Tuesday, June 4, 2024
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Podcast: AI prescription for banks

Financial institutions look to their tech providers to help them embrace new technologies, including AI. 

At cloud-based fintech nCino, Chief Industry Innovation Officer Anthony Morris works to identify technologies that banks need to implement to keep up with the “industry ahead of them,” he tells Bank Automation News on this episode of “The Buzz” podcast.  

Many banks want a “prescription” for AI, Morris says.  

“My role is to really help our organization craft that prescription, craft how the technology applies in the right part of the customer life cycle, in the right use case, with the right data,” he says. 

The Wilmington, N.C.-based tech provider’s bank clients include M&T Bank and Wells Fargo. 

The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

Whitney McDonald 08:34:15
Hello and welcome to the buzz of bank automation news podcast. My name is Whitney McDonald and I’m the editor of bank automation News. Today is June 3 2024. Joining me is Anthony Morris, Chief industry innovation officer at Encino. He will discuss how AI is unlocking a new value stream for banking in the Tech Trends he has his eye on. Hi, Anthony, welcome to The Buzz.

Anthony Morris 08:34:35
Awesome, thank you so much. I have been in the banking tech space for gosh, over 25 years. And that actually came from a number of years working for a couple of banks where I live and after spending probably the seven, eight years working frontlines working back office working sort of the bridge between technology and business, I was sort of convinced that this industry needed to be changed. I mean, we’re going back into the 90s to give you a bit of a bit of a footprint on my age. And I just was sort of inspired at the time as the internet was sort of being burst around the potential for what technology could actually do for the banking experience for automation for operations for everything and, and I really was spurned into not sparring, but spurred into an opportunity for a tech vendor or what we would call a FinTech before they were called that in the in the mid 90s. And as soon as I worked, started working for a software vendor, I got so enthused about how problems can be solved using technology and not just built on the vendors I worked for the customers I probably engaged with, I think the number is well over 400 banks across the globe and 25 some odd years. And all of that is informed and inspired and excited me in this industry, which is a bit bizarre because you don’t think banking technology is such an exciting thing. But for somebody who comes from the trenches of living it, it I don’t know, the spark hit. So I leverage all of that experience across every domain, in a product line of business line, a tech stack a geography and especially with the craziness of technology in the last you know, decade to help point the way of what can be done. And in my role at Encino. It’s exactly that it’s it’s this is where the world is going. This is where tech is going. This is what customers expect from their bank. This is what the executive need. These are what regulators want, and how you bring all of those sorts of elements of a Rubik’s Cube together to try to use technology to to execute, you know, a bank strategy. So my role is to help point that way for the company. I work for Encino. And help them get ahead of the curve. I’m a Canadian. So we all love hockey and the greatest hockey player of all time, Wayne Gretzky, you know, his motto was a skate to where the puck is going, not where it is. So my role is to help navigate our organization to where the market is going, not where it is today and I on today, but a trajectory for tomorrow. So I love playing that role with customers as well. So that’s a bit about me. Great.

Whitney McDonald 08:37:18
Well, thank you again, for being here. A couple of things to unpack there. I’m from Detroit. So that’s hockey town. So I definitely heard that one before. And being technology is so exciting, Anthony,

Speaker 1 08:37:31
if you’re if you’re in the community, if if you’re at a bank, it is because at the end of the day, banks don’t have physical products, it’s the tech that makes everything real. It’s their DNA, it’s their bones, it’s their flesh, it’s everything. So there’s only a, you know, a handful of people who get it, obviously all of your listeners listeners do. So I think it’d be a fun conversation. Well,

Whitney McDonald 08:37:55
you kind of started talking a little bit about your role, which is Chief industry innovation officer, maybe you could break that down a little bit on what that actually entails a little bit further, so that we can have a better understanding of, of what you do kind of day to day.

Speaker 1 08:38:09
You know, it’s it’s probably similar to those banks that have people who are trying to plot, you know, a two to five year strategy in an ever changing environment, right? So I am very lucky, I get to touch a lot of our customers, a lot of our partners and sort of the bridge between how we think and what we develop and what the market is saying and what they need. And and I try to marry that, like my role is very much Mehreen where the macro economic environment where the financial marketplace and the regulatory and the central banks are headed, and how does that translate down into the bank’s competitive models and business strategies and the tech that they need? Right? So I’m sort of this translator, if you will, of all of these market forces and helping to not help him but sort of trying to lead the way in terms of these are the technologies we need to embrace for the industry ahead of them. And AI is a per For example, right, like a lot of banks, you know, except for the really big ones that are, you know, figure everything out on their own, everybody else sort of wants a prescription they want to be led, how should we do this? What’s the best way? And, and my role is to really help our organization craft that prescription craft the tick how the technology applies, in the right part of the customer lifecycle in the right use case, you know, with the right data, you know, what does that sort of orchestration of different components look like? And what do we need to think about and modeler our product strategy around various elements to deliver so that ultimately, as a bank, you know, except again, for the really ultra big ones who tend to take what software suppliers provide, and then, you know, rework it on their own, provide a prescriptive approach to how to embrace new technologies, technologies have moved into the main stage or the mainstream. And, again, translate from where the puck is going to where do we need to skate today, to put us on the path to the future, and that, sometimes that means new products, new solutions, re tweaking old things, it’s really been a champion. So innovation is an overused buzzword for the last decade. I like to think in terms of practical investments that allow our organization and customers to continue the journey to skate to where the industry is going in a very controlled and responsible way. That’s a very long job description. But it’s a lot of fun. Because you get to do so many things.

Whitney McDonald 08:40:53
Yes, and I know that you mentioned AI, which of course, you can’t get away from Ai right now, in India finished in any industry, but especially, especially with what we do. So with that, that prescription that that idea behind that we have conversations all the time with, okay, where do we start with AI? Where’s AI headed? What’s step one, and I know that you just mentioned, it’s not necessarily where where you’re getting, but how, where you’re going, but how you get there. And so when you talk about that prescription or that journey, maybe you could break down what some of those conversations might look like, with institutions.

Speaker 1 08:41:32
You know, it’s it’s obviously the biggest topic of the last year. And you know, so many predictions of AI is going to be more fundamental to our industry in many industries than even the internet was 20 years ago, as as, you know, all of our society runs on the internet today, right. And the predictions are even more grandiose for AI. I mean, at the end of the day, as I said, like banking is a data business, and of story. And every conversation, you know, for the last 100 years, and, you know, banks in the 1920s to up until 20 years ago, it’s how do they use the information, they have to make a right decision, from a risk perspective, from a price perspective, and from a customer satisfaction perspective. So those fundamentals have not changed, right? It’s, it’s and, you know, even for 30, some odd years using risk modeling and statistical modeling to make decisions, you know, you can say, as a form of intelligence, because it really is the chat GPT moment almost a year ago. Now, if you can believe it really sparked an accelerator, or was a spark plug in the engine of our industry that, you know, once again, things are rapidly accelerating from an idea and a reality perspective than the industry can actually consume. Right? So it sort of caused a moment of major reflection, because every organization that we deal with, has a keen eye on this, you know, obviously, the very big organizations think that they can, and I’m not saying that they can’t, but you know, stand up 1000 people, their own AI innovation shops, and you know, go to town and build things. Well, typically, the larger organizations below that really need to partner with different vendors. And the starting point is actually really clear. And many banks have been on this journey for several years now, we have as well, is to leverage different forms of artificial intelligence. It’s not it’s an umbrella term, right, which includes many different technologies underneath it, is to start in those areas that will have the most immediate impact. And we’ll make the most of the data that they have access to, and is well orchestrated, and sort of clean because at the end of the day, all of your listeners know that, you know, banking data is a it’s a horrific landscape, right? The larger the bank, the more crazy the data is and how it sits and where it is. So those scenarios where the data is organized and clean and what I like to call healthy and accessible For those organizations will win more or get more ahead than others? Where are you start? Or where are you sort of embrace what’s going on today? It’s absolutely clear, there’s zero question, at least within the North American market, that it’s around, how do I drive? You know, new levels of efficiency that just have not been possible before? Period? End of story? It’s not necessarily the whiz bang, how do I make my mobile app suddenly come alive? to who I am? We’ll get there over time. It’s how do I get rid of redundant processes? How do I you know, if a small business or commercial loan is scheduled for renewal renewal? Why must a team of people comb over their financial statements and compare their covenants and, and all of these things, you know, to put a tick in the box to make sure that yeah, they’re good to go, that can be automated with AI, right? And seen as doing a lot of those things today. Shameless plug there. So it’s, it’s the front line, it’s how do I, you know, take the traditional mounds of manuals, and just ask a question, and I get the answer. I don’t, you know, smartest bankers know, the questions. The turnover rate, obviously, is, you know, we’re in this shift of migration of resources, right. So, removing redundancy, things like hyper automation, the intersection of, you know, robotic process automation, machine learning, bots, process, workflow, those things coming together. You know, it’s been the Nirvana banks for many years straight through processing, right, I want an account, I get it in real time, I’ve got a dispute. You know, the system can adjudicate it in real time, it doesn’t need to go back office, I got to do an investigation, I got a complaint, how do I compress that from two weeks, and five people to one day and two people and a bunch of tech? Right? Because all of that means that we’re not really touching, you know, the risk conversation of AI of AI making decisions around is somebody worthy for a loan, or is there you know, it’s not it’s got bias built into the data or whatever it may be. So, without a doubt, we actually did a survey, leading up to our annual user conference, which is, which was in May, you know, the number one issue on your plate for your institution on the next year? And so far, we’ve had, I believe the number is the initial respondents 80% indicated, efficiency, operational productivity, and as much automation as they can get out of technology, right? I mean, it is a direct reflection of the macro economic times the financial realities, given the rate changes and things of that nature, so that it’s common sense to start in that area. And many banks are right, and we are, you know, we are doing things to make that easier, and quicker, and more prescriptive, the cool things, the things that the regulators are gonna have to put frameworks around, you know, the, my banking app is meant for me, and no one else because it’s as human as calling the bank, those will come. There’s no stopping it. But right now, it’s sort of what’s the low hanging fruit that’s going to help my bottom line and not upset the regulators? Let’s go now. And it’s exciting because that’s the singular message I hear from everybody. Yes,

Whitney McDonald 08:47:39
efficiency continues to be a trend, you can’t really get through an earnings call or anything like that, without hearing that word. We’re leaning into efficiencies, and AI in order to do that, I know that you mentioned the low hanging fruit. Maybe we could talk a little bit, take that a little bit further and know that you mentioned redundancies and communication using AI. What other low hanging fruit is, is Encino hearing a need for from clients.

Speaker 1 08:48:12
So it sort of focuses on two or three areas. One is compressed the upfront processes around alone. Right meaning, you know, nobody wants to spend, obviously the effort and the resource and the cost relative to originate the loan. Because, you know, obviously, it’s the most costly effort, right? So how do I use these technologies to qualify a customer upfront before that, quote, you know, you apply for credit, right? How do you put them through and smart bankers do this? They’ve been doing this for hundreds of years. Right now we’re doing the technology do it digitally in real time, right. So the first part is sort of compress the time and the inputs and leverage what we know to sort of make a soft approval, if you will, but within a compliant framework, right. And do so in a way that ensures when I say the compliance framework that it adheres to, not just regulatory guidelines around disclosure and data capture and and and consent, but bias as well. Right. The second part of that is one. So once you sort of, yeah, we want to move forward with this request this opportunity this lead, whatever you want to call it, how do we make sure that the maximum level of automation for the most simplest of loans goes through? Right, it’s sort of the 8020 rule, right, we, you know, 80% of our loans, we want to be automated, we want to take automation to the next level, we want AI to ensure that the right documents are prefilled, that the right you know, AI has a great role to play in extracting information from documents, placing it in the right way and making sort of those low hanging decisions, right. So compressing the decision time, and the complexities around the automation. But we call human in the loop so that for credit decisions that aren’t simple, but still fall within a complexity sort of spectrum, that a user doesn’t have to go through five days, five people 20 documents, the system brings everything to them with the right intelligence. So the human is acting on that. And it’s sort of the proof point around making a decision and not seeing the technology did it all right. So there’s that bucket. The other one, which is probably about good half of our customers have said is, if you think of the whole portfolio management side, and a credit book of business, you know, whether it’s small business, commercial, even corporate, we had about a dozen corporate banking clients together in London last year, and they were really clear, which is, they have all of the data, they have all of the financial statements, you know, whether it’s monthly reporting, quarterly reporting, you know, based on the complexity of the facilities that have been extended, the data will say whether the customer is on side, how they’re performing against their cash flow with receivables and payments, the state of the industry, the state of their collateral, everything, right, we we just want automated renewals, we want automated reviews, you know, it’s so much time spent between relationship teams and the mid office to support those processes. Let’s just have those people focused on those customers, or those segments where there, those variables aren’t eight or nine out of 10. So those are sort of the three buckets and they all speak to efficiency and productivity, they don’t speak to AI is doing the decision so that the renewal of a $50 million operating line is happening without touch. Right, we will likely get closer there and several years. But we’re not there yet. So those are sort of the three key buckets. And everybody is, again, except for the large ones. They’re trying to understand the how the prescription from the organization of the data to how does this actually work from a data risk perspective? To how do I have total audit ability of all of all of the actions that are happening so that I can demonstrate to my audit team, and to my regulators? You know, how we proceeded with a certain activity? Which that tends to slow down the process, obviously, but that’s the world we live in.

Whitney McDonald 08:52:27
Yes, absolutely. And it’s definitely compliance is definitely top of mind when it comes to approaching AI. And you want to be able to cross your t’s and dot your i’s and show exactly how you are doing a process. And that’s why it’s not so like, okay, we’re just gonna implement AI and hope for the best. But yes, it’s definitely a slower process. And everyone kind of has their, their eye on regulators for whatever

Speaker 1 08:52:53
I have to tell you the, the angst of that is, you know, every customer, ie the bank’s customer. You know, you and I as consumers, small businesses, you know, larger b2b entities, everybody is wired to say, well, it’s 2024, I can track my pizza and my food to the guys one second outside my home. But you know, I have most of the most basic understanding of my loan in terms of where it is in the pipe. And I hear it from executives all the time, I was just with the CEO of a bank in Seattle the other day, and absolutely incredible organization and CEO, and he’s like, we want to get there, we will get there because but we can’t do it at the sacrifice of our regulators, you know, and customers don’t they sort of get that, but they don’t understand the complexities involved unless you work for a bank. You know, and every bank box is incredible journeys and using these texts, and as soon as the compliance teams comes into the room, you know, it’s it’s scaled right back. Right. So that’s just the reality of our world and that that has to be navigated.

Whitney McDonald 08:53:58
Yes, absolutely. And it is it is the case and I know that oftentimes my conversations end up being about Amazon and everyone has once the the most instant experiences that you see all the time with with Amazon Then but you’re right, it is a little bit slower of a rollout with with banking and the consumers might not know exactly why. But you do just have that that regulation and sensitive data and you have to do it all the right way. Right. Exactly,

Speaker 1 08:54:25
exactly. Mind you. I mean, different jurisdictions around the world have a different take on this, right? Like the things that the Nordics have been doing with technology, in banking, as well as a decade well ahead of the United States, right. But that’s a reflection of their society, their regulators, what consumers are willing to share from a data perspective in order, the experience or the value they get back. So, you know, it’s not the same in every country, obviously, your listeners are our US base, but it’s very fascinating to look at other markets around the world and how they have addressed some of these things that maybe are a bit more challenging the States because of the concern over privacy and control being sort of a bedrock of of US culture.

Whitney McDonald 08:55:11
What would you have US and Europe readership? There we go, there we go. Yes, I know, we spent a lot of time on AI, which, of course, but I wanted to ask you a little bit more just based on what you see every day? And, and what role that you are in? What other new technology, you’ve got your eye on what’s emerging? And similarly, what financial institutions should have their eye on as well?

Speaker 1 08:55:35
I would, you know, there are so many. And the interesting thing is that technology goes through hype cycles, right? Where, you know, in the initial phase is everyone’s like, Oh, my God, look what we can do and what have you. But you know, the hype hits the reality of the industry, in the business world, it very much hits, not just a bump in the road, but like a mountain in the road, right. And certain ones sort of trend away, and others sort of really start to take hold. And you know, that was the case with cloud in the early 2000 10s. I think I would put my eye on biometrics, right, which is not new. I mean, it’s not new, but has the banking industry really embraced it to the point of like, wow, right? I mean, the government has, because, you know, anybody who uses the Global Entry Program, or any, you know, electronic gate at any airport, right? It’s all it’s all biometric, right. And it’s only been in what the last three, four or five years where banks start using it for authentication purposes. But the the biometrics with natural language processing, and generative AI can dramatically redefine and experience probably surpassing what you might get at an Amazon. And I’ll give you a perfect example. Again, I was at this incredible customer in Seattle the other day, and he showed me a smaller bank, but 40 billion in assets. But he shows me how their customers use their mobile banking app. So this is obviously from a consumer lens. And he basically launched the app, and he had a conversation with it. He used his voice to authenticate it, which a lot of you know, IVR is due this day. But their digital assistant was talking to him. Right? He was talking back, it was, once it authenticated him, the whole interaction was totally it was like it was talking to Siri more or less the transactions, the money movements, the requests he had. It was so human, that it was sort of scary, in a good way. Right. And I had a chuckle moment, because, you know, the smaller banks, which you know, form, even though the large banks control, you know, a fair degree of the market, there’s such a proliferation, at least in the US, a smaller organizations, their size in this particular case, allows them to embrace these technologies, right, in a prescriptive way, partnering with the right vendors to achieve these wow moments, without again, sacrificing compliance or any risk related decisions. So I think the biometrics despite being around for a while has yet to actually get into the DNA of banking operations from an external or digital self service point of view. And I think that’s an incredibly fun opportunity. But again, you merge that with aspects of AI, you merge that with process, orchestration, and you very much get closer to the Nirvana which most banks want, which is as close to straight through processing, as close to human digital as you can, as close to the lowest price point to deliver extraordinary service and experiences, right? And use all that information to funnel sort of The next conversation whether it’s a banker lead or a human lead type of conversation. So that I love I mean, if this were three years ago ever would have been like blockchain is going to disrupt the industry to the point of the hype cycle I said earlier, right, like a tight, tight, tight, tight, right. And then we had an implosion and you know, despite many organizations, embracing aspects of digital currencies and things of that nature, from a connectivity perspective, right, we’re nowhere near the promise of what an open ledger system can do. Digital contracts, tidal movement, you know, real time transposition of value across a transaction cycle, right. So, you know, be interesting to see how that evolves. And I’ve been blathering on but there’s just, there’s just so much that it’s hard to focus as a bank as to where should we be embracing technology? Right. And the scenario I gave was just an example of customer experience. Right? Whereas anything that that drives to the bottom line these days, will get the money, you know, from a tech investment. So no,

Whitney McDonald 09:00:32
absolutely. And I mean, that’s something that I mean, tech spend quarter over quarter continues to be high, the investment is there, the the banks are looking to technology, there’s not much pullback there. But determining kind of based on your institution or based on your capital, what you can invest, it all kind of depends on where you prioritize that spending. And if if one bank is, is on the low hanging fruit side, we kind of discussed that if another is, here’s this example of biometric solutions. Hey, we could maybe explore that. But yeah, it’s definitely not to sound cliche, but it’s not a one size fits all approach. And we see that often

Speaker 1 09:01:14
works. Of course, of course, I mean, the other sort of key element to this conversation is that, you know, banks are very conservative in nature, right? Especially now, nobody’s going to project out five years in terms of, you know, our technology spend is going to be this we’re going to invest there, et cetera, et cetera, especially with the acceleration and the rapidity, not the rapidity, the velocity of the emergence and application of new technology. So it begs the question from a tech spending and a tech strategy perspective, in terms of, you know, you’ve heard the term run the bank changed the bank, right? And typically run the bank has been what 80 90% of the tech budget and 10% is innovation. Well, that is shifting and has to shift, right these new tax establish a new foundation and a data infrastructure, you know, external access, I like to say the industry is going from a closed model to an open model to a networked model, sort of like an evolution over time. And as tall as technology and infrastructure get get right sized or you know, configured for the modern era, that equation will shift and more money can either be saved for the bottom line, or invested in speed to turn around ideas into actions and less on just keeping, you know, 3040 50 year old technology going because nobody can figure out how to remove their core banking system.

Whitney McDonald 09:02:50
You been listening to the buzz, a bank automation news podcast, please follow us on LinkedIn. And as a reminder, you can rate this podcast on your platform of choice. Thank you for your time and be sure to visit us at Bank automation news.com For more automation news,

Transcribed by https://otter.ai



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