NCFA Fintech Confidential December 2020 (Issue 3)

Freeing humans for more complex tasks
Mishra summarizes the use of AI in financial
services in three ways: adding new revenue
streams, reducing operational costs and
improving the customer experience.
The growing accuracy of AI voice recognition
means bots can now verify your personal
information. Customers can speak naturally
to bots about problems like password resets,
which are easier to automate, leaving room
for human customer service agents to answer
more complex questions.
The days of IVR [interactive
voice recognition], where
you have to press one or two,
are gone; now you just talk
naturally like you’d speak to a
human being, says Mishra.
While AI can automate simple tasks, it can also
be used to enhance security. As technology
evolves, so does the ability of fraudsters, and
Mishra says AI has strong use cases in fraud
detection. MNP worked with a Canadian
government body to automate auditing of
employee insurance and travel claims, which
reached up to 70,000 claims a year. The
AI MNP developed could track anomalies
like duplicate claims, saving the client up to
$3 million a year and reducing time spent
reconciling the claims for weeks to hours.
“Imagine you predicted a woman’s score is
dependent on her gender, but did not factor
in the same correlation for men. You’ve
introduced a bias without knowing,” he says.
“However, if you’re predicting whether you
have COVID, that is a medical use case. It
is maybe more prone to males, so gender
becomes a critical variable.”
Many banks may start to use facial recognition
to verify the age of potential customers. If
some groups of people aren’t adequately
represented in a dataset, the AI could
categorize people from some ethnicities
are younger or older than they are. “It’s very
important for data scientists building these
models to understand the models and
remove bias,” Mishra says.
Keeping security front of mind
For financial institutions thinking of exploring AI,
Mishra says security, privacy and compliance
with policies is critical. While major cloud
providers like Microsoft invest billions into
cyber security, financial institutions must also
have the right governance processes in place.
“Cloud as a platform offers security, but it’s
the governance around cloud that will decide
whether the application is secure,” says
Mishra.
For more information on how you can leverage
AI in your organization, contact Dev Mishra
MBA, MBAN, BEng, at 416.596.1711 or dev.
mishra@mnp.ca
INSIDER VIEW
Biased algorithms a growing concern
Mishra notes the importance of ensuring
enterprises create unbiased AI applications.
Machine learning, which uses data and
algorithms to make predictions, requires
datasets to train itself. If those datasets
already have bias present, it could build an
application that is itself biased.
For this reason, many large companies have
responsible AI frameworks to ensure they use
AI in an ethical and responsible way. Mishra
provides an example of predicting students’
SAT scores where gender is included as a
variable for prediction.
Dev Mishra
National Practice Lead
Data Engineering, AI and ML at
MNP
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