Insurance and Robotic Process Automation (RPA) Robotic_Process_Automation_RPA_in_Insurance__UiPat | Seite 3

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the rise of InsureTech
partnerships, i.e. companies that
deliver services and products only
for specific fields of the industry;
this lead to customers using
different providers and getting
informed via insurance
aggregators;
With all these new directions
occurring in the industry, insurance
companies need to take advantage
of the growth opportunities, while also
preventing and managing inherent
risks. They have already started to
upgrade their technical capabilities
with automation tools, such as RPA
and cognitive and Artificial
Intelligence (AI) applications.
These technologies have allowed
companies in the insurance sector to
increase efficiency, eliminate errors
and reduce cost. And if there are still
some players that have not even
tested RPA, they are definitely
considering it, as this technology is
becoming a staple in an advancing
industry.
RPA’S KEY ADVANTAGES FOR INSURERS
Robotic process automation (RPA) is
a new, but fast-growing technology
that employs software bots to take
over repetitive, tedious rules-based
business tasks.
For many people in the work field
today, administration processes are
diminishing productivity and carving
out from the time spent on strategic
tasks. Organizations utilize RPA to take
care of a wide range of tasks – from
simple document workflows to
complex business processes. Gartner
analysts estimate that RPA’s adoption
will reach 41% by 2020. As with any
new technology, RPA will move from
Insurance in the age of intelligent automation - 3
early adopters to the mainstream. At
that point, robotic process
automation will become ubiquitous.
The time spent on gathering and
processing data amounts to
approximately 50% of the overall full-
time equivalents (FTEs).
According to a 2017 McKinsey Global
Institute report, insurance and finance
have a 43% automation potential,
particularly in process data, interface
and expertise. RPA can mimic
repetitive administrative tasks and
works perfectly for functions such as
application handling, claims
processing or data entry, freeing up
between 20 to 30% of capacity at the
company level. With the advent of
cognitive and AI tools - such as
machine learning, chatbots, computer
vision or OCR - automating more
complex processes is possible, for
example using image classification
for claims processing or employing
machine learning for analyzing text
when servicing customer queries.
Key aspects for insurers are creating
high-growing businesses, reducing
costs and, at the same time,
managing inherent risks. In order to
employ RPA successfully, companies
need to be clear about their
objectives, identify the suitable
repetitive, manually-intensive and
rules-based processes for
automation, and ensure automation
is accepted throughout the entire
organization.
RPA has been deployed successfully
in handling transactional,
administrative insurance processes,
such as basic investigation,
applications handling, claims
processing, data entry or notice of
loss.