5 RPA Use Cases & 15 Case Studies in Insurance Industry in ‘23

Robotic Process Automation (RPA) is transforming the efficiency and accuracy of insurance operations. Software bots can replicate human actions to automate high-volume, repetitive tasks. This frees employees to focus on higher-value work, unburdened by dull administrative activities.

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RPA adoption is accelerating across the insurance industry, driven by intense pressure to improve customer experiences and operate more cost-effectively amid rising claims costs and complex regulations.

As an expert in data extraction with over a decade of experience, I‘ve seen firsthand how RPA and AI can optimize insurance processes. In this comprehensive guide, we‘ll explore leading use cases, implementation best practices, and examples of insurers achieving quantifiable results with intelligent automation.

The RPA Opportunity for Insurance

Insurance involves numerous data-intensive, rules-based processes ripe for automation. Policy administration, underwriting, claims, customer service, and compliance all include repetitive manual work that bots can take over.

Insurance processes with high RPA automation potential – Source: McKinsey

McKinsey estimates that insurance could automate 25% of current processes using RPA, AI, and other technologies. This represents a massive productivity opportunity.

By handling repetitive tasks at scale with speed and consistency unattainable by human workers, RPA allows insurers to:

Reduce operational costs
Improve efficiency
Refocus staff on value-added work
Boost customer and employee satisfaction
Ensure compliance with regulations

Leading RPA platform provider UiPath analyzed common insurance processes and found automation could save:

19% of time where human expertise is currently required
34% of employee time spent on data processing
23% of time spent on stakeholder interactions

Next, let‘s explore the top use cases for RPA software bots at insurance firms.

Top 5 RPA Use Cases for Insurance

1. Claims Registration, Processing & Fraud Detection

Claims processing is hugely labor-intensive, often requiring manual gathering of data from various sources like police reports, medical records, photos of damage, etc. Humans must painstakingly extract data from documents, cross-reference against policies, enter into systems, and check for fraudulent claims.

RPA bots shine for these rules-based administrative tasks:

Information extraction – Automatically collect data from forms, emails, images and other documents using OCR and AI.
Data integration – Merge claim data from disparate sources into a unified view.
Systems population – Feed collected data into claims management and other backend systems.
Fraud flagging – Identify patterns indicative of fraudulent claims using algorithms.

This can reduce workload by 80% and cut claims processing time in half, per WorkFusion. Staff get freed up to handle complex claims and customer inquiries.

2. Underwriting & Pricing

Insurance underwriters collect data on applicants, evaluate risks, and determine appropriate premium pricing. This entails significant manual administrative work gathering documents, entering data, and analyzingrisk models.

RPA can take over the mundane underwriting tasks:

Data collection – Compile applicant information from various external and internal sources.
Data entry – Populate required fields in underwriting systems.
Loss analysis – Assess historical loss runs and patterns.
Pricing analysis – Apply algorithms to claims data to suggest optimal pricing.

This allows underwriters to focus their expertise on higher-level decision making and complex cases. RPA also ensures underwriting guidelines get applied consistently across applicants.

3. Policy Administration & Servicing

Policy administration involves high-volume repetitive tasks like quotes, billing, renewals, endorsements, cancellations, payments, and reporting. RPA excels at automating these transactional processes to boost efficiency.

Bots can also handle policyholder data validation, changes, inquiries, and servicing – freeing up staff for value-added interactions.

4. Regulatory Compliance

Insurers operate in a highly regulated environment requiring massive amounts of compliance reporting and documentation.

RPA helps automate:

Name screening – Check applicant names against watch lists to catch banned entities.
Customer validation – Verify identities and related information to combat fraud and money laundering.
Compliance reporting – Generate required compliance reports and filings.
Audit support – Maintain detailed audit trails across systems.

This reduces compliance risks and frees up staff currently bogged down with manual processes.

5. Responding to Queries

Customer and employee queries via calls, emails, chats, or self-service portals often include frequently asked questions. RPA bots can be programmed to understand common inquiries and automatically respond with answers.

For example, a bot could handle questions like:

What is my policy coverage amount?
When is my next payment due?
How do I file a claim?

Only unique and complex queries get routed to human agents. This dramatically speeds response times and improves satisfaction.

15 RPA Case Studies from Insurance Leaders

Now let‘s look at real-world examples of insurers deploying RPA to achieve tangible benefits:

Company	Business Function	Use Case	Results
Health insurer	Operations	Member enrollment Claims auditing	-60% effort 30% fewer errors
Specialty insurer	Underwriting	Data entry Risk evaluation	20,000 hours saved 15% faster underwriting
multiline insurer	Claims	FNOL intake Settlements	57% faster intake 44% faster settlements
Global life insurer	New business	Application processing	2 days faster 15 FTE capacity gain
Top 5 U.S. health insurer	Customer service	Call handling	$2.3 million saved 25% faster service
Leading reinsurer	Data operations	Reporting Reconciliation	80% effort reduction 99% accuracy
Global P&C insurer	Finance	Accounting Payments	45% cost reduction Accelerated close
Australian insurer	Policy servicing	Renewals Customer data	20,000 hours saved 98% auto-renewal
Major U.S. P&C insurer	Claims	Adjusting Estimates	30% faster estimates 15% higher auto-settlement
Multinational life insurer	Underwriting	Risk evaluation Policy issue	20% cost reduction 2 days faster issue
Top 10 U.S. auto insurer	Claims	First notice of loss Evidence gathering	50% faster FNOL 30% less required oversight
Midsize U.S. life insurer	New business	Application data extraction Medical records ingestion	60% faster underwriting 99.7% data accuracy
South African life insurer	Operations	Data migration Report generation	720 hours saved 90% faster SLA compliance
Global specialty insurer	Finance	Intercompany accounting Expense tracking	$140,000 saved 3 days faster close
Leading U.S. P&C insurer	Customer service	Payment processing Coverage questions	20% less call handle time 15% increase in online adoption

List of insurance companies achieving quantifiable benefits from RPA implementations

These real-world examples showcase RPA delivering significant productivity gains, cost reduction, and customer experience improvements across diverse insurance processes and business functions.

The Technology Powering Insurance RPA

Leading RPA platforms like UiPath, Automation Anywhere, and Blue Prism combine sophisticated automation capabilities:

Robust process mapping – Model complex business processes for bots to automate.
Integration adaptors – Seamlessly connect to insurance core systems like policy admin and claims.
OCR & AI skills – Extract data from documents using advanced optics and natural language processing.
Control room – Central interface to monitor and manage all bots enterprise-wide.
Analytics – Track KPIs like cycles times, TCO savings, capacity gained.

These enable insurers to start small with attended bots assisting employees, then scale up to unattended automation running 24/7.

RPA also interplays powerfully with other AI-driven insurance technologies:

Process mining maps current processes to identity automation opportunities.
Document processing classifies unstructured data using computer vision and NLP.
Chatbots handle customer inquiries at scale.

I‘ve seen firsthand working with insurers how combining RPA with AI unlocks immense productivity gains and improved experiences.

Quantifying the Insurance RPA Opportunity

Just how big is the opportunity for intelligent automation across insurance? Studies benchmark the potential:

McKinsey estimates insurers could automate 25% of operations by 2025 using RPA, AI, and advanced analytics.
More specifically, they found automating front and mid-office processes could reduce insurance labor costs 15-25%.

BCG sees automation generating over $15B in annual cost savings for insurers if widely adopted.
Forrester predicts RPA adoption growing at 20% CAGR, with insurance among the top investing industries.

As an expert in data extraction and analytics, I‘m confident these projections underestimate the full transformative potential of hyperautomation for insurance.

Best Practices for Insurance RPA Success

Based on my experience, here are best practices insurance firms should follow to maximize the benefits of RPA:

Start small, scale fast – Prove value with contained pilots, then rapidly expand to other processes.
Focus on enabling staff, not replacing them – Automate repetitive tasks so employees can focus on judgment-intensive work.
Develop Centers of Excellence – Concentrate RPA expertise for training, support, and oversight.
Leverage process mining – Analyze processes empirically to pinpoint automation opportunities.
Monitor KPIs – Continuously track progress against cost, efficiency, capacity and experience goals.
Communicate, train, involve – Change management and capability building is critical to user adoption. Employees should be active partners in designing automations.

Following these recommendations will lead to a smoother, more successful RPA journey – and faster realization of benefits.

Business Case Example: Automated Claims Processing

As an example, let‘s analyze a business case for automating claims processing at a midsize insurer:

Current Process: 50 FTEs spend 6 hours per claim gathering information, entering data, calculating settlements. $50/hr loaded cost per FTE.
RPA Solution: Attended bots assist workers, performing 40% of tasks. Software bot fully automates 30% of claims once stabilized.
Benefits: $1.2 million per year in labor cost avoidance. Claims processing capacity increased 15%. Higher staff productivity and satisfaction.
Costs: $200,000 upfront software license cost. $100,000 first year implementation services. $50,000 annual maintenance fees.
ROI: 133% return on investment in Year 1, payback in 9 months.

This illustrates how a focused RPA initiative can deliver significant hard dollar ROI along with productivity and experience improvements. The returns often fund expansion into further use cases.

Take the Next Step with Automation

Intelligent automation presents immense potential for insurance companies to reduce costs, gain efficiency, and improve both employee and customer experiences.

The use cases and examples here reveal real results insurers are already achieving with RPA, AI, and related technologies. To dig deeper into automation opportunities for your specific business challenges, schedule a personalized consultation with our team.

We‘re happy to provide tailored recommendations and RPA vendor matching based on your operations, systems, goals and constraints. RPA projects often show payback in months with the right focus and approach.

Now is the time to capture the benefits of hyperautomation that leading insurers are already realizing. We‘re here to help guide your automation journey.