Whether you are new to automation or working to expand your robotic process automation (RPA) initiative learning how to evaluate processes for automation is imperative. RPA is a powerful tool that can yield impressive results, such as efficiency gains, reduced overhead, and decreased cycle time. Yet if a company pursues processes that are not ideal, they may face unnecessary setbacks in making their program successful. Any investment of time and effort has an associated cost which deducts from the ROI that can be achieved. To maximize your return, let’s explore some criteria for process selection and examples from a variety of industries.
Criteria to use in process selection
While there are opportunities for automation across any business, we recommend evaluating all back-office processes first. These processes are the most ideal for automation and will yield the greatest return.
- Stable: If the process changes often, or utilizes applications that change often, the automated process has to be updated as well. Constant change management equals more manual intervention, which defeats the purpose of RPA.
- Rules-based and repetitive: Processes that are repetitive and follow clearly structured rules are ideal. Robots are rule followers. Give them a set of instructions and the work will be executed accordingly, without fail.
- High-volume or fluctuations in volume: This factor can have the greatest influence on ROI. Robots can process any volume of work 24/7/365 in a fraction of the time compared to their human counterparts, which translates to normalized operations and overhead avoidance for the business.
- Performed by more than one full-time employee (FTE): Initially, keep focus on processes that are performed by multiple FTEs. As we mentioned above, the time and effort invested in automating a process has an associated cost. When the cost to automate is greater than the cost of that one employee, ROI is much more difficult to achieve.
RPA for Mortgage Lending
According to the Mortgage Bankers Association, the combination of increasing regulations and manual efforts to ensure compliance have resulted in U.S. mortgage origination costs that are three times higher than they were a decade ago. Rising production costs and increased market fragmentation have encouraged lenders to implement RPA as a key component in their strategy to scale, remain competitive, and deliver a superior borrower experience.
Origination processes are notoriously complex and reliant on multiple systems, which translates to increased cycle time, increased production costs, and exposure to human error. In fact, it is estimated that mortgage loans typically pass through 15 to 18 system users for processing before being closed. Here are prime examples of processes that yield the best return with RPA:
- Initial and locked disclosures are lengthy processes that require accurate validation of loan information and timely processing. Locked disclosures must also be sent within 3 days of receiving an application or the lender could be responsible for the difference between the rate that was estimated and the current interest rate.
- Verification of AKAs, income, assets, and employment, as well as ordering fraud, flood, title, and appraisal all rely on third-party portals and require accurate validation of borrower information. Any discrepancies or excluded documents could delay the loan or cause the lender to incur penalties.
- Change of Circumstance (COC) and closing disclosures are also time-sensitive processes that require borrower acknowledgement to keep the loan on track for timely closing.
Without automation, it typically takes between 50 to 53 days to close a mortgage loan. As a result of automation, our clients are seeing an average reduction of 20 days on their closing time, as well as an average of 52% in cost savings. Check out what we’re automating for mortgage lenders.
RPA for Health Plans
One of the greatest contributing factors to a health plan’s administrative costs is manual intervention. It makes sense in some places, like member and provider engagement where human-to-human interaction is probably preferred. In areas of the business such as Claims, Enrollment, and Provider Maintenance, where the average employee is doing the same tasks day in and day out, the cost of manual intervention can be felt deeply. Studies have shown that the average cost to rework a claim is $25. Payers must also consider regulatory compliance, securing and maintaining new lines of business, member ratings, and a variety of other factors that can be positively impacted by offsetting those robotic tasks from humans to robots.
Claims adjudication processes carry the greatest automation ROI. The very nature of adjudication is tedious, and claims have to be touched repeatedly. Examiners have many different factors they must account for and various third-party portals, pricers, or government sites they must reference. As new lines of business are added, such as Medicare and Medicaid, claim management becomes even more complex. Often, the claims administration system isn’t configured to handle new business requirements, which is understandable as it changes constantly. Robots can be trained to do anything examiners do. For example, with Authorizations, robots can retrieve administrative and clinical data from multiple systems to apply authorizations to claims. They can review claim notes, validate or update claims with modifiers, add service rule overrides, price or reprice claims, or run fee schedule updates. Another common process is large-scale adjustments. One of our clients needed to process 64,000 claims in less than 8 days to meet a submission deadline. We deployed a solution quickly and all claims were processed within a few days at a 96% success rate.
Claims, Enrollment, and Provider Maintenance are just three examples, but RPA can be applied across the business. It’s important to focus less on process specifics and more on robot capabilities. If there are rules your employees follow to process work, robots can follow those too. And you can be assured work is always accurate, on time, and within compliance. Learn more about the ROI we are producing for health plans.
RPA for Insurers
Across the board, insurers have a variety of factors working against them: high-volume, manual work, often happening within duplicative legacy systems, decreasing margins due to increasing volatility and catastrophic losses, labor shortages, and changing consumer expectations. There couldn’t be a more ideal scenario for deploying a digital workforce.
Roughly one-third of insurance processes can easily be automated, but a Cognizant study found that about 70-80% of RPA investments focus on making claim and policy processing more efficient. For example, robots can accelerate claims intake by inputting FNOLs, notifying loss adjusters, and assigning the case to claims handlers. Subrogation candidates can be identified by evaluating claims notes, diaries, or police reports. When determining Cause of Loss or Bodily Injury, robots can be trained on what to look for in claims information to enable more timely and accurate registration of claims. Since automation utilizes your existing systems, robots can retrieve the data they need to accelerate onboarding, streamline intake and underwriting, and dramatically decrease the claims lifecycle overall. Read the RPA business case for Insurance.