NCFA Fintech Confidential December 2020 (Issue 3)

THREE
HUMAN-
CENTRIC
PRACTICES
TO BECOME
A BETTER
AI FINTECH
LEADER
You’ve seen them before - robo-advisors,
virtual agents, smart banking “platforms”
- yet with each new product launch and
press release, doesn’t it seem that artificially
intelligent tools aren’t living up to their selfproclaimed
smarts?
It happens with every technology wave, and
as far as tech waves go, AI is a tsunami. It goes
a little something like this: new technology
evolves, executives insist it’s just a fad, their
competitors embrace the tech, and then
everyone plays catchup. Generally, endusers
are the ones who feel the impacts of
this cycle, left with an endless barrage of
apps & platforms that don’t solve meaningful
problems.
At this point, I may sound quite pessimistic
about the potential of AI to create
meaningful and measurable value in
the FinTech sector. I’m not! In fact, quite
the opposite - I believe that machine
intelligence has the potential to transform
the banking industry - if we take a humancentric
approach to designing solutions
(while we’re at it, let’s stop creating apps &
platforms and all agree to design solutions
instead).
There are three practices that FinTech leaders
can adopt to bring aspects of a more humancentric
design lens into how they develop
new AI-enabled solutions.
1 - Understand Data Bias
We all have biases. It’s true. They don’t make
you a bad person, in fact, one could argue
that it makes you human. It’s not recognizing
our own biases that can lead to bad decision
making and the same can be said for the data
we work with.
Beyond just collecting and analyzing data,
organizations need to uncover how data
bias can influence the accuracy or reliability
of predictive systems. A comprehensive
understanding of the role that data bias can
play is crucial in building the next generation
of intelligent FinTech solutions. As powerful
as AI and machine learning tools are, they
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