AI transcript
[MUSIC]
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 leaning Temenos 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
in 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 and banking,
Temenos’ approach to AI,
and the importance of sustainability
in the industry for starters.
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 Temenos.
– Absolutely, so I actually started
with my hands on the keyboard.
So I was a developer many years ago.
When you said 25 years, I had to smile a bit
’cause it reminds me how long career has been.
But now, my career did start with the hands on the keyboard,
but I always really enjoyed that link
between what we were doing with technology
and how that was really impacting the customer.
And so as my career continued
to kind of go through my journey,
I really gravitated towards those areas
that had a strong customer centricity.
And so I spent about the past 15 years of my career
focused in the financial services industry.
So I’ve led transformations inside banks within techs,
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 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 hyper-personalization
to the clients.
It’s exciting when we talk to our clients.
So as you mentioned, I joined Temno’s in October,
and I’ve spent, in my past four months,
a lot of time out there just talking with the clients,
understanding what they’re thinking about,
whether it’s the CEO, CTO,
and they really want to get back to their customers, right?
Whether it’s 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 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 people realized,
like, oh, this is a great way to do all these things
with customer, 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?
Which was kind of that first introduction.
When you were sitting on the technology side,
whether inside the bank or at Vintex,
we thought, this is fantastic.
And what we realized was it was actually
really frustrating to the clients.
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, right?
– I’m just screaming representative in the phone,
is that right?
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 touch point with customer,
because now all that data can get pulled instantly.
And so you don’t have to go through
that representative representative.
And so I do think that we thought technology was leading
when kind of that era of the chat bots
and some of the different customer type efficiencies,
we’re playing out maybe five, 10 years ago.
But now I think technology truly is leading
and people are seeing it as an abler
versus again, just that cost efficiency.
– Right, right.
Maybe you can unpack a little bit
what it means from the banker side
to deliver a better experience
and 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 kind of artificial intelligence, right?
So machine learning, predictive analytics,
all these things, those are not, like we said,
they’re not going away,
but from the bankers perspective,
what are they excited about now?
What are some of the some of us banking customers doing
to leverage this tech to deliver better experiences
and make their clients happier?
– Yeah, I think 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, how can they help their team?
And then secondly, can they help their customers?
So from the perspective of helping their teams,
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?
How can we have those richer
more meaningful conversations enabled for our bankers?
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,
whether it’s pay-learning 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 the speed that customers expect now.
Everyone seems to have,
whether it’s chat, GBT or perplexity
or whatever loaded onto their phone,
everyone expects that instant answer now.
And so they expect that everywhere,
but we’re in a highly regulated space.
And so making sure that we do that
in a very responsible way.
But some of the things that we’re doing that,
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 going out to our clients,
we’re doing a lot of co-design around the AI solution.
So really saying, hey, here’s five or six 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 a AI powered solution
that allows the product managers at the bank
to create those financial products,
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 1,000 different banks
or more than 1,000 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.
For me, it’s also,
we don’t wanna leave any of our customers behind.
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’re gonna be on-prem,
if they wanna be in the cloud or if they want SaaS,
they have the optionality.
And so partnering most recently with Amidia to bring AI
to our on-prem banks has been hugely well received.
Just that ability to give that AI-driven analysis
with those massive data sets that they have on-prem
but allowing them to control the security around it,
allowing them to really not need to have
the deep technical expertise to analyze.
And so a lot of excitement there.
And it’s good too, because we were talking
with the bank the other day and he said,
our ability to have adequate data management
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, Teminos offers a platform.
And so when you’re talking about,
I just kind of wanted to unpack for the listener
what Teminos actually does.
And my understanding is, it’s services,
within you also have a platform where clients
can build products for their banks?
– Yeah, so 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 US,
our tier three regional banks will come in
and they’ll take an end-to-end platform
that provides all of the capabilities of banking.
– Almost like a turnkey banking solution, okay.
And that’s where we see a lot of the adoption of SaaS,
bring us a bank, even within kind of
that neo banking space as well.
But then we also, we also offer modular solutions
to our clients.
And so if you look at some of our tier one banks,
they don’t wanna 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 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 with our suite.
– 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, with that, it’s everything from tier one banks
all the way down to the near banks.
– Are you seeing similar or different trends
in terms of, I guess both adoption rates
from 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 customer service?
Like this is the big, it’s not just low 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 an option, right?
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 AI agent.
But I would say we see two different lens on this.
So one is regionally, you have different areas
that they’re more prone to adopt AI faster
than other regions.
And then from the customer tiering,
what I would say is the tier one, tier two banks,
absolutely they wanted embedded in their product.
The kind of tier three banks, regional banks,
they’re really focused on the personalization that it brings.
– Okay, 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 mentioned the example of only 25% of the data
actually going to analytics.
I’m getting that wrong on my paraphrasing,
but is that still kind of the biggest,
I don’t wanna say hurdle, but one of the biggest hurdles
to kind of leveling up success?
– It is, one of the first conversations that I often have
or something I always try to click into
and probably a bit of my 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 for us, 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 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.
Right.
And so sometimes it is, working with our clients,
we have a Temnos data product, our RTDH product
and it is bringing that data into a state
that it can then be leveraged.
And so kind of back to that optionality
that we talked to our clients about,
sometimes we may just take a portion of the bank
and 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, banks are highly regulated,
that’s not going away,
the regulations are gonna get tougher if not anything else.
And so we always keep that top of mind,
making sure that compliance standards
are absolutely embedded into our products
that 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 Temnos, 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 chat bot revolution,
if you wanna 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 wanna kind of shift gears for a second here
if we can and talk a little bit about sustainability
in the industry.
I know that Temnos 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 Temnos,
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, it’s not a trend.
I think when it really started becoming part
of the conversations, call it maybe 10 years ago
where it actually was part of annual reports
and things like that, I think people kind of questions,
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 to your point, we serve banks globally
and so we see different parts of the world
where it may be more around their carbon accounting
or some areas that may be like,
hey, we really want to understand
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.
And what’s really 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, 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.
There’s many consumers 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,
how do you see the future of AI growing and banking?
But I think really, 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 we have in our notes here to talk about AI agents,
which is kind of the latest thing
buzzword-wise in the past few months, right?
But certainly not a new thing
and certainly something that could wind up
really shaping the technology going forward.
We’ll have to see what 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 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 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 how AI is going to be accepted, right?
Is it the same as a friend or a foe?
If you have your top leadership just talking about
how much money we’re gonna save from AI, it’s a foe, right?
But we’re seeing the leaders of the organizations
really look at AI as 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,
whether you use the term eating their own dog food
or French would say drinking their own champagne.
We’ve been doing that ourselves to say,
“Hey, 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?
Is I think– – Any change, right?
There’s always gonna be a bit of fear.
And I think it’s up to us as the banking experts
and as partners to our clients
and then working with their teams
to help kind of show how the change does
actually help them, right?
And so when we see that kind of pivot away from,
“Oh my gosh, this is gonna replace me,”
to, “Wait a second,
“I’m actually gonna sit side-by-side with AI.”
And it’s gonna– – Plus one, you–
– Yes. – I forgive me in a rub.
I just wanted to give you credit.
I hadn’t heard somebody use Plus One
to talk about AI before and I love it, right?
It’s the co-pilot, whatever you wanna call it,
but Plus One is great.
– Yeah, and for me, I really focus on,
I hate the word artificial intelligence
because artificial, it’s fake.
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 the bankers,
hey, someone’s gonna walk into your branch,
you’re instantly gonna be able to know
more about that customer than they know about themselves.
And you’re gonna be able to have a really deep conversation
both about what’s right for them today,
what’s right for them in the future,
how they’re shaping those things.
Their eyes light up, right?
Because oftentimes they would have to,
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,
“Okay, this person has been with us for 10 years
“and 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,
“How long has this customer been with us?
“What is their familial history?”
So this may be a 30 year olds,
but maybe their family’s been with the bank for 25, 30 years.
And then when their customer walks up and they say,
“Hey, it’s been great, we’ve served your parents.”
And so excited to have you here with us.
And we had these great,
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 excited, right?
– Yeah, it really kind of,
you sort of made real in listening to you talk about that.
It’s a great example,
’cause it makes me think of the sort of abstract talk
about machine learning, AI tech, kind of,
freeing humans up to do what humans do
better 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, 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, ’cause there’s so many customers,
I’m getting frustrated and waiting, 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 today, I mean, the future is gonna be all
about human and AI collaboration.
We’re already seeing kind of AI agents.
So to your agentic AI, right?
And latest buzzword, 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 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.
I think we’ll start to see digital humans in making
so that you aren’t saying representative representation.
I was gonna say, when we were talking about that before,
I’m 100% for the plus one,
the augmented intelligence is also,
I like that way of thinking about it as well, right?
And I wanna see humans use the technology to thrive
and not talk about things like replacement, 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,
’cause I never call unless I have some weird question
or like I’ve missed four payments
and wanna 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 even think about how great would it be
if your phone pops up, ’cause I know we all,
or at least I know my phone is always within an order.
Yes, yep, yep.
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 free up any late fees?”
And you’re like, “Yes, done.”
Yeah, that’s exactly the one, yeah.
And so that proactive monitoring, bringing that,
so that you aren’t even having to call in, right?
You, how much better would that be
if it automatically reaches out to you?
Yeah, 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 leadership,
it’s so important, it’s such a tone for so many things,
but including an organization’s a bank’s kind of perspective
on embracing AI.
And you talked about getting 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,
maybe a pro tip to share with the audience?
Yes, I might overuse it, that’s probably the engineer in me.
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?
Why is, like, I know you wake up at six,
but I’m not waking up at six when you’re not home.
Like, why is the house waking up for me?
Smart home lights, yeah.
No, no, I mean, you know, for me,
I use it in a couple different ways.
Sometimes I use it just to say, is my message clear, right?
Like, when you’re so deep into whatever your specialty is,
right?
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 chat, GBT, or perplexity, or whatever,
co-pilot, and say, summarize this message.
What is the tone?
What level of audience is this reaching?
And hopefully, it’ll say, hey, this is actually
geared at a engineering audience.
Oh, well, wait a second, that’s not who I’m speaking to.
Right, that’s great.
Let me make sure that I bring this back into more
of a business speak, or this is very financially focused.
OK, wait a second.
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,
nine 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.
Yeah, and it got it pretty close to right.
Like, they like the different restaurants
that we took them to.
And there you go.
Yeah, so I use it quite often.
I also– 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.
Excellent.
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, whether it’s LinkedIn, if that’s
their favorite within just looking at Temenos.
They will definitely find a cluster of areas to go.
And then, of course, our website, just our www.temenos.com.
They can look at our products.
We do have more of the technical aspects, right?
So our developer portals, and then also just understanding
where our thought leadership is in the space.
Fantastic.
Barb, Morgan, thank you so much 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 just kind of– 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–
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.
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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 leaning Temenos 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
in 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 and banking,
Temenos’ approach to AI,
and the importance of sustainability
in the industry for starters.
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 Temenos.
– Absolutely, so I actually started
with my hands on the keyboard.
So I was a developer many years ago.
When you said 25 years, I had to smile a bit
’cause it reminds me how long career has been.
But now, my career did start with the hands on the keyboard,
but I always really enjoyed that link
between what we were doing with technology
and how that was really impacting the customer.
And so as my career continued
to kind of go through my journey,
I really gravitated towards those areas
that had a strong customer centricity.
And so I spent about the past 15 years of my career
focused in the financial services industry.
So I’ve led transformations inside banks within techs,
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 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 hyper-personalization
to the clients.
It’s exciting when we talk to our clients.
So as you mentioned, I joined Temno’s in October,
and I’ve spent, in my past four months,
a lot of time out there just talking with the clients,
understanding what they’re thinking about,
whether it’s the CEO, CTO,
and they really want to get back to their customers, right?
Whether it’s 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 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 people realized,
like, oh, this is a great way to do all these things
with customer, 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?
Which was kind of that first introduction.
When you were sitting on the technology side,
whether inside the bank or at Vintex,
we thought, this is fantastic.
And what we realized was it was actually
really frustrating to the clients.
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, right?
– I’m just screaming representative in the phone,
is that right?
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 touch point with customer,
because now all that data can get pulled instantly.
And so you don’t have to go through
that representative representative.
And so I do think that we thought technology was leading
when kind of that era of the chat bots
and some of the different customer type efficiencies,
we’re playing out maybe five, 10 years ago.
But now I think technology truly is leading
and people are seeing it as an abler
versus again, just that cost efficiency.
– Right, right.
Maybe you can unpack a little bit
what it means from the banker side
to deliver a better experience
and 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 kind of artificial intelligence, right?
So machine learning, predictive analytics,
all these things, those are not, like we said,
they’re not going away,
but from the bankers perspective,
what are they excited about now?
What are some of the some of us banking customers doing
to leverage this tech to deliver better experiences
and make their clients happier?
– Yeah, I think 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, how can they help their team?
And then secondly, can they help their customers?
So from the perspective of helping their teams,
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?
How can we have those richer
more meaningful conversations enabled for our bankers?
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,
whether it’s pay-learning 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 the speed that customers expect now.
Everyone seems to have,
whether it’s chat, GBT or perplexity
or whatever loaded onto their phone,
everyone expects that instant answer now.
And so they expect that everywhere,
but we’re in a highly regulated space.
And so making sure that we do that
in a very responsible way.
But some of the things that we’re doing that,
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 going out to our clients,
we’re doing a lot of co-design around the AI solution.
So really saying, hey, here’s five or six 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 a AI powered solution
that allows the product managers at the bank
to create those financial products,
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 1,000 different banks
or more than 1,000 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.
For me, it’s also,
we don’t wanna leave any of our customers behind.
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’re gonna be on-prem,
if they wanna be in the cloud or if they want SaaS,
they have the optionality.
And so partnering most recently with Amidia to bring AI
to our on-prem banks has been hugely well received.
Just that ability to give that AI-driven analysis
with those massive data sets that they have on-prem
but allowing them to control the security around it,
allowing them to really not need to have
the deep technical expertise to analyze.
And so a lot of excitement there.
And it’s good too, because we were talking
with the bank the other day and he said,
our ability to have adequate data management
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, Teminos offers a platform.
And so when you’re talking about,
I just kind of wanted to unpack for the listener
what Teminos actually does.
And my understanding is, it’s services,
within you also have a platform where clients
can build products for their banks?
– Yeah, so 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 US,
our tier three regional banks will come in
and they’ll take an end-to-end platform
that provides all of the capabilities of banking.
– Almost like a turnkey banking solution, okay.
And that’s where we see a lot of the adoption of SaaS,
bring us a bank, even within kind of
that neo banking space as well.
But then we also, we also offer modular solutions
to our clients.
And so if you look at some of our tier one banks,
they don’t wanna 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 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 with our suite.
– 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, with that, it’s everything from tier one banks
all the way down to the near banks.
– Are you seeing similar or different trends
in terms of, I guess both adoption rates
from 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 customer service?
Like this is the big, it’s not just low 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 an option, right?
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 AI agent.
But I would say we see two different lens on this.
So one is regionally, you have different areas
that they’re more prone to adopt AI faster
than other regions.
And then from the customer tiering,
what I would say is the tier one, tier two banks,
absolutely they wanted embedded in their product.
The kind of tier three banks, regional banks,
they’re really focused on the personalization that it brings.
– Okay, 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 mentioned the example of only 25% of the data
actually going to analytics.
I’m getting that wrong on my paraphrasing,
but is that still kind of the biggest,
I don’t wanna say hurdle, but one of the biggest hurdles
to kind of leveling up success?
– It is, one of the first conversations that I often have
or something I always try to click into
and probably a bit of my 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 for us, 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 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.
Right.
And so sometimes it is, working with our clients,
we have a Temnos data product, our RTDH product
and it is bringing that data into a state
that it can then be leveraged.
And so kind of back to that optionality
that we talked to our clients about,
sometimes we may just take a portion of the bank
and 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, banks are highly regulated,
that’s not going away,
the regulations are gonna get tougher if not anything else.
And so we always keep that top of mind,
making sure that compliance standards
are absolutely embedded into our products
that 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 Temnos, 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 chat bot revolution,
if you wanna 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 wanna kind of shift gears for a second here
if we can and talk a little bit about sustainability
in the industry.
I know that Temnos 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 Temnos,
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, it’s not a trend.
I think when it really started becoming part
of the conversations, call it maybe 10 years ago
where it actually was part of annual reports
and things like that, I think people kind of questions,
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 to your point, we serve banks globally
and so we see different parts of the world
where it may be more around their carbon accounting
or some areas that may be like,
hey, we really want to understand
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.
And what’s really 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, 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.
There’s many consumers 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,
how do you see the future of AI growing and banking?
But I think really, 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 we have in our notes here to talk about AI agents,
which is kind of the latest thing
buzzword-wise in the past few months, right?
But certainly not a new thing
and certainly something that could wind up
really shaping the technology going forward.
We’ll have to see what 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 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 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 how AI is going to be accepted, right?
Is it the same as a friend or a foe?
If you have your top leadership just talking about
how much money we’re gonna save from AI, it’s a foe, right?
But we’re seeing the leaders of the organizations
really look at AI as 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,
whether you use the term eating their own dog food
or French would say drinking their own champagne.
We’ve been doing that ourselves to say,
“Hey, 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?
Is I think– – Any change, right?
There’s always gonna be a bit of fear.
And I think it’s up to us as the banking experts
and as partners to our clients
and then working with their teams
to help kind of show how the change does
actually help them, right?
And so when we see that kind of pivot away from,
“Oh my gosh, this is gonna replace me,”
to, “Wait a second,
“I’m actually gonna sit side-by-side with AI.”
And it’s gonna– – Plus one, you–
– Yes. – I forgive me in a rub.
I just wanted to give you credit.
I hadn’t heard somebody use Plus One
to talk about AI before and I love it, right?
It’s the co-pilot, whatever you wanna call it,
but Plus One is great.
– Yeah, and for me, I really focus on,
I hate the word artificial intelligence
because artificial, it’s fake.
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 the bankers,
hey, someone’s gonna walk into your branch,
you’re instantly gonna be able to know
more about that customer than they know about themselves.
And you’re gonna be able to have a really deep conversation
both about what’s right for them today,
what’s right for them in the future,
how they’re shaping those things.
Their eyes light up, right?
Because oftentimes they would have to,
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,
“Okay, this person has been with us for 10 years
“and 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,
“How long has this customer been with us?
“What is their familial history?”
So this may be a 30 year olds,
but maybe their family’s been with the bank for 25, 30 years.
And then when their customer walks up and they say,
“Hey, it’s been great, we’ve served your parents.”
And so excited to have you here with us.
And we had these great,
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 excited, right?
– Yeah, it really kind of,
you sort of made real in listening to you talk about that.
It’s a great example,
’cause it makes me think of the sort of abstract talk
about machine learning, AI tech, kind of,
freeing humans up to do what humans do
better 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, 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, ’cause there’s so many customers,
I’m getting frustrated and waiting, 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 today, I mean, the future is gonna be all
about human and AI collaboration.
We’re already seeing kind of AI agents.
So to your agentic AI, right?
And latest buzzword, 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 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.
I think we’ll start to see digital humans in making
so that you aren’t saying representative representation.
I was gonna say, when we were talking about that before,
I’m 100% for the plus one,
the augmented intelligence is also,
I like that way of thinking about it as well, right?
And I wanna see humans use the technology to thrive
and not talk about things like replacement, 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,
’cause I never call unless I have some weird question
or like I’ve missed four payments
and wanna 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 even think about how great would it be
if your phone pops up, ’cause I know we all,
or at least I know my phone is always within an order.
Yes, yep, yep.
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 free up any late fees?”
And you’re like, “Yes, done.”
Yeah, that’s exactly the one, yeah.
And so that proactive monitoring, bringing that,
so that you aren’t even having to call in, right?
You, how much better would that be
if it automatically reaches out to you?
Yeah, 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 leadership,
it’s so important, it’s such a tone for so many things,
but including an organization’s a bank’s kind of perspective
on embracing AI.
And you talked about getting 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,
maybe a pro tip to share with the audience?
Yes, I might overuse it, that’s probably the engineer in me.
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?
Why is, like, I know you wake up at six,
but I’m not waking up at six when you’re not home.
Like, why is the house waking up for me?
Smart home lights, yeah.
No, no, I mean, you know, for me,
I use it in a couple different ways.
Sometimes I use it just to say, is my message clear, right?
Like, when you’re so deep into whatever your specialty is,
right?
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 chat, GBT, or perplexity, or whatever,
co-pilot, and say, summarize this message.
What is the tone?
What level of audience is this reaching?
And hopefully, it’ll say, hey, this is actually
geared at a engineering audience.
Oh, well, wait a second, that’s not who I’m speaking to.
Right, that’s great.
Let me make sure that I bring this back into more
of a business speak, or this is very financially focused.
OK, wait a second.
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,
nine 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.
Yeah, and it got it pretty close to right.
Like, they like the different restaurants
that we took them to.
And there you go.
Yeah, so I use it quite often.
I also– 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.
Excellent.
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, whether it’s LinkedIn, if that’s
their favorite within just looking at Temenos.
They will definitely find a cluster of areas to go.
And then, of course, our website, just our www.temenos.com.
They can look at our products.
We do have more of the technical aspects, right?
So our developer portals, and then also just understanding
where our thought leadership is in the space.
Fantastic.
Barb, Morgan, thank you so much 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 just kind of– 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–
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.
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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.
