The Intermediary – January 2026 - Flipbook - Page 70
T E C H N O L O GY
Opinion
Banking must get
more personal
C
onsumers are used
to algorithms that
perfectly curate every
part of their lives.
Netflix instantly
greets viewers with
personalised recommendations based
on the movies and shows they’ve
watched before. Spotify creates
custom playlists for listeners’ different
moods and moments throughout the
day. The list goes on.
Banks and financial institutions
hear these comparisons all too oen,
but they reflect a broader shi:
personalisation has become the
baseline across all digital experiences.
Banking services have already made
substantial digital progress.
Today’s banking customers are
looking for guidance on reaching their
financial goals. Instead, many are still
receiving static product offerings.
This personalisation gap isn’t due
to a lack of awareness or trying on
banks’ part - it’s about execution.
The manpower required to roll out
personalised banking services at
scale, both from a technological and
advisory perspective, has historically
made it economically infeasible – and
nearly impossible – for many banks.
With AI, banks have an opportunity
to deliver the level of personalisation
they want, and that consumers now
expect. But it’s not a simple ‘plug and
play’, banks need to first ready their
data and teams for AI.
More data than ever
Banks have a unique vantage point on
customers’ financial lives; they can
see how customers make and spend
their funds. Historically, however,
this visibility was limited only to a
customer’s activity within a single
institution.
With the rise of open banking and
data sharing across organizations,
banks are gaining an even clearer
view of how consumers engage across
their entire financial journey – not
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The Intermediary | January 2026
just a single account. For example,
with permissioned open banking and
data sharing between institutions, a
bank financing a mortgage can qualify
customers quickly – namely, verify
income – and personalise mortgage
recommendations based on a
customer’s complete financial history.
Banks now have more than enough
data to fuel AI-driven personalisation.
But AI is only as effective as the data
and teams behind it.
Here, we will walk through how
financial institutions can unlock
the full potential of AI to deliver
personalised banking experiences
that rival the tailored services
customers have become accustomed
to in their daily lives. Banks are
using AI to analyse data at a scale
that was previously unaainable.
Insights that teams used to have to
wait weeks for can now be generated
in minutes, enabling them to create
more personalised financial customer
experiences faster.
As the volume of data available
to banks continues to grow, from
open banking to their own internal
systems, the risk of duplicate data,
missing data or errors grows as well.
When data isn’t clean or connected,
AI operates with critical gaps – which
means the insights it generates have
gaps as well. Financial institutions
need to centralize their data so that
AI is not working off a fragmented
view of a customer but has complete
visibility to garner more reliable,
actionable insights.
Banks can then leverage these
insights to confidently market
products to relevant audiences and
provide the personalised financial
advice customers crave, but many say
they don’t currently receive.
Revenue-driving impact
While AI can uncover who individual
customers are, predict their
behaviour, and understand the context
of financial decisions like marriage or
ERIC BIERRY
is CEO at SBS
starting a family, it’s these findings,
combined with the teams behind
AI, that create personalised banking
experiences.
How teams use AI-driven insights to
engage and connect with customers is
what ultimately builds banks’ longterm relationships with them.
To do this in the best possible way,
banks need to invest in ongoing AI
training for all employees and bring
in more AI specialists to maximize
their adoption and impact. If teams
don’t know how to use AI tools, they’ll
default to using them for basic tasks,
if at all. Customers expect consistent,
individualised interactions from
their bank. To obtain these relevant
experiences, many grant banks grant
access to their data through open
banking or directly within their
banking systems.
As banks leverage AI to deliver these
experiences, transparency is critical–
for both customers and employees.
Customers need to understand how AI
informs decisions around personalised
product recommendations and
tailored financial advice. For
employees, it’s important to reinforce
that AI is meant to be a collaborator –
not a replacement.
This level of personalised advice,
enabled by AI, that banks can offer
at scale was previously reserved
for private banking clients with
substantial investable assets – a
profitable segment, but one that
couldn’t be scaled economically.
The banks that prepare their data,
teams, and customers for AI are the
ones that will deliver customer value
through personalisation, retain their
customer base and create long-lasting
loyalty. Those that don’t will lose
ground to competitors who do. ●
