Believe it or not, insurance claims don’t have to drag on for months and months. Modern core systems can speed up every stage of the process from first notice to final payout. Here’s how:

(For a broader look at end-to-end transformation, explore insurance claims automation. This post dives into one crucial piece: how to make it real.)

Insurance claims generally move through four stages:

1. First Notice of Loss (FNOL): The policyholder reports an incident.

2. Claim Review: The insurer checks policy coverage and gathers initial documentation.

3. Evaluation & Investigation: Damages are assessed, liability is determined, and fraud checks are triggered.

4. Settlement: The claim is approved, negotiated, or denied. Payment is issued to the appropriate parties.

So, how to automate insurance claims across this cycle?

• FNOL: Mobile apps and chatbots capture key details instantly, and walk the insured through the submission process. Automation ensures no critical data is missed, and feeds the data into the rest of the claims workflow.

• Claim Review: Rules engines verify coverage, flag missing data or documents (if any), and launch further workflow routing to adjusters or automatic approval/denial if the right data points are met and verified.

• Evaluation & Investigation: AI models estimate damage, flag suspicious activity, and prioritize high-value or high-risk cases to be reviewed by humans. Even though a human may get involved at this stage, not having to involve human labor on routine claims and prioritizing it for the higher-need claims means everyones claims get closed faster.

• Settlement: Smart contracts and digital disbursement platforms issue payments faster, and manual effort drops.

Automation doesn’t replace adjusters, but elevates them. Tedious tasks get offloaded so they can focus on complex cases and better customer service.

First Notice of Loss used to mean call centers, mailing documents, fax machines, wait times, and missing paperwork. Now, customers can file a claim in minutes, anywhere and anytime.

Here’s what powers that shift:

• Chatbots: Available 24/7 to collect data need to get a claim started and processed.

• Mobile apps: Let users upload images, voice notes, documents, and geolocation data.

• Telematics: Automatically trigger FNOL after a car accident via sensors, meaning an open claim can be waiting for a customer with some data pre-filled, rather than a customer having to do it all themselves.

• Automated intake forms: These guide users step-by-step through claim submissions, reducing errors and omissions.

Faster FNOL that’s also paried with an intelligent claims management system also means shorter claim cycles. According to McKinsey, intelligent case management systems that kick in immediately after FNOL make claim resolution faster. “Automated processes now cut down manual steps that once slowed claims, allowing customers to schedule repairs directly through digital platforms,” they say. “The impact is clear – more efficient claims handling leads to quicker settlements and improved customer satisfaction.”

With EIS, carriers can capture FNOL through digital channels, then route the claim automatically into a preconfigured workflow. No delays, no swivel-chair handoffs into a pile of paperwork that’ll sit for weeks—just straight-through processing that matches the claim type and complexity.

That’s the first major win in learning how to automate insurance claims online.

Absolutely. AI is already reshaping how insurers detect fraud, route workflows, and predict claim costs.

Here’s where AI claims capabilities shine:

• Natural Language Processing (NLP): Extracts context and claim detailes from free-form inputs like emails and voice notes.

• Computer Vision: Interprets photos for property or auto damage assessments.

• Predictive Analytics: Forecasts claim severity, expected payout, and risk of litigation for individual claims or predicted claims, like a surge of claims related to a natural disaster.

In benefits too, AI in group benefits claims processing is accelerating payment cycles, reducing errors, and automating claim review—all while cutting costs.

A recent Accenture study found that 65% of insurers plan to invest more than $10 million in claims tech, with AI playing a lead role in fraud detection and triage.

Within EIS OneSuite, AI can integrate directly into claims logic. For example, fraud analytics modules can score incoming claims in real time, using behavioral and historical data to flag anomalies before they hit the adjuster queue. Routing decisions can be optimized automatically, ensuring simple claims move quickly, while complex cases get the right human oversight.

Claims adjusters once juggled paper files and desktop apps. Not anymore.

Modern claims adjusters rely on integrated platforms built for speed and flexibility in the claims process. Examples include:

• Xactimate: For property insurance claim estimates.

• CCC Intelligent Solutions: For auto damage and AI-powered photo analysis.

• Snapsheet and Mitchell: Tools for digital claims handling and mobile inspections.

• EIS OneSuite & EIS ClaimSmart: A cloud-native, modular platform with solutions that power end-to-end claims automation, from FNOL to resolution — and that integrate seamlessly and natively with the rest of the insurance lifecycle, from underwriting to billing and everything in between.

The best adjuster tools today are:

• Cloud-based: Accessible from anywhere.

• AI-enabled: Handle routine decisions automatically.

• Low-code configurable: Let insurers adapt workflows without custom development work.
• On a unified, full-suite platform: Even if starting with a claims transformation, smart, forward-thinking insurers will look for platforms that can natively integrate all aspects of the insurance life cycle onto a single platform, like EIS OneSuite. This gives them the advantage of evolving in a future-forward way, and helps them get rid of tech debt over time.

EIS ClaimCore supports event-driven processes, so the moment a condition is met—say, documentation is uploaded or an estimate approved—the next task is triggered automatically. Adjusters don’t manage queues; they manage outcomes.

And because it’s part of a unified platform, claims data can drive real-time updates across policy, billing, and customer engagement layers. This creates a very context-aware service for customers—and eliminates the silos that slow down traditional claims processes.

So… How is AI used in insurance claims? Each solution is different, but AI can play a crucial role in several aspects of improving claims processing, including:

• Predictive Analytics: AI anticipates claim outcomes based on historical data.
• Image Recognition: Machine learning evaluates accident photos to estimate repair costs.
• Natural Language Processing (NLP): AI reads and extracts data from documents, eliminating manual entry.
• Fraud Detection: AI detects anomalies in claims data, preventing fraudulent payouts.

Automated Decision-Making: AI-based algorithms assess claims and make real-time payout recommendations.

Looking to streamline and modernize your claims operations? Discover how EIS helps insurers automate the entire claims lifecycle—from FNOL to resolution.