Why Financial Institutions are Banking on AI
Today,
AI-powered
banks
see
advantages
in
applying
the
technology
to
a
gamut
of
mission-critical
needs—from
customer
service
and
fraud
prevention
to
meeting
environmental,
social
and
governance
standards.
Today,
AI-powered
banks
see
advantages
in
applying
the
technology
to
a
gamut
of
mission-critical
needs—from
customer
service
and
fraud
prevention
to
meeting
environmental,
social
and
governance
standards.
With
AI
to
enhance
every
line
of
business
and
function,
banks
report
significant
return
on
investment
(ROI)
including
the
ability
to
increase
productivity,
reduce
risk
and
keep
customers
happy.
Globally,
financial
institutions
are
leaning
into
AI
technologies,
noting
the
potential
to
deliver
up
to
$1
trillion
of
added
value
each
year.1
It’s
clear
that
AI
is
transforming
the
way
banks
operate,
but
what’s
not
always
clear
is
how
they
can
successfully
implement
and
deploy
AI
projects.
Experts
recommend
a
shared,
centralized
infrastructure
for
AI—a
full-stack
solution
that
includes
both
hardware
and
software.
This
approach,
known
as
AI
as
a
platform,
is
ideal
for
three
reasons.
One,
it
consolidates
expertise,
productivity,
and
scale.
Two,
it
shortens
the
lifecycle
from
development
to
deployment.
And
three,
it
drives
down
total
cost
of
ownership
with
an
efficient
utilization
of
compute
and
storage
resources.
Advantages
of
the
AI-Powered
Bank
As
banks
sift
through
volumes
of
data,
AI
can
help
them
quickly
discover
patterns
and
identify
key
insights,
calculate
risk
and
automate
routine
tasks.
Work
performed
by
AI
is
done
at
extraordinary
speed
and
scale
with
the
added
benefits
of
the
technology
being
adaptable
and
essentially
tireless.
Executives
have
taken
notice.
While
89%
of
Directors
say
digital
is
embedded
in
all
business
growth
strategies,
they
identify
AI
as
the
top
breakthrough
technology.2
Here
we
explore
the
most
advantageous
and
strategic
business
use
cases
of
AI
for
banking.
Anti-money
laundering
and
identity
verification:
In
a
world
where
many
people
do
their
banking
online,
a
well-planned
transaction
monitoring
system
has
proven
fundamental
for
an
effective
anti-money
laundering
(AML)
system.
AI
is
helping
many
banks
boost
accuracy
for
their
AML
and
their
Know
Your
Customer
(KYC)
system
as
part
of
identity
verification.
Traditional
rule-
and
scenario-based
approaches
to
fighting
financial
crimes
have
made
money
laundering
an
ongoing
challenge
for
compliance,
monitoring
and
risk
organizations.
Rules
often
fail
to
capture
the
latest
trends
in
money-laundering
behavior.
Alternatively,
AI
machine
learning
(ML)
models
can
build
sophisticated
algorithms
using
granular,
behavior-indicative
data.
These
models
are
also
more
flexible,
able
to
quickly
adjust
to
trends
and
improve
over
time.
Even
minor
improvements
in
detection
accuracy
can
significantly
lower
costs
and
improve
regulatory
compliance.
Banks
have
been
able
to
reduce
false
positives
in
transactional
fraud
detection
using
AI
capabilities
such
as
deep
learning,
computer
vision
and
natural
language
processing.
AI
has
also
helped
enhance
identity
verification
in
compliance
with
AML
and
KYC
requirements.
Improving
transactional
fraud
prevention: Fraud
detection
can
be
complicated
as
perpetrators
continuously
update
their
schemes.
Online
fraud
losses
are
expected
to
reach
$48
billion
annually
this
year,3
making
fraud
detection
and
prevention
a
top
use
case
for
AI.
Because
AI/ML
can
process
massive
amounts
of
data
in
milliseconds,
the
technology
is
able
to
understand
and
apply
rules
of
fraud
detection,
increasing
accuracy.
The
speed
of
AI
attracts
many
major
banks
as
it
can
fight
fraud
while
protecting
the
customer
experience
by
not
introducing
delays
in
processing
credit
card
transactions.
One
leading
global
financial
institution
uses
a fraud-detection
AI/ML
system
that
employs
supervised
learning
to
look
for
established
fraud
patterns
and
unsupervised
learning
to
identify
emerging
fraud
patterns
in
real
time.
With
every
transaction,
the
algorithms
examine,
for
example,
a
cardholder’s
buying
habits,
geographic
location,
travel
patterns,
and
real-time
card
usage
data. The
result
is
a
more
trustworthy
transaction
experience
for
legitimate
cardholders
and
merchants
with
real-time
barriers
to
stop
criminals.
Virtual
assistants
and
chatbots:
Customer
experience
may
be
more
important
than
ever.
With
its
ability
to
resolve
customer
queries
while
reducing
operational
cost,
conversational
AI
rules
the
day.
In
fact,
a
new
study
anticipates
automation
will
save
banks
$7.3
billion
globally
this
year—that’s
862
million
hours,
equivalent
to
nearly
half
a
million
working
years.4
Guided
by
natural
language
processing,
AI-powered
automated
systems
can
deliver
highly
personalized
experiences
to
answer
a
variety
of
customer
service
requests.
Chatbots
and
virtual
assistants
are
able
to
open
new
accounts,
field
questions
about
existing
accounts,
assist
with
investments
and
trades,
report
lost
or
stolen
cards,
as
well
as
help
with
fraud
detection.
One
day
the
work
may
even
be
done
by
digital
avatars,
creating
an
omnichannel
experience
for
bank
customers.
Selecting
the
Right
AI
Solutions
Once
a
privilege
of
only
the
largest
financial
institutions,
AI
is
now
widely
available
for
banks
of
all
sizes
to
design,
deploy
and
build
solutions
safely,
quickly
and
cost
effectively.
There’s
just
one
catch.
To
get
the
most
from
its
AI
investment
in
terms
of
performance
and
scalability,
a
business
will
need
a
reliable
infrastructure
made
up
of
HPC,
storage
and
networking.
Many
banks
are
partnering
with
Dell
Technologies
for
an
AI-as-a-platform
approach.
By
applying
a
portfolio
of
Dell
Validated
Designs
for
AI,
organizations
have
experienced
a
20%
faster
time
to
value
and
benefits
of
$55.76
million
over
three
years.5
Offerings
from
Dell
Technologies,
featuring
Intel®
Xeon®
processors,
include
servers,
storage,
networking,
software
and
services
proven
in
labs
and
in
customer
deployments.
The
latest
Intel®
Xeon®
processors
have
built-in
accelerators
which
improve
performance
across
AI,
data
analytics,
storage
and
HPC
workloads.
This
includes
accelerated
AI
inferencing
–
up
to
10x
higher
PyTorch
real-time
inference
performance
with
built-in
Intel®
Advanced
Matrix
Extensions
(Intel®
AMX)
(BF16)
vs.
the
prior
generation
(FP32).6
HPC
built-in
acceleration
provides
increased
performance
for
financial
services—up
to
45%
higher
average
FSI
performance
vs.
the
prior
generation.7
As
one
CTO
said,
“The
hardware
would
usually
be
the
problem,
but
our
partnership
with
Dell
Technologies
has
taken
that
off
the
table.
With
Validated
Designs
for
AI,
instead
of
focusing
on
the
setup,
we
can
focus
on
developing
our
AI
solution
and
delivering
business
value.”
Beyond
the
numbers,
banks
are
seeing
unquantified
benefits
including
increased
employee
satisfaction,
greater
success
recruiting
and
retaining
data
scientists,
improved
customer
reputation
and
environmental
impacts.
Case
in
point:
An
AI-driven
reduction
in
fraud
keeps
more
data
secure,
protecting
customer
livelihoods
and
keeping
employee
productivity
high
while
safeguarding
the
organization’s
financial
health.
As
AI-powered
banks
make
major
strides,
they
must
do
so
at
scale
while
meeting
compliance
and
regulatory
requirements—and
most
importantly,
keeping
customers
satisfied.
Hence
the
importance
of
selecting
the
right
technology
foundation.
Backed
by
a
solid
AI
deployment,
financial
institutions
will
see
major
gains
in
business
intelligence,
productivity
and
ROI.
See
what
Dell
can
do
for
your
financial
organization.
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