Hello, and welcome to the NVIDIA AI Podcast. I'm your host, Noah Kravitz. Since its founding in 1993, Temenos has been on a mission to revolutionize banking. Its open platform enables people across the world to carry out their daily banking needs. and for banking providers to build new services and state-of-the-art consumer experiences using AI and other cutting-edge technology.
Starting a bit more recently, our guest has been leading Temenov's efforts to drive digital transformation from financial institutions across the world. In October of last year, 2024 to be specific. Barb Morgan joined Temenos as Chief Product and Technology Officer. bringing over 25 years of leadership experience and global product development organizations with her to the role. Barb has done a lot in banking and financial services, to put it mildly.
especially with AI and cloud tech. In fact, it'll be better to ask her to tell us about her background. So we'll start there in just a second. Except that I will add that Barb holds a Bachelor of Science in Computer Science. from the University of Central Oklahoma. That said, Barb is here to talk about generative AI in banking, Temena's approach to AI, and the importance of sustainability in the industry. We're starting.
So let's get to it. Bob Morgan, welcome, and thank you so much for joining the NVIDIA AI Podcast. Thanks, Noah. Excited to be here. Excited to have you. All right, so I teased it in the intro a little bit, but maybe we can start with you telling us a bit about your background, your journey into working with AI, and how you landed at Temina.
I actually started with my hands on the keyboard. So I was a developer many years ago. And when you said 25 years, I had to smile a bit because it reminds me how long career has been. But now, you know, my my career did start with the hands on the keyboard. I always really enjoyed that link between what we were doing with technology and how that was really impacted.
And so as my career continued to kind of go through my journey, I really gravitated towards those areas that had a strong customer center. 15 years of my career focused in the financial services industry. So I've led transformations in inside banks within tech. side by side with the banks, and really focused around modernizing core systems, building innovative products, and accelerating AI adoption, which you can't have a conversation anymore without AI. But AI isn't new to me.
We've been using it for years from fraud detection, risk modeling, automation. But what's really different now is we're seeing that shift. where, you know, Gen AI has shifted the entire landscape where it's not about efficiency. It's really about making the bank smarter, more intuitive, and bringing that, you know, hyper-personalization to the client.
It's exciting when we talk to our clients. So, you know, as you mentioned, I joined Temnos in October and I've spent, you know, in my past four months, a lot of time out there just talking with the client. you know, understanding what they're thinking about, whether it's the CEO, CTO, and they really want to get back to their customers. Having us run a banking suite for them on SaaS so that they can focus on their customers versus infrastructure.
leveraging AI, but that customer centricity is really coming out and it's paired so nicely with the Gen AI. It's interesting you mentioned the shift from efficiency, and not that efficiency is a thing of the past, I'm sure, in the banking sector especially, but kind of that shift from efficiency to...
you know, the customer relationship and how can we better serve customers? And is that something that you felt happening before Gen AI in particular kind of took center stage over the past couple of years? Or is it something that you think? kind of followed the technology that, you know, people realized like, oh, this is a great way to do all these things with custom, you know, personalization, customer service, what have you. And that trend sort of followed the tech.
I think the era of the chat box. Right. You know, which was kind of that first introduction. Yeah. When you were sitting on the technology side, you know, whether inside the bank or at the fintechs, we thought this is fantastic. And what we realized was it was actually really frustrating. I don't know if you've ever called into your bank and it's like, press one for this, press two for this, and then you just end up mashing that zero key. I'm just screaming representative into the phone.
And so now I think what we've seen where technology is leading is that Gen. AI can bring that human-centered approach and really bringing more humans back to that immediate. Now, all that data can get pulled instantly. And so you don't have to go through that representative, representative, representative. And so I do think that we thought technology was leading. when kind of that area of the chatbots and some of the different, you know, customer.
type efficiencies, you know, were playing out maybe five, 10 years ago. But now I think technology truly is leading and people are seeing it as an enabler versus, you know, again, just that cost efficiency. Maybe you can unpack a little bit what it means from the banker's side to deliver a better experience and how. how they're thinking about leveraging gen AI and related technologies. I love, I'm not even a developer, but I get on my high horse when people talk about gen AI as if it's the only.
artificial intelligence, right? So machine learning, predictive analytics, all these things. Those are not, you know, like we said, they're not going away. But from the banker's perspective, what are they excited about now? What are some of us banking customers doing to leverage this tech to deliver, you know, better experiences and make their clients happier?
You know, we're seeing kind of two themes really kind of play out when we have the conversations with the banks. And the first one is, you know, how can they help their team? And then secondly, when they help their customers. So from the perspective of helping their teams, you know, they're asking us questions of how can we give our bankers instant access to insight? How can we leverage the historical data and make recommendations almost instantly?
You know, how can we have those richer, more meaningful conversations enabled for our business? And so that's really kind of that internal look of his. How can AI sit side by side and really be that plus one in the conversation? I think for the customers, it goes back to that hyper-personalization. tailoring loan options or giving them insights that they hadn't thought about before, both from historical but also predictive in the future.
And then there's this speed that customers expect now. You know, everyone seems to have, whether it's, you know, chat GBT or perplexity or whatever loaded onto their phone, you know, everyone expects that instant answer. And so they expect that everywhere, but we're in a highly regulated space. And so making sure that we do that, you know, in a very responsible way.
But some of the things that we're doing that, you know, I really enjoy myself and try to entrench myself with the teams as much as I can on. is instead of just coming up with solutions and then going out to our clients, we're doing a lot of co-design around the AI solution. So, you know, really saying, hey, here's fiber.
use cases. Which of these stands out to you? Which one or two of these do? Let's sit side by side. Let's think about how we can co-develop this together. One that we're working on recently is an AI-powered solution that allows the product managers at the bank to create those financial products, you know, leveraging that data insight. And that was where that predictive future capabilities came into question, right? So based off of the history.
What can we predict? And we can give you the bank's knowledge. We have bank expertise as well because we serve a thousand different banks or more than a thousand banks. And so bringing that all together to think about future predictions, pulling it together and giving the right products to the right customers at the right time. You know, for me, it's...
It's also, we don't want to leave any of our customers behind. You know, one of the things that I really enjoy about what we bring to our clients is we focus on flexibility. And what I mean by that from a pure tech stack perspective is... If you need to be on-prem, if they want to be in the cloud, or if they want... they have the optionality. And so, you know, partnering most recently, you know, with NVIDIA to bring AI to our on-prem banks has been hugely well received.
Just that ability to, you know, give that AI-driven analysis with those massive data sets, you know, that they have on-prem, but allowing them to control the security around it, allowing them to, you know, really. Not need to have the deep technical expertise to analyze.
And so a lot of excitement there, you know, and it's good, too, because what, you know, we were talking with the bank the other day and he said our ability to have adequate data management, you know, is very limited. There's areas we've invested. but it might be 25% of our landscape that we actually can pull analytics. So these tools that can look across those massive data sets are really exciting. So to kind of take a step back for a second, if you don't mind.
Temenos offers a platform. And so when you're talking about, I just kind of wanted to unpack for the listener what. Temenos actually does. And my understanding is, you know, it's services, but then you also have a platform where clients can build products for their banks. in kind of three different ways. So first, we have a end-to-end banking platform. And so for our banks,
Within, like, let's say within the U.S., our tier three regional banks will come in and they'll they'll take an end to end platform that provides all of the capabilities of banking. Almost like a turnkey banking solution. And that's where we see a lot of the adoption of SAF. bring us away, you know, even within kind of that neo banking space as well. But then we also, you know, we also offer modular solutions to our clients. And so if you look at some of our tier one bank.
They don't want to replace their whole platform, right? And so, but they may come to us and say, hey, we just want your payments module. Or we just want your originations. And so, you know, giving... that choice and flexibility, whether they want the full platform or they want modulars within the platform.
And then we also offer products around what we call point solutions. So things that may be add-ons that they may choose to build themselves and plug into our platform, like their digital interface. Or we also offer a digital interface that they can leverage. Gotcha. Thank you. And you serve bank customers of all sizes? We do. So we have over a thousand banks globally. So we have a very global footprint from the Americas to MIA to APAC.
And so, you know, with that, it's everything from tier one banks all the way down to the neobank. similar or different trends in terms of, I guess, both adoption rates from, you know, smaller banks and larger banks when it comes to AI tools, but also what they're using them for? Or is it everyone primarily is, you know, customer service, like this is the big.
It's not just a little hanging fruit. Like it's a potentially really big win. Is that just where the focus is now? I would say AI is no longer enough. So they have to have AI, whether it's embedded, whether it's actually more of a feature functionality, maybe within their digital to allow their customers to click on some type of an AI agent. But I would say we...
We see two different lens on this. So one is regionally, you know, you have different areas that are more prone to adopt AI faster than other regions. And then from the customer tiering, what I would say is the, you know, tier one, tier two banks, absolutely. They want it embedded in their product. The, you know, kind of tier three banks, regional banks. They're really focused on the personalization.
You kind of alluded to this a little bit, but is Just gathering data and helping the banks kind of find and gather up and scrub and prepare and use. You know, you mentioned the example of, you know, only 25 percent of the data actually going to analytics. I'm getting that wrong in my paraphrasing. But is that still kind of the biggest, I don't want to say hurdle, but, you know, one of the biggest hurdles to kind of leveling up success?
conversations that I often have or something I always try to click into and probably a bit of my, you know, kind of geeky background leads me into is what does your data look like? Because in order to have responsible AI, you have to have your data in a state that you can actually leverage the tools and press. you know, having, we really take that AI explainability very seriously. And so we spend time with our customers to understand what is the state of their data.
And oftentimes what we find is if you think back to the transformation 10 years ago that banks were undergoing, it was a lot about. how it looked and felt to the customers. Not about transforming the back end. So, you know, many banks are made up of acquisitions, mergers over time. And so the front end looks really slick and great. And it looks like you're dealing with one bank and it's actually hitting. six different banks in the background.
And so sometimes it is, you know, working with our clients, you know, we have a Temnos data product, our TDH product, and it is bringing that data into a state that it can then be leveraged. And so, you know, kind of back to that optionality that, that we talk to our clients about, you know, sometimes we, we may just take a portion of the bed.
And, you know, really focus on getting the data streamlined and getting it ready to be able to use that embedded AI and then proving it out. And I think as we see, you know, banks are highly regulated. that's not going away. The regulations are going to get tougher if not anything else. And so, you know, we always keep that top of mind, making sure that, you know, compliance standards are absolutely, you know, embedded into our product.
fully auditable. And so that's where a lot of our conversations end up leading around data is, are you ready? Right, right. I'm speaking with Barb Morgan. Barb is the Chief Product and Technology Officer at Temeno. a role she started within the last year. The current chapter in an illustrious career in global product development, particularly across banking and financial services.
And we've been talking about generative AI in particular and the banking perspective on the chatbot revolution, if you want to put it that way. But just as a leaping off point, so much more, obviously, before. chat GPT and the bots came in the world of machine learning and obviously sense. the pace. It's just been breakneck. Barb, I want to kind of shift gears for a second here, if we can, and talk a little bit about sustainability in the industry.
I know that Temenos has a point of view on this and is actively working with client organizations to help them be more green. And I would think that your perspective, both in the industry and also in kind of the international nature of the work that you do with Temenos. Curious to hear both the company's perspective and what you're up to with clients to help them be more green, but also your take, having been around the industry and around the world literally for a few decades now.
So to me, sustainability, you know, it's not a trend. I think when it really started becoming part of the conversations, call it, you know, maybe 10 years ago where it actually was part of annual reports and things like that. I think people kind of questioned, like, is this long term? And now what we've seen the shift is it's really a responsibility of the organization.
And so when we sit down and we talk with our banks and why it's important to us and bringing some of those solutions forward that allow them to be greener, we talk about both. what it means to them, where their focus is. So, you know, to your point, we serve banks globally. And so we see different parts of the world where, you know, it may be more around their carbon accounting or...
areas that may be like, hey, we really want to understand, you know, how our cloud deployments are helping. And so understanding, like, how can we drive a greener banking future? And there are always great conversations because they really often talk to the values of the organizations. And so you get to actually spend time in the cultural side of the bank. Kind of cool for the lack of a better word.
about those conversations is when you can use AI to bring the culture forward in the solutions through something that really matters to them, it's a very rewarding solution, right? So, you know, like I talked about the... smart carbon accounting, helping our customers track their carbon footprint, both through how they're using their software, but then being able to offer that to their customers.
You know, there's many customers who want to know, like, hey, how are the purchases that I'm making impacting my carbon footprint? Right. So not only are we talking to our customers, but we're actually impacting their end customers as well. So kind of to piggyback off that a little bit and open it up a little more abstractly, I guess. This is a big question, but I'll throw it at you. You can handle it.
how do you see the future of banking being shaped by ai and i guess the flip side of that is you know how do you see the future of ai growing in banking but i think really you know there there's been so much we kind of joked about it for a second there's been so much in the past couple of years with gen ai and the pace isn't slowing down and
You know, we have in our notes here to talk about AI agents, which is, you know, kind of the latest thing buzzword-wise in the past few months, right? But certainly not a new thing and certainly something that, like, could wind up really shaping, you know, the technology going forward. We'll have to see how it plays out.
Do you have a strong view on what you think is going to happen with AI and banking and banking kind of being reshaped by the technology? And that can be, you know, short term, next couple of years, take it a little further out if you like. What are your thoughts kind of generally on this? Yeah, I think even before stepping into that, I think that the one thing that I really see and I think it's important to kind of talk about is the leadership of an organization really shapes.
Right. It's seen as a friend or a foe. You know, if you have your top leadership just talking about how much money we're going to save from AI. Right. It's a foe. Right. But we're seeing the leaders of the organizations really look at AI as. you know, not as a threat and really. talking about it as an enabler. getting people curious, getting people engaged, more and more organizations. And we do this ourselves.
you know, whether you use the term eating their own dog food or French would say drinking their own champagne. You know, we've been doing that ourselves to say, hey, let's. Let's actually use this on ourselves. And then if it works well for us, great. We can start to expand it to our customers. And so when you start to see the leadership of the organizations, whether it's the CEO or any of the C-suite, talking about how they're curious. how they're using it in their daily lives.
how they're getting in there and playing around themselves and thinking about how can I get rid of repetitive, time-consuming tasks and focus on deeper matters and more strategic work. you start to see that really come out. And I think that's important in order for people to see AI as a tool to amplify the human potential, not to replace it. Are the bankers, the employees, to put it that way?
Are they thinking about it the same way? Is there excitement? Is there fear around job replacement? Any change, right? There's always going to be a bit of fear. And I think it's up to... you know, us as the banking experts in, you know, as partners to our clients and then, you know, working with their teams to help kind of show how the change does. actually help them. Right. And, and so when we see that kind of pivot away from, oh my gosh, this is going to replace me.
to, wait a second, I'm actually going to sit side by side with AI. Yes. Forgive me to interrupt. I just wanted to give you credit. I hadn't heard somebody use plus one. Just talk about AI before, and I love it, right? It's, you know, the co-pilot, whatever you want to call it, but plus one is great. Yeah, you know, and for me, I really focus on, I hate the word artificial.
intelligence because you know artificial it's fake you know there's just that negative connotation and so I often start out by talking with our clients about thinking about it as augmented intelligence. And that gives you that plus one effect, right? And then when you show, you know, the bankers, hey, someone's going to walk into your brand.
you're instantly going to be able to know more about that customer than they know about themselves. And you're going to be able to have a really deep conversation both about what... right for them today, what's right for them in the future, how they're shaping those things.
Right. Because, you know, oftentimes they would have to, you know, the customer would sit in the lobby. They would do a bunch of research. They might be pulling paper files out. They're trying to remember, OK, this person has been with us for 10 years and they. They have a mortgage and they have a car and they have this.
Right, right. Oh, gosh, what else could I offer them? When they can, through natural language questions, say, you know, how long has this customer been with us? What is their familial history, right? So, you know, this may be a... You know, it may be a 30-year-old, but maybe their family's been with the bank for 25, 30 years. And then when, you know, their customer walks up and they say, hey, it's been great. You know, we've served your parents.
So excited to have you here with us. And we had these great, you know, we're looking at what loans that you have with us. We could consolidate those together. We could offer you a better rate. We have this great potential over here. They're exciting, right? Yeah, it really kind of, you sort of made real and listening to you talk about that. It's a great example because it makes me think of the sort of abstract talk.
about machine learning, AI tech, kind of, you know, freeing humans up to do what humans do better or best. And in this case, I can relate because It's not quite AI, but if it's not in my phone calendar, I forget it, right? And so I can only imagine being a banker.
having so many clients to serve. As you said, you know, I'm in the lobby waiting because the banker is doing their best to kind of do a crash course on my whole history with the bank to serve me because there's so many customers. I'm getting frustrated and waiting, et cetera, et cetera. Yeah, let the AI do it. And then it just, in real time, it pops up. And yeah, that's a great example. And to me, I mean, the future is, you know, the future is going to be all about human and AI collaboration.
You know, we're already seeing kind of AI agents, so to your agentic AI, right, you know, latest buzzword, you know, handling those routine banking tasks. But if you can set it up where it's doing your segmentation, then it's doing some product suggestions, then it's seeing as you offer those products, maybe it's... It's actually shaping that segmentation. And so those agents are continually learning from each other. And then you can bring that to that human collaboration. It's just exciting.
You know, I think we'll start to see digital humans in making, you know, so that you aren't saying representative, representative. I was going to say, you know, we were talking about that before. I'm, I'm a hundred percent for, you know, the plus one, the augmented intelligence is also, I like, I like that way of thinking about it as well. Right. And I want to see humans use the technology to thrive and not talk about things like replacement, et cetera, et cetera.
That being said, I'm an impatient person. And so I always gravitate towards the self-checkouts at stores. And so if the automated banking menu could give me, because I never call unless I have some, you know.
weird question or like i've missed four payments and want to try to beg somebody to give me grace right so yeah get the automated system to that point and i'll be happy yeah or or even you know think about how great would it be if it you know Your phone pops up because I know we all, or at least I know my phone is always within and under.
anywhere. And if it just said, hey, Noah, looks like you missed your last payment. Would you like us to auto debit from your account? And we'll forgive any late. And you're like, yes, done. Yeah, that's exactly the one. And so that proactive monitoring, bringing that, you know, so that you aren't even having to call in. You know, how much better would that be if it automatically, you know, reaches out to you?
If my creditors happen to be listening to the podcast, I just made that example up. We're good. Barb, before we get to wrapping up, I wanted to ask you, and I think this is something I need to start asking guests going forward. So thank you for inspiring me. You mentioned in your work talking to, you know, leadership is so important. It sets such a tone for so many things, but including an organization's a bank.
kind of perspective on embracing AI. And you talked about getting, you know, these clients, these banking leaders to start using the tools in their own life. Do you have a routine? Do you have things that you use AI for on a daily, regular basis that, you know, maybe a pro tip to share with the audience? Yes, I might reuse it. That's probably the engineer in me.
You know, my husband, I'll be traveling and I'll get a message like, can you turn this thing off? Like, why are all the lights coming on? Like, I know you wake up at six, but I'm not waking up at six when you're not home. Right, right. Why is my house waking up for me? Smart home life. No, no. I mean, you know. a couple different ways. Sometimes I use it just to say, is my message clear?
When you're so deep into whatever your specialty is, you feel like your message is clear because you've been living, eating, breathing, working on it for a while.
I can quickly throw that into whatever my favorite tool is, whether it's, you know, ChatGBT or Perplexity or whatever, Copilot and say, you know, summarize this message. What is the tone? You know, what level of... audience is this reaching and hopefully it'll say you know hey this is actually you know geared at a engineering audience oh well wait a second that's not who i'm speaking
Right. Let me make sure that I bring this back into, you know, more of a business speak or, you know, this is very financially focused. OK, wait a second. You know, and so I use it oftentimes in a way to sense check me, but I also use it for a bit. Silly stuff, right? So we have four kids back in the state, all college age, 19 to 22. And we were going on holidays in Mexico. And as much as I think I'm a cool mom. I absolutely used AI to say, what are the best things to do down in Mexico? Totally.
And it got it pretty close to right. They liked the different restaurants that we took them to. There you go. So I use it quite often. You know, I play with a lot of tools outside of the financial industry because I think it's important to see how other industries are leveraging AI. It gives us ideas into the financial space.
whether it's maybe the insurance space. I was on my insurance app the other day and they have AI embedded. And I thought, wow, this is really cool. And so looking for ways that other people are using AI is sometimes the way that I use AI.
Barb, for listeners who would like to learn more about Temenos' approach to AI, other services Temenos offers, maybe something a little more engineering geeky oriented i don't know if there's a developer blog or you have other social media anything where would you direct them to go after listening yeah you know whether it's
LinkedIn, if that's their favorite, you know, within just looking at Temenos, they will definitely find a plethora of areas to go. And then, of course, our website, right? Just our www.temenos.com. They can look at our products. We do have, you know, more of the technical aspects, right? So our developer portals, and then also just understanding, you know, where our thought leadership is in this space. Fantastic.
for joining the podcast. This was a pleasure. I learned some things, which I knew I would. We talked before we started. Banking's not my wheelhouse. So I appreciate that. Thank you. But more so, it's always fascinating to talk to somebody who's... a leader in their field and has been living and breathing it for long enough to you know
We're talking about world-changing technology, but there are deeper things that have been around for a while now that are really important to shaping your perspective. So your perspective is greatly appreciated. Thank you.