Name: Generative AI: Extending the boundaries of what automation can do
Uploaded: 2024-07-04T12:57:59.567Z
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English

{{00:00:05}}
Hi, I'm David Penn, Research
Analyst with Finovate.

{{00:00:07}}
We're here at FinovateSpring
in San Francisco, and

{{00:00:09}}
joining me is Sarah Hinkfuss.

{{00:00:10}}
She is the partner with
Bain Capital Ventures.

{{00:00:13}}
Sarah, thanks for joining us today.

{{00:00:14}}
Thanks for having me.

{{00:00:15}}
We're going to talk a little bit about
AI today, if that's okay with you.

{{00:00:18}}
Fantastic.

{{00:00:19}}
We're in San Francisco,
so it feels appropriate.

{{00:00:21}}
Perfectly.

{{00:00:22}}
And certainly here at FinovateSpring,
we've heard quite a lot of conversation

{{00:00:24}}
about AI, a lot of companies demonstrating
about it, a lot of folks on stage

{{00:00:27}}
talking about it, so let's get down and
hear what you have to say about this.

{{00:00:30}}
Could you give us an overview of
some of the sorts of benefits that

{{00:00:33}}
you've seen financial institutions
realize by embracing AI technologies?

{{00:00:37}}
Yeah, so what's so exciting about
where AI is today is that traditional

{{00:00:41}}
AI has been a part of what financial
services firms have used for decades.

{{00:00:45}}
And so that's really the traditional ways
of thinking about structured data analysis

{{00:00:48}}
and predictive analysis that is the core
of what financial services firms do.

{{00:00:52}}
And then it's been in the last 18
months that we've seen the explosion

{{00:00:55}}
of the potential with generative AI.

{{00:00:57}}
And what generative AI is doing is
really filling in the holes where

{{00:01:00}}
traditionally I could not solve
problems because those problems have

{{00:01:04}}
to do with text based information.

{{00:01:06}}
And so all of this additional unstructured
data that cannot be used in spreadsheets

{{00:01:10}}
traditionally can now be extracted and
then used and analyzed in a way that

{{00:01:15}}
makes it accessible for automation.

{{00:01:17}}
And so the way that I think about
it for financial services firms is

{{00:01:20}}
generative AI  allows us to extend the
boundaries of what automation can do.

{{00:01:25}}
And that is particularly exciting because
financial services is financial services

{{00:01:30}}
because of all of that extra work that
has to be done with the unstructured data.

{{00:01:34}}
So the potential is to really
help firms become much more

{{00:01:38}}
streamlined and much more efficient.

{{00:01:40}}
Which we believe will do a lot
to actually expand the product

{{00:01:43}}
roadmap of what firms can offer.

{{00:01:45}}
Expand the number of, and types
of people that they can serve.

{{00:01:48}}
As well as to actually improve the
overall underwriting and pricing process

{{00:01:52}}
to make the entire process more fair.

{{00:01:54}}
Very interesting.

{{00:01:54}}
I have to admit that was one
of the best descriptions of the

{{00:01:57}}
rise and roll of Generative AI.

{{00:01:58}}
Great.

{{00:01:59}}
I feel like I've heard all the lies.

{{00:02:00}}
oh, yes, the way you
described filling that hole.

{{00:02:02}}
That was fantastic.

{{00:02:03}}
Let me ask you this then.

{{00:02:04}}
Is it, in your opinion, critical for
financial services to embrace AI?

{{00:02:08}}
Is it something you just
have to figure out how to do?

{{00:02:10}}
Yes, I think it'll become a way that
go to market is happening, and so

{{00:02:15}}
the opportunity to stand behind would
mean that your competitors are going

{{00:02:19}}
to be able to be more efficient.

{{00:02:21}}
Your competitors will be able to grow
revenue faster, and so in the way that

{{00:02:25}}
there is a rising tide that lifts all
boats, that's the way that I think

{{00:02:27}}
about the opportunity to embrace it.

{{00:02:29}}
That's interesting.

{{00:02:30}}
Are there any things that you think
that financial institutions can learn

{{00:02:33}}
from some of the early adopters either
within or without the industry of AI?

{{00:02:36}}
Are there any sort of common obstacles
common challenges that you think financial

{{00:02:40}}
institutions maybe can skip a step on?

{{00:02:42}}
Yeah, totally.

{{00:02:43}}
So if I think about the first
applications of generative AI, it's

{{00:02:46}}
actually not in the core engine room
of what a financial institution is.

{{00:02:50}}
It's really in the way, for
example, how code is developed.

{{00:02:53}}
It is in the way that customer service
reps are actually meeting the questions

{{00:02:57}}
of all your customers who are calling in.

{{00:02:59}}
And so those applications are
actually the same across industries.

{{00:03:03}}
So it's not a vertical.

{{00:03:04}}
example.

{{00:03:05}}
It's actually horizontal.

{{00:03:06}}
And so you can look to the best
enterprises and what they're

{{00:03:09}}
doing today and actually integrate
those same types of applications.

{{00:03:13}}
So one example is Chime and obviously
the financial services space.

{{00:03:16}}
And last year, when everything was
new, they came out and talked about

{{00:03:20}}
how they're enabling their engineers.

{{00:03:22}}
They've actually built an internal model
trained on their code base for deployments

{{00:03:25}}
that enables their product velocity to
be that much faster because they know

{{00:03:29}}
that one of their core market values
is that they actually can improve the

{{00:03:34}}
products faster than their competitors.

{{00:03:35}}
And that's why they win
over their customers.

{{00:03:37}}
Interesting.

{{00:03:38}}
I'm thinking maybe the way of finishing
up, what would you say are some of the

{{00:03:41}}
most important factor or factors for
financial institutions when they're about

{{00:03:45}}
to embark upon that AI, adoption journey?

{{00:03:48}}
Yeah.

{{00:03:49}}
So two things I would call out.

{{00:03:50}}
One is actually data quality itself.

{{00:03:52}}
And so it's.

{{00:03:54}}
It's the old adage of garbage in garbage
out also applies to generative AI.

{{00:03:58}}
And so one of the challenges and
the reason why we're seeing a lot

{{00:04:01}}
of financial services institutions
look outside of their four walls for

{{00:04:04}}
help is because they have all this
great data but it's literally in

{{00:04:08}}
like boxes on people's desks, right?

{{00:04:11}}
Like their entire storerooms of
information and that's the data that

{{00:04:14}}
you want to get out and actually
give access to within the models to

{{00:04:16}}
make use of everything that you have.

{{00:04:18}}
And so there's this entire
process of actually standardizing

{{00:04:21}}
and getting access to data.

{{00:04:22}}
So it's the first one.

{{00:04:23}}
The second thing I'd say is it
does require change management.

{{00:04:26}}
And so there are different ways or
models to think about for integrating AI.

{{00:04:31}}
Or if you think about a spectrum
of automation, it could be from the

{{00:04:34}}
co pilot, which is like asking a
question and getting an answer, all

{{00:04:38}}
the way to full automation of work.

{{00:04:40}}
And so each and every step along that
journey of levels of automation implies

{{00:04:44}}
different things around the way that
your current employees and your current

{{00:04:47}}
infrastructure has to embrace AI.

{{00:04:50}}
And so thinking through those change
management implications from a process

{{00:04:53}}
perspective, from a hiring perspective,
from an ROI perspective, all of that

{{00:04:57}}
is really important to do before
you start on this journey as well.

{{00:05:00}}
Wow, Definitely some work to be done.

{{00:05:03}}
Of course.

{{00:05:03}}
But good and exciting
work at the same time.

{{00:05:05}}
It's a really exciting time.

{{00:05:06}}
Absolutely.

{{00:05:07}}
thank you very much for
sharing your insights.

{{00:05:08}}
You gave some fantastic explanations.

{{00:05:09}}
I think it's going to go a long
way for helping people understand

{{00:05:11}}
exactly where things like gen
AI fit into the full picture.

{{00:05:14}}
So thank you very much for
being part of our conversation.

{{00:05:16}}
Thanks for having me.

{{00:05:17}}
Thank you.

{{00:05:17}}
And thank you as well.

Hi, I'm David Penn, Research
Analyst with Finovate.

We're here at FinovateSpring
in San Francisco, and

She is the partner with
Bain Capital Ventures.

We're going to talk a little bit about
AI today, if that's okay with you.

We're in San Francisco,
so it feels appropriate.

And certainly here at FinovateSpring,
we've heard quite a lot of conversation

about AI, a lot of companies demonstrating
about it, a lot of folks on stage

talking about it, so let's get down and
hear what you have to say about this.

Could you give us an overview of
some of the sorts of benefits that

you've seen financial institutions
realize by embracing AI technologies?

Yeah, so what's so exciting about
where AI is today is that traditional

AI has been a part of what financial
services firms have used for decades.

And so that's really the traditional ways
of thinking about structured data analysis

and predictive analysis that is the core
of what financial services firms do.

And then it's been in the last 18
months that we've seen the explosion

And what generative AI is doing is
really filling in the holes where

traditionally I could not solve
problems because those problems have

And so all of this additional unstructured
data that cannot be used in spreadsheets

traditionally can now be extracted and
then used and analyzed in a way that

And so the way that I think about
it for financial services firms is

generative AI  allows us to extend the
boundaries of what automation can do.

And that is particularly exciting because
financial services is financial services

because of all of that extra work that
has to be done with the unstructured data.

So the potential is to really
help firms become much more

Which we believe will do a lot
to actually expand the product

Expand the number of, and types
of people that they can serve.

As well as to actually improve the
overall underwriting and pricing process

I have to admit that was one
of the best descriptions of the

oh, yes, the way you
described filling that hole.

Is it, in your opinion, critical for
financial services to embrace AI?

Is it something you just
have to figure out how to do?

Yes, I think it'll become a way that
go to market is happening, and so

the opportunity to stand behind would
mean that your competitors are going

Your competitors will be able to grow
revenue faster, and so in the way that

there is a rising tide that lifts all
boats, that's the way that I think

Are there any things that you think
that financial institutions can learn

from some of the early adopters either
within or without the industry of AI?

Are there any sort of common obstacles
common challenges that you think financial

So if I think about the first
applications of generative AI, it's

actually not in the core engine room
of what a financial institution is.

It's really in the way, for
example, how code is developed.

It is in the way that customer service
reps are actually meeting the questions

of all your customers who are calling in.

And so those applications are
actually the same across industries.

And so you can look to the best
enterprises and what they're

doing today and actually integrate
those same types of applications.

So one example is Chime and obviously
the financial services space.

And last year, when everything was
new, they came out and talked about

They've actually built an internal model
trained on their code base for deployments

that enables their product velocity to
be that much faster because they know

that one of their core market values
is that they actually can improve the

And that's why they win
over their customers.

I'm thinking maybe the way of finishing
up, what would you say are some of the

most important factor or factors for
financial institutions when they're about

to embark upon that AI, adoption journey?

It's the old adage of garbage in garbage
out also applies to generative AI.

And so one of the challenges and
the reason why we're seeing a lot

of financial services institutions
look outside of their four walls for

help is because they have all this
great data but it's literally in

Like their entire storerooms of
information and that's the data that

you want to get out and actually
give access to within the models to

And so there's this entire
process of actually standardizing

The second thing I'd say is it
does require change management.

And so there are different ways or
models to think about for integrating AI.

FinovateSpring

Expert Insight

Sarah Hinkfuss, Partner of Bain Capital Ventures, talks about how generative AI is transforming the way financial institutions leverage unstructured data, streamline processes, improve underwriting, and expand their product offerings. The conversation also touches on the importance of data quality and change management in AI adoption for financial institutions, providing valuable lessons from early adopters.