Claims automation is changing how insurers operate. It cuts costs, improves speed, and delivers better customer experiences. Rather than being a future goal, it’s now a competitive standard for better customer service and satisfaction. 

For a deeper dive into transformation strategies, explore insurance claims automation. This article answers one key question: what is it, really?

Insurance is built on processes. Historically, that meant paper files, call centers, and manual handoffs along each step of the way, no matter what function you were working in (underwriting, claims, etc.). Automation eliminates a lot of that manual work, making insurance more time efficient and more error-free.

In insurance, automation refers to the use of digital tools and intelligent systems to complete routine tasks with little or no human intervention. It spans every core function:

• Underwriting: Rule-based pricing, instant quote generation, and real-time data enrichment

• Policy administration: Self-service changes, automated billing, and system-triggered policy actions

• Claims: Streamlined workflows that replace routine human review of non-complex cases with AI and business rules

That’s why artificial intelligence in insurance sector strategies often begin with automation. It provides the infrastructure for faster, smarter, and more scalable operations.

Within that broader trend, claims automation is where results make a huge difference for both insurers and customers alike. According to Mckinsey, one insurer was able to improve the accuracy of claims routing by 30%, and reduce customer complaints by 65%.

Claims automation is the use of software, rules engines, and AI to manage the full claims lifecycle from first notice of loss to payout. It reduces manual effort and improves accuracy.

Instead of forms, phone calls, and delays, automated systems handle:

• FNOL intake via chatbot or mobile

• Real-time validation of coverage and policy details

• Auto-routing based on claim type, severity, or risk

• Low-risk auto-approvals with instant disbursement
• Event-driven triggers that keep workflows moving

For carriers, the benefits are operational. Costs drop, resolution times shrink, and accuracy improves. For customers, it’s a better experience that often leads to faster payout. They experience less back-and-forth with claims reps, more transparency, and faster outcomes.

That’s why artificial intelligence insurance companies prioritize claims automation. According to BCG, by applying generative AI in things like damage assessment, fraud detection, claims processing, and data-driven insights, insurers could cut loss adjustment expenses by 20% to 30%, and see a 3% to 4% reduction in claims payouts. 

EIS supports these outcomes through an event-driven architecture that enables straight-through processing.

Claims processing covers every step from incident to closure. It includes:

1. First Notice of Loss (FNOL)

2. Document collection and verification

3. Claim review and investigation

4. Decision or negotiation

5. Payment and settlement

Automation reshapes this flow. Instead of isolated tasks, each step becomes part of a connected, intelligent system.

• A chatbot captures FNOL, pre-fills forms, and triggers next steps

• Uploaded images are scanned by AI for damage estimates

• NLP tools can classify and route the claim based on urgency or complexity

• Business rules validate coverage and flag issues

• Payment engines release funds instantly when thresholds are met

Claims automation turns manual review into event-driven decisioning. It gives carriers the ability to scale with confidence and adapt workflows to changing risk or product lines.

For this example, we’ll use a typical auto claim.

After an accident, a customer submits photos of damage through a mobile app. A computer vision tool identifies the damage, estimates cost, and checks it against policy limits. The system verifies coverage, screens for fraud, and routes it to a human for review and approval. A process that once took days or weeks can now potentially be done in a matter of hours or less. That’s the power of the best insurance claims AI.

Or consider a home insurance triage situation.

An NLP engine reads an email describing a water leak. It extracts key data points, classifies the claim, and routes it to the right team based on policy, geography, and severity. It eliminates the human burden of all of this data gathering and data entry, which is what sets apart the best insurance claims management software.

All this depends on the right infrastructure: open, modular, and event-driven.

With EIS OneSuite, insurers can:

• Configure new workflows with low-code tools

• Embed AI directly into claims workflows where appropriate

• Trigger subsequent tasks automatically as claims progress

• Integrate with policy, billing, and other systems for seamless updates and transparency

The architecture of OneSuite powers intelligent, agile, customer-centric claims operations without heavy IT overhead. And because it’s built with on MACH-based architecture and reduces technical debt, insurers can go live faster, scale quickly, and adapt to whatever comes next.

Ready to implement smart automation in your claims operation? Explore the full potential of modern insurance claims automation with our industry-leading platform.

FAQ: What is claims automation?

Q: How can claims automation improve the claims process for insurers?

A: Claims automation streamlines the claims process by reducing manual tasks and increasing efficiency. Key benefits include:

• Faster claim processing times
• Improved accuracy and reduced errors
• Enhanced customer satisfaction through quicker payouts
• Better data analytics for informed decision-making

Q: What are the common technologies used in claims automation?

A: Claims automation leverages several technologies to enhance efficiency:

• Artificial Intelligence (AI) for decision-making
• Machine Learning (ML) for predictive analytics
• Robotic Process Automation (RPA) for repetitive task handling
• Cloud computing for scalability and accessibility 

Q: What types of claims can be automated?

A: Various types of claims can be automated, including:

• Auto insurance claims
• Benefits insurance claims
• Property insurance claims
• Liability claims

Q: How does claims automation affect customer experience?

A: Claims automation significantly enhances customer experience by:

• Providing instant updates and notifications
• Reducing wait times for claim resolution
• Offering self-service options for claim submissions
• Facilitating easy communication through chatbots

Q: What are the challenges of implementing claims automation?

A: While claims automation offers many benefits, challenges include: 

• Integration with existing legacy systems
• Data security and privacy concerns
• Employee training and adaptation to new processes
• Initial costs of technology investment

Q: What metrics should insurers track to measure the success of claims automation?

A: Insurers should monitor key metrics to gauge automation effectiveness:

• Claim processing time
• Claims accuracy rate
• Customer satisfaction scores
• Cost savings achieved through automation

Q: How can claims automation help reduce fraud?

A: Claims automation aids in fraud detection by:

• Utilizing AI algorithms to identify suspicious patterns
• Performing real-time data analysis during claims processing
• Integrating cross-reference capabilities with external databases
• Generating alerts for potential fraudulent activities

Q: What is the future of claims automation in the insurance industry?

A: The future of claims automation looks promising, with trends including: 

• Increased use of AI and ML for smarter decision-making
• Greater personalization of customer interactions
• Expansion into new types of insurance products
• Enhanced collaboration between insurers and technology providers