RPA in Insurance: Your Complete Guide

Will you be content if you hire and pay four people but only three show up to actually do the work?

And yet, many employers do just that. According to McKinsey, an average worker spends 1.8 hours daily gathering and aggregating data, a task that is redundant and doesn’t have a direct impact on business success, and, above all, can be easily automated.

Is your insurance company looking for ways to relieve your employees from this routine burden while cutting costs and minimizing errors? If so, you can consult a robotic process automation company to build or customize an RPA solution specific to your needs.

But before that, where can you use RPA in insurance? And how to prepare for its implementation — either in specific processes or company wide?

What is RPA, and how can it serve the insurance sector?

In the insurance industry, robotic process automation (RPA) refers to rule-based software bots that can perform repetitive manual tasks, such as extracting claims data, aggregating client information from various internal and external sources, and performing background checks.

If we look at the statistics of RPA implementation, the insurance sector, along with retail, are the main beneficiaries of this technology.

With this popularity, Juniper Research predicts that almost a half of the insurance sector will invest in RPA by 2024. And McKinsey believes that those who have already adopted the technology will be able to automate 25% of their manual processes by 2025.

Deploying RPA in the insurance sector brings about the following benefits:

• Facilitates integration with legacy systems. RPA can serve as a bridge between modern software, such as an ERP solution, and the existing legacy programs and devices that are still important for business. Sometimes deploying RPA in insurance can replace legacy systems altogether. For instance, a North American insurer Security Benefit saved 40,000 labor hours in one year by automating legacy processes.
• Reduces manual work. There are many real-life examples of when adopting RPA in insurance took the excessive load off employees’ backs and gave them more time for higher-value tasks. For instance, Encova Insurance saved its workers 25 hours a week by automating their customer retention process, while Australian Unity spared its employees 22,493 hours of manual labor over the course of eight months thanks to RPA.
• Lowers attrition rates. When employees are not overwhelmed with tedious routine tasks, their job satisfaction increases. A large insurance group based in Hong Kong used to delegate routine clerical work to junior staff, who made mistakes resulting in high employee turnover. The company reported lower attrition rates after automating 80% of these processes.
• Cuts costs. Deploying RPA in insurance does require initial investment, but it helps companies to save money in the long run. For instance, a global insurance provider saved £140,000 in six months after deploying just 13 RPA robots.

Top 7 robotic process automation insurance use cases

Underwriting

Underwriters must analyze information from numerous sources to assess risks and find the best rates and policy options for their clients. In the life insurance niche, for instance, this task can take up to four weeks. Underwriters spend on average 40% of their time on data gathering and entry.

Bots can aggregate and process data from internal and external sites and display it on a dashboard for faster and more convenient decision making. According to McKinsey, using RPA in insurance can reduce data processing time by 34%. Moreover, enhanced with AI, bots can perform the following tasks:

• Populate corresponding fields in the internal system
• Analyze clients’ claim history and suggest pricing
• Verify if the person already has an existing policy
• Assess loss runs
• Identify health risks, such as checking if the person smokes
• Extract the client’s credit rating from third-party resources, such as Experian

When RPA takes over the trivial tasks, human underwriters can focus their efforts to streamline more complex cases.

A Tier 1 US insurer turned to Accenture to automate data extraction from different policy systems and provide underwriters with a 360-degree of the client and their risks. Prior to this collaboration, underwriters wasted a lot of time to perform this task manually. And now they could use this time to better serve the customer.

Business process improvement

The insurance sector is full of paper-intensive processes, which makes it challenging to assess operational efficiency and identify areas for improvement. When automation bots take over, it becomes possible to track their workflow and record each step. Afterwards, during audits, companies can review the logs and measure parameters, such as processing speed and the number of manual interventions required, to identify candidates for process optimization.

Even by simply automating a process, the efficiency increases in terms of speed and error rate.

To achieve this, many organizations are incorporating insurance RPA into their workflow. Cattolica Assicurazioni, an Italian insurance firm, turned to UiPath to automate their processes. They investigated the process of financial reconciliation and found that it contained very few exceptions and could be almost fully digitized. They deployed RPA bots to perform tedious tasks, such as matching 20.000 lines of numbers. The financial department allocated six months to complete this project. With RPA automating 90% of the process, the company accomplished this task in merely two months with a zero error rate.

Claims management and fraud detection

McKinsey reports that automation reduce the amount of manual work by 80%.

As you can see from the stats, this is a major robotic process automation insurance use case. When claim registration is done manually, it results in errors, slow service, and unpleasant customer experience. Incorporating RPA in insurance can streamline the whole process from First Notice of Loss (FNOL) to settlement:

• Integrate claims data from multiple sources, such as medical records for RPA in health insurance, photos of damaged vehicles, etc.
• Process scanned paper claims by classifying them and entering into the system correctly
• Assist in claims verification and sport fraudulent claims
• Identify any missing information and bring this issue to the responsible officer’s attention

The Canadian claims management provider SCM Insurance Services fully automated data entry for FNOL, which allowed claims to be completed 80% faster. And a large US property and casualty insurer, EXL, could decrease worker compensation claim handling time by 60% within the first four months of deploying RPA in insurance claims processing.

Policy administration and cancellation

Even though current software packages for policy administration save employees a lot of labor, they still include complex navigations through multiple applications, causing inefficiency and opening room for error.

Insurance robotic process automation solutions, backed by machine learning and natural language processing, can receive emails from policy holders, extract data, make the required changes, such as bank mandate and address alteration, and send confirmations. The technology can handle policy rating, issuing, endorsing, renewing, and cancellation, among other tasks.

Zurich Insurance Group deployed an automation solution built by Capgemini based on BluePrism software. It involves RPA robots early in policy handling as they enter policy details into the system, issue invoices, and draft policy documents that officers can review. Both Zurich clients and the insurer benefit greatly from this approach. Raffaele Nutricati, Head of Robotic Process Automation at Zurich Commercial Insurance, said, “Not only are they receiving policies of higher quality than those processed in the traditional manner, there is a significant decrease in the number of emails and phone calls to clarify information with our support desk.”

Regulatory compliance

The insurance sector relies on several compliance standards, such as tax law and HIPAA privacy rules, to guide documentation and processes. Officers are expected to monitor and act upon any changes in regulations. They need to align claim types with the corresponding jurisdiction as fast as possible, risking a regulatory breach.

Automation bots can take over this responsibility by monitoring regulations, validating customer data accordingly, keeping a log of changes, and generating regulatory reports. For example, one popular compliance use case is Name Screening Alert Review for Sanctions on politically exposed persons (PEP). Screening systems can generate thousands of alerts every day, and it would be exhausting to verify any false positives manually. RPA in insurance can pre-process these alerts, significantly limiting the number of false positives remaining for manual verification.

Customer service

As we established above, deploying RPA in insurance speeds up client-facing services and almost eliminates error rates, resulting in a better customer experience. With the abundance of insurance companies, clients always have an option to leave one provider for another. According to Deloitte’s survey, 41% of respondents have left their insurer after experiencing poor customer service.

Moreover, automation enables companies to perform advanced analytics to gain a better understanding of customer expectations and provide personalized offerings. For example, a client has posted on social media about his upcoming trip. An RPA assistant takes notice of this information, and when the client contacts an insurance agent about, let’s say, home insurance, the smart assistant will notify the agent about the vacation, enabling the agent to produce a customized offer covering all of the client’s needs.

Such an approach will give you a competitive advantage as 88% of clients complain about the lack of personalization in insurance products.

Query processing

The insurance sector receives large volumes of broker and customer queries that demand fast resolution. Manual query processing can be error prone and exhausting for employees, while deploying RPA insurance bots will guarantee faster and more accurate results.

Hollard Group managed to facilitate broker communication through automating 98% of email handling processes. As a result, they reduced execution time by 600%, saving 2,000 hours of employee time per month.

The path to successful adoption of robotic process automation in insurance

Here are the five steps that you can take to prepare yourself and your company for the upcoming automation project:

• Identify candidate processes for automation. Opt for processes that are well-structured, rule-based, and don’t have many exceptions. It is also a good practice to choose frequently used processes as they will amplify the benefits and speed up return on investment. According to Gartner, the ideal RPA candidate should not include more than 20 steps or involve over three applications.
• Optimize processes before automation. Analyze the process first and eliminate any unessential steps. Also, even though every employee performs the task differently, come up with a standardized process version for automation.
• Involve your employees from the beginning. This will help people appreciate RPA benefits, give improvement suggestions, and will make them generally motivated to use the new system.
• Select your RPA platform. There are four well-established RPA vendors, namely UiPath, Blue Prism, Automation Anywhere, and WorkFusion.
• Find a vendor who will help you incorporate the selected RPA insurance tools into your existing system. Most likely, you will still need to customize your preferred RPA solution to cover all your needs and fit into your workflows. An experienced robotic process automation company will ensure a seamless integration.

You can learn more about RPA adoption challenges and how to overcome them in our recent article.

What’s next for RPA in insurance?

Deploying robotic process automation in the insurance industry can speed up operations, bring down expenses, and increase customer satisfaction. But this is just the beginning of the road towards intelligent process automation (IPA), which will empower RPA bots to take over tasks typically reserved for humans. With the help of cognitive technologies, such as AI, emotion recognition, and optical character recognition, RPA can maximize its contribution across the insurance value chain.

You can learn more about intelligent automation from our recent article that compares IPA to RPA. We also composed a comprehensive guide on how to start with enterprise automation and how much it will cost to implement an RPA solution. Finally, you can discover more on RPA in finance by visiting our blog.

Want to increase efficiency and cut costs by automating some of your manual insurance processes? Drop us a line! Our RPA experts will help you select the right automation platform and will customize the solution to cover your unique needs.