AI Digital Insurance

RPA use cases in insurance, healthcare, and financial industries

“Every company is now a tech company” – that 2018 headline from the Wall Street Journal captured how every company, like it or not, must develop its digital capabilities to stay relevant in the modern economy. Unfortunately, upgrading is never a simple, one-off procedure and many industries are bound to legacy systems for managing their data or organizing their core processes. Moreover, working in an outdated environment often requires straddling incompatible pieces of software, which results in employees spending time on rote operations that only increase the chances of damaging errors.

For some organizations, it’s obvious that a full core system overhaul is in order. However, core modernization requires significant planning and IT investment—something many businesses have had to set aside in order to focus on the immediate demands of the COVID-19 pandemic. And even the most forward-thinking businesses struggle with the IT inefficiencies inherent in any complex organization. That’s why companies in the insurance, healthcare, and financial services industries are increasingly turning to robotic process automation (RPA) to get that much-needed efficiency boost without slowing down the pace of business.

In this blog, we’ll explore how today’s insurers, banks, and healthcare providers are leveraging RPA to stay competitive in the digital era.

The essential RPA use case

Simply put, RPA is a tool for automating high-volume repetitive tasks at the user interface level. The RPA “robot” or “bot” performs tasks as a human user would.

At its most basic level, RPA has been used to automate moving files/folders, copying and pasting text, making read and write requests to databases, logging in to applications, filling out forms, handling emails, and scraping or extracting data. Today, RPA can be leveraged to do much more. With artificial intelligence (AI) and machine learning (ML) techniques, RPA’s functions are expanding to allow for more intelligent automation, especially with customer experience applications.

The distinct advantage of RPA is that it requires zero overhaul of the underlying systems – RPA merely sits on top of the preexisting software framework and works alongside human users. This means RPA is relatively fast to deploy, demands little re-training of employees or wrangling with legacy systems, and provides a clear return on investment—often within a few months. The result is an overall efficiency bump: while the robots eliminate errors in formerly manual tasks, employees can devote their time to more valuable and skill-intensive work. This low-overhead approach to automation has business leaders—especially those working in data-driven industries—scanning their operations for the time-consuming manual processes that would make ideal use cases for RPA.

Payroll processing is one such case: a high-volume, rule-based task that must be regularly performed at practically every business. Traditionally, payroll at a given company requires employees to read digital or hand-written timesheets, calculate pay, and enter bank transfers every month. RPA can automate that entire process, reading and manipulating the data according to preset rules, navigating the banking UI to file transfers, and organizing the generated pay slips for ease of access.

The discovery of plenty of other obsolete workflows ripe for hassle-free automation has fueled the remarkable explosion of the RPA market. Gartner has recorded double-digit growth rates for RPA each year for the last three years, fueling rising competition that has also reduced prices by 10-15% in the last year.

Applying RPA: use cases across industries

Here are some of the ways RPA is improving the operational efficiency and customer experience of businesses in particular industries.


  • Claims processing, submissions, and customer setup
    When insureds file claims, the relevant data must be logged in the insurer’s claims system and the proper forms generated for documentation, like issuing the First Notice of Loss (FNOL). These are easily automated with RPA, as are the similar data-scraping, entry, and generation steps involved in reviewing submissions and preparing new accounts. With more advanced RPA, businesses can now automate preliminary claims evaluations and damages estimates, too.

Banking & Financial Services

  • Cards activation
    Using a rule-based RPA, the notoriously lengthy process for reviewing credit card applications and validating information can be reduced from days to hours, or even minutes. By effectively eliminating the long waiting periods associated with processing a new credit card application, banks are able to greatly improve customer satisfaction.
  • Fraud reporting
    SAR reports and compliance documents are  extremely time-consuming tasks that banks and other financial services firms must regularly file. Firms can use RPA with natural language processing (NLP) capabilities to automate the process of generating and filing such reports.


  • Scheduling
    An optimal appointment depends upon a variety of factors gathered from both the applicant and provider. At a traditional healthcare provider, an employee is charged with manually scheduling, tracking, and confirming appointments. An RPA bot can remove that necessity by seamlessly managing both patient and doctor availabilities—taking into account diagnostics, patient preference, and any other relevant data—to quickly and accurately schedule appointments, without any human intervention. By automating the process of scheduling an appointment, RPA enables better experiences for both customers and employees.

Using RPA strategically

These use-cases represent just broad examples of how RPA can cut costs, save time, and improve the customer experience. But RPA is not a one-size-fits-all platform: every business is unique, and your use-cases for RPA will depend upon the specific arrangement and bottlenecks of your particular software environment.

RPA has been adopted with alarming speed by a majority of insurers in North America, and an ever-growing number of participants in the health and financial industries worldwide. According to research by Gartner, 90% of large organizations will have implemented some form of RPA by 2024.

This rapid growth testifies to the value of RPA, but it also points to the deeper problem: the poorly integrated systems upon which too many businesses heavily rely. Novarica warns that over-investment in RPA might accelerate insurers’ tech debt, as they fail to modernize core systems and keep apace with the rate of organizational change. RPA currently serves as a wildly popular and effective patch, and such surface-level fixes will always be needed. But it’s just that—a patch. In other words, RPA is best used situationally as part of a broader, long-term strategy for enterprise-wide modernization and digital transformation.

As RPA evolves alongside AI and ML, however, its value proposition for businesses will change, too. By 2022, 80% of organizations which have deployed RPA will introduce AI, Gartner reports. AI enables more intelligent automation of any typical RPA use case, and also extends the applicability of RPA beyond strictly rule-bound processes. These advances will have an especially pronounced impact on the customer experience, putting powerful customer engagement tools within the reach of far more businesses.

With natural language processing, for instance, modern RPA software can “understand” customer email queries and automatically reply with the appropriate response, or route the query to the relevant customer service representative. RPA’s potential to enhance customer experiences extends to call centers, where RPA can act as a low-level filter for the most common customer questions. In a similar manner, the robot can learn to “pass” the call up the line for cases that require a human touch.

New and exciting applications will continue to emerge for more advanced syntheses of RPA and AI. But whether RPA represents a game-changing revolution or a much-appreciated convenience will depend most of all on your individual business. Nevertheless, the promise of further savings and improvements in customer experience ensures that RPA will be in every business’ strategy playbook for the foreseeable future.

Identifying optimal RPA use-cases in 2021

The global pandemic has forced businesses to reevaluate their operational efficiency and come up with new ways of making each employee as valuable as possible. RPA has proven itself as a low-cost solution with clear benefits to many organizations, especially ones juggling with legacy systems. And as the potential of RPA to improve customer experiences and radically upshift employees’ efficiency expands with intelligent automation, the case for RPA will only grow stronger. Yet deciding how and where to install RPA in the value-chain is a question not every business is equipped to answer.

Ready to get started? Here’s how ValueMomentum can help your firm leverage RPA to stay competitive in the digital era.