Reducing Cycle Times with Robotic Process Automation (RPA)

October 20, 2017 by Jeanette Sherman

Of all the KPIs measured and treasured in insurance, cycle time is the most critical. Insurers today use RPA as a way to shear lag time, increase efficiency, lower claims processing costs, get agents paid faster, keep existing customers satisfied and delight new applicants.

When application processing takes too long, take-up rates drop day by day. The longer it takes for an application to move through the system, the more likely it is that the customer will walk away. When customers aren’t buying the policies they applied for, revenue and agent satisfaction suffers – and you can kiss potentially valuable referrals goodbye.

According to research from Accenture, “a successful RPA implementation can yield a 40 to 80 percent reduction in processing costs, and up to an 80 percent reduction in processing time.”

Those are some unquestionably newsworthy numbers, predicated on the successful implementation of RPA. When applied to the right processes, RPA delivers on its promises to dramatically reduce cycle time.

But questions remain about what those processes may be, and how to avoid the deeply disappointing results that have led some firms to reject RPA – making the biggest mistake of all.

When RPA Doesn’t Work

The Journal of Financial Perspectives: Insurance identified 10 common mistakes that will undo the purpose of adopting RPA, incur pointless expense, and shove you into a permanent seat in the Trough of Disillusionment. We’ve chosen three missteps to highlight.

1) Targeting RPA at the wrong processes

“Targeting RPA at a highly complex process is a common mistake. This results in significant automation costs, when that effort could have been better spent automating multiple other processes. Often these processes are tackled only because they are very painful for agents, but may not offer huge savings.”

Rather than throwing RPA at an overall set of issues, take time to examine the processes best suited for automation that will lead to accomplishing your organizational goals, such as:

  • Processes that need to be faster and more efficient – and that will directly improve the customer experience, especially streamlining the application process

  • Processes with quality or consistency issues, such as eliminating NIGO data

  • Upstream and downstream processes that change or evolve during business cycles, such as a minor form change required to comply with a new regulation

2) Using the wrong RPA methodology

“Quite often companies try to apply an over-engineered software delivery method to RPA, with no-value documentation and gates, leading to extended delivery times – often months where weeks should be the norm.”

Once you’ve identified the best processes to automate, work closely with your vendor to make sure the implementation method matches the tasks and can deliver the improvements you need as quickly as you need them.

3) Automating too much of a process or not optimizing for RPA

“Often we see that companies try to totally eliminate human input in a process, which ends up in a very significant automation effort meaning additional cost or a delay to benefits. But we equally often see no effort in changing existing processes to allow RPA to work across as much of a process as possible, and hence reduced savings.”

The human touch is essential to the success of RPA. Regardless of what the most starry-eyed futurists promote, our reality – and the reality we can expect to live in for the foreseeable future – is that AI is leagues away from full and faithful replication of human decision-making processes. Intelligent Automation solutions, like Captricity’s, harmonize with RPA by automating the processes that can be done without a human, while leaving humans in the loop for the types of subjective, complex decision-making that can still only be done by workers.

RPA’s “Make It Work” Moment

Insurers already have the data they need to make RPA work, in the form of first-party data created from the interactions with customers during primary business processes. The “dark data” that’s locked up inside paper forms, call transcripts, chat logs — in any type of consumer communication — is the type of information that can make seemingly poor investments in RPA take flight.

Captricity enables insurers to use analog inputs — including handwritten forms — to feed into their RPA systems, as well as typed and web forms. By transforming raw input into normalized data that is then enhanced with data cleaning, validation, and enrichment solutions, the Captricity solution delivers high-quality data capture and enhancement. As a result, insurers can turn fragmented efforts into the kind of intelligence that creates dramatically improved straight-through processing rates for applications.

By automatically validating and enhancing key business data, Intelligent Automation can transform raw input into RPA-ready data insurers can rely on — before your RPA vendor sends incomplete or invalid data to downstream workflows.

Captricity is refining the future of RPA, developing solutions that derive the highest possible value from your RPA efforts. There’s a reason that 13 of 20 the largest insurers in the U.S. trust Captricity. Discover them at www.captricity.com

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