re not jaded by experience. And I’ll tell you what I mean, by that, you know, I’m, I’ve been around a little while. So if I see a problem, a finance problem, you know, in the back of my mind, it’s like, Wow, I’ve seen something like this before, I have a pretty high degree of confidence how to solve for this problem. Students have never seen that before. So they will come at it in a totally different way. I can’t tell you how many times that’s happened, where students will come at a problem. And they’ll bring a solution. It’s like, where’d you come up with that? And there’ll be well, I was working for, you know, Daimler Benz in Beijing last last year on an internship and we had this problem, and it’s like, wow, yeah, I’ve never worked for Daimler Benz in Beijing before. So that’s never going to be a consideration of mine. They’re not jaded by experience. So they are, I think, sometimes the most objective of really, really educated sources that you can go to, you also have all these professors that are doing research, cutting, edge research, they’re teaching, and so they’re staying very, very apprised of the latest technologies. And students have these as a resource, rather than just having maybe if you were hired a consulting firm, you know, one or two partners, they have a university full of researchers, this is what they do for a living. So I think the advantage of using a university is really multi dimensional. But those are the those are the big ones that come to mind.

Myra Thomas
Sure, sure. So talk to me about what might be the first if I know you can’t reveal too much. But what do you think if you had the list 123. The first major 123 pushes for the FDIC, and this new initiative and what they’re doing, we’ll be working on so she had to say, you know, we’re working on, you know, x as far as automation, what would those three things or even one thing be?

Jimmy Lenz
Yeah, I think they’re exploring a couple of different things. As I said, they are exploring something I can’t be I can’t be too specific, they are exploring some aspects. And Sultana has talked about, you know, digital assets and things along those lines. So they are exploring some things in that, in that universe. They’re exploring some attributes of banking of people that are consumers of banks, they are certainly using students to to explore some of those kinds of things. And so those are those are probably the top two that we’re working on. And then there’s the third is a general automation of processes and and how that can actually be facilitated. So those are kind of one two and three, I would say in no particular order. You know, the the some of the some of the the the factors around digital assets, some of the the attributes of consumers and their interactions with banks, and then some of the attributes of automation, large scale automation within financial institutions.

Myra Thomas
Well, that sounds like a good place to stop. Thank you so much, Jamie, for joining us. That wraps up this episode of the Buzz. Thanks for listening and please let us know how we’re doing at Bank automation news.com and of course on Twitter and LinkedIn. Thanks very much. Thanks for listening.

Myra Thomas
Good day My name is Myra Thomas and I’m editor of Bank Automation News. Recently I had the pleasure of speaking with Jimmy Lenz director of the Master of Engineering and financial technology and Master of Engineering and society, cybersecurity. And Franken Irene Salerno Visiting Professor of financial economics at Duke University’s Pratt School of Engineering in the masters of engineering programs in FinTech and cyber security, he started his career as an equity and derivatives trader over 25 years ago, Jimmy found he reveled in fast moving atmospheres that required both strategic thought and the ability to take immediate action. Jimmy was an early adopter of electronic trading and leg later algorithmic trading solutions. His success propelled him into a number of senior management roles in the finance in the financial community, including leading nysc broker dealer with foreign and domestic operations chief risk officer and chief credit officer at a top three broker dealer and the head of predictive analytics for one of the largest wealth management firms in the US. Jimmy holds an undergraduate degree from the University of South Carolina Masters of Science in finance from Washington University in St. Louis, and doctor of business administrative administration finance from Washington University’s Olin Business School. Recently, we got a chance to talk about the unique partnership between Duke University’s Pratt School of Engineering and the Federal Deposit Insurance Corporation. The FDIC recently announced that strategic partnership to support their technological innovation in the banking and financial services sector. Our organization bank automation news recently had the chance to speak with solten manchi. The FDIC is first Chief Innovation Officer pointed earlier this year. And he noted and I quote, this exciting collaboration with Duke will amplify our efforts to drive innovation in the banking ecosystem. And within the FDIC, we share common interests to better understand the opportunities and the risks of new technologies, and to build a first of its kind strategic innovation program. Welcome, Jimmy, I really appreciate you taking time out of your busy schedule to speak with me today.Jimmy Lenz
Absolutely. Thank you very much for having me today. This is this is always exciting to talk to people.Myra Thomas
Yes. So you know, I guess the best place to start is what exactly is a master in masters in FinTech?Jimmy Lenz
Sure, great question. By the way, as a opener, the Master of Engineering in financial technology is almost one of a kind. There are only two engineering schools in the United States that offer a graduate degree like this. There are I know, several, several engineering schools that are trying. And so what we are doing is we’re providing students with a background and these are mainly students with quantitative undergraduate degrees, some are coming from industry, that was some industry experience. But with a little bit of a quantitative background, in all cases, the tools necessary to move into FinTech. And when I say move into FinTech, I mean, both the the the traditional FinTech companies, your alley pays your rocket mortgages, your places like that, as well as traditional firms that are kind of starting to to maybe move a little bit in that direction. You see some of the large banks and things like making large acquisitions, and we’re trying to build things internally. Well, that’s what we’re, we’re training students to do is to move into those roles.Myra Thomas
Sure, sure. So talk to me a little bit about how engineering fits into FinTech. Yeah,Jimmy Lenz
great question. I was so hoping you I asked that. So I previously have taught in business schools. And one of the things that I noticed about business schools, and hey, I can throw rocks because my graduate and doctorate are both from business schools. So I feel I can throw rocks a little bit. The the business schools are great. They tend to teach in a very theoretical manner. engineering schools teach in a very applied manner, right? engineers build things, they build bridges, they build buildings, they build software. And and for FinTech, this is something that is very applied. This isn’t a theoretical realm. People are hiring students to build things to create new things to develop new ideas into into products that can be used services that can be used. And so that’s why engineering I think, the the fifth in engineering is just perfect. When I have the opportunity to go to to go to Duke in any engineering school. It I just jumped at it because I knew this is where this is where FinTech really belonged.Myra Thomas
Sure, sure. And so, you know, looking at this new partnership with the FDIC, you know, it’s all and you know, Sultans, new role. It’s all revolving around innovation. But what does innovation really mean in the banking system? I mean, term.

Jimmy Lenz
sold sounds great by the way in, in that new role and kind of the way he thinks about it. But I think of you know FinTech in general, FinTech, I’ll give you an analogy here FinTech is to banking, what Google is to the internet. Not only is it a portal, but it’s a it’s a user designed experience. And so this is a this is a very different way for for banks to start thinking about things because in the past, banks have been kind of like a supermarket, you walk in, and you take what’s on the shelf. Well, FinTech has turned things around 180 degrees. Right now you go in and you design the user experience that you want, you interact like you want, usually on a mobile device. So think of Rocket Mortgage, why is Rocket Mortgage making over 50% of the loans in America today, because you can do it on your phone, and you do it when you want and how you want, you don’t go into an office, you don’t meet with a loan officer, you don’t carry in member bazillions of papers and all that you don’t do any of those things, right. It’s a user design experience. And people have gotten used to that people have gotten used to that, from the way they interact on the internet, the way they buy things, the way they do everything. And so why should banking be any different? Well, it’s not, of course, people are taking that and and running with it. And so those companies that are becoming most successful, are those companies that can allow users to define what their experience is going to be there no longer, you know, the the grocery store.

Myra Thomas
Jimmy Okay, well, I’m sorry about that he dropped, he dropped off for a second there. So you know, what role can automation play in this whole process? You know, what sort of technologies do you see rolling out, that can facilitate this innovation and banking,

Jimmy Lenz
there are a number of things that we’re already seeing happening. So automation is being used in a lot of different ways. And it’s being used both by FinTech companies and by traditional companies are starting to embrace more and more automation. In the past, banking has relied on people and when there was a problem, they brought more people in, well, now FinTech companies have started up. And they’ve one of the one of the advantages they have is they automate a lot, they automate a lot of processes. Now, there are a couple of advantages to doing this. And, you know, people see automation in a couple of different ways. A lot of people see it as eliminating jobs or just for efficiencies. But automation is actually a opens up a lot of a lot of new roles. And it’s also a really nice risk mitigant. The the regulator’s very rightly have said, we want to see more automation, we want to see more repeatable processes, we want to see things that happen in an automated fashion. And I think that’s exactly the right tack to take, what soltana is doing and what he is exploring, I think, is partially automation. And partially some of the new technologies that we see actually in finance, and you know, things like blockchain and some of the digital currencies and some of those kinds of things that are being embraced, which are also elements of this automated, you know, the this increase in automation that we’re seeing. Sure. Now, the

Myra Thomas
funny thing is, you know, you’re talking about this partnership, and we’re, you know, talking, when I reporter talk to solten, you know, getting the idea that the FDIC is looking at looking at itself as being the teacher being the initiator of automation, cutting edge automation in an innovation in the banking system. Whereas, you know, traditionally, the FDIC has been seen as a stop gap or a lifesaver to the banks or, you know, in other federal, you know, regulatory bodies, financial regulatory bodies are seen as adversaries, oftentimes, to financial institutions. So having the FDIC sort of come out, saying, you know, here’s our role, you know, sort of leading innovation seems kind of strange, correct. I mean, you know, do you get the sense that, you know, banks are going to buy into this process?

Jimmy Lenz
It does seem kind of strange, who will admit that, I think there have been a lot of role changes since the financial crisis. And where the FDIC has been seen as a stop gap. I think they’ve been seen as a little bit more of a partner than maybe some of the other regulatory agencies. And so I think there is at this point, some, I think they are there more banks are going to be more open to this kind of thing. The other thing about this is is they are the FDIC, they are the Federal Deposit Insurance Corporation, as an insurer, this will also help them right. So more automation, the quicker they can get information, the quicker they can help a bank that might be in distress, the fact that they see behind The curtain is everywhere, there are a set there amassing a lot of information, a lot of data, a lot of very dynamic data, or they at least they can have a lot of dynamic data. They may know a bank has a problem before the bank does. And they can step in a little bit quicker, I think in their role at ensure the fact that they’re pushing automation, the fact that they’re pushing innovation, I think that is it helps both them and their banking partners. And I think the banking partners will see that I really do believe that they’re the the part that the FDIC plays in the banking system allows them kind of a little bit more leeway than say if it was one of the other other regulators. Sure, sure.

Myra Thomas
So give me the skinny on, you know, what actually is happening with Duke and the FDIC? Well,

Jimmy Lenz
we, um, wow, I it’s, um, I think we were all amazed at how fast we hit the ground running. So we, we announced the partnership, and we, we, that was in the late spring. Within a month, they had already basically formulated a couple of internships they wanted our students to work on the the the issue that we had this year was we actually had a lot more internship offers for students and we had students for internships. But we ended up working with the FDIC on three different internships. So they deck it up that fast, they already have people assigned to it from the FDIC, we work with them to articulate the questions a little bit. And the students have been reporting out almost, I guess, reporting out weekly, to the the sponsors at the FDIC teams of students that are working on these problems. One of the problems, I know has been adjusted a little bit because it had so much interest within the FDIC, that they they met with some of that the heads of various departments, because of the early findings. So we hit the ground running really quickly, the students will continue to work on these internship projects, for the, you know, kind of the remainder of the summer it through through the end of July. And then I think in the in the fall, we have a couple of more things that are that are on on on deck right now to be initiated. I see this as an ongoing, I think we will continue to the FDIC will continue to work with us on all types of new projects and initiatives. So we a couple of our projects are more based on the legacy upgrading some of the legacy, and some of them are based on emerging technologies. So it’s they’re using us kind of across the board.

Myra Thomas
So you’re talking about obviously, legacy systems for the FDIC itself, I would assume, right?

Jimmy Lenz
these are these are, I would say, yes, legacy systems and kind of some of the just the things that banks are going to be saddled with for a long time. So different ways to think about them different approaches to take to to move things forward. And so we’re looking at some very, very data centric approaches to, you know, to answer certain questions and to move things and maybe a little bit direction, a different direction.

Myra Thomas
Yeah, I’m always amazed to when I talk to bankers, and I’ve talked to a lot of bankers, even big, you know, global banks, that when you get behind the scenes, you pull back the curtain, that there’s still a lot of manual processes that exist, you know, batch systems and whatever else that they’re doing behind the scenes that you would just be perplexed by. So, you know, automation efforts coming from the FDIC, you know, to push this seems like a, you know, really timely thing. But do you think there any sort of specific challenges within the banking world that the FDIC specifically wants to address?

Jimmy Lenz
I think there are a lot of there. I mean, salthill, you’ve met him, you’ve talked to him, he, he has a plate that, you know, just gigantic, so he’s always thinking about a lot of different things that, by the way, he’s an engineer, too. So he thinks about things and, and are really, really large way. And so I think there are a lot of legacy things that they’re looking at, they also have to be very, very cautious. And I know they are very, very cognizant of the difference. As you mentioned, you talk to all kinds of bankers, you know, global banks, but there’s also these 5000 community banks that they deal with that have very, very different resources and resource constraints and things like that. And so they’re really trying to think I think across the constituency, and one of the things that they’ve kind of tasked us to do is to think across that constituency, so that we can you know, it basically improve the improve things for all of their, of all of their their clients. rather than, you know, just the global banks, or just maybe the Super Regionals or they’re really, really trying to look across the platform, which of course is much harder because of the different constraints that different banks have.

Myra Thomas
Sure. I mean, yeah, like you say, I mean, I recently spoke with a relatively large community develop, well, relatively small, forgive me, community development, financial institution, and I know that the Biden agenda is pushing, you know, trying to figure out how to aid these institutions. And I guess today for financial institutions, that really means automation, you know, whether it’s, you know, loan turnover time, loan turn, you know, turn rates, or whatever it might be automation is the key to all of this. And looking at, I guess, the next stage, you know, artificial intelligence, obviously, is, you know, the thing that banks are talking about now, and deploying automation, automation related to AI. And, obviously, the unintended consequence of this is possible bias. And I know that the FDIC is very much interested in figuring out how to shepherd these integrations without, you know, that unintended bias being a part of it. But I’m also interested in add banks, but I’m also interested in how the FDIC sees utilizing AI within their own organization is that something that you guys will be addressing,

Jimmy Lenz
we are addressing some aspects of AI and machine learning within the within the the larger ecosystem, not within the FDIC, but within their constituent banks. And we are looking at that, in fact, we’ve been contacted by another regulator, to help them with with bias with identifying certain kinds of bias, and, you know, making the making them, making them aware of different different sorts of approaches and things like that. So there are, that’s something that’s very top of mind, we think with with everyone, it’s one of the, I would say it’s one of the unseen or unforeseen consequences of a proliferation of AI and machine learning tools is right now, machine learning tools are very accessible. But having the being able to use them, and understanding what the outputs are, are two very different things. And I do worry about that a little bit. soltana and I have talked about this at length

Jimmy Lenz
that while machine learning tools are out there, understanding what goes in, and what comes out is really important. And that’s that’s one of the things that I spent a fair amount of time actually teaching machine learning in, in FinTech, like I’ll be teaching it this semester I’m in and I spent a fair amount of time on on bias in you know, in different kinds of machine learning applications, things like that, and how to how to detect it, how to how to look for it, how to be very overt about about those kinds of things. And so I think, I think you bring up a great point, and I don’t think it can be brought up enough. I do worry about that, though, with this proliferation of tools. People that are not trained, and are not don’t understand, you know, some of the impacts of what they’re doing, as well as maybe they they could, I think it really calls for experts who understand econometrics and understand statistics, understand, you know, how these these different algorithms work, because otherwise you do you do end up with these things. And I really do believe that a lot of the bias that we see, and there have been some really, really bad cases of it, right, some of the bias that we’ve seen, it’s unintentional, I really think it’s, it’s because in a lot of cases, the folks that are that are, that are putting these together are just not as you know, don’t have as much experience as they might, in you know, in these areas know what to look for and know how to measure for these kinds of things. I don’t think people overtly go out and say, I’m going to do something bad. I think they just don’t know.

Myra Thomas
So talk to me a little bit about this, because I got into arguments with people about this trying to explain it to now now I’ve got a teacher here. very educated teacher. The

Jimmy Lenz
the idea of bias of sometimes that we have what’s called omitted variable bias. So you you may have, you may be putting together a machine learning algorithm to for anything, it could be. It could be for credit decisioning or it could be for you know, the flavor of popsicles people like doesn’t really matter. And you’re you’re putting you’re bringing in all of these variables, all these features that you want to include and you want to test to see do these have a statistical significance? Well, if you don’t even consider something this omitted variable bias if something was never a consideration, you may bias your results. And not even not even understand that there was something you should have included that you didn’t, you know, those kinds of things now can we test

Unknown Speaker
for that

Jimmy Lenz
we can test for some of those kinds of things, not all of them, but we can can test for some of them. But only if you’re aware of the fact that you can do that. You know, sometimes I tell students, if you’re, if you’re, you know, results look too good, be very suspect. There’s probably something wrong. I know that you’re not smart students, but be very suspect when your results are better than you expect. And sometimes people don’t people aren’t suspect. And so I think those kinds of things occur, as I said, I don’t think most people go out with the intention of you know, I’m, I want to do something wrong, I think they just don’t know.

Myra Thomas
Right, right. Explain to our audience the difference between AI and machine learning,

Jimmy Lenz
no, machine learning is a school under the AI umbrella. So it’s part of the the big AI umbrella. So artificial intelligence is, is rather large machine learning is part of that. And machine learning,

Jimmy Lenz
What we do is we use that to detect different kinds of patterns in data that wouldn’t be detected otherwise. And they and we use a lot of different algorithms to do this. So, you know, we may test if we’re, if we’re doing something, not only a bunch of different variables, but a bunch of different algorithms that we use, that are used that are really useful for different kinds of purposes, their regression algorithms, and there are clustering algorithms, there’s all kinds of things that are out there, that we use to detect certain patterns and, and to forecast things. Because at the end of the day, almost all of these are used for forecasting purposes, sometimes for categorization and things like that. But usually,

we’re going to even use those for some kind of forecasting purposes. And they tend to be a because of the the nature of machine learning, they tend to be very, very, they can’t be very accurate, in in doing this kind of thing. But we’re using them typically for those kinds of purposes, but there’s not, you know, the one thing that, you know, I want people to to make sure people understand is, when we talk about machine learning, it’s not like there’s a machine learning algorithm, there are hundreds of these, there are new ones being developed all the time. And every time you you tweak, one, you just created a new one. And we do that all the time. In fact, that’s what I teach students how to do is this now you can adjust the algorithms, you know, once they learn the kind of the math behind them. So yeah, those those kinds of things occur.

Myra Thomas
What do you think is the best application of artificial intelligence for a bank or financials to have? Or for FinTech? What do you see as some of the better applications of AI?

Jimmy Lenz
Yeah, I think there are a number, one of the things that I’ve always kind of been a fan of is giving customers back their own data. And so think of think about it this way, if you’re a small business, and you’re using a bank, and the bank doesn’t really matter, that bank has seen all of your cash flows. Not only are they seeing all the cash flows, they’re seeing the times that the cash flows come in both time as far as chronological time, in business cycles, macro economic cycles, things like that, such that and they also see all of a lot of your competitors, in similar industries. And so they are seeing a lot of different things. What if the bank could use that and give it back to you and say, Hey, we notice that you know, in a certain business cycle, you are probably going to need, you’re probably going to ramp up your production. And so you may need a larger line of credit, before they actually need it. What if you could do things like that, basically give people back their own data, because this is data that it might be hard for them to analyze? We were talking about, you know, using machine learning and computational power and things like that. Well, banks have a lot of that. What if you could do that for an individual to? What if you could, what if you gave them back their own data in a really consumable form? That said, Hey, it looks like, you know, this is happening, this might happen. And and maybe it’s, it’s a little bit like, when you go to Amazon, you buy a book, and they said, people who buy this book, also like these three, and you look at the other three, and you’re like, wow, that other one looks pretty good. Um, there’s there, there’s a real value to that. I mean, sure, Amazon’s trying to sell you another book. But they’re sifting through all of this data that you could never do yourself. They can also see across this large spectrum of things that are occurring, that you can’t do. So I love the idea of giving you back your own data in a really consumable form. Maybe it sells you more services, maybe it just tells you something about your business. Maybe they tell you hey, if you’re a coffee shop in, you know, Seattle, and it’s a sunny day, you know, expect your business to be off 10% I don’t know you know, there are all kinds of things like that. That they can see. But as a you know, as a small business owner or medium sized business owner, you may not be aware of.

Myra Thomas
Sure. So, you know, if the FDIC is championing, you know, innovation within their own organization, as well, as, you know, trying to promote it, financial institutions in the US, they turned to do so why university? Why do they turn to you? Why do they turn to your students?

Jimmy Lenz
I think there are a couple of reasons. One, because these, the students that they’re dealing with in a lot of cases are very similar what you would hire if you hired one of the, you know, big consulting firms, right, they’re usually fairly early in their career people that would show up, but they’re in the process of learning the very latest techniques. So you mentioned machine learning and artificial intelligence, they’re just learning the latest techniques right now. So they’re going to be very, very on, you know, the newest technologies and things along those lines. They are also I think, in a mode, and I love this about students, one of the things I love about working with students, is they’re not jaded by experience. And I’ll tell you what I mean, by that, you know, I’m, I’ve been around a little while. So if I see a problem, a finance problem, you know, in the back of my mind, it’s like, Wow, I’ve seen something like this before, I have a pretty high degree of confidence how to solve for this problem. Students have never seen that before. So they will come at it in a totally different way. I can’t tell you how many times that’s happened, where students will come at a problem. And they’ll bring a solution. It’s like, where’d you come up with that? And there’ll be well, I was working for, you know, Daimler Benz in Beijing last last year on an internship and we had this problem, and it’s like, wow, yeah, I’ve never worked for Daimler Benz in Beijing before. So that’s never going to be a consideration of mine. They’re not jaded by experience. So they are, I think, sometimes the most objective of really, really educated sources that you can go to, you also have all these professors that are doing research, cutting, edge research, they’re teaching, and so they’re staying very, very apprised of the latest technologies. And students have these as a resource, rather than just having maybe if you were hired a consulting firm, you know, one or two partners, they have a university full of researchers, this is what they do for a living. So I think the advantage of using a university is really multi dimensional. But those are the those are the big ones that come to mind.

Myra Thomas
Sure, sure. So talk to me about what might be the first if I know you can’t reveal too much. But what do you think if you had the list 123. The first major 123 pushes for the FDIC, and this new initiative and what they’re doing, we’ll be working on so she had to say, you know, we’re working on, you know, x as far as automation, what would those three things or even one thing be?

Jimmy Lenz
Yeah, I think they’re exploring a couple of different things. As I said, they are exploring something I can’t be I can’t be too specific, they are exploring some aspects. And Sultana has talked about, you know, digital assets and things along those lines. So they are exploring some things in that, in that universe. They’re exploring some attributes of banking of people that are consumers of banks, they are certainly using students to to explore some of those kinds of things. And so those are those are probably the top two that we’re working on. And then there’s the third is a general automation of processes and and how that can actually be facilitated. So those are kind of one two and three, I would say in no particular order. You know, the the some of the some of the the the factors around digital assets, some of the the attributes of consumers and their interactions with banks, and then some of the attributes of automation, large scale automation within financial institutions.

Myra Thomas
Well, that sounds like a good place to stop. Thank you so much, Jamie, for joining us. That wraps up this episode of the Buzz. Thanks for listening and please let us know how we’re doing at Bank automation news.com and of course on Twitter and LinkedIn. Thanks very much. Thanks for listening.