According to Culp, there are several areas where robotics really hits home for financial
services firms. That includes regulation and compliance and financial risk management.
"Robotics can help firms review employees' disclosures regarding personal accounts and
automatically examine account openings and paper statements – making employees' trades
and transfer disclosures subject to immediate and appropriate levels of review. Disclosure
attestations and transfer disclosures can also be examined automatically, and robotics can
reconcile employee reports on gifts and entertainment to the expense system and spot
possible anomalies and potential issues."
Cognitive Computing
Move over artificial intelligence. Enter cognitive computing.
Cognitive computing is not really a new technology. Think IBM Watson, a question-answering
computer system which was created back in 2007 to compete on the iconic American game
show Jeopardy. If you remember, it handily beat two of the show's greatest human champions
in 2011.
Cognitive computing fuses the technologies of artificial intelligence, machine learning, neural
networks, and natural language processing. While AI is designed to augment human thinking
to solve complex problems, cognitive computing tries to mimic the human thought and
reasoning processes. And it is programmed to learn from its mistakes.
Cognitive computing is expected to
grow by leaps and bounds. The market
size for this next-generation computing
system was valued at $8.87 billion in
2018. More importantly, it is projected
to reach $87.39 billion by 2026, growing
at an annual compound annual growth
rate (CAGR) of 31.6% from 2019 to 2026.
What is driving this growth? According
to the advisory firm Deloitte, the
volume and velocity of data is what is
driving cognitive computing for many
applications -- including the area of risk
management.
"Companies and public sector
organizations have progressed in terms of
using massive amounts of internal and
external data to take a more preventative
risk stance," says Samir Hans, Deloitte
Advisory principal. "However, traditional
methods of analysis have become
increasingly incapable of handling this
data volume. Instead, cognitive capabilities
—including data mining, machine learning,
and natural language processing—are
supplanting traditional analytics and being
applied against these massive data sets to
help find indicators of known and unknown
risks."
Samir Hans sees fraud detection as one of
the best examples for utilizing cognitive
computing.
THE NEW RISK MANAGEMENT | 11
