Insurance Best Practices: Leveraging RPA to Gain Efficiencies, Increase Customer Satisfaction

With digital transformation on their minds, insurers are making significant investments in foundational and emerging technologies, and they have more investments planned for the future: A 2018 Accenture survey found that 90% of insurers surveyed have a long-term plan for technology innovation. Naturally, the expectation is that these new digital technologies will streamline processes to reduce operating costs, improve the customer experience and more effectively use big data.

While insurers are thinking ahead and envisioning a digital future, achieving digital transformation can pose complex challenges. As such, it requires a systematic approach that involves a number of steps taken over the course of a few years. The first step is to integrate technologies that standardize and optimize insurance processes, such as underwriting and claims. In doing so, insurers increase resource utilization by redistributing volume peaks and valleys across all resources. Data digitization and workflow automation follow, thereby reducing paper flow and standardizing the way digital documents move throughout the insurance process.

With the incoming content chaos now tamed, the next step involves routing the now-indexed content to the relevant parties, like adjusters and underwriters, so it can be processed. To do this, the content must be fed to the insurer’s legacy core systems. Ideally, this tedious and time-consuming process would be automated. But most legacy systems are inflexible and complex — and not optimized for automation. Redeveloping them to support automation would require a level of effort and expertise — not to mention time — that’s beyond the capability of many IT teams and outside of many insurers’ budgets. As a result, insurers continue to run legacy systems and their employees continue to manually feed content to them.

Here is where robotic process automation comes in: RPA bridges the gap by feeding indexed data into the systems in an automated, cost-effective way. In this white paper, we dive into the best practices to consider so that you can achieve success in your RPA implementation. But first, let’s clearly define RPA.

Meet RPA

Deployed in a number of different industries, RPA is a software tool that automates routine tasks. It falls under the intelligent process automation technology category, which includes machine learning, natural-language generation, cognitive agents and smart workflow, all of which enhance productivity and efficiency, reduce operational risks and costs, and improve customer experiences by mimicking activities typically carried out by humans. Over time, these IPA technologies learn to perform these activities even better than humans.

An insurer using RPA tools can configure software to capture and interpret applications for processing a transaction, communicating with other digital systems, triggering automatic responses and manipulating data. RPA won’t automate all tasks, but by tackling many of the most mundane and repetitive ones, RPA improves processes and the customer experience, all while reducing cycle times and overhead. In fact, a McKinsey report stated that RPA “helped one large insurance cooperative to reduce queue procedures affecting 2,500 high-risk accounts a day, freeing up 81% of FTEs to take on proactive account management positions instead.”

In practice, RPA benefits carriers in a number of specific ways, including:

• Simplifying new-business onboarding. Bringing on new clients requires moving around a lot of inter-departmental data, and ensuring that forms are properly completed before they reach the underwriter. RPA coordinates and oversees this, eliminating re-keying of data between systems, ensuring flexibility when taking information from multiple locations, and making sure that the underwriter isn’t bogged down with chasing down information for incomplete forms.

• Processing claims faster. Typically, employees who process claims must gather information from various sources and documents and move that information into new systems, which is a time-consuming task. RPA streamlines this with a single keystroke.

• Making policy changes easier. Cancelling or changing policies requires employees to toggle among email, a policy administration system, a CRM application and more, making these time-consuming tasks. RPA can interact with all these systems and applications concurrently to streamline the processes.

• Increasing the reliability of data. Humans aren’t infallible — they make mistakes. RPA is immune to humanlike errors: It doesn’t key in data incorrectly and its “mind” doesn’t wander.

This ability to perform countless skills without human help is contributing to RPA’s popularity. In fact, it’s one of the fastest-growing technologies: The global RPA market was valued at $597.5 million in 2018, and has an expected compound annual growth rate (CAGR) of 31.1% through 2025, according to a recent report by Grand View Research.

RPA Deployment: Best Practices

As with so many technology implementations, after the initial cost and time investments, the realized benefits of RPA aren’t far behind. With RPA, however, there’s no need to dive in to a big, expensive RPA project from the get-go. An RPA project can start small to avoid significant upfront financial and resource investments. A carefully chosen process with well-defined success criteria can demonstrate a quick win to senior leadership within your organization. Then, with an initial win under your belt for a project that required minimal funding, it will be easier to build momentum and gain additional buy-in for the long-term RPA vision.

Here are some best practices to consider as you gear up for your RPA project:

Take baby steps. Certainly, a “crawl-walk-run” approach isn’t a new concept for any company implementing complex IT or business process management solutions. The “crawl” phase — the initial pilot program with RPA — may take eight to 10 weeks for an insurer. While there’s no set timeframe, what matters is that during this phase, RPA is applied to a process that can establish its credibility and show enough ROI for the insurer to want to extend it. In the “walk” stage, the insurer should look for other processes that would benefit from RPA to build in additional ROI (more on this in the next point). This phase might take as many as 12 weeks. The “run” stage is where the majority of the effort comes in. Perhaps a six-month-plus endeavor, the “run” stage is where the center of excellence emerges and where, when the insurer is evaluating RPA, it’s strategically regarded as a tool that drives ROI. At this point, the insurer is evaluating processes across divisions that could benefit from RPA and building a team of stakeholders that also brings technical and process expertise.

Select repetitive processes to enable with RPA. As with any significant implementation, challenges will crop up throughout an RPA journey. One possible pain point is selecting the right first process to enable with RPA. To this end, insurers should look for low-complexity, repetitive tasks and high-volume processes. This is a critical early decision that a partner can help with.

Find an RPA-savvy partner. RPA implementation partners can help by filling the gaps in expertise that may emerge during the implementation process. Working with a People, Process and Technology partner like Canon complements an insurer’s center of excellence, significantly reduces deployment time and ultimately puts RPA plans into action so the insurer can reap the benefits of RPA faster.

Engage IT early in the process. RPA software vendors and even industry analysts can sometimes give the impression that RPA implementation doesn’t require the help of an insurer’s IT team. As a result, many insurers’ business units or departments skip IT altogether — and wish they hadn’t. Since IT is intimately involved with connecting systems and applications, involving the IT team early helps ensure a smooth integration process.

Use clean data. Data itself may be another hurdle impeding the success of an RPA project. To get the most out of RPA, insurers must provide the technology with clean, structured and high-quality data. This means no duplicate files and no corrupt and incorrect data. Preferably, it will be standardized in a consistent template the RPA system will understand. Using poor-quality data means the RPA technology won’t process the content effectively, and manual intervention will then be required.

Address job-loss fears. RPA may also stoke job-loss fears among employees, as many tasks will become automated. But at worst, implementing RPA likely means the insurer won’t be hiring as many new employees as before. It’s important for an insurer’s RPA strategy team to consider change-management principles by communicating the benefits of RPA and emphasize that RPA won’t automate everything: Human intervention is still needed. Employees will see a shift in their job duties so that they have more free time to focus on higher-value work performed further upstream. For example, to process a claim, an employee must gather information from a variety of sources, copy the information and then take time to assess the claim. The entire process may take 20 minutes. RPA would automate the process of collecting the information and aggregating it into one place, providing the employee with more time to assess the claim. In short, RPA will allow employees to focus on higher-value tasks.

RPA Success Found

One leading financial insurance services company knows all too well the benefits RPA delivers. Before working with Canon to process its claims, the company’s employees spent time performing daily indexing and subsequently looked up related information in a legacy policy system.

Initially, Canon conducted a current-state analysis of the company’s claims process. The Canon team then performed an RPA suitability assessment to ensure the process was a good match for RPA technology. After the assessment, Canon deployed nine software bots to perform indexing and to find related information in the company’s policy system. There were a couple of bumps in the road due to some dirty data in one of the legacy systems, but once these issues were eliminated, RPA’s real benefits shone. By replacing formerly manual process with RPA, a number of the company’s employees could be redeployed into more strategic roles, optimizing their value and making formerly tedious, time-consuming processes more efficient.

Today, not all of the company’s claims are indexed and matched automatically by RPA. Those that cannot be processed by RPA are passed to exception queues, where Canon’s on-site and offshore resources review and correct the claims before passing them further upstream to the financial insurance services company’s adjusters.