RPA in insurance: 10 use cases & adoption guidelines

May 28, 2024

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RPA in insurance

by Veronika Poleshuk,

RPA Business Analyst

RPA in insurance involves implementing software bots to automate tedious and repetitive insurance activities, such as claims processing, contracts management, and invoice processing. AI-enabled RPA bots can handle more complex operations like fraud detection or interactions with customers.

With solid experience in robotic process automation services, Itransition helps insurance service providers implement reliable RPA solutions to optimize their most time-consuming and high-volume workloads.

Robotic process automation in insurance: market stats

Scheme title: Technology deployment and pilot rates among P/C insurers 2023
Data source: content.naic.org — ChatGPT Discussion for NAIC Emerging Technology Working Group

Scheme title: Technology deployment and pilot rates among L/A/B insurers
Data source: content.naic.org — ChatGPT Discussion for NAIC Emerging Technology Working Group

forecasted size of the RPA in the insurance market by 2031

RPA in Insurance Market Research And Markets, 2023

expected CAGR of the RPA in BFSI market segment from 2024 - 2032

Robotic Process Automation in BFSI Market Polaris Market Research, 2024

10 RPA use cases in insurance

The range of RPA use cases is growing in virtually every sector, and the insurance industry is no exception. Let's look at some of the most common ways to apply RPA for insurance automation.

Claims processing

Extracting data from different channels and in multiple formats, entering it into the corporate database for further processing, and sending quotations is rather time-consuming. Hopefully, insurance companies can use software bots to automate and speed up such activities. When powered with artificial intelligence capabilities, software bots can also process unstructured data, such as pictures of damaged vehicles or hand-written medical records, as well as identify specific patterns associated with fraudulent claims and alert claim handlers of potential fraud.

Underwriting

The underwriting process involves gathering extensive customer information to estimate risk rates and set premiums accordingly. With the help of RPA, the process can be significantly sped up. With automated data collection, validation, and entry, underwriters can quickly access reports with the most relevant information, such as loss runs containing a customer's entire claim history, to make fact-based underwriting decisions.

Policy administration & servicing

Many insurance policy administration tasks, including form registration, payment request processing, and account updates, are now performed by RPA bots. Moreover, insurance businesses implement AI-powered RPA bots that can operate as intelligent virtual assistants to process customer requests for policy issuance, cancellation, and renewal without supervision. This way, insurers facilitate self-service customer experience while reducing operating costs.

Accounting & financial management

Tax reporting, payment processing, and invoicing are important aspects of the insurance business. RPA bots can perform real-time data extraction and form filling faster and more accurately than humans, helping businesses improve their fiscal and accounting processes and avoid potential delays or penalties.

Customer service

Intelligent RPA bots can be deployed for various customer service and support tasks. These include call center routing, sending claim status updates, and providing additional information, such as insurance coverage or payment plan changes. As a result, companies reduce waiting time and, therefore, ensure customer satisfaction.

Policy cancellation

Policy cancellation tasks involve many mundane and effort-intensive activities, such as gathering policy data across various sources, performing return premium calculations, and inputting cancellation dates in a policy administration system. The adoption of software robots allows insurers to automate most of these tasks to achieve billing accuracy and regulatory compliance. Additionally, with the help of AI-powered RPA bots, companies can generate personalized cancellation emails, which builds customer loyalty and trust.

BI & analytics

Since RPA bots are rather efficient in collecting, extracting, and inputting business data, insurance companies can use them for various data analytics and decision-making purposes. With automated data management activities, businesses can better measure their operational efficiency, spot market trends, and identify business opportunities.

Fraud detection

Fraudulent claims lead to billions of annual losses in the global insurance industry. Combined with AI and machine learning fraud detection algorithms, RPA bots can recognize inconsistent data within claims to detect those with the highest probability of fraud. After isolating suspicious claims, a bot can trigger an investigation request.

Human resource management

RPA bots are also used to streamline a variety of HR-related insurance activities. These encompass candidate screening, personal document processing, corporate credentials generation, and training schedule creation.

Marketing automation

RPA can act as a powerful marketing booster. An insurance company can rely on software bots to automate data collection for market analysis and custom segmentation, compile mailing lists, and publish marketing content on social media according to the predefined schedule.

RPA + AI at work

Itransition’s experts have prepared a demo video demonstrating how claims processing can be automated with RPA. Similar to this process, our team can help you streamline any of your operations, from underwriting to policy administration.

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Real-life examples of RPA in insurance

- 50%

call times

One of Europe's top insurance companies intended to enhance customer service and make it more personalized. However, the company’s agents were spending work hours on repetitive and tedious tasks, which did not allow PZU to achieve this goal. The implementation of RPA helped PZU automate preliminary analysis of claims for damages, updates of legal provisions in the claims system, and data input on direct costs incurred. As a result, the company was able to provide more tailored customer service, reduce the call times to its customer service center, and improve the accuracy of entered data.

60%

operational cost reduction

Nsure aimed to automate communications with customers to minimize interactions with agents. Each month, Nsure’s agents manually processed more than 100,000 customer requests in the form of calls, emails, and text messages, which was too time-consuming and posed the risk of data errors. The implementation of an RPA solution complemented with generative AI and NLP helped the company solve this challenge. The solution analyzes incoming customer messages, evaluates their intent, routes customers to the appropriate departments, and even recommends the next possible actions to agents. Today, RPA bots help the company process the majority (over 90%) of incoming customer requests.

30%

of agents’ work time freed up

Abu Dhabi-based insurance provider aimed to automate quote generation and policy registration, as ADNIC employees spent 2 to 4 working hours completing these tasks manually. The company implemented an RPA bot integrated with AI technology to automate the tasks above. As a result, ADNIC was able to free up the working time of its agents and redirect them to managing WhatsApp business chats. This helped the company improve the quality of customer service significantly.

€80mn

gross net savings

Italy's leading insurance company used RPA technology to automate over 1,000 business processes across 40 business units. This large-scale $1 billion RPA transformation has enabled Generali to achieve numerous business advantages. The company accelerated the processing of customer requests, personalized customer service, increased productivity and employee morale, and reduced business costs.

- 50%

call times

60%

operational cost reduction

30%

of agents’ work time freed up

€80mn

gross net savings

- 50%

call times

60%

operational cost reduction

30%

of agents’ work time freed up

€80mn

gross net savings

Benefits of RPA in insurance

Improved efficiency

RPA bots can tirelessly operate around the clock and handle clerical tasks way faster than humans, especially if complemented by AI. According to our partner and automation leader, UiPath, RPA-based insurance automation can lead to a 5x speed increase in performing some key activities.

Savings

Intelligent automation of insurance operations saves hours spent on manual and repetitive tasks, which can result in significant savings for businesses. According to UiPath, reduced business costs are the most reported impact of AI-powered RPA automation.

Superior accuracy

Manual insurance operations are error-prone, especially when it comes to collecting and entering data in multiple formats from different sources. As researchers from Ulm University revealed in their experiment, RPA bots are significantly more accurate than human operators, so they can help companies improve data quality.

Enhanced regulatory compliance

Performing tasks with proper accuracy is also an essential element of regulatory compliance, especially in highly regulated sectors like insurance. A bot with a close-to-zero error rate can be an excellent assistant for administrators and accountants.

Easy integration

Thanks to their non-invasive and highly flexible nature, RPA bots can be integrated with legacy systems without changing or replacing pre-existing setups, which means manual processes can be automated with relative ease and low investment.

Better scalability

Compared to human teams, RPA bots are faster and cheaper to scale up on demand when the volume of work grows. This allows insurance companies to become more flexible, seizing new business opportunities or adjusting to increased demand faster.

Improved customer service

Intelligent bots can answer FAQs in chats, provide information about a company’s products or services, or direct customers to help center articles. That way, agents can spend more time serving customers and improving the service quality.

Best RPA platforms for insurance

RPA platforms provide insurance companies with a full spectrum of functionalities, including low-code/no-code GUIs and monitoring tools, to easily configure their own bots and harmonize their workflows. Here are the current RPA platform market leaders, according to Gartner's 2023 Magic Quadrant for Robotic Process Automation.

Pros

Low-code UX app builder
Top scalability, customization, and ease of deployment
Solid integration capabilities

Cons

Complex pricing policy and service/product offering
A steep learning curve

Target companies

SMEs
Large enterprises

Pricing

Two packages (Pro and Enterprise)
Price on request

Pros

AI-powered cognitive automation
Solid data analytics capabilities
Strong focus on cloud technologies

Cons

Limited image processing capabilities
Challenging upgrade from AA’s legacy platform to Automation 360

Target companies

Medium businesses
Large businesses

Pricing

Three packages (Community, Cloud Starter, and Advanced), pricing from $750 per month for the Cloud pack

Pros

Extensive partner and customer ecosystem
Wide range of industry-specific functionalities
Solid security features

Cons

Limited low-code development capabilities
High licensing cost

Target companies

Medium businesses
Large businesses

Pricing

Price on request
A choice between flat and consumption-based pricing models

Pros

Integrates seamlessly with Microsoft solutions
More affordable pricing compared to other platforms
Low-code development support

Cons

Dependent on the Microsoft software ecosystem
Less flexibility in building complex automation

Target companies

SMEs
Large enterprises

Pricing

Per user plan ($15 per user/month)
Per user plan with attended RPA ($40 per user/month)
Per flow plan (Starting at $500 per month)

Pros

Relatively easy and quick bot deployment
Advanced RPA script reusability
Responsive technical support

Cons

Limited unattended automation capabilities
Non-intuitive user interface

Target companies

SMEs
Large enterprises

Pricing

Price on request

Implementation guidelines for RPA in insurance

Facilitate staff training & upskilling

New technologies require new skills for proper implementation and functioning. That's why insurance companies should focus on recruiting and retaining qualified IT professionals with proven experience in RPA and related technologies, such as machine learning and natural language processing, or partner with professional vendors with relevant experience.

Identify a suitable use case

Insurance companies that haven’t previously dealt with robotic process automation should start with small automation that can be scaled to prove the viability of RPA technology for business. For example, a company can launch a pilot project to automate a repetitive, rule-based process with a high human error rate. This can include extracting data for insurance claims applications, filling data in internal claims management systems, or sending customer account closure notifications.

Define the right adoption framework

Make sure your ERP implementation framework includes the following activities:

Implementation roadmapping with key project phases, deliverables, and timeframes
Cost/benefit analysis and budgeting to define the required investment and avoid cost overruns
Post-deployment evaluation based on relevant metrics to measure the success of your RPA solution

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Challenges of RPA in insurance

Issue

Solution

Limitations of traditional RPAs

Many insurance workflows follow a pure "if/then" logic, which makes RPA particularly useful. After all, old-gen bots follow a strictly rule-based approach and can handle structured data like numbers quite well. However, as traditional software bots cannot process unstructured data, such as images and videos, their application can be somehow limited.

Nowadays all major RPA platforms, like UiPath and Automation Anywhere, combine traditional RPA features with AI-powered cognitive automation. With AI, bots can process both structured and unstructured data and extract meaningful insights from it.

Potential workflow disruptions

The implementation of RPA can affect both corporate performance and organizational culture. Although most of these changes have a positive impact, integrating RPA technology into the corporate environment can significantly disrupt established workflows and result in performance bottlenecks.

To make RPA adoption painless and smooth, companies should develop and implement robust change management strategies. A thorough change impact analysis should be an integral part of these strategies, so that the company can predict potential adoption challenges and make necessary adjustments, such as conducting personalized user training and onboarding.

Data security & compliance concerns

As RPA solutions have to handle sensitive data in many cases, data compromise and loss will lead to serious reputational and financial damage.

Companies should ensure that their RPA tools and bots operate in accordance with global and industry-specific data processing and security standards, such as GDPR and HIPAA. Therefore, RPA-enabled solutions must offer robust data security mechanisms, such as end-to-end data encryption, audit trails, and granular access controls.

An opportunity for RPA pioneers

Despite the proven benefits of RPA, the insurance sector has been lagging behind the financial and banking sectors in terms of RPA implementation maturity. This makes RPA adoption a great opportunity for companies willing to embark on a challenging but rewarding digital transformation journey. To walk this path safely and turn your insurance company into an automated enterprise, rely on Itransition's team of experienced RPA developers and consultants.

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