Top 7 use cases of RPA in insurance

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

McKinsey reports that 25% of the insurance industry will be automated by 2025. The consultancy also believes that adopting RPA in insurance can decrease data processing time by 34%. With these predictions, no wonder the market is exploding. Research forecasts the RPA in insurance market to reach $1.2 billion by 2031, growing at a CAGR of 28.3% from 2022.

But how does using RPA in insurance services benefit your company?

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 do the following:

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

Real-life example:

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.

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.

Real-life example:

Cattolica Assicurazioni, an Italian insurance firm, turned to UiPath’s RPA in insurance services 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.

McKinsey reports that automation can cut claims processing costs by 30% and reduce the amount of manual work by 80%.

Handling a claim manually results in errors, slow service, and unpleasant customer experience. RPA in insurance can streamline the whole process from First Notice of Loss (FNOL) to settlement:

Real-life example:

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.

RPA in insurance 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.

Real-life example:

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.”

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.

Every country has its own regulations when it comes to running the insurance business.

Real-life example:

ERGO is an insurer based in Germany. It’s part of Germany’s law that if a client switches from one insurance broker to another, the new one can ask the incumbent to send all the active contracts. ERGO struggled to comply, as the number of such requests was large and they were effort intensive. The insurer turned to Blue Prism’s RPA in insurance services to automate the process. As a result, ERGO saved over 2000 hours of manual labor to comply with this rule.

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.

With RPA in insurance services, companies can shorten the duration of customer calls and use advanced analytics to gain a better understanding of customer expectations and provide personalized offerings.

Real-life example:

A large European insurer, PZU Group, turned to UiPath to enhance customer experience with robotic process automation. After experimenting with RPA in small-scale projects, PZU deployed the technology for five of its critical applications, and it had a tremendous impact. Automation increased the productivity of insurance consultants, cutting the average time of a call with a customer by 50%. And the accuracy of the entered data reached 100%.

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.

Real-life example:

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.

Step 1: 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.

Step 2: 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.

Step 3: 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.

Step 4: Select your RPA platform

There are four well-established RPA vendors, namely UiPath, Blue Prism, Automation Anywhere, and WorkFusion. To help you decide, we prepared a detailed guide comparing RPA vendors.

Step 5: 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.

Deploying RPA in insurance 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 and RPA in healthcare by visiting our blog.

At ITRex, we’ve built a solid expertise in robotic process automation and are happy to offer our RPA in insurance services to address your business needs.