>> We're back.
Paul Gillin with Rob Rachet here
at the Red Hat Summit in Ansible Fest 2023 in Boston.
And we've been talking a lot about digital analytics
about how data is transforming organizations.
And we have a company here
that's walking the walk joining us right now.
Banco Galicia out of...
Did I pronounce that correctly?
>> Banco Galicia.
>> Galicia out of Argentina.
Erico Behmer is the Chief Information Officer.
Victoria Martinez is the Latin American manager
for business development for data science at Red Hat.
And the bank has recently completed.
You've been a Red Hat customer for a long time.
I see you've several case studies
on Red Hat site about the bank.
You recently completed a digital onboarding initiative.
Tell us what the objective,
what was the goal of that initiative
and why did you make the investment at this point?
>> Okay, well,
bank is an a hundred percent Argentina Capitals banks.
Back in 2019,
we were facing an ambitious to grow our market shares
in the corporate sector.
So we had a really manual process in the onboarding
because there is a lot of information and papers
and documents that we have to process manually
to onboard a company, you know, a status,
power of attorneys, these kind of documents
that are all papers, paperworks.
So the whole process to onboard a company,
it was more or less to, to 20 days average.
So it was really tough for us, it was an expensive process.
And of course, we used to, she lost lot
of opportunities in companies that abandoned the process
in the middle because of the time.
So we realized that we had to work deeply
in a new solution in order to shorten that time
and to improve our customer experience.
>> How did you really look at, did you look at, I guess,
did you really look at the whole process
and I think again, you brought in Red Hat
and as Paul was saying, you have a long relationship.
How did you work together to really get through this?
Because when I went and looked at the little case study,
there's a lot of technology there
not just OpenShift for data science.
You know, there's a lot of, and I think there,
what will be interesting to the folks watching is
they're just starting their AI journey.
And I think to your point,
you have a really good use case.
I think that you started with kind of that use case.
What was it that Red Hat helped you with
in getting started and getting going with that?
>> Well, to be honest, this project began a time before that.
We were trying with, with different technologies,
more closed, more black boxy technologies.
So we had a couple of attempts failing
and we were really frustrated because we wanted
and we believe that using LLP technologies,
we could reach the digitalization we wanted.
So in that time, the Red Hat consultant team came up
with a solution to change the whole stack
that we were using and to start building the project
over OpenShift.
We were using OpenShift for, for a long time.
We had almost 25 cluster right now
with 300 projects, 15,000 pots running every time.
So we were really excited to change this technology stack
and to start building with different mindset,
with an open sort mindset.
So that's why how we started.
>> Victoria, describe the process
by which you become involved with a project like this.
Does the bank come to you and say,
"This is what we want to do and how will you help us?"
Or how, where were they
in their journey when, when you became involved?
>> Yes, also, we'll start with this to file attempts,
a particularly need with the digitalization with NLP.
And we share this vision with our world
with the open source technology
bringing these workloads with machine learning
the models and the data stuff on the containers.
This was a new way to concept this vision
with the AI technology
because when we start was a different reality.
Today we have the trend topic with ChatGPT, with the AI,
we are living in the, in the boom.
But that this, those years ago,
we share a new vision
and a different thing with the project.
We want to build the capability
with NLP in the bank.
Not only a project, not only solve a use case
and was totally different with the another experience
because there was, there was close.
And the thing with the compliance
and the customers very sensitive
with the data and all the solution is on-prem.
We share this new vision, a start
with a little use case
and with a little MVP
and then we launch to all the onboarding processes.
>> So you built the NLP from scratch?
>> Yes.
>> Yourself?
What role does NLP play now in the onboarding process?
>> Well, it's one of the central pieces
of the whole process because, you know,
to analyze the whole document
and paperworks today needs different technologies
like AI.
So the process is more or less in four parts,
you know, steps.
The first steps is the, the processing
of the images with computer vision, the libraries
and plugins in order to clean the images, I don't know,
delete the stamps rotates, change, contrast of the documents
in order to the second step
which is the OCR to, to capture better each letter.
Then is the magic of the NLP,
trying to put the letters together to form words and using
of course natural language processing and to complete words
with letters that we missed during the OCR process.
And at the end is the entity recognition
and mapping that closed the whole matching process
in order to capture name of the company,
name of the powers attorneys, I don't know,
the activity of the company, balance sheets process,
all the whole balance sheets,
healthy situation of companies and those kind
of information is all an structure in just images,
pdf files.
So this is the, the important thing regarding to AI
which is not simple to use another technology to do that.
>> Yeah, it seems like you started right,
sounds like right before the pandemic hit.
And it would seem that this became probably more,
even more important during that
because then you would have less people involved
in the entire process.
Did that help accelerate the investment
that the bank made into this project?
>> I actually, as you told, the project began
before pandemic and during the pandemic was one
of the, you know, the key pieces to maintain the growing
and growing by the time
because by the time we will releasing the first step
of the projects and automating the whole process end to end.
And yeah, what was definitely a key success factor to
in order to, to keep our growing and to maintain, you know,
the customer satisfaction and well, yeah,
the satisfaction of our customers
during the pandemic was really tough for people and
for companies too.
>> Right.
>> And you chose to use a number
of cloud native constructs
in building this using APIs, containers,
OpenShift, Kubernetes.
What benefits do you expect to realize over the longer term
from using these cloud native constructs?
>> Well, in, in one hand, you know,
to build with counted technologies
in containers nowadays it's running on-prem.
But for example, one of the troubles we face
during the project was
we couldn't reach the computational power
to train the models.
So it was easy to move tho those components to the cloud,
use public power consumption,
and then go back to our on-prem
in order to apply the models already train it.
So I think that this is the facility and the, you know,
the, the benefits of clouds.
And in the other hand,
we build a platform, API oriented.
So by the time nowadays, ChatGPT,
all the other technologies that we can plug in
and renovate, you know,
modern inside technology using different kind of components,
new ones to try different NLP models,
of course ChatGPT to recognize new entities or words.
So it's like a Lego, like a Lego system.
>> Yeah, it seems that that flexibility and the ability
to burst up into the cloud when you needed
to do the big training portions
of it also would help you be more efficient
in how you use your resources on premise.
But is that something that you look to continue to do?
Is that, so as you, like you said,
build another part to the Lego, add another Lego block in,
are you using still doing that bursting
to certain to cloud to go and do that?
>> Well, we have a, of course our journey to the cloud
as many companies.
As we are a bank,
we are a regulated company.
So we are, we are trying to move consistently, but security.
So we are adopting different part
of the cloud by the time.
At the same time we are rebuilding
and rearchitecture our channels, for example.
So yes, we are expanding the possibilities
to move this, these technologies and to keep growing
and growing, scaling to the public cloud.
>> Victoria, as someone who works with the,
who knows the Latin American market very well,
can you contrast what is the state
of open source in Latin America compared to North America?
Is it any different?
>> No, the innovation is in the communities
and in the open source.
This globalization
that we live don't have a gap be between us,
between Latin America or North America or the Europeans.
We live a new way to concept the technology
and to interact with the users with the velocity.
It's the same for every country,
for the complete world, for the global thing,
there is the same need.
We are living a new era and we need to accelerate this thing
and improve with open source.
And we in Red Hat trying to alert the use cases
with machine learning ops
with OpenShift data science and the new, with OpenShift AI
and trying to connect the new start technology stack
for the delivery and application and intelligent application
with models and machine learning and AI.
>> You heard about OpenShift AI at the summit this week?
Do you, what's your reaction to it, Erico?
Is it something that you would plan to adopt quickly
or perhaps you already have?
>> Well, I actually, we start,
we begin building this this project
before the OpenShift AI exits,
but we are really excited to try new technologies
to go further, you know
so well to the, these days there was a lot
of launches like AI automation we've even driven.
So we are really excited to try all those technologies,
to improve the modernization of the company.
>> It seems like this is a, you're actually well ahead
of even some of the ones that I've talked
to in the US where they're still trying to figure
out their cloud journey in the financial services.
I talk to a lot of, even some of the largest banks
in the US haven't even gone to certain,
like haven't moved to cloud databases
or anything of that nature.
Do you feel that you're way out there on the edge
or do you feel like you have this all under control
because of the help you've gotten out of Red Hat?
>> Actually, we say that we have our own basing.
So we are moving, you know, film and security
but we are not facing that.
It's under, out of control.
You know, we are controlling the technology
and not the technology controlling us.
>> That's great.
>> Well, it's a terrific story
and if you want to read more about it, it's
on the Red Hat site,
"Banco Galicia Streamlines digital onboarding
with AI platform built on Red Hat Technologies."
There's quite a bit of details there
about what they're doing, and you are out
on the leading edge, whether you think of it or, or not.
Thank you so much for sharing your story with us.
>> Well thank you very much Paul and Rob for the interview.
>> Paul Gill and Rob Rachet at Red Hat Summit 2023.
Wrapping up day two, we'll be back in a minute.