Robotic Process Automation Examples Across 4 Industries

Is your organization looking for ways to cut costs, help your team be more productive, and reduce human errors in your manual operations? If you’re like many organizations trying to compete on a global scale, the answer is yes. Today’s economic landscape is putting greater demands on workers, requiring them to be more operationally effective. Recently, robotic process automation (RPA) has been emerging as an attractive solution to these demands, one that not only improves efficiency but also frees up workers for more valuable, creative tasks that provide greater value to organizations. And with RPA tools clocking in at 65% of the cost of full-time workers, it’s an option that cannot be overlooked.

While RPA will likely have applications in all industries eventually, some have already begun to embrace it—namely healthcare, banking, insurance, and tax. What’s the common denominator? They all have a lot of manual, repetitive taskwork (like data entry) and a high number of tasks that involve switching between applications. In other words, they all require tasks that are perfect for bots to replicate.

Below are actual robotic process automation examples from each of those industries, all of which demonstrate the unique value proposition of RPA.

Robotic Process Automation Examples

Robotic Process Automation In Healthcare

Healthcare organizations are finding they can improve their quality of service and increase efficiency with the help of RPA:

  • Highly skilled care management nurses spend a good deal of time tracking down patient data from various sources—authorization systems, claims systems, medical records, etc. RPA can take over that data-gathering piece, leaving nurses more time to spend with patients.
  • A good portion of claims administration and processing, as well as the complaints and appeals process, can be automated. Bots can aggregate claims notes into a single document and add any relevant supporting documents. Using this information, human claims analysts can focus on the analytical steps—negotiating payments and identifying/mitigating problems—then hand everything back to a bot to complete the final steps.

Robotic Process Automation In Insurance

There are numerous ways RPA is already being applied to the insurance industry:

  • Insurance organizations faced with open enrollment periods often hire short-term employees to help process the influx of applications. Rather than onboarding and training temporary staff, they can instead use software bots to process much of this work.
  • Every time insurers enroll small groups, they handle mountains of data for each applicant, including beneficiary information and any other qualifying documentation. RPA can handle the document collection and data processing, giving insurance workers time to handle the “exception” cases—those that require additional research and exploration, communication, and ultimately, a judgement call.
  • RPA can streamline the workflow for premium advice notes. Typically, a number of operations have to occur for an advice note to be fully populated with data. For one company, using RPA to streamline this workflow reduced what was once a two-day process to just 30 minutes.

Robotic Process Automation In Banking/Finance

These three real-life instances show where RPA provides value in banking and finance:

  • A large consumer and commercial bank redesigned its claims process and deployed 85 software robots, or bots, to run 13 different processes. It was able to handle 1.5 million requests per year. As a result, the bank was able to add capacity equivalent to around 230 full-time employees at approximately 30 percent of the cost of recruiting more staff. The bank also recorded a 27 percent increase in tasks performed “right first time.”
  • Financial services employee workloads often include intensive (and error-prone) tasks like manually copying and pasting relevant data into a central system. Automating these processes not only reduces errors and saves time, but also lets employees focus on handling loan exceptions and navigating potentially bad deals that require additional communication and judgement calls.
  • A U.S. bank turned to RPA to automate its billing system, eliminating revenue leakage due to mismatches between rate cards and client invoices. This presented certain challenges for traditional bots, however, in that client invoices and contracts were in different formats (paper form or PDFs) and multiple languages. The bank utilized natural language processing techniques to scan fee schedules and invoices and translated process requirements into an automated, executable business process workflow, identifying billing opportunities and breaks. As a result, managers uncovered revenue leakage of 9 to 10 percent, of which they recovered 3 to 4 percent.

Robotic Process Automation (RPA): Tax

Property tax specifically revolves around data: valuation amounts, due dates, addresses, and more. Most corporate property tax teams spend an inordinate amount of time doing data entry as well as data-gathering to support valuation and appeal amounts.

  • When it comes to challenging appraisals, many companies struggle with short time frames for staging appeals, limited resources to handle the task, and too much data to sort through. One large North American petroleum company uses RPA to automate the data retrieval process. An automation bot scours appraisal sites daily in search of available assessments for any of the company’s thousands of wells. When an assessment is available, the bot downloads the information, retrieves associated well data from other sites such as well information, production history, and oil prices, and analyzes the data. Based on the collected information, a company reviewer determines if the appraisal is fair or if it should be challenged. If a challenge decision is made, the bot automatically files an appeal on the company’s behalf.
  • A more advanced cousin of RPA, machine learning, is also being used in the tax industry. Property tax software like MetaTasker “teaches” computers so they can start to apply some business context around physical tasks—tasks that would be beyond the reach of an RPA bot. MetaTasker uses a machine learning algorithm to mine data from tax documents, saving knowledge workers from what could amount to hundreds of hours of manual data entry. That data is then automatically imported into your enterprise system and is ready to use.

Cases like these not only help organizations do more with fewer resources, but also give knowledge workers more time to devote to reducing property tax bills.

Streamline Your Own Mission-Critical Operations With RPA

Emerging technologies like RPA and machine learning are within reach of every organization, whether that means utilizing an already-designed software application or seeking out a partner with process automation expertise. Either way, you’ll end up with a solution that benefits your business now—and sets you up for success well into the future.

Brandon Van Volkenburgh is a leading expert in progressive technologies including cloud computing, blockchain, and machine learning. He has played an integral role in the creation of innovative CrowdReason products such as TotalPropertyTax and MetaTasker.