How Insurance Companies are Using the UiPath Enterprise RPA Platform to Improve 11 Core Processes

The evolving digital age continues to raise customer expectations, spurring demand for better customer experience and lowering tolerance for manual processes and human error.

Many industries have been able to easily respond to this shift in consumer mentality, but the insurance industry—rooted in decades of complex, time-consuming processes—has struggled to hit the mark companies time, money, and relationships.

With more customers expecting tailored communication and services, insurance providers must streamline their processes as well as lower their overall costs in order to remain competitive.

Additionally, with customers becoming increasingly sensitive to how and why their personal information is being used and stored, companies must improve processes to ensure client information isn't misused, mismatched, or lost.

These pressures have led companies to explore ways to automate and streamline their existing processes to reduce error rates, processing times, and overall costs.

Thankfully, opportunities for robotic process automation (RPA) have arisen across the global insurance industry. A report indicates that 43% of operations could be automated in the insurance and finance industries to create better customer experiences.

Here are 11 ways that insurance companies around the world are using RPA to make their businesses more responsive and profitable.

We also invite you to join us for our webinar Using Hyperautomation to Drive Efficiencies in Insurance.

1

A smooth, timely, and successful underwriting process ensures that insurance companies understand the risk associated with new customers and that new clients get the appropriate rate and policy for their needs.

But this early, data-rich process can be cumbersome and time-intensive for companies, slowing down onboarding, frustrating customers, and increasing the likelihood of errors because of manual processing and unstructured data from forms.

To streamline contributing issues with their processes for underwriting and new business onboarding, a global insurance company based in Switzerland turned to the UiPath Enterprise RPA Platform and UiPath Official Training and Business Partner Cognizant for help.

The insurance company needed a precise system that would compare account records to help reconcile funds with their clients' bank statements. Before RPA, these records were compared manually within their account database, requiring employees to pull the balances and update the reconciliation information for individual customers.

This manual process was extremely time-consuming and was susceptible to inaccuracies because of human error.

By using the UiPath Platform to build their automation robots, the company was able to automate the extraction of data from the bank statements of clients and compare them within the accounting system. These automated comparisons ensured that the balances were accurate and matched across the system, with a lower error rate than before RPA implementation.

Once the data was reconciled, the Robot updated the information across the company's system.

The ROI Of automated labor

The successful implementation of the UiPath Robot allowed the insurance company to streamline their new business onboarding and underwriting processes.

The automation of these processes resulted in:

• 100% process accuracy

• Zero errors

• Improved quality and speed of processing

• 80% reduction in turnaround time

• 25% of human effort saved

2

At the center of all insurance companies is a robust claims process. But one of the most resource and time-intensive parts of the claims process often lies within manual third-party reimbursement efforts frequently carried out by paper communications.

As is the case with nearly all business practices, the more people you involve, the slower things go. In order to get reimbursed by third parties, insurance companies must swap sensitive information about their claims with the outside party, ensuring the information matches their records in order for reimbursement to be approved. From there, the initial company must double-check that the reimbursement is credited to the correct account in their system and that the payment is successfully processed.

Additionally, across insurance industries and types, manual processing comes with a much higher per-claim cost than electronic, automated claim processing. In some cases, an electronically processed claim can cost nearly 56% less than a paper claim.

With large amounts of sensitive, timely information passed between insurance agencies and their third-party counterparts, many companies have invested in technology to streamline the reimbursement process to lower the associated human error rate and allow employees to focus on higher-value work.

After learning about UiPath Enterprise RPA Platform, a United Kingdom–based insurance company turned to RPA to automate the recovery of reimbursements from third-party insurers.

The company had been facing challenges with a lackluster manual process that was time-consuming and error-filled. Overall, it was taking up valuable employee time, ate up budget, and hampered the product's efficiency.

After implementation, the unattended UiPath Robots smoothly handled reconciliation between the disparate systems. The company was able to automate the generation of chase letters—per the defined dunning process—and emails to defaulters.

Finally, the Robots performed cash applications for received payments and followed up with predefined reports on outstanding balances weekly.

The ROI of automated labor

By implementing the UiPath Robots, the insurance company was able to improve their third-party reimbursement process.

The benefits of the automation were:

• Improved speed of transactions and communication with third parties

• Faster communication to third parties about recoveries

• Maintenance of low expense ratios

• Improved capture of multistate business

• Reduced cycle time

• Increased cash flow

3

For many insurance companies, slow claims handling ranks as one of the top shortcomings in their internal processes.

According to a 2016 study of U.S. insurance companies, agencies struggle with claims filing—and associated regulatory requirements—across five main areas:

1. 1. Timely claims handling

2. 2. Claims and underwriting file documentation

3. 3. Compliant policy termination notices

4. 4. Compliant claims and underwriting disclosures

5. 5. Compliant grievance and appeals processes

To counteract delays, inaccuracies, and backlog, insurance companies around the world have turned to robotic automation software to ensure that claims are created and handled in a timely manner, without putting the business at risk of regulatory violation.

Faced with a manual and repetitive back-office process for creating claim files, a leading insurance company in Romania turned to the UiPath Enterprise RPA Platform and UiPath Official Training and Business Partner FutureWorkForce for help with automation.

The process, which involved structured information and predetermined rules, required employees to handle 1,500 tasks per week, with an average handing time of eight minutes per transaction.

The company was able to implement its new unattended Robots within four weeks and to run them for approximately 22 hours per day. The Robots constantly checked the work request location for new requests, relieving the existing backlog.

With automation efforts, the average handling time was reduced from eight minutes to six minutes per transaction.

The ROI of automated labor

With the Robots handling four key applications during automation, the company was able to process its backlog of claims file creation and cut down on the processing time of new requests.

Other benefits of RPA implementation were:

• Approximately 75% of effort automated

• A 25% reduction in average handling time

• A reduced backlog, from 4,000 requests to 0 in one month

• Increased team capacity

• A 94% first-pass yield

• Increased customer satisfaction

• Improved employee satisfaction and focus on meaningful tasks

• Better company reputation with local authorities

4

While trade credit insurance plays a vital role in protecting businesses against bankruptcy and delinquent commercial trade debt, companies within the industry face a low global saturation rate and lack of awareness among potential customers.

In 2018, only 3% of North American businesses and 15% of Western European businesses bought trade credit insurance.

This low purchase rate means that when companies receive credit limit requests from customers, they need their underwriting process to go smoothly, without errors; otherwise, they will risk losing vital business to slow, antiquated systems.

When an AA-rated South African trade credit insurance company was looking to improve their credit limit request underwriting process, they turned to UiPath Official Training and Business Partner Deloitte to help boost efficiency with RPA.

The company had struggled with the complexity of the underwriting process because of the high amount of repetitive manual processing and high cost of operation it involved.

Before RPA, underwriters had to manually collect data from more than 20 screens and external sources to compile complete information.

After implementing the robot built on the UiPath Platform, the company was able to automatically collect the necessary data and assemble and present it on a central dashboard for underwriters to access.

This decreased the performance from 4–18 minutes to 2–11 minutes, reducing processing cycle time by 40–50%.

The ROI of automated labor

By automating their credit limit request underwriting process, the company's underwriters were able to spend more time on high-value customer interactions.

Other benefits of RPA implementation were:

• Data for credit limit requests processed within one hour of receipt 85% of the time

• Processing time reduced by 50%

• Data gathered for approximately 900 cases per day

• 400 hours saved per month in the UK

• More than 2,000 potential hours saved across Northern Europe

• Improved quality of decisions

• Consistent validation and audit trail of underwriting data

5

The maturing digital era means that not only do customers and brokers expect a more engaged online experience, but that their preferred communication methods are shifting to online, too.

In 2018, around 124.5 billion business emails were sent and received each day.

That's a staggering number for any industry, and a significant challenge for insurance companies who receive sensitive, key information from brokers thousands of times per week.

The Hollard Group, a South-African insurer, turned to UiPath Official Training and Business Partner LarcAI to help automate their insurance broker-driven communications by adding virtual components in end-user processes due to a volume of emails coming from the broker community.

The company, which received 1.5 million emails per year from insurance brokers, was processing those emails by interpreting their information and attachments manually to identify the context and classify the content.

This process required accuracy and meeting time-sensitive deadlines, due to the need to be in compliance with service level agreement (SLAs) and specific regulatory and statutory provisions.

To build a robot that addressed all of their needs, the company's RPA solution included machine learning, natural language processing, intelligent OCR, and analytics capabilities that were combined in a single user interface.

The automation combined the accuracy, speed, and scale of the UiPath Enterprise RPA Platform with the expert capabilities from Microsoft Cognitive Toolkit, IBM Watson, and ABBYY.

Watch the webinar: Intelligent Indexing for the Insurance Industry with LarcAI and UiPath

By accessing the email source, interpreting content contextually, classifying and filing documents, extracting data, updating necessary systems, interacting with human users to complete instructions, and delivering confirmations once the process was complete, the UiPath Robot effectively streamlined the company's broker communications challenge.

The ROI of automated labor

In addition to making broker communication more efficient through RPA, machine learning, language processing, intelligent optical character recognition (OCR), and analytics, the implementation of the Robot:

• Saved 2,000 hours per month of processing time

• Fully automated 98% of the process

• Reduced mean time to execute by 600%

• Cut cost per transaction by 91%

• Improved staff satisfaction

• Reduced errors and improved the quality of information

Read more about how this leading insurer integrated RPA and AI to save 2,000 hours of processing time per month.

6

Across the global insurance industry, companies are pushing to modernize legacy systems that balloon man-hours and costs. While the infrastructure around these processes is strong, it can handle increasingly high-volume claims demands only so well.

Add to this the higher expectations for claim processing time from customers, and insurance companies must explore better, faster, and more accurate ways for assessing and updating claim files or face backlash from policyholders.

To automate their high-volume, repetitive, and manual claim file process, a leading insurance company in Romania turned to the UiPath Enterprise RPA Platform and UiPath Official Training and Business Partner FutureWorkForce for help.

The company's process involved reading documents and structuring information based on a set of predetermined rules. In order to complete their work, employees had to handle approximately 250 tasks per day over multiple screen swaps. This took them an average of 12 minutes per transaction.

After building on the UiPath Platform over six weeks, the company created unattended Robots that ran five hours per day to collect data, validate it, and monitor it for any errors outside of standard working hours.

By overseeing the quality of the data and processing it, the Robots allowed claim inspectors to resolve key issues and exceptions promptly during their workdays.

The newly automated process required human intervention only for business exceptions, reducing the average handling time to only two minutes per transaction.

The ROI of automated labor

The software Robot built on the UiPath Platform was able to automate key process steps within the company, from gathering claim file reports to saving payment proof to streamlining the company's claim file assessments.

Other benefits of the automations were:

• Approximately 75% of efforts were automated

• Average handling time was reduced by 83%, from 12 minutes to 2 minutes

• Impressive first-pass yield rates (100% for the first two parts of the process and 50% for the third part)

• Improved process accuracy

• Increased customer satisfaction

• Boost in employee focus on more meaningful tasks

7

For most people, filing a vehicle insurance claim often means that their primary mode of transportation is out of commission while damage is resolved. For insurance companies, this can mean processing vehicle hire from non-recommended providers as part of the policy holder's vehicle rental coverage.

So, when an auto insurance company was facing issues with the efficiency of their non-recommended hire adjudication process, they turned to the UiPath Enterprise RPA Platform to upgrade their claims process from manual to automated.

The company's claims unit had faced challenges with an off-shore process related to non-recommended hire adjudication. The purpose of the work was to evaluate whether claims should be extended, taken off hire, or closed and to identify whether there were any customer complaints.

And because the process wasn't in-house, it required a Citrix-based automation.

By using the UiPath Platform to build their Robot, the company was able to automate the process with an auto-trigger when a claim approached its deadline. The Robot was able to look at the policy eligibility and route the user for exception processing when necessary. It then validated the claim using the claim application, the invoices from the rental companies, and the hire allocation spreadsheets.

The company incorporated business rules and logic/decision tree capabilities in the automation process to enable the Robot to work within the existing process flow and escalate if further attention was needed.

Finally, if an exception arose, the Robot routed the claim to the relevant department for action.

The ROI of automated labor

By implementing the UiPath Robot into their non-recommended hire adjudication process, the auto insurance company was able to more easily handle an off-shore process that handled claims.

The benefits of the automation were:

• 30% increase in process automation

• Removal of costly system integrations

• More than 65% improvement in average handle time (AHT)

• 50% improvement in productivity

• Standardization of the process

• Process replacement across 44 global claims centers in the client's organizations

8

Valuation reports not only help policyholders understand the benefits of their insurance but also prepare insurance companies for the financial impacts of coverage claims in the future.

In order to compile accurate and complete valuations, companies must maintain a robust database of customer information, policy details, and claims costs.

When manually handled, matching and compiling information from across multiple databases takes valuable time away from staff who could carry out higher-value work instead.

Additionally, human error during this reporting can cost the company money if valuations are underbid and can result in lost or frustrated customers in the future.

To streamline a cumbersome back-office process, one leading insurance company turned to RPA to automate their valuation report compilation.

Before RPA, the company had to complete the process with manual, repetitive work based on structured information and predetermined rules. This, combined with a 25% exception rate, robbed employees of valuable time they could instead spend on higher-value work.

Partners and clients who had requested the valuation report were faced with a system overloaded by 160 transactions per day and an average handling time of 22.5 minutes per transaction.

After implementing the UiPath unattended Robots to run 11 hours per day, from 7 a.m. to 6 p.m., the company was able to automatically check for new requests.

Robots opened the new-requests folder; picked up the request for processing in first-in, first-out order; extracted information from different systems; and put together the valuation report.

Once reports were generated, Robots updated the request status to “completed” or marked it for review when necessary.

The ROI of automated labor

By automating their valuation report process, the company was able to reduce average handling time from 22.5 minutes to 7.5 minutes per transaction.

Other benefits of RPA implementation were: 

• Approximately 75% of efforts were automated

• SLAs were improved from four days to approximately two days

• Improved standardization

• Easier scalability in peak times

• Increased customer satisfaction

• Employees were more focused on meaningful work

9

It's no secret that auto insurance companies process and store large amounts of customer data, and a lot of that data comes into their system during policy setup.

From Know Your Customer processes that require companies to check driver's license and VIN numbers against state and national databases to valuation information on specific vehicles, ensuring that policies are set up in a timely, accurate way presents a challenge for many companies.

This initial phase is also where customers get their first major impressions of a company's customer service. And, as a $200B market in the U.S. alone, there is a lot to be gained or lost if challenges or errors are encountered during set up.

When a leading German insurance agency was facing inefficiencies with their vehicle insurance policy setup process, they turned to RPA for improvement.

The company had been stuck with a manual, repetitive, unstructured process that included handwritten texts, scanned paper documents, and information from various emails.

With a volume of 7,092 cases per month and an average handling time of 7.5 minutes per case, the department was falling behind. The work, which took 12 full-time equivalents (FTEs), involved the use of multiframe and web-based applications and relied on a system that was available only during daily operations.

Within four weeks, the company had implemented the solution proposed by UiPath. The new automation extended the applications' ability to improve scalability.

Once this was done, the Robots picked details from Excel files updated by an employee—which included information from emails, too—and combined them with scrapped details from scanned invoices using OCR.

Based on the inputted data, a Robot performed a precheck in the mainframe and set up the policy in the system based on a structured process.

The ROI of automated labor

By implementing the UiPath Robots, the company was able to clean up and automate their vehicle insurance policy setup process.

Benefits of doing this included:

• 60% of effort was automated

• Average handling time was reduced by 40–50%

• SLAs improved

• Improved cost savings from faster identification of inconsistencies

• Eliminated manual labor of two FTEs

• Error rates were reduced to 0%

• Customer satisfaction increased

• Employees focused on more value-add work

10

Changing policy needs due to increasingly smart cars, alternative transportation availability, and competitive pricing among auto insurance companies mean policy cancellations are a regular occurrence for agencies.

Additionally, factors such as fraud, license revocation, and lack of payment trigger policy cancellations, too.

Because of the wide range of reasons for cancellation, many auto insurance companies have turned to automation solutions to alleviate slow processing times and cumbersome manual policy reviews.

After learning about the UiPath Enterprise RPA Platform, a leading German insurance company opted to automate their vehicle insurance cancellation policy.

Before RPA, the company had to extract the cancellation date and cancellation type from free text in scanned emails and documents.

Employees supporting this process handled 8,730 transactions per month, with an average handling time of 1.5 minutes per transaction and four full-time equivalents.

In order to do the work, the team had to work within a mainframe, multiple web-based applications, and Outlook. The applications' was also only available during daily operations.

Similar to the policy setup automation, the first step was to extend the applications' availability to work around the clock.

After that, Robots were able to select details from Excel—such as cancellation dates and types—and scan invoices using OCR. They then carried out a precheck in the mainframe and canceled the policy.

The ROI of automated labor

By using RPA to handle their policy cancellation process, the company was able to more easily review information from paper and digital sources to carry out cancellations.

Other benefits of the four-week RPA implementation included:

• 50% of effort was automated

• Average handling time was reduced by 30–40%

• SLAs improved (almost to real time)

• Faster cost savings

• 0% error rates

• Increase in customer satisfaction

• Employees were more focused on value-add work

11

Big data visualization not only help insurance companies understand their sales numbers but also helps them visualize trends.

When updated weekly, intermediary sales dashboards give teams a better understanding of their performance and KPIs, as well as allow them to see where they can improve.

But in order to get the most out of a dashboard, insurance teams often have to manually pull sales data daily or weekly to keep it up to date for review.

When used correctly, dashboards can increase sales revenue by 37% and result in a 45% increase in customer retention.

But the process of gathering data and manually updating the dashboard can take up valuable time and resources better spent on the sales process itself.

After running into challenges with manually creating a weekly dashboard that summarized their weekly sales data, a leading insurance company turned to the UiPath Enterprise RPA Platform.

The company, which implemented RPA over seven weeks, had previously used a repetitive, manual process with a structured, predetermined rule base to create a dashboard each week.

Before RPA, it took 3.5 hours on average to handle the dashboard creation every week.

After implementing the UiPath unattended Robots to run regularly once per week, the company was able to automate their dashboard process.

The Robots referenced a predefined share-point folder and selected the input file for processing before extracting information and adding the data into the previous week's formula tab. This updated prediction graphics, links for sales, and product dashboards.

The Robots then compiled a final report, which was sent to the CFO each week.

The ROI of automated labor

By automating their intermediary dashboard creation, the company was able to cut down their average handling time from 3.5 hours to 30 minutes per week.

Other key benefits included:

• 90% of efforts were automated

• Average handling time was reduced by 85%

• SLAs improved from four hours to 30 minutes

• Error rates decreased

• Standardization improved

• Easier scalability in peak times

• Customer satisfaction increased

• Employees focused on more value-add work

Join global insurance companies making their businesses more efficient with UiPath

UiPath Enterprise RPA Platform doesn’t just help insurance companies work faster; it enables them to work smarter.

By embracing RPA, you join insurance companies---and companies in other industries---around the world in freeing your professional teams from repetitive tasks and empowering them to focus on creative, strategic, and value-add work.

Recognized as an RPA technology and industry leader, UiPath helps companies create great customer experiences while decreasing operational costs and error rates.

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