a series of validations on the submissions, aggregates the results,
updates the status tracker, and sends email notifications as process
milestones are achieved or issues arise.
The company has achieved a number of significant results,
including:
■ Actuaries can now focus on exceptions, reviewing model results
identified by the robot as being outside of predefined tolerances.
■ Cycle times are shorter because the robots operate on a 24/7
basis and submissions outside of business hours are immediately processed.
■ Rework is minimized because each work step is consistently
executed and automatically documented.
■ Key review and decision points have been incorporated where
human judgment is needed; in some instances, signoffs from
the process owner are required before the robot will proceed
to the next milestone.
RPA was similarly effective in performing quarterly analysis
across 20 property and casualty reserve segments. Despite the use
of reserving software, the reserving process was inefficient, with
significant time spent on manual activities such as data preparation
prior to the selection of assumptions.
To improve the efficiency and controls, RPA took on data
preparation subprocess tasks, including:
■ Copying and pasting prior-year data to current spreadsheets;
■ Aggregating and copying current evaluation data to the latest
diagonal;
■ Uploading the triangles and other data into the reserving software;
■ Setting initial assumptions based on the prior evaluation selections process; and
■ Exporting initial results into data visualization and reporting
software.
Just like a human, the robot worked across multiple plat-
forms—including Excel (with macros), reserving software, and
data visualization tools—providing additional information for
better decision-making and allowing actuaries to focus on the
selection of assumptions and interpretation of results.
In this situation, implementing RPA led to:
■ 25 to 30 percent productivity gains and overall cycle time
reductions;
■ Improved controls; and
■ Earlier and better insights into emerging trends and business
implications.
Automation in Context:
Driving to Holistic Solutions
It’s important to recognize that RPA is one of a variety of technologies that can be leveraged to drive automation in finance, risk,
and actuarial functions. Further, it’s only one element of broader
modernization and transformation initiatives. Those programs
may also involve:
■ Rationalization of modeling, valuation, and analysis systems,
and migration to next-generation platforms;
■ Centralization of modeling, valuation, reserving, and other
critical functions;
■ Enhanced data management practices, including big data
techniques, and the embedding of analytics throughout the
value chain;
■ New sourcing strategies, including using resources in low-er-cost offshore locations and/or outsourcing to third-party
providers;
■ Adopting new or updated talent management strategies; and
Companies seeking to boost their returns on transformation and
automation investments and enhance the value that the actuarial
segment can bring to the business should consider their options
holistically and decide which tool, or combination of tools, is right
for their unique circumstances and objectives.
Robots Join the Team
Figure 3: The future of actuarial work
® Standard processes
automated with robots
complementing the
traditional workforce
® Focused on creation
and communication of
business insights and
higher-value analytical
tasks
® Information interpreters
and data and analytics
champions supporting
new products and
offerings
® Highly connected
teams across actuarial,
finance, risk claims and
underwriting teams