RPA in insurance: 10 use cases and adoption guidelines

RPA in insurance: 10 use cases and adoption guidelines

January 19, 2023

Intelligent automation technologies and RPA services delegate a growing number of tasks to machines and allow human professionals to focus on more motivating and high-value duties, such as business analytics, data-driven decision-making, and customer care.

Robotic process automation (RPA) in the insurance industry entails the implementation of software bots programmed to mimic and replace humans in performing some of the most repetitive and time-consuming functions.

Let’s find out where RPA is applied in the insurance industry, which benefits come from its adoption, and how to streamline its implementation.

Table of contents

RPA in the insurance market stats

Scheme title: Deployment rates of modern technologies among more than 100 insurer CIO members of the Novarica Insurance Technology Research Council
Data source: novarica.com—Insurers Actively Adopting Emerging Technology with Clear Value like RPA and Chatbots, 2020

the global RPA market share of the BFSI sector, which makes it the leading segment.

Robotic Process Automation Market Report Grand View Research, 2022

the share of insurance companies that have already implemented RPA in their business processes.

Emerging Technology in Insurance Novarica, 2020

10 RPA use cases in insurance

The range of RPA use cases is growing relentlessly in virtually every sector, and the insurance industry is no exception to this positive trend. Let's take a look at some of the most interesting ways to leverage RPA for insurance automation.

Claims processing

Extracting data in multiple formats from several channels (such as pictures of damaged vehicles, police reports, medical records or certificates), entering it into the corporate database to process insurance claims, and sending quotations manually can be challenging and time-consuming. All claims management activities can be automated and sped up using software robots.

Underwriting

This process involves gathering information to estimate customers' risk rates and set the premiums before they take out an insurance policy. RPA can boost data collection, data entry into corporate systems, and validation to speed up the underwriting process. Then, the most relevant information can be extracted to compile a wide range of reports (including loss runs containing a customer's entire claim history) and provide product pricing recommendations.

Policy administration and servicing

Before the advent of robots, insurance companies relied on traditional policy administration systems to streamline their workflows. RPA bots, however, are faster and much more scalable. They can take care of many back-office functions including form registration, payouts, account updates, and more. They are also very efficient in classifying cases by type and processing or routing requests related to insurance policy reviews.

Accounting

Another important aspect of administration involves fiscal and accounting processes such as tax reporting, payment processing, and invoicing. Once again, RPA bots can help out with key data extraction and form filling faster and more accurately than humans, avoiding potential delays or penalties.

Customer service

RPA bots can be deployed for a variety of customer service and support tasks to reduce waiting times and therefore increase customer satisfaction. These may include sending claim status updates and providing additional information, such as insurance coverage, payment plan changes, and call center routing.

Policy cancellation

Canceling policies is a time-consuming process involving multiple interactions with emails, CRM, a policy administration system, and other tools or data sources. The adoption of software robots allows administrators to automate most of the work required to fill out forms and move data between different software solutions.

BI and analytics

The ability of RPA bots to automatically extract data from selected sources can be invaluable for data analytics and business intelligence purposes, since it helps insurance businesses to better measure their operational efficiency, spot market trends, and identify business opportunities.

Fraud detection

Fraudulent claims account for around 10% of property-casualty insurance losses, according to the Coalition Against Insurance Fraud. Combined with AI and machine learning fraud detection algorithms, RPA bots can autonomously isolate suspicious claims reporting inconsistent data, triage them into a special queue for further analysis, and trigger an investigation request.

Human resources

RPA bots are also reliable allies when it comes to streamlining a variety of HR-related insurance processes. These encompass candidate screening, employee onboarding, payroll, personal document processing, attendance and absence management, and employee expense reimbursement.

Marketing

RPA can act as a powerful marketing booster. Several insurance companies rely on software bots to automate data collection for market analysis and custom segmentation, compile mailing lists, and publish marketing content on social media throughout the month.

Real-life examples of RPA in insurance

- 50%

call times

One of Europe's top insurance companies leveraged RPA to halve call center times, reduce administrative workload for customer support, and thus let agents focus on front-office activities.

50%

fully automated purchases

This online insurance shopping platform adopted RPA to automate communications with customers, half of whom can now complete their purchase without interacting with an agent.

-30%

work time

This Abu Dhabi-based insurance provider implemented RPA bots to automate quote generation and policy registration while redeploying employees in decision-making roles.

$80m

in gross savings

Italy's leading insurance company automated over 1,000 processes, including claims processing, through more than 300 RPA robot applications deployed across 25 entities.

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Benefits of RPA in insurance

The adoption of RPA in insurance can positively impact every function of your business and help you achieve a competitive edge in the market.

Improved efficiency

RPA bots can tirelessly operate round the clock and handle clerical tasks way faster than humans. 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

Faster insurance operations result in significant savings. Based on UiPath's case studies, for example, an insurance company was able to save 18,000 person-hours and about £140,000 in six months after deploying RPA bots to automate its workflows.

Superior accuracy

Manual processes in insurance are error-prone, especially when it comes to collecting and entering data in multiple formats and from various sources. Fortunately, RPA bots are significantly more accurate than human operators.

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 insurance 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 experience

Insurers face tense situations with customers right after unfortunate events on a daily basis. In such scenarios, managing paperwork quickly and efficiently via software robots is critical to delivering better customer experience.

Best RPA platforms for insurance

RPA platforms provide insurance companies with a full spectrum of native 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 2021 Magic Quadrant for Robotic Process Automation.

Pros
  • Low-code UX app builder
  • Top scalability, customization, and ease of deployment
  • Solid integration capabilities
Cons
  • Financially demanding for small automatization projects
  • Complex pricing policy and service/product offering
Target companies
  • SMEs
  • Large enterprises
Pricing
  • Two packages (Pro and Enterprise)
  • Price on request

Pros
  • Artificial intelligence-powered cognitive automation
  • Solid data analytics capabilities
  • Strong focus on cloud technologies
Cons
  • Inaccurate data extraction from images
  • 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
    • Built-in API connectors
    • Integration with Microsoft’s software ecosystem
    • Low-code development support
    Cons
    • Windows-centric
    • Complex navigation between Desktop and cloud-based Power Automate
    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
    • Extensive partner and customer ecosystem
    • Wide range of industry-specific functionalities
    • Solid security features
    Cons
    • Low-code app development and API integration can be improved
    • Limited responsiveness to customer inquiries
    Target companies
    • Medium businesses
    • Large businesses
    Pricing
    • Price on request
    • A choice between flat and consumption-based pricing models

    Implementation guidelines for RPA in insurance

    To catalyze the structural shift towards process automation, insurance companies will need to take into account a handful of key factors, including:

    Upskill your staff

    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 other organizations boasting this expertise. Furthermore, with RPA bots taking over tedious clerical tasks, insurance companies should help their employees develop strategic, analytical and social skills, which cannot be replicated by robots.

    Identify a suitable use case

    Where are robots worth deploying? Generally speaking, RPA is best suited for automating repetitive tasks and high-volume intensive processes affected by a high human error rate. Indeed, according to PwC's 2019 Actuarial RPA survey, RPA's most popular use cases in insurance involve data processing and reporting tasks. These include sending outputs (usually emails), running ETL processes, creating audit trails, compiling reports for stakeholders, and acquiring data from Oracle, SAP, or other enterprise systems.

    Other important and fairly widespread use cases relate to activities that are not exclusive to the insurance sector but common among all industries, namely finance and accounting processes such as reconciliations, GAAP reporting, and so on.

    Scheme title: RPA adoption rate in insurance business processes

    Data source: pwc.com—PwC’s 2019 actuarial robotic process automation (RPA) survey report

    Finance/accounting processes
    Data and reporting processes

    Define an adoption framework

    Defining a suitable framework will help you streamline RPA implementation. This should encompass several factors, including:

    • Implementation roadmap detailing key project phases and their timeframe.
    • IT system reconfiguration in light of your software ecosystem, corporate workflows, and automation goals.
    • Cost/benefit assessment and accurate 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

    Insurance service providers should be prepared to face the following issues when planning their RPA implementation project.

    Issue

    Solution

    Limitations of traditional RPAs

    Issue

    Solution

    The majority of insurance workflows follow a pure "if/then" logic, making RPA particularly useful even in its most basic configurations. Old-gen bots, in fact, follow a strictly rule-based approach and can handle structured data like numbers quite well. On the other hand, they may have a hard time facing exceptions and extracting unstructured data from sources like images and videos.

    Today's trend among major RPA platforms like UiPath and Automation Anywhere is to combine traditional RPA features with AI-powered cognitive automation so that bots can gain a deeper understanding of the data they process and perform more advanced tasks.
    Process fragmentation

    Issue

    Solution

    Automating non-synergistic processes might make them faster, but not necessarily more efficient. So much so that, according to Deloitte's 2022 Automation with intelligence report, immature and fragmented processes represent one of the top barriers to effective automation. Rather, automating single processes without harmonizing the entire corporate workflow might result in new bottlenecks.

    Insurance companies should embrace a more comprehensive, end-to-end approach to process automation and standardization, possibly relying on BPM and data analytics tools to identify inefficiencies or redundant procedures and predict the potential effects of RPA-driven process adjustments.
    Resistance to change

    Issue

    Solution

    An obsolete corporate culture and the consequent resistance to change can seriously hinder RPA adoption. The three main embodiments of this rather common challenge are employees afraid of job disruptions caused by mass automation, top managers not yet ready to delegate crucial tasks to robots, and stakeholders reluctant to invest in automation.

    These issues can be mitigated by enhancing employees’ soft skills with a solid training plan, gradually implementing RPA to highlight the first small achievements, and sharing existing automation experiences and success stories from early adopters.

    An opportunity for RPA pioneers

    Despite the proven benefits of RPA in insurance and its widespread adoption in the BFSI macro-group as a whole, Deloitte highlighted the fact that the insurance industry has been lagging behind the financial and banking sectors in terms of RPA implementation maturity. Whether it’s the effect of a particularly conservative mindset or a matter of process fragmentation, this low propensity for change may represent both a weak point for this industry and an opportunity for far-sighted companies willing to embark on a challenging but rewarding automation 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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