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Automated Claims Processing
The Key to Faster, Smarter Insurance Payouts
Filing an insurance claim shouldn’t feel like stepping into a black hole of endless paperwork, slow responses, and frustrating delays. But for many policyholders and insurers, that’s exactly what happens.
The traditional claims process is riddled with inefficiencies, outdated manual workflows, and the ever-present risk of human error. This can easily lead to poor customer experiences, increased costs, and unnecessary claims leakage. In fact, 68% of complaints received by the National Association of Insurance Commissioners stem from claims issues.
That’s where claims processing automation comes in, handling and accelerating tasks that once required manual intervention. Examples include fraud detection, policy verification, damage assessments, and payments — all completed with greater speed and precision. And today’s ambitious insurers aren’t just using insurance claims automation to speed things up. They’re rethinking claims from the ground up with AI, machine learning, and real-time data integration.
When insurance industry veterans ask, “What is automated claims processing?”, we can honestly say it’s not about removing the human touch from the process. It’s about getting rid of friction that slows down resolutions. An automation-powered claims system can cut insurers’ cost per claim by 30%, reduce fraud-related losses, and improve customer satisfaction scores.
By adopting automated claims processing, insurers can improve efficiency and reduce costs while also meeting the growing demand for seamless, digital-first experiences. Insurers using claims automation aren’t just keeping pace with industry expectations. They’re setting the standard for faster, fairer, and more accurate claims resolutions.
How do you automate claims processing?
The shift from manual claims handling to automation isn’t just about digitizing forms or speeding up approvals. It’s about transforming the entire lifecycle of a claim with intelligent workflows and real-time decision-making.
What is the automation process in insurance?
To give a more exact answer to this question: It’s the systematic use of technology to eliminate manual bottlenecks, optimize adjudication, and improve accuracy across every touchpoint of a claim’s journey. This process typically includes:
- Intelligent First Notice of Loss (FNOL): AI-driven intake powered by chatbots, voice recognition, advanced sensor technologies (e.g., telematics), and more.
- Automated Fraud Detection: AI models analyze historical claims data and external data sources for real-time detection of claim inconsistencies or major fraud risk factors.
- Straight-Through Processing (STP): For simpler, more straightforward claims, automation can handle assessments, approvals, and payments without human intervention.
- Dynamic Claims Assignment: ML-driven triage routes complex claims to the best adjusters based on skill set, location, or workload capacity.
- Integrated Vendor Management: Third-party repair shops, medical providers, and rental services are seamlessly looped into claims workflows through API integrations.
The role of process automation software in claims
Broadly speaking, process automation software refers to any technology that automates repeatable tasks, streamlines workflows, and reduces reliance on manual processing. But in claims automation, it does much more than expedite: It also improves accuracy, helps prevent fraud, and strengthens customer engagement.
EIS solutions like ClaimCore® and ClaimSmart™ exemplify how process automation software drives transformation.
- ClaimCore allows insurers to comprehensively monitor, customize, and control the claims lifecycle for maximum efficiency by crafting seamless automated workflows.
- The ClaimGuard™ module of ClaimSmart uses a proprietary AI-powered risk scoring model to improve fraud detection.
- ClaimPulse™, the other half of ClaimSmart, uses intelligent FNOL to quickly ingest claims data and accordingly personalize the customer journey. It also delivers real-time updates to customers on claim status.
By integrating these capabilities into a cloud-native, API-first architecture, insurers ensure data fluidity across claims, billing, and policy administration.
What is an example of process automation in claims?
Automation ensures that an auto insurance claim follows the appropriate chain of events following an accident:
- Immediate FNOL Trigger: A vehicle’s telematics sensors detect an impact and instantly generate an FNOL in the insurer’s core system.
- AI-Driven Data Collection: A chatbot guides the policyholder through a structured intake, asking only relevant, personalized questions based on policy details.
- Seamless Claims Routing: If the claim is straightforward, it moves to straight-through processing for automated approval or denial. If complex (or potentially) fraudulent, it’s routed to an adjuster specializing in tougher cases.
- Instant Vendor Engagement: API integrations can deliver notifications to towing services, repair shops, or medical providers, based on the severity of the incident. This allows automatic authorizations for service estimates and helps arrange treatment for any injuries to the policyholder.
- Real-Time Payout Processing: Once all claim conditions are met, the system digitally initiates payment processing, reducing payout cycles from weeks to days — or sometimes even hours.
This isn’t just a hypothetical scenario. This is how insurers leveraging EIS solutions are redefining claims automation in today’s insurance industry.
What is the claims processing workflow?
A well-executed claims processing workflow is more than just a checklist of tasks. It’s a dynamic ecosystem powered by smart tech, strategic orchestration, and IT process automation. Think of it as behind-the-scenes choreography, transforming a jumbled pile of data and documents into a fast, fair, and frictionless customer experience.
What’s claims intelligence?
At its most efficient, the claims workflow doesn’t just handle claims — it learns from them, adapts to them, and improves over time.
That’s where claims intelligence enters the picture. It’s the brain behind the operation: using data analytics, AI, and machine learning to continually analyze and optimize every stage of the claims process.
By combining historical data with real-time insights and predictive modeling, claims intelligence helps insurers make faster, smarter decisions. This can mean spotting a suspicious claim that a human adjuster might not quickly recognize, prioritizing high-impact tasks, or getting payments out the door in record time.
When paired with robust IT process automation, claims intelligence becomes even more powerful. Consider it this way: automation handles the “what,” while intelligence drives the “why” and “when.” Together, they allow insurers to:
Flag anomalies and reduce fraud with advanced risk scoring.
Refine workflows continuously using real-time data.
Auto-prioritize tasks and assign claims based on complexity and capacity.
Minimize manual touchpoints without sacrificing accuracy or empathy.
In short, claims intelligence takes the guesswork out of claims processing. It enables insurers to move from reactive to proactive — from slow and siloed to seamless and strategic.
How can AI be used in claims processing?
If automation is the engine of modern insurance operations, artificial intelligence is the GPS — constantly recalculating, optimizing, and steering claims toward the most efficient resolution.
How is AI used in claims management?
Here’s the short answer: Everywhere it makes sense. Increasingly, that can mean places where AI may not have previously fit. But with the support of a cloud-native core platform like EIS OneSuite, the technology can be more versatile than ever.
Today’s insurers can embrace claims processing using AI to transform slow, manual workflows into real-time decision-making powerhouses. From intake to investigation to payout, AI claims solutions are enabling smarter, faster, and more consistent outcomes.
Here are some of the practical ways this can play out in the modern insurance industry:
- Intelligent Document Ingestion: AI scans, reads, and understands unstructured data from accident reports, medical records, and repair estimates — so adjusters don’t have to.
- Predictive Analytics for Claims Routing: Machine learning models prioritize incoming claims based on severity, complexity, and historical patterns. As such, adjusters and other claims team members can focus their attention where it’s needed the most.
- Natural Language Processing (NLP): Chatbots and virtual assistants use NLP to guide customers through the FNOL phase. This reduces call center volume and helps improve claims data accuracy at the point of entry.
- Real-Time Fraud Detection: AI and ML are rewriting the rules of risk detection. Advanced algorithms can identify anomalies and suspicious behaviors faster than claims team members ever could. In turn, human adjusters can better apply their expertise and determine the fraudulence (or genuineness) of a claim without sacrificing efficiency in the overall claims lifecycle.
- Proactive Communication: AI-driven systems can generate personalized updates for policyholders while a claim gets processed. This helps customers know exactly what’s going on at all times, in real time. They don’t have to feel like the time in between filing a claim and learning about its resolution is a “black box” experience.
The beauty of claims AI is clear in terms of its speed or efficiency — but it’s just as important because of its adaptability. As these systems learn from every processed claim, they continuously refine their models, helping insurers bring truly intelligent automation into the claims processing lifecycle.
The results? Claims teams work smarter. Customers get answers faster. And insurers gain a competitive edge that’s powered by reliably data-driven insights, not guesswork.
Claims automation case study
Let’s look at some real-world claims automation processing examples that show the transformative impact the technology can have for insurers:
Improving claims efficiency at scale: Tokio Marine & Nichido Fire
Inefficient claims processes that lack automation can slow down claims approvals, drive up call center costs, and frustrate customers.
Tokio Marine & Nichido Fire, a leading Japanese P&C insurer, knew this firsthand and wanted to make a major change. Adopting EIS ClaimSmart allowed the insurer to automate their FNOL process and enable customers to submit claims digitally 24/7. The results speak for themselves:
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- Millions saved each year through effective automation and less need for manual intervention.
- 20% reduction in call center volume, as customers could track claims in real time.
Reducing costs while boosting customer experiences
Without automated claims processing, insurers often can’t process claims digitally and lack reliable, efficient data collection. The burden this puts on agents (due to the frequent need for multiple follow-ups with policyholders) slows down claims and makes errors more likely. This can raise costs, including loss-adjustment expenses.
All the while, customers can’t stand how slow everything is.
A mutual insurance company serving 15 US states tackled these issues by adopting claims processing automation via EIS ClaimSmart. The solution’s ClaimPulse module allowed them to enable digital FNOL, streamline claims assignments, and equip claims workflows with AI-driven decision-making. Customers could also now monitor and manage their claims digitally.
This led to critical bottom-line benefits:
- Lower LAE, based on the elimination of redundant manual steps.
- Faster claims processing, leading to higher customer satisfaction.
Minimizing claims leakage
Whether due to inefficiency, fraud, or manual error, claims leakage accounts for anywhere from 20% to 30% of all claim payouts. This causes the insurance industry to lose $30 billion each year.
Outdated claims processing systems with little or no automation contribute to the danger of claims leakage. Rules-based fraud detection systems can completely miss new types of fraud that their engineers didn’t know about, or create false positives that waste fraud investigators’ time.
Meanwhile, these old systems also contribute to subrogation failures and salvage losses. Respectively, carriers can miss chances to recover costs from at-fault third parties and rack up unnecessary costs by not assessing damaged property value fast enough.
Automation-driven EIS solutions including ClaimSmart and ClaimCore can help insurers turn leakage around. For example, they enabled Tokio Marine to use ML-powered fraud detection from ClaimGuard and identify new fraud tactics before they escalate. The insurer enjoyed the following benefits:
- A 5x increase in fraudulent claim detection (and a major drop in false positives).
- A 40% reduction in fraud-related costs.
Meanwhile, the event-driven architecture of ClaimCore® battles other types of leakage. It can automatically detect subrogation-worthy claims, ensuring recovery actions are triggered early to maximize financial recoupment
The future of claims processing is here
Claims processing automation brings speed, accuracy, and intelligence to one of insurance’s key operational areas. But it’s not just about pace or efficiency. It means delivering seamless, transparent claims experiences for customers while protecting insurers’ bottom lines.
When deployed with ClaimCore, EIS OneSuite provides a firm foundation for modern claims automation. ClaimCore streamlines workflows, automates FNOL, and enhances fraud detection.
Meanwhile, ClaimSmart takes things further. ClaimGuard prevents fraud with ML-driven risk scoring, and ClaimPulse streamlines the claims lifecycle while keeping policyholders informed in real time.
Ambitious insurers who adopt digital-first claims processing automation are setting themselves up for the industry’s evolution ahead of time. EIS can help you get there.