AI transcript
0:00:10 [MUSIC]
0:00:13 Hello, and welcome to the NVIDIA AI podcast.
0:00:15 I’m your host, Noah Kravitz.
0:00:17 Since its founding in 1993,
0:00:21 Temenos has been on a mission to revolutionize banking.
0:00:23 Its open platform enables people across the world
0:00:25 to carry out their daily banking needs,
0:00:27 and for banking providers to build new services
0:00:30 and state-of-the-art consumer experiences
0:00:33 using AI and other cutting-edge technology.
0:00:35 Starting a bit more recently,
0:00:37 our guest has been leaning Temenos efforts
0:00:38 to drive digital transformation
0:00:41 from financial institutions across the world.
0:00:44 In October of last year, 2024, to be specific,
0:00:47 Barb Morgan joined Temenos as chief product
0:00:48 and technology officer,
0:00:51 bringing over 25 years of leadership experience
0:00:53 in global product development organizations
0:00:54 with her to the role.
0:00:57 Barb has done a lot in banking and financial services
0:01:00 to put it mildly, especially with AI and cloud tech.
0:01:02 In fact, it’ll be better to ask her
0:01:03 to tell us about her background.
0:01:05 So we’ll start there in just a second,
0:01:07 except that I will add that Barb holds
0:01:09 a Bachelor of Science in Computer Science
0:01:11 from the University of Central Oklahoma.
0:01:13 That said, Barb is here to talk about
0:01:14 generative AI and banking,
0:01:16 Temenos’ approach to AI,
0:01:18 and the importance of sustainability
0:01:19 in the industry for starters.
0:01:20 So let’s get to it.
0:01:23 Bob Morgan, welcome, and thank you so much
0:01:25 for joining the NVIDIA AI podcast.
0:01:27 – Thanks, Noah, excited to be here.
0:01:29 – Excited to have you.
0:01:31 All right, so I teased it in the intro a little bit,
0:01:34 but maybe we can start with you telling us a bit
0:01:35 about your background,
0:01:37 your journey into working with AI,
0:01:39 and how you landed at Temenos.
0:01:41 – Absolutely, so I actually started
0:01:43 with my hands on the keyboard.
0:01:46 So I was a developer many years ago.
0:01:49 When you said 25 years, I had to smile a bit
0:01:51 ’cause it reminds me how long career has been.
0:01:55 But now, my career did start with the hands on the keyboard,
0:01:58 but I always really enjoyed that link
0:02:00 between what we were doing with technology
0:02:02 and how that was really impacting the customer.
0:02:05 And so as my career continued
0:02:07 to kind of go through my journey,
0:02:10 I really gravitated towards those areas
0:02:13 that had a strong customer centricity.
0:02:15 And so I spent about the past 15 years of my career
0:02:18 focused in the financial services industry.
0:02:23 So I’ve led transformations inside banks within techs,
0:02:24 side by side with the banks,
0:02:27 and really focused around modernizing core systems,
0:02:29 building innovative products,
0:02:31 and accelerating AI adoption,
0:02:34 which you can’t have a conversation anymore without AI.
0:02:37 But AI isn’t new to me.
0:02:40 We’ve been using it for years from fraud detection,
0:02:42 risk modeling, automation,
0:02:45 but what’s really different now is we’re seeing that shift
0:02:50 where Gen AI has shifted the entire landscape
0:02:51 where it’s not about efficiency,
0:02:54 it’s really about making the bank smarter,
0:02:58 more intuitive, and bringing that hyper-personalization
0:02:59 to the clients.
0:03:01 It’s exciting when we talk to our clients.
0:03:05 So as you mentioned, I joined Temno’s in October,
0:03:08 and I’ve spent, in my past four months,
0:03:12 a lot of time out there just talking with the clients,
0:03:13 understanding what they’re thinking about,
0:03:15 whether it’s the CEO, CTO,
0:03:19 and they really want to get back to their customers, right?
0:03:22 Whether it’s having us run a banking suite for them on SaaS
0:03:24 so that they can focus on their customers
0:03:28 versus infrastructure, leveraging AI,
0:03:31 but that customer centricity is really coming out,
0:03:33 and it’s paired so nicely with the Gen AI.
0:03:37 – It’s interesting you mentioned the shift from efficiency,
0:03:39 and not that efficiency is a thing of the past,
0:03:42 I’m sure in the banking sector especially,
0:03:44 but kind of that shift from efficiency
0:03:47 to the customer relationship
0:03:49 and how can we better serve customers?
0:03:53 And is that something that you felt happening
0:03:56 before Gen AI in particular
0:03:58 kind of took center stage over the past couple of years,
0:04:00 or is it something that you think
0:04:03 kind of followed the technology that people realized,
0:04:06 like, oh, this is a great way to do all these things
0:04:08 with customer, you know,
0:04:10 personalization, customer service, what have you,
0:04:13 and that trend sort of followed the tech?
0:04:17 – I think the era of the chat box, right?
0:04:20 Which was kind of that first introduction.
0:04:23 When you were sitting on the technology side,
0:04:25 whether inside the bank or at Vintex,
0:04:26 we thought, this is fantastic.
0:04:28 And what we realized was it was actually
0:04:30 really frustrating to the clients.
0:04:33 I don’t know if you’ve ever called into your bank
0:04:37 and it’s like, press one for this, press two for this,
0:04:40 and then you just end up mashing that zero key, right?
0:04:43 – I’m just screaming representative in the phone,
0:04:44 is that right?
0:04:47 And so now I think what we’ve seen
0:04:50 where technology is leading,
0:04:55 is that Gen AI can bring that human centered approach,
0:04:58 and really bringing more humans back
0:05:00 to that immediate touch point with customer,
0:05:05 because now all that data can get pulled instantly.
0:05:07 And so you don’t have to go through
0:05:10 that representative representative.
0:05:14 And so I do think that we thought technology was leading
0:05:16 when kind of that era of the chat bots
0:05:21 and some of the different customer type efficiencies,
0:05:23 we’re playing out maybe five, 10 years ago.
0:05:26 But now I think technology truly is leading
0:05:28 and people are seeing it as an abler
0:05:31 versus again, just that cost efficiency.
0:05:32 – Right, right.
0:05:34 Maybe you can unpack a little bit
0:05:37 what it means from the banker side
0:05:39 to deliver a better experience
0:05:43 and how they’re thinking about leveraging Gen AI
0:05:44 and related technologies.
0:05:46 I love, I’m not even a developer,
0:05:50 but I get on my high horse when people talk about Gen AI
0:05:52 as if it’s the only kind of artificial intelligence, right?
0:05:54 So machine learning, predictive analytics,
0:05:57 all these things, those are not, like we said,
0:05:58 they’re not going away,
0:05:59 but from the bankers perspective,
0:06:01 what are they excited about now?
0:06:04 What are some of the some of us banking customers doing
0:06:07 to leverage this tech to deliver better experiences
0:06:09 and make their clients happier?
0:06:12 – Yeah, I think we’re seeing kind of two themes
0:06:14 really kind of play out
0:06:16 when we have the conversations with the banks.
0:06:20 And the first one is, how can they help their team?
0:06:22 And then secondly, can they help their customers?
0:06:26 So from the perspective of helping their teams,
0:06:27 they’re asking us questions of,
0:06:30 how can we give our bankers instant access to insight?
0:06:33 How can we leverage the historical data
0:06:36 and make recommendations almost instantly?
0:06:38 How can we have those richer
0:06:42 more meaningful conversations enabled for our bankers?
0:06:45 And so that’s really kind of that internal look of his,
0:06:48 how can AI sit side by side
0:06:52 and really be that plus one in the conversation.
0:06:54 I think for the customers,
0:06:56 it goes back to that hyper personalization,
0:06:59 whether it’s pay-learning loan options
0:07:00 or giving them insights
0:07:02 that they hadn’t thought about before,
0:07:06 both from historical, but also predictive in the future.
0:07:09 And then there’s the speed that customers expect now.
0:07:11 Everyone seems to have,
0:07:13 whether it’s chat, GBT or perplexity
0:07:15 or whatever loaded onto their phone,
0:07:17 everyone expects that instant answer now.
0:07:19 And so they expect that everywhere,
0:07:21 but we’re in a highly regulated space.
0:07:23 And so making sure that we do that
0:07:25 in a very responsible way.
0:07:28 But some of the things that we’re doing that,
0:07:31 I really enjoy myself and try to entrench myself
0:07:33 with the teams as much as I can on
0:07:36 is instead of just coming up with solutions
0:07:37 and going out to our clients,
0:07:40 we’re doing a lot of co-design around the AI solution.
0:07:45 So really saying, hey, here’s five or six use cases.
0:07:46 Which of these stands out to you?
0:07:48 Which one or two of these do?
0:07:50 Let’s sit side by side.
0:07:53 Let’s think about how we can co-develop this together.
0:07:54 One that we’re working on recently
0:07:56 is a AI powered solution
0:07:59 that allows the product managers at the bank
0:08:01 to create those financial products,
0:08:04 leveraging that data insight.
0:08:07 And that was where that predictive future capabilities
0:08:08 came into question, right?
0:08:12 So based off of the history, what can we predict?
0:08:14 And we can give you the bank’s knowledge.
0:08:17 We have bank expertise as well,
0:08:19 because we serve 1,000 different banks
0:08:21 or more than 1,000 banks.
0:08:22 And so bringing that all together
0:08:25 to think about future predictions,
0:08:27 pulling it together and giving the right products
0:08:30 to the right customers at the right time.
0:08:33 For me, it’s also,
0:08:35 we don’t wanna leave any of our customers behind.
0:08:38 One of the things that I really enjoy
0:08:40 about what we bring to our clients is,
0:08:41 we focus on flexibility.
0:08:46 And what I mean by that from a pure tech stack perspective
0:08:48 is if you’re gonna be on-prem,
0:08:50 if they wanna be in the cloud or if they want SaaS,
0:08:51 they have the optionality.
0:08:56 And so partnering most recently with Amidia to bring AI
0:09:02 to our on-prem banks has been hugely well received.
0:09:06 Just that ability to give that AI-driven analysis
0:09:09 with those massive data sets that they have on-prem
0:09:12 but allowing them to control the security around it,
0:09:16 allowing them to really not need to have
0:09:19 the deep technical expertise to analyze.
0:09:21 And so a lot of excitement there.
0:09:24 And it’s good too, because we were talking
0:09:26 with the bank the other day and he said,
0:09:29 our ability to have adequate data management
0:09:30 is very limited.
0:09:32 There’s areas we’ve invested,
0:09:35 but it might be 25% of our landscape
0:09:37 that we actually can pull analytics.
0:09:40 So these tools that can look across those massive data sets
0:09:42 are really exciting.
0:09:45 – So to kind of take a step back for a second,
0:09:49 if you don’t mind, Teminos offers a platform.
0:09:51 And so when you’re talking about,
0:09:53 I just kind of wanted to unpack for the listener
0:09:55 what Teminos actually does.
0:09:57 And my understanding is, it’s services,
0:10:01 within you also have a platform where clients
0:10:03 can build products for their banks?
0:10:07 – Yeah, so in kind of three different ways.
0:10:11 So first we have a end-to-end banking platform.
0:10:15 And so for our banks, within like, let’s say within the US,
0:10:17 our tier three regional banks will come in
0:10:19 and they’ll take an end-to-end platform
0:10:22 that provides all of the capabilities of banking.
0:10:25 – Almost like a turnkey banking solution, okay.
0:10:29 And that’s where we see a lot of the adoption of SaaS,
0:10:32 bring us a bank, even within kind of
0:10:33 that neo banking space as well.
0:10:38 But then we also, we also offer modular solutions
0:10:39 to our clients.
0:10:42 And so if you look at some of our tier one banks,
0:10:44 they don’t wanna replace their whole platform, right?
0:10:46 And so, but they may come to us and say,
0:10:50 hey, we just want your payments module
0:10:53 or we just want your originations.
0:10:56 And so giving that choice and flexibility,
0:10:58 whether they want the full platform
0:11:01 or they want modulars within the platform.
0:11:03 And then we also offer products
0:11:05 around what we call point solutions.
0:11:08 So things that may be add-ons that they may choose
0:11:10 to build themselves and plug into our platform,
0:11:11 like their digital interface.
0:11:14 Or we also offer a digital interface
0:11:17 that they can leverage with our suite.
0:11:18 – Gotcha, thank you.
0:11:20 And you serve bank customers of all sizes?
0:11:24 – We do, so we have over a thousand banks globally.
0:11:27 So we have a very global footprint
0:11:30 from the Americas to Mia to APAC.
0:11:34 And so, with that, it’s everything from tier one banks
0:11:37 all the way down to the near banks.
0:11:40 – Are you seeing similar or different trends
0:11:42 in terms of, I guess both adoption rates
0:11:44 from smaller banks and larger banks
0:11:45 when it comes to AI tools,
0:11:47 but also what they’re using them for?
0:11:50 Or is it everyone primarily is customer service?
0:11:53 Like this is the big, it’s not just low hanging fruit.
0:11:55 Like it’s a potentially really big win.
0:11:56 Is that just where the focus is now?
0:12:00 – I would say AI is no longer an option, right?
0:12:03 So they have to have AI, whether it’s embedded,
0:12:07 whether it’s actually more of a feature functionality,
0:12:09 maybe within their digital to allow their customers
0:12:13 to click on some type of AI agent.
0:12:17 But I would say we see two different lens on this.
0:12:21 So one is regionally, you have different areas
0:12:25 that they’re more prone to adopt AI faster
0:12:26 than other regions.
0:12:28 And then from the customer tiering,
0:12:32 what I would say is the tier one, tier two banks,
0:12:34 absolutely they wanted embedded in their product.
0:12:38 The kind of tier three banks, regional banks,
0:12:42 they’re really focused on the personalization that it brings.
0:12:44 – Okay, you kind of alluded to this a little bit,
0:12:49 but is just gathering data and helping the banks
0:12:54 kind of find and gather up and scrub and prepare and use.
0:12:59 You mentioned the example of only 25% of the data
0:13:00 actually going to analytics.
0:13:02 I’m getting that wrong on my paraphrasing,
0:13:04 but is that still kind of the biggest,
0:13:07 I don’t wanna say hurdle, but one of the biggest hurdles
0:13:09 to kind of leveling up success?
0:13:13 – It is, one of the first conversations that I often have
0:13:15 or something I always try to click into
0:13:18 and probably a bit of my kind of geeky background
0:13:21 leads me into is what does your data look like?
0:13:24 Because in order to have responsible AI,
0:13:26 you have to have your data in a state
0:13:29 that you can actually leverage the tools.
0:13:34 And for us, we really take that AI explainability
0:13:35 very seriously.
0:13:37 And so we spend time with our customers
0:13:40 to understand what is the state of their data.
0:13:43 And oftentimes what we find is if you think back
0:13:45 to the transformation 10 years ago
0:13:47 that banks were undergoing,
0:13:51 it was a lot about how it looked and felt to the customers,
0:13:53 not about transforming the back end.
0:13:57 So many banks are made up of acquisitions,
0:13:58 mergers over time.
0:14:02 And so the front end looks really slick and great
0:14:04 and it looks like you’re dealing with one bank
0:14:06 and it’s actually hitting six different banks
0:14:07 in the background.
0:14:08 Right.
0:14:13 And so sometimes it is, working with our clients,
0:14:17 we have a Temnos data product, our RTDH product
0:14:22 and it is bringing that data into a state
0:14:24 that it can then be leveraged.
0:14:27 And so kind of back to that optionality
0:14:29 that we talked to our clients about,
0:14:32 sometimes we may just take a portion of the bank
0:14:36 and really focus on getting the data streamlined
0:14:39 and getting it ready to be able to use that embedded AI
0:14:40 and then proving it out.
0:14:44 And I think as we see, banks are highly regulated,
0:14:45 that’s not going away,
0:14:49 the regulations are gonna get tougher if not anything else.
0:14:52 And so we always keep that top of mind,
0:14:54 making sure that compliance standards
0:14:58 are absolutely embedded into our products
0:15:00 that fully auditable.
0:15:02 And so that’s where a lot of our conversations
0:15:04 end up leading around data is, are you ready?
0:15:05 Right, right.
0:15:07 I’m speaking with Barb Morgan.
0:15:11 Barb is the chief product and technology officer
0:15:14 at Temnos, a role she started within the last year,
0:15:17 the current chapter in an illustrious career
0:15:19 in global product development,
0:15:21 particularly across banking and financial services.
0:15:24 And we’ve been talking about generative AI in particular
0:15:27 and the banking perspective on the chat bot revolution,
0:15:29 if you wanna put it that way,
0:15:30 but just as a leaping off point,
0:15:34 so much more obviously before chat GPT and the bots came
0:15:37 in the world of machine learning and obviously sense
0:15:40 the pace, it’s just been breakneck.
0:15:42 Barb, I wanna kind of shift gears for a second here
0:15:45 if we can and talk a little bit about sustainability
0:15:46 in the industry.
0:15:49 I know that Temnos has a point of view on this
0:15:52 and is actively working with client organizations
0:15:53 to help them be more green.
0:15:55 And I would think that your perspective,
0:15:58 both in the industry and also in kind of the international
0:16:01 nature of the work that you do with Temnos,
0:16:04 curious to hear both the company’s perspective
0:16:07 and what you’re up to with clients to help them be more green,
0:16:10 but also your take, having been around the industry
0:16:13 and around the world literally for a few decades now.
0:16:17 – So to me, sustainability, it’s not a trend.
0:16:19 I think when it really started becoming part
0:16:22 of the conversations, call it maybe 10 years ago
0:16:25 where it actually was part of annual reports
0:16:28 and things like that, I think people kind of questions,
0:16:30 like is this long-term?
0:16:31 And now what we’ve seen the shift is,
0:16:34 it’s really a responsibility of the organization.
0:16:38 And so, when we sit down and we talk with our banks
0:16:39 and why it’s important to us
0:16:42 and bringing some of those solutions forward
0:16:45 that allow them to be greener,
0:16:48 we talk about both what it means to them,
0:16:49 where their focus is.
0:16:52 So to your point, we serve banks globally
0:16:54 and so we see different parts of the world
0:16:59 where it may be more around their carbon accounting
0:17:01 or some areas that may be like,
0:17:04 hey, we really want to understand
0:17:06 how our cloud deployments are helping.
0:17:08 And so understanding like,
0:17:11 how can we drive a greener banking future?
0:17:14 And there are always great conversations
0:17:17 because they really often talk to the values
0:17:18 of the organizations.
0:17:20 And so you get to actually spend time
0:17:22 in the cultural side of the bank.
0:17:26 And what’s really kind of cool for the lack of a better word
0:17:30 about those conversations is when you can use AI
0:17:32 to bring the culture forward in the solutions
0:17:34 through something that really matters to them,
0:17:37 it’s a very rewarding solution, right?
0:17:41 So, like I talked about the smart carbon accounting,
0:17:44 helping our customers track their carbon footprint
0:17:47 both through how they’re using their software
0:17:49 but then being able to offer that to their customers.
0:17:51 There’s many consumers who want to know,
0:17:54 like, hey, how are the purchases that I’m making
0:17:56 impacting my carbon footprint, right?
0:17:58 So not only are we talking to our customers
0:18:00 but we’re actually impacting their end customers as well.
0:18:04 – So kind of to piggyback off that a little bit
0:18:06 and open it up a little more abstractly, I guess.
0:18:07 This is a big question,
0:18:09 but I’ll throw it at you, you can handle it.
0:18:13 How do you see the future of banking being shaped by AI?
0:18:15 And I guess the flip side of that is,
0:18:17 how do you see the future of AI growing and banking?
0:18:21 But I think really, there’s been so much,
0:18:22 we kind of joked about it for a second.
0:18:24 There’s been so much in the past couple of years
0:18:26 with gen AI and the pace isn’t slowing down.
0:18:30 And we have in our notes here to talk about AI agents,
0:18:32 which is kind of the latest thing
0:18:34 buzzword-wise in the past few months, right?
0:18:35 But certainly not a new thing
0:18:37 and certainly something that could wind up
0:18:40 really shaping the technology going forward.
0:18:41 We’ll have to see what plays out.
0:18:43 Do you have a strong view on what you think
0:18:47 is going to happen with AI and banking
0:18:49 and banking kind of being reshaped by the technology?
0:18:52 And that can be short-term next couple of years,
0:18:54 take it a little further out if you like.
0:18:56 What are your thoughts kind of generally on this?
0:18:59 – Yeah, I think even before stepping into that,
0:19:02 I think the one thing that I really see
0:19:06 and I think it’s important to kind of talk about
0:19:09 is the leadership of an organization
0:19:13 really shapes how AI is going to be accepted, right?
0:19:16 Is it the same as a friend or a foe?
0:19:18 If you have your top leadership just talking about
0:19:21 how much money we’re gonna save from AI, it’s a foe, right?
0:19:25 But we’re seeing the leaders of the organizations
0:19:28 really look at AI as not as a threat
0:19:32 and really talking about it as an enabler,
0:19:35 getting people curious, getting people engaged,
0:19:38 more and more organizations, and we do this ourselves,
0:19:40 whether you use the term eating their own dog food
0:19:44 or French would say drinking their own champagne.
0:19:46 We’ve been doing that ourselves to say,
0:19:49 “Hey, let’s actually use this on ourselves.”
0:19:51 And then if it works well for us, great.
0:19:53 We can start to expand it to our customers.
0:19:56 And so when you start to see the leadership
0:19:58 of the organizations, whether it’s the CEO
0:20:02 or any of the C-suite, talking about how they’re curious,
0:20:04 how they’re using it in their daily lives,
0:20:08 how they’re getting in there and playing around themselves
0:20:11 and thinking about how can I get rid of repetitive,
0:20:14 time-consuming tasks and focus on deeper matters
0:20:15 and more strategic work,
0:20:18 you start to see that really come out.
0:20:20 And I think that’s important in order
0:20:22 for people to see AI as a tool
0:20:26 to amplify the human potential, not to replace it.
0:20:30 – Are the bankers, the employees, to put it that way,
0:20:32 are they thinking about it the same way?
0:20:33 Is there excitement?
0:20:35 Is there fear around job replacement?
0:20:37 Is I think– – Any change, right?
0:20:39 There’s always gonna be a bit of fear.
0:20:44 And I think it’s up to us as the banking experts
0:20:46 and as partners to our clients
0:20:49 and then working with their teams
0:20:52 to help kind of show how the change does
0:20:54 actually help them, right?
0:20:59 And so when we see that kind of pivot away from,
0:21:01 “Oh my gosh, this is gonna replace me,”
0:21:02 to, “Wait a second,
0:21:05 “I’m actually gonna sit side-by-side with AI.”
0:21:08 And it’s gonna– – Plus one, you–
0:21:09 – Yes. – I forgive me in a rub.
0:21:10 I just wanted to give you credit.
0:21:12 I hadn’t heard somebody use Plus One
0:21:14 to talk about AI before and I love it, right?
0:21:17 It’s the co-pilot, whatever you wanna call it,
0:21:18 but Plus One is great.
0:21:22 – Yeah, and for me, I really focus on,
0:21:25 I hate the word artificial intelligence
0:21:28 because artificial, it’s fake.
0:21:30 There’s just that negative connotation.
0:21:33 And so I often start out by talking with our clients
0:21:36 about thinking about it as augmented intelligence.
0:21:40 And that gives you that Plus One effect, right?
0:21:43 And then when you show the bankers,
0:21:46 hey, someone’s gonna walk into your branch,
0:21:48 you’re instantly gonna be able to know
0:21:51 more about that customer than they know about themselves.
0:21:55 And you’re gonna be able to have a really deep conversation
0:21:57 both about what’s right for them today,
0:22:00 what’s right for them in the future,
0:22:02 how they’re shaping those things.
0:22:03 Their eyes light up, right?
0:22:06 Because oftentimes they would have to,
0:22:08 the customer would sit in the lobby,
0:22:09 they would do a bunch of research,
0:22:11 they might be pulling paper files out,
0:22:12 they’re trying to remember,
0:22:15 “Okay, this person has been with us for 10 years
0:22:17 “and they have a mortgage and they have a car
0:22:19 “and they have this.”
0:22:19 – Right, right.
0:22:21 – “Oh gosh, what else could I offer them?”
0:22:24 When they can, through natural language questions, say,
0:22:27 “How long has this customer been with us?
0:22:29 “What is their familial history?”
0:22:33 So this may be a 30 year olds,
0:22:37 but maybe their family’s been with the bank for 25, 30 years.
0:22:40 And then when their customer walks up and they say,
0:22:44 “Hey, it’s been great, we’ve served your parents.”
0:22:47 And so excited to have you here with us.
0:22:49 And we had these great,
0:22:51 we’re looking at what loans that you have with us,
0:22:53 we could consolidate those together,
0:22:54 we could offer you a better rate.
0:22:57 We have this great potential over here.
0:22:58 They’re excited, right?
0:23:01 – Yeah, it really kind of,
0:23:03 you sort of made real in listening to you talk about that.
0:23:04 It’s a great example,
0:23:07 ’cause it makes me think of the sort of abstract talk
0:23:11 about machine learning, AI tech, kind of,
0:23:14 freeing humans up to do what humans do
0:23:15 better best.
0:23:18 And in this case, I can relate because it’s not quite AI,
0:23:21 but if it’s not in my phone calendar, I forget it, right?
0:23:24 And so I can only imagine being a banker,
0:23:26 having so many clients to serve.
0:23:28 As you said, I’m in the lobby waiting
0:23:30 because the banker is doing their best
0:23:33 to kind of do a crash course on my whole history
0:23:36 with the bank to serve me, ’cause there’s so many customers,
0:23:37 I’m getting frustrated and waiting, et cetera.
0:23:39 Yeah, let the AI do it.
0:23:41 And then it just, in real time, it pops up.
0:23:43 And yeah, that’s a great example.
0:23:47 And today, I mean, the future is gonna be all
0:23:50 about human and AI collaboration.
0:23:52 We’re already seeing kind of AI agents.
0:23:54 So to your agentic AI, right?
0:23:58 And latest buzzword, handling those routine banking tasks.
0:24:02 But if you can set it up where it’s doing your segmentation,
0:24:04 then it’s doing some product suggestions,
0:24:07 then it’s seeing, as you offer those products,
0:24:10 maybe it’s actually shaping that segmentation.
0:24:12 And so those agents are continually learning
0:24:13 from each other.
0:24:17 And then you can bring that to that human collaboration.
0:24:19 It’s just exciting.
0:24:23 I think we’ll start to see digital humans in making
0:24:26 so that you aren’t saying representative representation.
0:24:29 I was gonna say, when we were talking about that before,
0:24:33 I’m 100% for the plus one,
0:24:35 the augmented intelligence is also,
0:24:37 I like that way of thinking about it as well, right?
0:24:41 And I wanna see humans use the technology to thrive
0:24:43 and not talk about things like replacement, et cetera.
0:24:46 That being said, I’m an impatient person.
0:24:49 And so I always gravitate towards the self-checkouts
0:24:51 at stores.
0:24:55 And so if the automated banking menu could give me,
0:24:58 ’cause I never call unless I have some weird question
0:25:00 or like I’ve missed four payments
0:25:03 and wanna try to beg somebody to give me grace, right?
0:25:05 So yeah, get the automated system to that point
0:25:07 and I’ll be happy.
0:25:10 Yeah, or even think about how great would it be
0:25:13 if your phone pops up, ’cause I know we all,
0:25:16 or at least I know my phone is always within an order.
0:25:17 Yes, yep, yep.
0:25:19 Anywhere, and if it just said,
0:25:22 “Hey, Noah, looks like you missed your last payment.
0:25:24 “Would you like us to auto debit from your account
0:25:27 “and we’ll free up any late fees?”
0:25:28 And you’re like, “Yes, done.”
0:25:30 Yeah, that’s exactly the one, yeah.
0:25:34 And so that proactive monitoring, bringing that,
0:25:36 so that you aren’t even having to call in, right?
0:25:38 You, how much better would that be
0:25:41 if it automatically reaches out to you?
0:25:45 Yeah, if my creditors happen to be listening to the podcast,
0:25:48 I just made that example up, we’re good.
0:25:51 Barb, before we get to wrapping up, I wanted to ask you,
0:25:53 and I think this is something I need to start asking guests
0:25:56 going forward, so thank you for inspiring me.
0:26:00 You mentioned in your work talking to leadership,
0:26:03 it’s so important, it’s such a tone for so many things,
0:26:06 but including an organization’s a bank’s kind of perspective
0:26:07 on embracing AI.
0:26:10 And you talked about getting these clients,
0:26:12 these banking leaders, to start using the tools
0:26:12 in their own life.
0:26:13 Do you have a routine?
0:26:16 Do you have things that you use AI for
0:26:19 on a daily, regular basis that,
0:26:22 maybe a pro tip to share with the audience?
0:26:27 Yes, I might overuse it, that’s probably the engineer in me.
0:26:30 My husband, I’ll be traveling and I’ll get a message,
0:26:31 like, can you turn this thing off?
0:26:33 Like, why are all the lights coming on?
0:26:36 Why is, like, I know you wake up at six,
0:26:38 but I’m not waking up at six when you’re not home.
0:26:40 Like, why is the house waking up for me?
0:26:41 Smart home lights, yeah.
0:26:43 No, no, I mean, you know, for me,
0:26:45 I use it in a couple different ways.
0:26:49 Sometimes I use it just to say, is my message clear, right?
0:26:54 Like, when you’re so deep into whatever your specialty is,
0:26:55 right?
0:26:57 You feel like your message is clear
0:26:59 because you’ve been living, eating, breathing,
0:27:00 working on it for a while.
0:27:03 I can quickly throw that into whatever my favorite tool is,
0:27:06 whether it’s chat, GBT, or perplexity, or whatever,
0:27:10 co-pilot, and say, summarize this message.
0:27:12 What is the tone?
0:27:16 What level of audience is this reaching?
0:27:20 And hopefully, it’ll say, hey, this is actually
0:27:22 geared at a engineering audience.
0:27:24 Oh, well, wait a second, that’s not who I’m speaking to.
0:27:25 Right, that’s great.
0:27:29 Let me make sure that I bring this back into more
0:27:33 of a business speak, or this is very financially focused.
0:27:34 OK, wait a second.
0:27:37 And so I use it oftentimes in a way to sense, check me.
0:27:40 But I also use it for a bit silly stuff, right?
0:27:45 So we have four kids back in the state, all college age,
0:27:47 nine to 22.
0:27:50 And we were going on holidays in Mexico.
0:27:53 And as much as I think I’m a cool mom,
0:27:56 I absolutely used AI to say, what are the best things
0:27:57 to do down in Mexico?
0:27:58 Totally.
0:28:01 Yeah, and it got it pretty close to right.
0:28:03 Like, they like the different restaurants
0:28:04 that we took them to.
0:28:05 And there you go.
0:28:07 Yeah, so I use it quite often.
0:28:11 I also– I play with a lot of tools
0:28:13 outside of the financial industry,
0:28:16 because I think it’s important to see how other industries are
0:28:16 leveraging AI.
0:28:19 It gives us ideas into the financial space,
0:28:21 whether it’s maybe the insurance space.
0:28:23 I was on my insurance app the other day,
0:28:25 and they have AI embedded.
0:28:27 And I thought, wow, this is really cool.
0:28:32 And so looking for ways that other people are using AI
0:28:34 is sometimes the way that I use AI.
0:28:35 Excellent.
0:28:38 Barb, for listeners who would like to learn more
0:28:43 about Temenos approach to AI, other services Temenos offers,
0:28:47 maybe something a little more engineering, geeky oriented.
0:28:48 I don’t know if there’s a developer blog,
0:28:51 or you have other social media, anything.
0:28:54 Where would you direct them to go after listening?
0:28:56 Yeah, whether it’s LinkedIn, if that’s
0:29:00 their favorite within just looking at Temenos.
0:29:03 They will definitely find a cluster of areas to go.
0:29:09 And then, of course, our website, just our www.temenos.com.
0:29:10 They can look at our products.
0:29:13 We do have more of the technical aspects, right?
0:29:16 So our developer portals, and then also just understanding
0:29:19 where our thought leadership is in the space.
0:29:19 Fantastic.
0:29:22 Barb, Morgan, thank you so much for joining the podcast.
0:29:24 This was a pleasure.
0:29:26 I learned some things, which I knew I would.
0:29:27 We talked before we started.
0:29:30 Banking’s not my wheelhouse, so I appreciate that.
0:29:30 Thank you.
0:29:32 But more so, it’s just kind of– it’s always
0:29:36 fascinating to talk to somebody who’s a leader in their field
0:29:39 and has been living and breathing it for long enough to–
0:29:42 we’re talking about world-changing technology,
0:29:44 but there are deeper things that have been around for a while
0:29:48 now that are really important to shaping your perspective.
0:29:50 So your perspective is greatly appreciated.
0:29:52 Thank you.
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0:00:13 Hello, and welcome to the NVIDIA AI podcast.
0:00:15 I’m your host, Noah Kravitz.
0:00:17 Since its founding in 1993,
0:00:21 Temenos has been on a mission to revolutionize banking.
0:00:23 Its open platform enables people across the world
0:00:25 to carry out their daily banking needs,
0:00:27 and for banking providers to build new services
0:00:30 and state-of-the-art consumer experiences
0:00:33 using AI and other cutting-edge technology.
0:00:35 Starting a bit more recently,
0:00:37 our guest has been leaning Temenos efforts
0:00:38 to drive digital transformation
0:00:41 from financial institutions across the world.
0:00:44 In October of last year, 2024, to be specific,
0:00:47 Barb Morgan joined Temenos as chief product
0:00:48 and technology officer,
0:00:51 bringing over 25 years of leadership experience
0:00:53 in global product development organizations
0:00:54 with her to the role.
0:00:57 Barb has done a lot in banking and financial services
0:01:00 to put it mildly, especially with AI and cloud tech.
0:01:02 In fact, it’ll be better to ask her
0:01:03 to tell us about her background.
0:01:05 So we’ll start there in just a second,
0:01:07 except that I will add that Barb holds
0:01:09 a Bachelor of Science in Computer Science
0:01:11 from the University of Central Oklahoma.
0:01:13 That said, Barb is here to talk about
0:01:14 generative AI and banking,
0:01:16 Temenos’ approach to AI,
0:01:18 and the importance of sustainability
0:01:19 in the industry for starters.
0:01:20 So let’s get to it.
0:01:23 Bob Morgan, welcome, and thank you so much
0:01:25 for joining the NVIDIA AI podcast.
0:01:27 – Thanks, Noah, excited to be here.
0:01:29 – Excited to have you.
0:01:31 All right, so I teased it in the intro a little bit,
0:01:34 but maybe we can start with you telling us a bit
0:01:35 about your background,
0:01:37 your journey into working with AI,
0:01:39 and how you landed at Temenos.
0:01:41 – Absolutely, so I actually started
0:01:43 with my hands on the keyboard.
0:01:46 So I was a developer many years ago.
0:01:49 When you said 25 years, I had to smile a bit
0:01:51 ’cause it reminds me how long career has been.
0:01:55 But now, my career did start with the hands on the keyboard,
0:01:58 but I always really enjoyed that link
0:02:00 between what we were doing with technology
0:02:02 and how that was really impacting the customer.
0:02:05 And so as my career continued
0:02:07 to kind of go through my journey,
0:02:10 I really gravitated towards those areas
0:02:13 that had a strong customer centricity.
0:02:15 And so I spent about the past 15 years of my career
0:02:18 focused in the financial services industry.
0:02:23 So I’ve led transformations inside banks within techs,
0:02:24 side by side with the banks,
0:02:27 and really focused around modernizing core systems,
0:02:29 building innovative products,
0:02:31 and accelerating AI adoption,
0:02:34 which you can’t have a conversation anymore without AI.
0:02:37 But AI isn’t new to me.
0:02:40 We’ve been using it for years from fraud detection,
0:02:42 risk modeling, automation,
0:02:45 but what’s really different now is we’re seeing that shift
0:02:50 where Gen AI has shifted the entire landscape
0:02:51 where it’s not about efficiency,
0:02:54 it’s really about making the bank smarter,
0:02:58 more intuitive, and bringing that hyper-personalization
0:02:59 to the clients.
0:03:01 It’s exciting when we talk to our clients.
0:03:05 So as you mentioned, I joined Temno’s in October,
0:03:08 and I’ve spent, in my past four months,
0:03:12 a lot of time out there just talking with the clients,
0:03:13 understanding what they’re thinking about,
0:03:15 whether it’s the CEO, CTO,
0:03:19 and they really want to get back to their customers, right?
0:03:22 Whether it’s having us run a banking suite for them on SaaS
0:03:24 so that they can focus on their customers
0:03:28 versus infrastructure, leveraging AI,
0:03:31 but that customer centricity is really coming out,
0:03:33 and it’s paired so nicely with the Gen AI.
0:03:37 – It’s interesting you mentioned the shift from efficiency,
0:03:39 and not that efficiency is a thing of the past,
0:03:42 I’m sure in the banking sector especially,
0:03:44 but kind of that shift from efficiency
0:03:47 to the customer relationship
0:03:49 and how can we better serve customers?
0:03:53 And is that something that you felt happening
0:03:56 before Gen AI in particular
0:03:58 kind of took center stage over the past couple of years,
0:04:00 or is it something that you think
0:04:03 kind of followed the technology that people realized,
0:04:06 like, oh, this is a great way to do all these things
0:04:08 with customer, you know,
0:04:10 personalization, customer service, what have you,
0:04:13 and that trend sort of followed the tech?
0:04:17 – I think the era of the chat box, right?
0:04:20 Which was kind of that first introduction.
0:04:23 When you were sitting on the technology side,
0:04:25 whether inside the bank or at Vintex,
0:04:26 we thought, this is fantastic.
0:04:28 And what we realized was it was actually
0:04:30 really frustrating to the clients.
0:04:33 I don’t know if you’ve ever called into your bank
0:04:37 and it’s like, press one for this, press two for this,
0:04:40 and then you just end up mashing that zero key, right?
0:04:43 – I’m just screaming representative in the phone,
0:04:44 is that right?
0:04:47 And so now I think what we’ve seen
0:04:50 where technology is leading,
0:04:55 is that Gen AI can bring that human centered approach,
0:04:58 and really bringing more humans back
0:05:00 to that immediate touch point with customer,
0:05:05 because now all that data can get pulled instantly.
0:05:07 And so you don’t have to go through
0:05:10 that representative representative.
0:05:14 And so I do think that we thought technology was leading
0:05:16 when kind of that era of the chat bots
0:05:21 and some of the different customer type efficiencies,
0:05:23 we’re playing out maybe five, 10 years ago.
0:05:26 But now I think technology truly is leading
0:05:28 and people are seeing it as an abler
0:05:31 versus again, just that cost efficiency.
0:05:32 – Right, right.
0:05:34 Maybe you can unpack a little bit
0:05:37 what it means from the banker side
0:05:39 to deliver a better experience
0:05:43 and how they’re thinking about leveraging Gen AI
0:05:44 and related technologies.
0:05:46 I love, I’m not even a developer,
0:05:50 but I get on my high horse when people talk about Gen AI
0:05:52 as if it’s the only kind of artificial intelligence, right?
0:05:54 So machine learning, predictive analytics,
0:05:57 all these things, those are not, like we said,
0:05:58 they’re not going away,
0:05:59 but from the bankers perspective,
0:06:01 what are they excited about now?
0:06:04 What are some of the some of us banking customers doing
0:06:07 to leverage this tech to deliver better experiences
0:06:09 and make their clients happier?
0:06:12 – Yeah, I think we’re seeing kind of two themes
0:06:14 really kind of play out
0:06:16 when we have the conversations with the banks.
0:06:20 And the first one is, how can they help their team?
0:06:22 And then secondly, can they help their customers?
0:06:26 So from the perspective of helping their teams,
0:06:27 they’re asking us questions of,
0:06:30 how can we give our bankers instant access to insight?
0:06:33 How can we leverage the historical data
0:06:36 and make recommendations almost instantly?
0:06:38 How can we have those richer
0:06:42 more meaningful conversations enabled for our bankers?
0:06:45 And so that’s really kind of that internal look of his,
0:06:48 how can AI sit side by side
0:06:52 and really be that plus one in the conversation.
0:06:54 I think for the customers,
0:06:56 it goes back to that hyper personalization,
0:06:59 whether it’s pay-learning loan options
0:07:00 or giving them insights
0:07:02 that they hadn’t thought about before,
0:07:06 both from historical, but also predictive in the future.
0:07:09 And then there’s the speed that customers expect now.
0:07:11 Everyone seems to have,
0:07:13 whether it’s chat, GBT or perplexity
0:07:15 or whatever loaded onto their phone,
0:07:17 everyone expects that instant answer now.
0:07:19 And so they expect that everywhere,
0:07:21 but we’re in a highly regulated space.
0:07:23 And so making sure that we do that
0:07:25 in a very responsible way.
0:07:28 But some of the things that we’re doing that,
0:07:31 I really enjoy myself and try to entrench myself
0:07:33 with the teams as much as I can on
0:07:36 is instead of just coming up with solutions
0:07:37 and going out to our clients,
0:07:40 we’re doing a lot of co-design around the AI solution.
0:07:45 So really saying, hey, here’s five or six use cases.
0:07:46 Which of these stands out to you?
0:07:48 Which one or two of these do?
0:07:50 Let’s sit side by side.
0:07:53 Let’s think about how we can co-develop this together.
0:07:54 One that we’re working on recently
0:07:56 is a AI powered solution
0:07:59 that allows the product managers at the bank
0:08:01 to create those financial products,
0:08:04 leveraging that data insight.
0:08:07 And that was where that predictive future capabilities
0:08:08 came into question, right?
0:08:12 So based off of the history, what can we predict?
0:08:14 And we can give you the bank’s knowledge.
0:08:17 We have bank expertise as well,
0:08:19 because we serve 1,000 different banks
0:08:21 or more than 1,000 banks.
0:08:22 And so bringing that all together
0:08:25 to think about future predictions,
0:08:27 pulling it together and giving the right products
0:08:30 to the right customers at the right time.
0:08:33 For me, it’s also,
0:08:35 we don’t wanna leave any of our customers behind.
0:08:38 One of the things that I really enjoy
0:08:40 about what we bring to our clients is,
0:08:41 we focus on flexibility.
0:08:46 And what I mean by that from a pure tech stack perspective
0:08:48 is if you’re gonna be on-prem,
0:08:50 if they wanna be in the cloud or if they want SaaS,
0:08:51 they have the optionality.
0:08:56 And so partnering most recently with Amidia to bring AI
0:09:02 to our on-prem banks has been hugely well received.
0:09:06 Just that ability to give that AI-driven analysis
0:09:09 with those massive data sets that they have on-prem
0:09:12 but allowing them to control the security around it,
0:09:16 allowing them to really not need to have
0:09:19 the deep technical expertise to analyze.
0:09:21 And so a lot of excitement there.
0:09:24 And it’s good too, because we were talking
0:09:26 with the bank the other day and he said,
0:09:29 our ability to have adequate data management
0:09:30 is very limited.
0:09:32 There’s areas we’ve invested,
0:09:35 but it might be 25% of our landscape
0:09:37 that we actually can pull analytics.
0:09:40 So these tools that can look across those massive data sets
0:09:42 are really exciting.
0:09:45 – So to kind of take a step back for a second,
0:09:49 if you don’t mind, Teminos offers a platform.
0:09:51 And so when you’re talking about,
0:09:53 I just kind of wanted to unpack for the listener
0:09:55 what Teminos actually does.
0:09:57 And my understanding is, it’s services,
0:10:01 within you also have a platform where clients
0:10:03 can build products for their banks?
0:10:07 – Yeah, so in kind of three different ways.
0:10:11 So first we have a end-to-end banking platform.
0:10:15 And so for our banks, within like, let’s say within the US,
0:10:17 our tier three regional banks will come in
0:10:19 and they’ll take an end-to-end platform
0:10:22 that provides all of the capabilities of banking.
0:10:25 – Almost like a turnkey banking solution, okay.
0:10:29 And that’s where we see a lot of the adoption of SaaS,
0:10:32 bring us a bank, even within kind of
0:10:33 that neo banking space as well.
0:10:38 But then we also, we also offer modular solutions
0:10:39 to our clients.
0:10:42 And so if you look at some of our tier one banks,
0:10:44 they don’t wanna replace their whole platform, right?
0:10:46 And so, but they may come to us and say,
0:10:50 hey, we just want your payments module
0:10:53 or we just want your originations.
0:10:56 And so giving that choice and flexibility,
0:10:58 whether they want the full platform
0:11:01 or they want modulars within the platform.
0:11:03 And then we also offer products
0:11:05 around what we call point solutions.
0:11:08 So things that may be add-ons that they may choose
0:11:10 to build themselves and plug into our platform,
0:11:11 like their digital interface.
0:11:14 Or we also offer a digital interface
0:11:17 that they can leverage with our suite.
0:11:18 – Gotcha, thank you.
0:11:20 And you serve bank customers of all sizes?
0:11:24 – We do, so we have over a thousand banks globally.
0:11:27 So we have a very global footprint
0:11:30 from the Americas to Mia to APAC.
0:11:34 And so, with that, it’s everything from tier one banks
0:11:37 all the way down to the near banks.
0:11:40 – Are you seeing similar or different trends
0:11:42 in terms of, I guess both adoption rates
0:11:44 from smaller banks and larger banks
0:11:45 when it comes to AI tools,
0:11:47 but also what they’re using them for?
0:11:50 Or is it everyone primarily is customer service?
0:11:53 Like this is the big, it’s not just low hanging fruit.
0:11:55 Like it’s a potentially really big win.
0:11:56 Is that just where the focus is now?
0:12:00 – I would say AI is no longer an option, right?
0:12:03 So they have to have AI, whether it’s embedded,
0:12:07 whether it’s actually more of a feature functionality,
0:12:09 maybe within their digital to allow their customers
0:12:13 to click on some type of AI agent.
0:12:17 But I would say we see two different lens on this.
0:12:21 So one is regionally, you have different areas
0:12:25 that they’re more prone to adopt AI faster
0:12:26 than other regions.
0:12:28 And then from the customer tiering,
0:12:32 what I would say is the tier one, tier two banks,
0:12:34 absolutely they wanted embedded in their product.
0:12:38 The kind of tier three banks, regional banks,
0:12:42 they’re really focused on the personalization that it brings.
0:12:44 – Okay, you kind of alluded to this a little bit,
0:12:49 but is just gathering data and helping the banks
0:12:54 kind of find and gather up and scrub and prepare and use.
0:12:59 You mentioned the example of only 25% of the data
0:13:00 actually going to analytics.
0:13:02 I’m getting that wrong on my paraphrasing,
0:13:04 but is that still kind of the biggest,
0:13:07 I don’t wanna say hurdle, but one of the biggest hurdles
0:13:09 to kind of leveling up success?
0:13:13 – It is, one of the first conversations that I often have
0:13:15 or something I always try to click into
0:13:18 and probably a bit of my kind of geeky background
0:13:21 leads me into is what does your data look like?
0:13:24 Because in order to have responsible AI,
0:13:26 you have to have your data in a state
0:13:29 that you can actually leverage the tools.
0:13:34 And for us, we really take that AI explainability
0:13:35 very seriously.
0:13:37 And so we spend time with our customers
0:13:40 to understand what is the state of their data.
0:13:43 And oftentimes what we find is if you think back
0:13:45 to the transformation 10 years ago
0:13:47 that banks were undergoing,
0:13:51 it was a lot about how it looked and felt to the customers,
0:13:53 not about transforming the back end.
0:13:57 So many banks are made up of acquisitions,
0:13:58 mergers over time.
0:14:02 And so the front end looks really slick and great
0:14:04 and it looks like you’re dealing with one bank
0:14:06 and it’s actually hitting six different banks
0:14:07 in the background.
0:14:08 Right.
0:14:13 And so sometimes it is, working with our clients,
0:14:17 we have a Temnos data product, our RTDH product
0:14:22 and it is bringing that data into a state
0:14:24 that it can then be leveraged.
0:14:27 And so kind of back to that optionality
0:14:29 that we talked to our clients about,
0:14:32 sometimes we may just take a portion of the bank
0:14:36 and really focus on getting the data streamlined
0:14:39 and getting it ready to be able to use that embedded AI
0:14:40 and then proving it out.
0:14:44 And I think as we see, banks are highly regulated,
0:14:45 that’s not going away,
0:14:49 the regulations are gonna get tougher if not anything else.
0:14:52 And so we always keep that top of mind,
0:14:54 making sure that compliance standards
0:14:58 are absolutely embedded into our products
0:15:00 that fully auditable.
0:15:02 And so that’s where a lot of our conversations
0:15:04 end up leading around data is, are you ready?
0:15:05 Right, right.
0:15:07 I’m speaking with Barb Morgan.
0:15:11 Barb is the chief product and technology officer
0:15:14 at Temnos, a role she started within the last year,
0:15:17 the current chapter in an illustrious career
0:15:19 in global product development,
0:15:21 particularly across banking and financial services.
0:15:24 And we’ve been talking about generative AI in particular
0:15:27 and the banking perspective on the chat bot revolution,
0:15:29 if you wanna put it that way,
0:15:30 but just as a leaping off point,
0:15:34 so much more obviously before chat GPT and the bots came
0:15:37 in the world of machine learning and obviously sense
0:15:40 the pace, it’s just been breakneck.
0:15:42 Barb, I wanna kind of shift gears for a second here
0:15:45 if we can and talk a little bit about sustainability
0:15:46 in the industry.
0:15:49 I know that Temnos has a point of view on this
0:15:52 and is actively working with client organizations
0:15:53 to help them be more green.
0:15:55 And I would think that your perspective,
0:15:58 both in the industry and also in kind of the international
0:16:01 nature of the work that you do with Temnos,
0:16:04 curious to hear both the company’s perspective
0:16:07 and what you’re up to with clients to help them be more green,
0:16:10 but also your take, having been around the industry
0:16:13 and around the world literally for a few decades now.
0:16:17 – So to me, sustainability, it’s not a trend.
0:16:19 I think when it really started becoming part
0:16:22 of the conversations, call it maybe 10 years ago
0:16:25 where it actually was part of annual reports
0:16:28 and things like that, I think people kind of questions,
0:16:30 like is this long-term?
0:16:31 And now what we’ve seen the shift is,
0:16:34 it’s really a responsibility of the organization.
0:16:38 And so, when we sit down and we talk with our banks
0:16:39 and why it’s important to us
0:16:42 and bringing some of those solutions forward
0:16:45 that allow them to be greener,
0:16:48 we talk about both what it means to them,
0:16:49 where their focus is.
0:16:52 So to your point, we serve banks globally
0:16:54 and so we see different parts of the world
0:16:59 where it may be more around their carbon accounting
0:17:01 or some areas that may be like,
0:17:04 hey, we really want to understand
0:17:06 how our cloud deployments are helping.
0:17:08 And so understanding like,
0:17:11 how can we drive a greener banking future?
0:17:14 And there are always great conversations
0:17:17 because they really often talk to the values
0:17:18 of the organizations.
0:17:20 And so you get to actually spend time
0:17:22 in the cultural side of the bank.
0:17:26 And what’s really kind of cool for the lack of a better word
0:17:30 about those conversations is when you can use AI
0:17:32 to bring the culture forward in the solutions
0:17:34 through something that really matters to them,
0:17:37 it’s a very rewarding solution, right?
0:17:41 So, like I talked about the smart carbon accounting,
0:17:44 helping our customers track their carbon footprint
0:17:47 both through how they’re using their software
0:17:49 but then being able to offer that to their customers.
0:17:51 There’s many consumers who want to know,
0:17:54 like, hey, how are the purchases that I’m making
0:17:56 impacting my carbon footprint, right?
0:17:58 So not only are we talking to our customers
0:18:00 but we’re actually impacting their end customers as well.
0:18:04 – So kind of to piggyback off that a little bit
0:18:06 and open it up a little more abstractly, I guess.
0:18:07 This is a big question,
0:18:09 but I’ll throw it at you, you can handle it.
0:18:13 How do you see the future of banking being shaped by AI?
0:18:15 And I guess the flip side of that is,
0:18:17 how do you see the future of AI growing and banking?
0:18:21 But I think really, there’s been so much,
0:18:22 we kind of joked about it for a second.
0:18:24 There’s been so much in the past couple of years
0:18:26 with gen AI and the pace isn’t slowing down.
0:18:30 And we have in our notes here to talk about AI agents,
0:18:32 which is kind of the latest thing
0:18:34 buzzword-wise in the past few months, right?
0:18:35 But certainly not a new thing
0:18:37 and certainly something that could wind up
0:18:40 really shaping the technology going forward.
0:18:41 We’ll have to see what plays out.
0:18:43 Do you have a strong view on what you think
0:18:47 is going to happen with AI and banking
0:18:49 and banking kind of being reshaped by the technology?
0:18:52 And that can be short-term next couple of years,
0:18:54 take it a little further out if you like.
0:18:56 What are your thoughts kind of generally on this?
0:18:59 – Yeah, I think even before stepping into that,
0:19:02 I think the one thing that I really see
0:19:06 and I think it’s important to kind of talk about
0:19:09 is the leadership of an organization
0:19:13 really shapes how AI is going to be accepted, right?
0:19:16 Is it the same as a friend or a foe?
0:19:18 If you have your top leadership just talking about
0:19:21 how much money we’re gonna save from AI, it’s a foe, right?
0:19:25 But we’re seeing the leaders of the organizations
0:19:28 really look at AI as not as a threat
0:19:32 and really talking about it as an enabler,
0:19:35 getting people curious, getting people engaged,
0:19:38 more and more organizations, and we do this ourselves,
0:19:40 whether you use the term eating their own dog food
0:19:44 or French would say drinking their own champagne.
0:19:46 We’ve been doing that ourselves to say,
0:19:49 “Hey, let’s actually use this on ourselves.”
0:19:51 And then if it works well for us, great.
0:19:53 We can start to expand it to our customers.
0:19:56 And so when you start to see the leadership
0:19:58 of the organizations, whether it’s the CEO
0:20:02 or any of the C-suite, talking about how they’re curious,
0:20:04 how they’re using it in their daily lives,
0:20:08 how they’re getting in there and playing around themselves
0:20:11 and thinking about how can I get rid of repetitive,
0:20:14 time-consuming tasks and focus on deeper matters
0:20:15 and more strategic work,
0:20:18 you start to see that really come out.
0:20:20 And I think that’s important in order
0:20:22 for people to see AI as a tool
0:20:26 to amplify the human potential, not to replace it.
0:20:30 – Are the bankers, the employees, to put it that way,
0:20:32 are they thinking about it the same way?
0:20:33 Is there excitement?
0:20:35 Is there fear around job replacement?
0:20:37 Is I think– – Any change, right?
0:20:39 There’s always gonna be a bit of fear.
0:20:44 And I think it’s up to us as the banking experts
0:20:46 and as partners to our clients
0:20:49 and then working with their teams
0:20:52 to help kind of show how the change does
0:20:54 actually help them, right?
0:20:59 And so when we see that kind of pivot away from,
0:21:01 “Oh my gosh, this is gonna replace me,”
0:21:02 to, “Wait a second,
0:21:05 “I’m actually gonna sit side-by-side with AI.”
0:21:08 And it’s gonna– – Plus one, you–
0:21:09 – Yes. – I forgive me in a rub.
0:21:10 I just wanted to give you credit.
0:21:12 I hadn’t heard somebody use Plus One
0:21:14 to talk about AI before and I love it, right?
0:21:17 It’s the co-pilot, whatever you wanna call it,
0:21:18 but Plus One is great.
0:21:22 – Yeah, and for me, I really focus on,
0:21:25 I hate the word artificial intelligence
0:21:28 because artificial, it’s fake.
0:21:30 There’s just that negative connotation.
0:21:33 And so I often start out by talking with our clients
0:21:36 about thinking about it as augmented intelligence.
0:21:40 And that gives you that Plus One effect, right?
0:21:43 And then when you show the bankers,
0:21:46 hey, someone’s gonna walk into your branch,
0:21:48 you’re instantly gonna be able to know
0:21:51 more about that customer than they know about themselves.
0:21:55 And you’re gonna be able to have a really deep conversation
0:21:57 both about what’s right for them today,
0:22:00 what’s right for them in the future,
0:22:02 how they’re shaping those things.
0:22:03 Their eyes light up, right?
0:22:06 Because oftentimes they would have to,
0:22:08 the customer would sit in the lobby,
0:22:09 they would do a bunch of research,
0:22:11 they might be pulling paper files out,
0:22:12 they’re trying to remember,
0:22:15 “Okay, this person has been with us for 10 years
0:22:17 “and they have a mortgage and they have a car
0:22:19 “and they have this.”
0:22:19 – Right, right.
0:22:21 – “Oh gosh, what else could I offer them?”
0:22:24 When they can, through natural language questions, say,
0:22:27 “How long has this customer been with us?
0:22:29 “What is their familial history?”
0:22:33 So this may be a 30 year olds,
0:22:37 but maybe their family’s been with the bank for 25, 30 years.
0:22:40 And then when their customer walks up and they say,
0:22:44 “Hey, it’s been great, we’ve served your parents.”
0:22:47 And so excited to have you here with us.
0:22:49 And we had these great,
0:22:51 we’re looking at what loans that you have with us,
0:22:53 we could consolidate those together,
0:22:54 we could offer you a better rate.
0:22:57 We have this great potential over here.
0:22:58 They’re excited, right?
0:23:01 – Yeah, it really kind of,
0:23:03 you sort of made real in listening to you talk about that.
0:23:04 It’s a great example,
0:23:07 ’cause it makes me think of the sort of abstract talk
0:23:11 about machine learning, AI tech, kind of,
0:23:14 freeing humans up to do what humans do
0:23:15 better best.
0:23:18 And in this case, I can relate because it’s not quite AI,
0:23:21 but if it’s not in my phone calendar, I forget it, right?
0:23:24 And so I can only imagine being a banker,
0:23:26 having so many clients to serve.
0:23:28 As you said, I’m in the lobby waiting
0:23:30 because the banker is doing their best
0:23:33 to kind of do a crash course on my whole history
0:23:36 with the bank to serve me, ’cause there’s so many customers,
0:23:37 I’m getting frustrated and waiting, et cetera.
0:23:39 Yeah, let the AI do it.
0:23:41 And then it just, in real time, it pops up.
0:23:43 And yeah, that’s a great example.
0:23:47 And today, I mean, the future is gonna be all
0:23:50 about human and AI collaboration.
0:23:52 We’re already seeing kind of AI agents.
0:23:54 So to your agentic AI, right?
0:23:58 And latest buzzword, handling those routine banking tasks.
0:24:02 But if you can set it up where it’s doing your segmentation,
0:24:04 then it’s doing some product suggestions,
0:24:07 then it’s seeing, as you offer those products,
0:24:10 maybe it’s actually shaping that segmentation.
0:24:12 And so those agents are continually learning
0:24:13 from each other.
0:24:17 And then you can bring that to that human collaboration.
0:24:19 It’s just exciting.
0:24:23 I think we’ll start to see digital humans in making
0:24:26 so that you aren’t saying representative representation.
0:24:29 I was gonna say, when we were talking about that before,
0:24:33 I’m 100% for the plus one,
0:24:35 the augmented intelligence is also,
0:24:37 I like that way of thinking about it as well, right?
0:24:41 And I wanna see humans use the technology to thrive
0:24:43 and not talk about things like replacement, et cetera.
0:24:46 That being said, I’m an impatient person.
0:24:49 And so I always gravitate towards the self-checkouts
0:24:51 at stores.
0:24:55 And so if the automated banking menu could give me,
0:24:58 ’cause I never call unless I have some weird question
0:25:00 or like I’ve missed four payments
0:25:03 and wanna try to beg somebody to give me grace, right?
0:25:05 So yeah, get the automated system to that point
0:25:07 and I’ll be happy.
0:25:10 Yeah, or even think about how great would it be
0:25:13 if your phone pops up, ’cause I know we all,
0:25:16 or at least I know my phone is always within an order.
0:25:17 Yes, yep, yep.
0:25:19 Anywhere, and if it just said,
0:25:22 “Hey, Noah, looks like you missed your last payment.
0:25:24 “Would you like us to auto debit from your account
0:25:27 “and we’ll free up any late fees?”
0:25:28 And you’re like, “Yes, done.”
0:25:30 Yeah, that’s exactly the one, yeah.
0:25:34 And so that proactive monitoring, bringing that,
0:25:36 so that you aren’t even having to call in, right?
0:25:38 You, how much better would that be
0:25:41 if it automatically reaches out to you?
0:25:45 Yeah, if my creditors happen to be listening to the podcast,
0:25:48 I just made that example up, we’re good.
0:25:51 Barb, before we get to wrapping up, I wanted to ask you,
0:25:53 and I think this is something I need to start asking guests
0:25:56 going forward, so thank you for inspiring me.
0:26:00 You mentioned in your work talking to leadership,
0:26:03 it’s so important, it’s such a tone for so many things,
0:26:06 but including an organization’s a bank’s kind of perspective
0:26:07 on embracing AI.
0:26:10 And you talked about getting these clients,
0:26:12 these banking leaders, to start using the tools
0:26:12 in their own life.
0:26:13 Do you have a routine?
0:26:16 Do you have things that you use AI for
0:26:19 on a daily, regular basis that,
0:26:22 maybe a pro tip to share with the audience?
0:26:27 Yes, I might overuse it, that’s probably the engineer in me.
0:26:30 My husband, I’ll be traveling and I’ll get a message,
0:26:31 like, can you turn this thing off?
0:26:33 Like, why are all the lights coming on?
0:26:36 Why is, like, I know you wake up at six,
0:26:38 but I’m not waking up at six when you’re not home.
0:26:40 Like, why is the house waking up for me?
0:26:41 Smart home lights, yeah.
0:26:43 No, no, I mean, you know, for me,
0:26:45 I use it in a couple different ways.
0:26:49 Sometimes I use it just to say, is my message clear, right?
0:26:54 Like, when you’re so deep into whatever your specialty is,
0:26:55 right?
0:26:57 You feel like your message is clear
0:26:59 because you’ve been living, eating, breathing,
0:27:00 working on it for a while.
0:27:03 I can quickly throw that into whatever my favorite tool is,
0:27:06 whether it’s chat, GBT, or perplexity, or whatever,
0:27:10 co-pilot, and say, summarize this message.
0:27:12 What is the tone?
0:27:16 What level of audience is this reaching?
0:27:20 And hopefully, it’ll say, hey, this is actually
0:27:22 geared at a engineering audience.
0:27:24 Oh, well, wait a second, that’s not who I’m speaking to.
0:27:25 Right, that’s great.
0:27:29 Let me make sure that I bring this back into more
0:27:33 of a business speak, or this is very financially focused.
0:27:34 OK, wait a second.
0:27:37 And so I use it oftentimes in a way to sense, check me.
0:27:40 But I also use it for a bit silly stuff, right?
0:27:45 So we have four kids back in the state, all college age,
0:27:47 nine to 22.
0:27:50 And we were going on holidays in Mexico.
0:27:53 And as much as I think I’m a cool mom,
0:27:56 I absolutely used AI to say, what are the best things
0:27:57 to do down in Mexico?
0:27:58 Totally.
0:28:01 Yeah, and it got it pretty close to right.
0:28:03 Like, they like the different restaurants
0:28:04 that we took them to.
0:28:05 And there you go.
0:28:07 Yeah, so I use it quite often.
0:28:11 I also– I play with a lot of tools
0:28:13 outside of the financial industry,
0:28:16 because I think it’s important to see how other industries are
0:28:16 leveraging AI.
0:28:19 It gives us ideas into the financial space,
0:28:21 whether it’s maybe the insurance space.
0:28:23 I was on my insurance app the other day,
0:28:25 and they have AI embedded.
0:28:27 And I thought, wow, this is really cool.
0:28:32 And so looking for ways that other people are using AI
0:28:34 is sometimes the way that I use AI.
0:28:35 Excellent.
0:28:38 Barb, for listeners who would like to learn more
0:28:43 about Temenos approach to AI, other services Temenos offers,
0:28:47 maybe something a little more engineering, geeky oriented.
0:28:48 I don’t know if there’s a developer blog,
0:28:51 or you have other social media, anything.
0:28:54 Where would you direct them to go after listening?
0:28:56 Yeah, whether it’s LinkedIn, if that’s
0:29:00 their favorite within just looking at Temenos.
0:29:03 They will definitely find a cluster of areas to go.
0:29:09 And then, of course, our website, just our www.temenos.com.
0:29:10 They can look at our products.
0:29:13 We do have more of the technical aspects, right?
0:29:16 So our developer portals, and then also just understanding
0:29:19 where our thought leadership is in the space.
0:29:19 Fantastic.
0:29:22 Barb, Morgan, thank you so much for joining the podcast.
0:29:24 This was a pleasure.
0:29:26 I learned some things, which I knew I would.
0:29:27 We talked before we started.
0:29:30 Banking’s not my wheelhouse, so I appreciate that.
0:29:30 Thank you.
0:29:32 But more so, it’s just kind of– it’s always
0:29:36 fascinating to talk to somebody who’s a leader in their field
0:29:39 and has been living and breathing it for long enough to–
0:29:42 we’re talking about world-changing technology,
0:29:44 but there are deeper things that have been around for a while
0:29:48 now that are really important to shaping your perspective.
0:29:50 So your perspective is greatly appreciated.
0:29:52 Thank you.
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AI is transforming banking by providing hyper-personalized services and real-time insights, enhancing customer experiences and ensuring robust data security. Barb Morgan, chief product and technology officer at Temenos, shares her expertise on how AI is transforming the banking landscape.