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5 RPA Use Cases & 10 Case Studies in Insurance Industry in '24

Robotic Process Automation technology offers a wide range of benefits to insurance companies, from shifting the workforce to more valuable tasks to reducing manual errors in claims processing/ fraud detection processes. According to McKinsey, the insurance industry has the potential to automate 25% of the process by 2025, and most of its automation potential comes from operational processes where RPA can help (Figure 1). Another study from McKinsey also reveals that auto insurance,  property & casualty (P&C) insurance, and employees’ computers are areas where insurers can benefit most from automation due to the high standardization of processes.

Insurance areas where RPA can automate most
Figure 1. Potential processes to automate in insurance industry. Source: McKinsey

Regardless of where your business uses RPA, the technology reduces the time spent on repetitive tasks. UiPath estimates that current RPA technology can save insurers:

  • 19% of the time where human expertise is currently required
  • 34% of employee time in the data processing
  • 23% of stakeholder interaction time

The following are the top RPA use cases in insurance:

1. Claims Registration & Processing & Fraud Detection

Claims processing is a labor-intensive process where insurers need to collect information from multiple sources. Some example sources where insurers spent time on gathering and checking information are:

  • Auto insurance: Police reports of accidents, driver’s licenses, and photos of damaged vehicles
  • Travel insurance: Photos of damaged luggage and boarding pass
  • Life insurance: Historical medical records

Processing these data sources manually makes the process dull, time-consuming and prone to errors. According to Workfusion, automated claims processing reduces manual workload by 80% and the time necessary for the process by 50% Insurance companies can leverage RPA bots to automate the following steps of claims processing:

  • Extraction of information
  • Integration of claim related sources
  • Inputting data into the systems
  • Identification & verification of fraudulent claims

2. Underwriting & Pricing

Insurance underwriters evaluate and analyze the risks involved in insuring people and assets. Then, they set pricing for identified risks. The underwriting process involves collecting information regarding the background of insurable people or assets. When RPA is combined with AI and analytics, bots can:

  • Collect data from external and internal sites
  • Fill required data fields in internal systems
  • Assess loss runs
  • Analyze the history of customers’ claims and provide pricing options based on previous results

For a more detailed account, check our articles on AI underwriting and underwriting automation.

3. Policy Administration & Servicing

Policy processes include rating, quoting, binding, issuing, endorsing, and renewing.  A conventional policy administration software may be expensive, require high-maintenance, and not be scalable enough to meet the growing number of customers. RPA can automate transactional and administrative areas of policy activities such as accounting, settlements, risk capture, credit control, tax, and regulatory compliances.

4. Regulatory Compliance

The insurance industry is regulated by strict laws that aim to standardize documentation and audit trails. Manual control of compliance contains the risks of errors and regulatory breaches. RPA automates those processes and ensures that data is accurate, and maintains a complete log of changes. Log files enable insurers to monitor regulatory compliance regularly through internal reviews. Some compliance processes RPA can automate are:

  • Name screening
  • Compliance checking
  • Client research & validation of customer information
  • Data security operations
  • Generation of compliance reports

To explore how RPA can be used in reporting, feel free to read our in-depth article about RPA for reporting with 17 use cases.

5. Responding to Queries

Most industries involve the process of responding to customer and employee queries. RPA bots can interpret incoming emails, resolve simple inquiries, and when they detect complex queries, they can pass them to humans.

Case studies about RPA in insurance

Here, we listed 10 case studies from insurance companies. If you want to see a more comprehensive list of RPA case studies, feel free to check our related article.

CompanyBusiness FunctionCase StudyResults
A health insurance companyOperationsMember enrollment process
Commercial claims testing audit
Reduced effort
Reduced errors
A life and financial services companyHR OperationsHR record processing
Physician statement orders
$200k savings p.a.
A shared service provider, part of a insurance groupOperations
Streamlining processes that involves involved tracking Excel spreadsheets and consistent communication to and from all the parties involved in handling processes & reconciliation
56% reduction in incoming email resolution time 38% reduction in incoming phone call volumes, despite an increase in transaction volumes in the same time frame
Bajaj Allianz General InsuranceOperations
Streamlining 22 processes such as procurement of proposals, approvals & issuance. Mostly focuses on processes of policy issuance.
Cut down redundant tasks Improved efficiency
Higher customer satisfaction
American Fidelity Customer ServiceCustomer facing processes such as managing customer emails
Increased productivity Improved accuracy Freed employees to focus on customer service.
Hollard GroupCustomer ServiceStreamlining broker communications through email automation
Saved 2,000 hours per month of processing time Fully automated 98% of the process Reduced execution time by 600% Cut cost per transaction by 91%
EXLOperationsEnd-to-end claims processingReduced processing time
Reduced audit
Improved accuracy
Private sector insurance companyCustomer Service
Processing queries from SMEs via email, direct branch request, phone, agents and third party resellers are automated
Reduction in quote generation time Reduced policy booking time Increased conversion rate Reduced errors
Life insurance companyPolicy Admin SystemProposal form processing
Improved customer satisfaction Error Reduction Improved SLA compliance Reduction in cost of service
An insurance companyCustomer ServiceAutomatic processing of quotes and payouts10 FTEs cost saving
Reduced quote generation time

Recommendations to insurance business leaders

  1. Leverage process mining to understand insurance operations and determine the processes to automate.
  2. Work with machine learning/deep learning companies to augment the capabilities of RPA bots.
  3. Collaborate with insurtech companies and use their cloud computing platforms to speed up your digital transformation process.

For more on RPA

If you still have questions on RPA applications, read our comprehensive articles:

If you want to explore RPA in more detail, download our in-depth whitepaper on the topic:

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If you are ready to try using RPA in your business, feel free to check our comprehensive list of RPA vendors to choose the right RPA vendor for your business.

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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1 Comments
IntelliBuddies
Sep 15, 2021 at 04:56

Thanks for sharing this information article, I got a lot of information about use case of RPA Automating Insurance Industry….

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