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Robotic Process Automation in insurance is on the rise. Like other industries that have a lot of rule-based and repetitive tasks, RPA can help organizations achieve quicker, more cost-effective, and error-free processes that free up existing staff to do more value-driven work.

Policy underwriting and claim automation are two of the flagship uses of RPA in the Insurance sector. However, RPA technology can also assist with a range of tasks, such as enhancing the customer experience and managing changes within the regulatory landscape.

This article will look at RPA in the insurance industry and examine market size, benefits, trends, challenges, use cases, and case studies.


RPA in Insurance market size

RPA in Insurance market size

The global Robotic Process Automation market size in the insurance sector is worth more than $100 million in 2024. However, with a strong compound annual growth of around 28%, analysts expect the size of the insurance market to exceed $1.2 billion by 2032.

North America ($427m) and Europe ($325m) account for the biggest share of the global market. However, about one-fifth of spending comes from Asia-Pacific, with that share expected to grow considerably as the region continues on its digital transformation trajectory.


Factors influencing the growth of

RPA in Insurance

Robotic Process Automation (RPA) in Insurance -  Case Studies, Examples, Benefits & Challenges

Rapid RPA adoption within the insurance industry is driven by a complex set of factors. Let’s explore some of the industry-specific problems that RPA solves.


#1. Shifting regulatory landscape

Regulations within the insurance industry are always evolving. Technology, economic conditions, and interventions from political or consumer groups have resulted in changes in the sector in recent times, leaving some insurers struggling to keep up. However, failure to comply with regulations can result in heavy fines.

Enterprise RPA tools allow insurers to collect data, build reports, and automate other compliance tasks.


#2. Skills shortage

The insurance industry is suffering from a skills shortage. Indeed, in the UK last year, firms had five vacancies for every 100 positions. Some of the roles include actuaries, underwriters, and strategists.

Insurance process automation can help with these problems by providing a digital workforce that can perform repetitive, high-volume tasks. This assistance frees up existing employees to grapple with more value-driven jobs, meaning employers can do more with less.


#3. Digital transformation

The insurance industry is data-intensive. In recent years, the sector has gone through a digital transformation to meet the evolving needs of clients. Consumer demand, coupled with increased competition and a clear need for efficiency, means insurance firms must embrace digital technologies to stay ahead of the curve.

Further advances in RPA technology, such as AI, ML, and cloud computing, have created opportunities for insurance firms. RPA can help integrate these tools within the insurance tech regulatory ecosystems and allow for more advanced digital transformation.


#4. Cost reduction pressure

Insurance prices have been soaring for years. There are myriad factors that influence the high costs of premiums, including the costs of paying out claims, fraud, and increasing regulatory compliance.

Contrary to popular belief, insurance companies don’t have huge profit margins. In fact, they typically operate at a margin of around 2% to 3%. However, the perception among the public is that these businesses are taking home excessive profits.

RPA tools allow insurance firms to operate more cost-effectively, which can reduce the cost of premiums for their users. By reducing their reliance on human labor, firms can provide streamlined services without compromising on quality.


#5. Changing consumer demands

Competition within the insurance industry is immense, with the battle for customers increasingly decided by delivering better service. The insurance industry needs to meet consumer demand for more cost-effective policies that are simple to understand. Customer self-service options like claims processing automation can help insurance firms meet modern expectations.

RPA helps streamline these processes, and when augmented with other AI tools, like Generative AI, the technology can handle customer inquiries and help with requests.


Benefits of RPA in Insurance

Robotic Process Automation (RPA) in HR: Case Studies, Examples, Benefits & Challenges in Human Resources

RPA has become popular within the insurance niche for several compelling reasons. Let’s take a look at why firms in the insurance sector are embracing RPA solutions.


#1. Increased operational efficiency

All businesses yearn to increase operational efficiency, but with competition so stiff in the insurance sector, firms face an additional layer of pressure. Thankfully, insurance is full of tasks that can be optimized thanks to ​​RPA for claims processing, customer service, underwriting, and more.


#2. Reduced costs

RPA bots allow insurance teams access to a digital workforce that works 24-7, 365 days a year. These tools never get tired, don’t need a break, and don’t ask for a pay rise. Automation helps insurance teams reduce their headcount or rotate workers into more customer-facing, value-driven roles.


#3. Increased job satisfaction

Job satisfaction in the insurance industry is 64%, which is above the national average of 57% for all occupations. However, long hours and frequent stress are frequently cited by insurance professionals as downsides to their jobs. RPA helps alleviate mundane and repetitive tasks and allows workers to engage in the sort of meaningful duties that improve job satisfaction.


#4. Better customer experiences

RPA tools can automate customer onboarding and services, leading to quicker and more satisfying experiences. Moreover, insurance firms can automate communication and provide omnichannel support so their customers can enjoy more personalized interactions.

Customer self-service tools also mean support is available around the clock. All of these details improve the customer experience by giving consumers what they want.


#5. Increased accuracy

Thanks to RPA tool’s ability to automate rule-based tasks, human error and inaccuracies are effectively eliminated. These benefits mean improved reputation, lower costs, better customer experiences, and enhanced regulatory compliance.


Use cases of Robotic Process

Automation in Insurance

Use cases of Robotic Process Automation in Insurance

RPA has transformed the insurance industry by automating manual tasks. Let’s explore some of the most compelling RPA use cases within the insurance sector.


#1. Claim processing

RPA in claims processing helps teams with data entry, document retrieval and verification, and distribution of information. When performed manually, these duties are repetitive and time-consuming, which pulls workers away from more complex tasks. RPA solves this and makes insurance firms faster and more productive while reducing operating costs.

Insurance claim process automation facilitates more transparency and real-time status updates across a variety of devices, meeting the demands of modern consumers.


#2. Underwriting

RPA in insurance underwriting helps employees work much faster by automating information gathering, data entry, and customer analysis. Underwriting is the cornerstone of insurance because assessing risk and pricing policies with accuracy is often the difference between success and failure.

RPA in insurance underwriting helps ensure quicker processing times without compromising on accuracy or compliance. Overall, it leads to excellent customer satisfaction, too.


#3. Policy administration

Once insurance policies have been sold, there is a fair amount of administration involved in keeping them in good standing. RPA helps with policy renewals by automating communication, issuing policy updates, and collecting premiums.

The technology is also used to update policies and customer details automatically, ensuring good data quality. Finally, RPA is a perfect choice for policy cancellations because it automates records, sends relevant communications, and can even process refunds.


#4. Regulatory compliance

Regulatory compliance is a big deal within the insurance sector. However, firms can lighten the load on their employees by using RPA to ensure high-quality and consistent data collection and reporting.

RPA can also monitor compliance issues and bring them to the attention of relevant internal parties. Finally, teams can set up bots to scour relevant websites and regulatory bodies of communication for updates or changes in rules and ensure they are reflected in the company’s guidelines.


#4. Augmenting legacy software

Much like the banking and financial services industries, the insurance sector is still reliant on legacy software. In fact, a Capgemini survey from a few years ago suggested that around 80% of insurance firms were operating with software that was at least ten years old.

The costs of upgrading these systems and worries about business disruption are a big part of the reason why insurance teams stick with out-of-date systems. However, RPA is adept at acting as a bridge between these arcane systems and more modern tools. For a fraction of the cost of overhauling IT infrastructure, teams can use RPA to interact with current software and open up the world of modern cloud-based tools.


#5. Customer service

As we mentioned above, customer expectations in the insurance sector have changed remarkably in recent years. New and disruptive companies have come on the block, offering a more personalized type of service with greater transparency, speed, and simplicity. Indeed, insurance had a reputation for being stuffy and overly dry in the past, and winning the custom of younger users requires a different approach.

RPA tools can help insurance teams automate their customer service, making it more responsive, quick, and personalized. Improving consumer experiences is a huge predictor of customer trust and loyalty, and RPA can help firms cross this divide.


#6. Machine learning and data analytics

Modern underwriting uses a blend of machine learning for predictive analysis, fraud detection, and even personalized pricing. RPA tools in insurance can assist with this process by collecting data from various sources and cleaning the information. This process ensures the data is reliable, leading to increased accuracy.

RPA tools can also analyze data for insurance firms and spot anomalies and trends in claims. What’s more, RPA can help distribute the data to relevant parties, dashboards, and databases.


#7. Marketing

Insurance is such a competitive niche that marketing teams spend an incredible amount of money on promotion. For example, in the US, Geico had a marketing budget of $1.5 billion in 2022. According to HubSpot’s State of Marketing Report 2023,  the average marketing budget for insurers was 11.2% of total revenue.

Delivering cost savings while still acquiring customers is vital for firms jostling for a place in a crowded marketplace. RPA marketing automation tools can help bring value in several different ways.

RPA marketing automation within the insurance sector includes mechanizing email marketing and social media campaigns. However, when paired with ML or data analytics tools, RPA can help teams extract campaign data and assist with measurement and attribution.


#8. Intelligent Document Processing (IDP)

Insurance firms need to process a lot of documents, from internal records to health and financial data. RPA augmented with Intelligent Document Processing can help teams read and understand paperwork or PDFs and extract data to send to internal systems. These tools can also help teams with digitization efforts by parsing unstructured documents and migrating the information to databases and spreadsheets.


RPA in Insurance Case Studies

use case studies of RPA in Insurance

With so many great insurance process automation use cases out there, it’s clear why adoption is growing in the sector by the day. However, case studies are where it all comes to life, and the potential of the technology is realized.


Insurance RPA case study #1

Our first RPA in insurance case study comes from the research paper, Ditching labor-intensive paper-based processes: Process automation in a Czech insurance company (Marek, 2019). The authors write that a Czech-based international insurance company was faced with several issues. New legislation and regulations forced them to modernize their operations, which were predominantly paper-based and awash with workflow inconsistency.

The team took an Agile approach and digitized their underwriting process, centralized their workflows and company data into one platform, and used RPA tools to drive greater productivity.

The project was a great success. They cut quote preparation time by 40%, reduced costs by 50%, and drove down errors to below 1%.


Insurance RPA case study #2

The following case study is an example of RPA in life insurance and annuity business process management services. The firm in question was a software provider with a global portfolio of clients in the insurance and retirement fund sector. The problem here was obvious: the firm received over 800,000 policy requests each year, all of which they processed manually. These requests came in the form of PDFs, which required manual entry into various systems. The process was time-consuming and subject to human error.

However, adopting an RPA solution was not straightforward. One big issue was that each client they served had its own requirements, so there was a lot of variation in requirements. In effect, there was a lack of process standardization that was not solvable by traditional means because each client had a unique workflow.

The firm analyzed its processes and identified rule-based, repetitive tasks that could be performed by RPA. They looked for deterministic tasks that were high-volume and time-intensive. Some of the processes identified included updating policy data, actioning requests from customers, and sending customers letters and notifications. The team implemented RPA solutions for these workflows.

The implementation was a roaring success. Some of the net results included a near 60% reduction in manual effort and a 70% reduction in processing time. What’s more, the firm was able to slash its headcount by 50%, saving a huge amount of spending each month.


Insurance RPA case study #3

A leading European insurance broker and risk consultant with over 500 back office and customer service wanted to implement robust claims processing automation. When the insurer’s clients were hospitalized, the firm would pay for the stay and recoup the money from the patient after they signed a form to identify exemptions. When performed manually, it required long phone calls and lots of repetitive manual tasks.

The client implemented an RPA solution to automate claims from hospitals, day clinics, and pharmacies. The impact was significant, which led to the insurer improving and centralizing operations, achieving steady-state savings of almost 50% and a total cost benefit of 46%.

This case study shows how Robotic Process Automation insurance claims are quicker, cheaper, and more accurate, leading to happier customers and greater productivity.


Challenges of RPA Implementation

in the Insurance sector

challenges load testing and RPA

While the benefits of RPA in insurance claims processing and underwriting are clear, there are some challenges that firms must overcome to get the most from their RPA implementations.


#1. Legacy infrastructure

As mentioned earlier, many insurance firms are operating with legacy systems. Much of this infrastructure was designed well before cloud computing or remote access was a concern, meaning that the software is not straightforward to integrate with RPA solutions.

Despite these challenges, there are a number of ways that organizations can bridge the gap between their existing outdated and complex software and modern RPA tools. For starters, screen-scraping technology is capable of extracting data from interfaces and transferring it to cloud-based systems. Similarly, insurance firms can explore APIs or even build middleware to connect legacy systems.

Overall, while there are lots of options available, a lot depends on the particulars of the insurance software. RPA and enterprise software testing software like ZAPTEST can provide the flexibility you need to ensure high levels of data quality, security, and system compatibility. Perhaps most importantly, ZAPTEST Enterprise also comes with powerful software test automation tools and the assistance of a ZAP Expert to help with planning, implementing, deploying, testing, and maintaining an RPA project.


#2. Data quality

Any RPA implementation needs clear, accurate information. However, many insurance firms keep data within silos, which can cause some issues when it comes to centralizing information for automation solutions. RPA can help migrate this data to cloud systems or on-prem databases. What’s more, it can help ensure comprehensive data collection and clearing.


#3. Complex decision-making

RPA is made to process high-volume, predictable tasks. However, if insurance companies want to get the most from these tools, they will need to handle unstructured data and exceptions and make decisions.

Thankfully, RPA tools that are integrated with AI can offer the best of both worlds. RPA can handle heavy-duty work, with Cognitive AI tools capable of reading unstructured data, making decisions, and dealing with exceptions.


#4. Compliance

Uncompromising regulatory requirements and ever-evolving data privacy laws are a burden that insurance firms are all too aware of. Implementing RPA solutions will require planning to ensure that data is handled safely and responsibly.


RPA in Insurance trends

rpa trends & market size

RPA is making huge advances in the insurance sector thanks to its flexibility and integration with AI/ML tools and other technologies. Let’s explore some of the big trends in the insurance RPA space.


#1. Omnichannel communication

Insurance is becoming far more customer-focused. In part, that has to do with competition and changing consumer demands. LLM chatbots and Intelligent Virtual Assistants can work across the entire customer journey and provide personalized service via email, text, social media, or messenger platforms. Customer self-service options provided 24-7 will connect with RPA tools, which can send and receive data and ensure records are updated in real-time.


#2. AI-assisted risk assessment

AI-based models are already in use within the insurance industry. However, the predictions and insights these generate are only as good as their inputted data. RPA tools help teams collect, clean, and send data to predictive models to help insurance firms achieve a greater level of accuracy and insights that mitigate risk and error and improve profitability.

In addition, Cognitive AI tools are also being used for fraud detection, which, in the future, attenuate risk and help insurance firms stay more competitive.


#3. Low and no-code tools and test automation

Low and no-code tools are increasingly used within the insurance sector to help build customized applications. In the past, teams needed deep coding knowledge to build and test apps. These days, non-technical teams and developers are leveraging no code and software test automation tools to build automation tools rapidly.

Thanks to these user-friendly tools complete with drag-and-drop interfaces, insurance firms can become more responsive to consumer needs thanks to shorter software development lifecycles. Perhaps more significantly, it reduces the costs of bringing tools to market, which can boost customer service and onboarding, as well as internal automation tools that help free staff from repetitive tasks.


#4. Managed RPA

The IT skills shortage means that some insurance firms who want to implement automation solutions have seen projects delayed or shelved. What’s more, adding IT staff with the requisite expertise is often quite expensive. As a result, more insurance organizations are turning to Managed RPA services to help them at every stage of the project implementation.

ZAPTEST Enterprise clients can take advantage of this kind of service. Alongside getting first-rate RPA and test automation tools, insurance firms can also reap the benefits of having a ZAP Expert to help them with planning, deployment, and maintenance.


#5. RPA centers of excellence (CoE)

Many insurance firms understand that RPA will play a big part in the future of the industry. As a result, they are future-proofing their business by setting up RPA centers of excellence (CoE) to ensure they are well-placed to take advantage of the myriad benefits of automation technology.

Investing in an RPA CoE helps fill the skills gap, encourages innovation, and helps teams identify processes that are ripe for automation.


The Future of Robotic Process

Automation in Insurance

future of rpa

Insurance is a data-rich industry with a heavy reliance on rule-based decisions and predictive analytics. In other words, it’s a sector that will continue to be revolutionized by RPA and AI. Let’s take a look at how RPA tools will impact the insurance firms of tomorrow.


1. Assisted Insurance RPA

RPA applications in the insurance sector have typically focused on back-end processes. However, Assisted RPA will provide a seamless interaction with front-end customer service staff, helping them deal with consumer requests quickly and easily by automating data entry and recall, analyzing information to assist with decision-making, and sending relevant communications to policyholders.


2. Hyperautomation

The insurance industry is massively data-driven. Hyperautomation, which will involve a mix of RPA, AI, ML, and other technologies, could automate underwriting, claims processing, fraud detection, customer service, and more. The net result could be a fully automated insurance broker with high quality and rapid service at low costs.


3. Telematics and IoT

While IoT may not quite have delivered on its promise, there is still plenty of room for smart sensors and similar technology within the Insurance industry. P&C insurance RPA tools could connect with smart homes and cars to validate insurance claims, while telematics data could track things like cars or exercise and activity via smartphones or wearable devices.


4. Complex risk models

While risk models already have a solid level of accuracy, AI/ML tools could make these predictions almost proactive. With enough data and the right analytics tools, this technology could make highly personalized predictions with unerring accuracy, saving the industry billions per year.

However, AI-assisted RPA in insurance underwriting could run into ethical issues around user data. As far back as 2016, some insurers admitted to looking at policyholders’ social media accounts to evaluate risk. Indeed, the Tesco supermarket chain uses Clubcard data to determine household risk scores for its financial services.

Whether this undeclared information will be used within claims processing automation is open to speculation. Insurance firms will need to weigh the profitability of this approach against the ethical issues and potential reputational damage.


Final thoughts

There are many benefits of Robotic Process Automation in insurance. From helping reduce costs, drive productivity, and improve the customer experience, RPA in insurance can provide an impressive return on investment.

Claim automation and underwriting are perhaps the two most compelling use cases of RPA in the sector. These time and information-intensive tasks currently require a fair degree of human intervention across the insurance sector. However, the transformation is already underway. Insurance firms help people stop worrying about their future; RPA technology does the same thing for insurance firms.

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Alex Zap Chernyak

Alex Zap Chernyak

Founder and CEO of ZAPTEST, with 20 years of experience in Software Automation for Testing + RPA processes, and application development. Read Alex Zap Chernyak's full executive profile on Forbes.

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