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The Ultimate 2025 Guide to Claims Automation in Insurance
Amir Prodensky
CEO
Nov 21, 2025
18 min read
Learn what really works (and what doesn’t) in modern claims automation.
I still remember the first time I filed an insurance claim.
It took weeks of phone calls, emails, and waiting. Fast-forward to today, and that kind of process feels ancient. Insurance claims automation is completely changing the game.
At its core, it’s about using smart technology to handle claims faster, more accurately, and with far less manual work. Instead of people chasing paperwork and typing the same details again and again, automation takes care of those repetitive steps. Instantly.
And this shift couldn’t come at a better time. Claims are increasing, customers expect real-time answers, and insurers are under pressure to do more with less. The old way simply can’t keep up.
That’s where automation steps in. It doesn’t just speed things up. It cuts errors, reduces costs, and makes the customer experience smoother from start to finish. Take Strada, for example. It’s an AI-powered phone agent platform helping insurers transform their front-line operations. It engages customers naturally, handles routine calls automatically, and frees up human teams to focus on high-value tasks.
In this guide, you’ll get clear, actionable insights into how claims automation really works, why it matters now, and how to make it deliver measurable results for your business.
Ready to see how automation is reshaping insurance? Let’s dive in.
What is claims automation, and how does it work?
Claims automation insurance is all about using technology to replace manual, repetitive tasks in the claims process.
Instead of people keying in data, sending endless emails, or following up by phone, smart systems handle most of the work.
This is often powered by artificial intelligence (AI), machine learning (ML), and/or robotic process automation (RPA), tools that make insurance claims processing automation faster and more accurate.
Here’s how a fully automated claims lifecycle typically works:
Intake → the process starts when a customer reports a claim by phone, SMS, app, or web form.
Data extraction → tools like optical character recognition (OCR) and intelligent document processing (IDP) pull key details from documents, photos, or emails.
Validation → AI compares data against policy details, fraud databases, or repair estimates.
Adjudication → rules engines and ML models decide claim outcomes or flag exceptions for human review.
Settlement → payments are processed automatically through integrated finance systems.
These systems only work well when integrated with core insurance platforms and workflows such as policy administration, CRM, billing, and analytics. Integration ensures data flows seamlessly, keeping every department in sync.
Several platforms lead the way in insurance claims processing automation. Each offers unique tools for automation, compliance, and scalability.
To see how these tools stack up, let’s take a quick look at some of the most popular claims automation platforms and what makes each one stand out.
Platform | Core strengths | Unique features |
Strada | FNOL & communication | AI voice + SMS agents, 24/7 intake |
Conduent | Enterprise automation | Scalable claims processing |
Damco | End-to-end claims | Cloud-based, customizable modules |
Kognitos | RPA + natural language | Human-readable automation scripts |
Appian Connected Claims | Workflow orchestration | Low-code integration, analytics dashboard |
Strada stands out for its AI-powered voice and SMS agents. It handles 24/7 FNOL, capturing claim details instantly and reducing phone call workloads, so claims move faster from the first interaction.
So, claims automation isn’t just about saving time. It’s about transforming how insurance feels for everyone involved. When AI, RPA, and intelligent systems work together, you cut delays, reduce human error, and create smoother experiences for policyholders.
So what happens when everything’s done manually? What are the downsides of that approach? Let’s take a closer look.
What challenges does manual claims processing have?
Manual claims processing might feel comfortable, but it hides a maze of inefficiencies. If your team still relies on spreadsheets, paper forms, or endless phone calls, you’re likely facing some major roadblocks.
Before exploring automation, it’s key to understand why manual methods struggle to keep up.
Here are the most common pain points:
Slow resolutions → claims can take days or weeks as each manual handoff adds delay and risk.
Frequent errors → typos, missing details, and duplicate entries lead to costly rework and compliance issues.
High costs → more staff are needed for repetitive tasks, leaving little room for growth.
Disconnected systems → when data is scattered across policy, billing, and CRM tools, teams spend time searching instead of solving.
These challenges don’t just frustrate insurers. They slow down everyone involved, from customers waiting for payouts to teams managing backlogs. Manual processes also make it harder to stay compliant or detect fraud, since verification and pattern detection take too long.
Scalability is another limit. As volumes grow, manual work simply can’t keep up. That’s why many insurers now turn to Strada’s AI-powered agents, which capture claim details via natural voice or SMS and trigger automated workflows instantly — cutting delays, errors, and costs.
Next, let’s take a look at the main benefits automation brings to the insurance industry.
Why is claims automation vital for insurers today?
Insurance is changing fast. Claim volumes keep rising, driven by aging populations, chronic health conditions, and growing policyholder bases.
At the same time, customers expect faster responses, full transparency, and simple digital experiences. Manual claim handling just can’t keep up anymore.
Operational pressures are piling on. Insurers face:
Higher costs from labor and administration
Tighter regulations and compliance demands
Customer pressure for instant answers and real-time updates
That’s where insurance claims automation makes all the difference. By automating repetitive claim tasks, you cut costs and process claims faster.
AI-powered validation and data checks improve accuracy and reduce fraud. Automation ensures every claim follows consistent rules, keeping compliance tight and errors low.
The benefits go beyond efficiency. Insurance claim automation helps insurers focus on what matters most: the customer.
Faster settlements build trust. Accurate, transparent communication reduces disputes. Happy customers stay longer, renew policies, and recommend your brand.
Automation also gives insurers a competitive edge. It’s not just about doing things quicker. It's about doing them smarter, at scale, and with reliability regulators can trust.
This is where Strada makes a real impact. Strada’s AI-powered voice and SMS agents handle FNOL calls, policy servicing, and renewals, all autonomously. It engages customers 24/7, capturing accurate information instantly and triggering faster claim initiation.
By reducing manual workloads, Strada helps insurers improve reliability, response times, and customer satisfaction, all while staying compliant.
And automation delivers more than efficiency; it improves accuracy, consistency, and results. That’s exactly what insurers will need in 2025.
So what exactly lies at the core of workflow automation? Let’s break it down.
What key technologies power claims automation?
Behind every fast, accurate, and customer-friendly claim process lies a network of smart technologies.
Insurance claims automation isn’t driven by a single tool. It’s powered by several integrated systems that work together to remove manual effort, speed up decisions, and deliver better outcomes.
Before we dive into the details, here’s a simple diagram to help you visualize how these technologies work together and how each one fits into today’s insurance claims automation ecosystem
Now let’s take a closer look at each one.
AI and Machine Learning
AI and ML learn from past claims to predict outcomes, detect fraud, and guide adjusters.
They spot duplicate or suspicious activity instantly, helping teams focus on high-risk or high-value cases for faster, more accurate settlements.
Optical Character Recognition (OCR) and Intelligent Document Processing (IDP)
OCR turns scanned or handwritten forms into digital data, while IDP extracts and validates key details automatically.
Less manual typing
Faster turnaround
Fewer errors
Easy, searchable access
Robotic Process Automation (RPA)
RPA bots handle repetitive tasks like data entry, verification, and notifications — running nonstop for consistent, reliable workflows.
Natural Language Processing (NLP)
NLP powers chatbots and voice agents that understand and respond to customers 24/7, bridging automation in insurance claims processing and empathy.
Blockchain and IoT
Blockchain ensures transparent, tamper-proof transactions, while IoT devices provide real-time data (from vehicle sensors to smart homes) for faster, verified claims.
Bringing all these technologies together in a real-world solution is where Strada truly shines.
Strada’s AI-powered conversational platform is built specifically for insurance, with pre-trained models that already understand policy language, claim categories, and customer intent. It uses NLP, AI, and automation to handle the critical first steps of claims, especially FNOL.
Through voice and SMS, Strada’s AI agents collect accurate claim information, verify key details, and trigger workflows instantly within the insurer’s system.
And here’s why that matters:
Customers can report claims 24/7 without waiting on hold.
Data is captured correctly the first time, reducing follow-up calls and delays.
Claims move forward immediately, cutting days off the process.
Human agents are freed up to handle sensitive or complex cases.
Strada’s platform doesn’t just make automation smarter, it makes it conversational. By blending technical accuracy with human-like communication, it creates a smoother experience for both insurers and policyholders.
In short, each technology plays a different role in insurance claims automation, but they’re most powerful when they work together. The outcome is simple: faster claims, lower costs, and happier customers who feel heard and supported every step of the way.
Now let’s take a closer look at what you can actually hand over to automation.
What parts of claims processing can be automated?
When you look at the entire claims journey, from first notice to final payout, you’ll see dozens of steps that rely on data, rules, and repetition. That’s exactly where claims automation insurance delivers the biggest impact.
Let’s walk through which parts of the claims process are most ready for automation and how they work together to create a faster, more connected workflow.
Data capture and extraction
Every claim starts with information, often scattered across forms, photos, PDFs, or emails.
Automated data capture tools and OCR extract details like policy numbers, dates, and descriptions instantly. IDP then validates and structures that data so it’s ready for review. No manual typing, no delays.
Strada simplifies one of the most time-consuming steps, the initial claims intake. Its AI-powered voice and SMS agents work 24/7, capturing FNOL details instantly.
The moment a claim is reported, Strada automatically triggers workflows: creating a claim file, notifying adjusters, and sending required documents. No manual intervention needed.
By automating intake, Strada removes delays, reduces errors, and helps customers start their claims journey faster and with less frustration.
Validation and eligibility checks
Once data is captured, automation takes over eligibility checks. Systems like Strada can initiate a workflow that instantly compares claim details against policy coverage, prior claims, and regulatory requirements.
This ensures accuracy and consistency right from the start.
Fraud detection and anomaly flagging
AI models analyze thousands of data points in real time to flag potential fraud. By spotting unusual claim patterns or duplicate data, automation in insurance claims processing helps insurers act early, protecting both customers and the business.
Adjudication and routing
This is where robotic process automation insurance claims really shine. Here’s what it can do in practice:
Auto-approve simple claims → RPA bots handle clear-cut cases instantly.
Route complex cases smartly → the right claims go straight to the right adjusters.
Eliminate delays → routine tasks run in the background 24/7.
Keep workflows predictable → every step follows consistent, rules-based logic.
RPA bots can automatically approve straightforward claims and route more complex cases to human adjusters. Rules-based decisions mean faster resolutions, fewer bottlenecks, and a more predictable workflow.
Customer communication and self-service
Automation isn’t just about speed. It’s about better communication. Chatbots and self-service portals let customers file, track, or update claims anytime. NLP enables friendly, conversational interactions that feel personal while keeping costs low.
Payment processing and settlement
Once a claim is approved, payment workflows can run automatically. Integrated systems calculate amounts, verify banking details, and trigger payments, cutting settlement times from days to minutes.
Reporting and real-time analytics
automation of insurance claims also powers smarter decision-making. Real-time dashboards monitor claim volumes, processing speed, and performance trends, giving insurers a clear picture of efficiency and outcomes.
To make it easier to see where automation delivers the most value, the table below breaks down each step of the claims process, showing how feasible automation is and which tools are typically used.
Claims process step | Automation feasibility | Typical tools & platforms |
Data capture & extraction | Very high | OCR, IDP, AI-based document tools |
Validation & eligibility checks | High | RPA, rule engines, policy databases |
Fraud detection | High | AI/ML models, analytics platforms |
Adjudication & routing | High | RPA, decision engines, workflow tools |
Customer communication | Very high | Chatbots, NLP platforms, Strada |
Payment & settlement | Moderate to high | RPA, ERP, finance automation tools |
Reporting & analytics | High | BI dashboards, data visualization tools |
Automation touches every step of modern claims handling. By combining intelligent tools with platforms like Strada, insurers can process claims faster, reduce workloads, and keep customers informed at every stage.
The result? Fewer delays, fewer errors, and a claims experience that actually builds trust.
So how exactly does automation improve customer interactions? Let’s find out.
How does claims automation improve customer experience?
Filing an insurance claim can be one of the most stressful moments for a customer. There’s uncertainty, paperwork, and a lot of waiting.
Automation in insurance claims makes this process faster, clearer, and far more customer-friendly.
The first big benefit is speed. Automated systems use AI and pre-set workflows to process claims almost instantly. What once took days or weeks can now take hours. Faster resolutions mean customers spend less time worrying and more time getting back to normal.
It also adds transparency. Real-time status updates through digital portals and chatbots keep customers informed at every step. They can log in, check progress, or ask questions anytime, with no more wondering what’s happening behind the scenes.
Accuracy is another big win. With data automatically verified and cross-checked, errors drop dramatically. That translates into fair, consistent payouts and fewer disputes, which strengthens trust between insurers and customers.
Here’s how automation transforms the experience overall:
24/7 access → customers can submit and track claims anytime through online and mobile tools.
Personalized service → integrated analytics tailor updates and recommendations based on individual needs.
Consistent communication → automated systems ensure every customer gets timely, reliable updates.
A standout example is Strada, an AI-powered conversational platform built for insurers. Its voice and SMS agents deliver real-time support with zero hold times, answering FAQs, sharing claim updates, and securely capturing information around the clock.
Strada gives customers control and confidence while freeing human teams to handle more complex tasks.
Automation in insurance claims turns a stressful process into a smooth, transparent, and positive experience, one that builds satisfaction, loyalty, and lasting trust.
The benefits for customers are clear. But every process has its challenges. Let’s look at what you might run into and how to avoid it.
What challenges and limitations should insurers anticipate?
Even though automation of insurance claims brings major advantages, implementing it isn’t always plug-and-play. Insurers stepping into automation need to understand the practical challenges that come with new technology.
With the right planning and mindset, most of these can be managed, but it’s important to go in prepared.
Upfront сosts and training
Automation isn’t free. There’s an initial investment in software, system upgrades, and employee training.
Teams need time to learn how to use new tools and workflows effectively. But, these costs pay off quickly through faster processing, reduced manual work, and better customer satisfaction.
Integration with legacy systems
Many insurers still rely on older systems for policies and claims. Integrating automation tools, AI models, or robotic process automation insurance claims workflows with these legacy platforms can be complex.
It often requires technical support and careful change management to ensure data moves smoothly between systems. In reality, the main challenges usually come down to:
Data silos → key information locked in outdated systems or formats.
Integration gaps → new automation tools don’t “talk” easily with old software.
Change resistance → teams need time and training to trust and adopt new workflows.
Technical debt → custom patches and manual workarounds slow progress.
That said, solutions like Strada make this easier. Strada offers native integrations with leading AMS, CRM platforms, and policy or claims systems.
These ready-made connectors reduce engineering lift, speed up deployment, and minimize disruption to existing workflows.
Data quality and consistency
AI is only as good as the data it learns from. Inconsistent, incomplete, or outdated data can lead to poor decisions and inaccurate automation results.
Before rolling out automation widely, insurers should clean and standardize their data, especially if they’re using AI for claims triage or fraud detection.
Keeping humans in the loop
Not every claim can be automated. Complex or disputed cases still need human judgment and empathy.
The best approach combines automation with oversight, letting technology handle routine tasks while humans focus on nuanced decisions, negotiations, or customer reassurance.
Change management and culture
Automation often changes how teams work. That can lead to resistance if it’s not managed carefully.
Clear communication, proper training, and leadership support are essential to get everyone on board. When people understand automation is there to help, not replace them, adoption grows naturally.
Data privacy and security
Insurers handle highly sensitive information. Any automation partner must meet strict security standards.
Strada makes this a priority through SOC 2 Type 2 compliance and robust data isolation protocols. That ensures every customer interaction, from voice calls to SMS data capture, stays secure and compliant.
Automation comes with challenges, but they’re manageable. With clean data, thoughtful planning, and trusted partners like Strada, insurers can modernize their claims operations confidently and see real results faster.
Next, let’s look at how you can bring automation into your workflow.
How to successfully implement claims automation?
If you’re ready to bring automation into your claims operations, the good news is that success doesn’t require a complete overhaul overnight.
The best implementations start small, focus on measurable wins, and build momentum over time.
Insurance claim processing automation works best when it fits naturally into your existing systems and people’s daily workflows. Here’s a simple roadmap to help you do it right.
Let’s check the details.
#1 Assess your current claims process
Before diving into automation, take a close look at how claims flow through your business today. Map out each step, from intake to settlement, and identify where delays, bottlenecks, or manual tasks slow things down.
Ask questions like: Which tasks are repetitive or prone to human error? Where do customers experience the most friction or delays? What systems already work well, and which need improvement?
This clarity helps you pinpoint automation opportunities that deliver the biggest impact first.
#2 Choose the right technology and partners
Once you know what to automate, select the right tools and partners. Look for solutions that integrate easily with your existing systems and support long-term scalability.
Platforms like Appian, Kognitos, Conduent, and Damco offer strong foundations for process automation, analytics, and compliance tracking.
When evaluating technology, consider:
Ease of integration with your existing claims or policy systems
Low-code customization to adjust workflows without deep engineering
Proven industry experience in insurance and regulatory environments
Getting started with Strada doesn’t require a big IT project — it’s designed to plug right into your existing insurance operations. Here’s a quick step-by-step guide to help you launch fast and see results from day one:
Identify your use cases
Start with the highest-impact areas like renewals, claims intake (FNOL), or policy servicing. These are proven Strada workflows that deliver immediate ROI by cutting call times and reducing manual data entry.
Set up your voice AI agent
Strada’s insurance-trained conversational AI can handle inbound and outbound calls. Configure your agent to greet customers, collect key details, verify policy data, and trigger next steps automatically — all without coding.
Connect your systems
Link Strada to your CRM, AMS, billing, or policy systems. Its native integrations ensure that call outcomes (like quote updates or payment promises) instantly sync to the right place — no manual re-entry.
Design your workflows
Use Strada Workflows’ no-code automation builder to define what happens after every call.
For example, when a customer reports a claim, Strada can create a claim file, assign an adjuster, and send follow-up documents automatically.
Test and scale
Run pilot calls, review real-time reports, and adjust your workflows for accuracy. Once optimized, scale across more use cases (from renewals to customer service), with zero extra engineering lift.
With Strada Voice AI and Workflows, every call turns into instant action: faster claims, fewer errors, and a better customer experience.
#3 Take a modular, scalable approach
Avoid trying to automate everything at once. Instead, roll out automation in stages. Choose one process, like claims intake or validation, and automate that first. Measure results, make improvements, then move to the next area.
A modular approach reduces risk and allows for human collaboration at every stage. Automation should support your people, not replace them.
By combining human oversight with digital speed, you’ll maintain accuracy and trust while increasing efficiency.
#4 Train, adapt, and continuously improve
Change doesn’t stick without buy-in. Train your staff early and involve them in redesigning workflows. Encourage feedback and make it clear how automation helps them focus on more meaningful work, not just data entry.
Keep evolving. Automation is never “done.” Review processes regularly, update systems, and adopt new AI capabilities as they emerge.
A continuous improvement mindset ensures your automation strategy stays relevant and effective.
#5 Track the right KPIs
You can’t improve what you don’t measure. Monitor KPIs that reflect both efficiency and customer experience:
Processing speed → how quickly are claims resolved?
Error rates → are accuracy levels improving?
Customer satisfaction → do customers feel better served?
Compliance → are regulatory and audit requirements met automatically?
Regularly reviewing these metrics helps you see what’s working and where to fine-tune.
#6 Leverage Strada’s easy deployment model
For many insurers, one of the biggest hurdles is getting automation live quickly. That’s where Strada stands out. Its AI voice agents are designed for rapid deployment, with no long setup cycles or complex integrations required.
With Strada’s Workflows engine, you can create customizable call flows that trigger real-time business actions after customer interactions.
For example, when a caller reports a FNOL, Strada can automatically open a claim in your core system, send a confirmation text, and notify the adjuster, all within seconds.
It’s also built for flexibility. You can start with a single use case, like FNOL or policy servicing, then expand into renewals or customer follow-ups.
Strada’s platform supports incremental automation, allowing smooth human handoffs whenever needed. That means your teams stay in control while the system handles the routine tasks.
Successful insurance claim processing automation happens when technology, people, and process align.
With the right plan, the right mindset, and intelligent tools, you’ll transform your claims process from manual and reactive to automated, proactive, and customer-first.
So what ensures the success of automation implementation? Let’s take a closer look.
What best practices and frameworks ensure claims automation success?
Technology alone doesn’t guarantee success. To get real results from insurance claim process automation, you need the right frameworks, teams, and habits in place.
These best practices help insurers implement automation effectively, sustain performance, and continuously improve.
Adopt agile implementation frameworks
Forget long, rigid project plans. The best automation programs use agile frameworks like Scrum or Kanban. They focus on small, iterative releases with constant feedback.
In practice, that means:
Start small → launch one workflow or process at a time to prove quick wins.
Get feedback early → involve adjusters, agents, and ops teams from day one.
Iterate fast → refine automation steps weekly instead of waiting for a “perfect” rollout.
Measure results → track time saved, error reduction, and customer satisfaction after each sprint.
Scale what works → expand successful automations across other processes.
This approach builds momentum and ensures automation grows in the right direction.
Strengthen data governance
Automation thrives on clean, consistent, and compliant data. That’s why a strong data governance framework is essential.
Define how data is collected, validated, and stored, and make sure privacy and compliance standards like GDPR and HIPAA are followed.
Clear ownership and quality checks keep your AI models accurate and trustworthy, which is essential for both regulators and customers.
Build a center of excellence (CoE)
A CoE acts as the internal engine for innovation and continuous improvement. It brings together experts from IT, claims, and compliance to share best practices, manage automation pipelines, and ensure scalability.
This structure keeps automation aligned with business goals while avoiding duplication of effort across teams.
Foster IT–business collaboration
Successful transformation happens when IT and business units work hand in hand. Encourage joint planning, open communication, and shared KPIs.
Business teams understand workflows best, while IT ensures solutions are robust and scalable. Collaboration keeps automation practical, grounded, and value-driven.
Use process mining and workflow analytics
Tools like Celonis and UiPath Process Mining help visualize how claims actually flow through your systems. They reveal hidden bottlenecks, inefficiencies, and ROI opportunities, letting you target the right areas for automation first.
Here’s what to look for when using process mining:
Track claim cycle time → spot where delays occur most often.
Identify manual touchpoints → find steps still relying on human input or rework.
Measure volume vs. effort → see which claim types consume the most time.
Uncover exceptions → detect patterns where workflows break or loop back.
Prioritize fixes → focus automation on areas with the biggest ROI impact.
Data-driven insights mean you’re not guessing where to optimize next.
Invest in continuous training
As technology evolves, so should your teams. Offer regular upskilling programs for both claims and IT staff.
Training builds confidence, boosts adoption, and helps employees see automation as an opportunity, not a threat.
Strada takes best practices further with continuous AI model evaluation and built-in testing tools to ensure accuracy and reliability. Its platform includes real-time monitoring, data privacy safeguards, and SOC 2–compliant security, so automation runs smoothly and safely at scale.
Strada’s dedicated support teams help insurers maintain performance, adapt workflows, and fine-tune automation as business needs change.
As you can see, automation isn’t a one-time project. It’s a continuous improvement journey. By following these frameworks, you’ll build a foundation for claims automation that’s scalable, compliant, and ready for the future.
But how can you tell if automation is really delivering results for your business? Let’s find out.
How to measure ROI and business impact of claims automation?
Once you’ve rolled out insurance claim automation, the next step is figuring out if it’s really working.
Measuring ROI and business impact isn’t complicated, it’s about tracking the right mix of numbers and outcomes that clearly show progress. Let’s walk through how to do that in a practical, no-fluff way.
Identify quantifiable KPIs
Start with data that proves progress. Track average claim processing time, which should fall as automation speeds up workflows. Measure cost per claim to confirm reduced manual effort, and monitor error rate reduction to ensure fewer disputes.
Watch your straight-through processing (STP) rate: more claims handled without human touch means higher efficiency.
To visualize how these KPIs connect to business outcomes, the table below offers a simple example of an ROI dashboard you can customize for your own organization.
KPI category | Example metric | Target goal | Measured result | Impact |
Efficiency | Avg. claim processing time | < 2 days | 1.4 days | Faster settlements |
Cost | Cost per claim | -25% | -30% | Reduced expenses |
Accuracy | Error rate | < 2% | 1.3% | Fewer reworks |
Automation | Straight-through processing rate | 60% | 68% | Higher throughput |
Customer | NPS / CSAT | +15% | +18% | Better satisfaction |
Fraud | False positive rate | -20% | -25% | More accurate detection |
Operations | Audit pass rate | 100% | 100% | Full compliance |
Financial | Claim leakage | -10% | -14% | Improved profitability |
Focus on customer-centric metrics
Efficiency is great, but customer experience seals the deal. Keep tabs on NPS for loyalty and CSAT for immediate satisfaction.
A drop in complaint rates shows automation is improving clarity and reducing friction.
Evaluate fraud detection accuracy
Smart algorithms now flag suspicious claims instantly. The key is balance — higher detection rates with fewer false positives. That saves time, protects genuine customers, and prevents unnecessary payouts.
In practice, here’s what to track:
Detection rate → how many fraudulent claims your system catches.
False positive rate → how often legitimate claims get flagged by mistake.
Review time → how quickly flagged claims are investigated and resolved.
Recovered value → the amount saved by preventing fraudulent payouts.
Customer impact → whether automation reduces friction for honest policyholders.
Track operational gains
Look beyond numbers to team impact. Measure productivity gains, scalability, and compliance audit pass rates. Automation should free your people for higher-value work, not replace them.
Assess financial outcomes
Follow the money. Compare pre- vs. post-automation costs, check claim leakage reduction, and track cash-flow speed to see how fast settlements move.
Benchmark your results
Put your data in context by comparing it with industry standards. It’s the best way to identify what’s working and where to improve.
Now you know how and with which tools to automate insurance claims settlement. It’s time to start taking action, one step at a time. But before you do, let’s quickly recap.
Conclusion
Insurance claims automation is transforming how the entire industry operates. It’s changing the experience for customers, adjusters, and insurers alike, turning slow, manual workflows into fast, accurate, and transparent processes.
The result? Quicker resolutions, lower costs, and happier policyholders.
But the best outcomes don’t come from technology alone. Successful automation happens when advanced tools work hand in hand with human judgment.
Claims still need empathy, oversight, and clear communication, and automation simply gives teams more time to focus on what matters most: helping customers.
If you haven’t started your automation journey yet, now’s the time. Begin by assessing your claims operations, identifying repetitive tasks, and exploring solutions that fit your goals.
Platforms like Strada make that next step simple. Its AI-driven phone agents and Strada Workflows platform deliver powerful front-office automation that drives immediate ROI.
From managing claim intake to enabling seamless human handoffs, Strada scales effortlessly as your needs grow.
Looking ahead, insurance claim automation isn’t just a competitive advantage; it’s a necessity. Insurers that start using it will be faster, more customer-focused, and ready for the future.
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The Ultimate 2025 Guide to Claims Automation in Insurance
Amir Prodensky
CEO
Nov 21, 2025
18 min read
Learn what really works (and what doesn’t) in modern claims automation.
I still remember the first time I filed an insurance claim.
It took weeks of phone calls, emails, and waiting. Fast-forward to today, and that kind of process feels ancient. Insurance claims automation is completely changing the game.
At its core, it’s about using smart technology to handle claims faster, more accurately, and with far less manual work. Instead of people chasing paperwork and typing the same details again and again, automation takes care of those repetitive steps. Instantly.
And this shift couldn’t come at a better time. Claims are increasing, customers expect real-time answers, and insurers are under pressure to do more with less. The old way simply can’t keep up.
That’s where automation steps in. It doesn’t just speed things up. It cuts errors, reduces costs, and makes the customer experience smoother from start to finish. Take Strada, for example. It’s an AI-powered phone agent platform helping insurers transform their front-line operations. It engages customers naturally, handles routine calls automatically, and frees up human teams to focus on high-value tasks.
In this guide, you’ll get clear, actionable insights into how claims automation really works, why it matters now, and how to make it deliver measurable results for your business.
Ready to see how automation is reshaping insurance? Let’s dive in.
What is claims automation, and how does it work?
Claims automation insurance is all about using technology to replace manual, repetitive tasks in the claims process.
Instead of people keying in data, sending endless emails, or following up by phone, smart systems handle most of the work.
This is often powered by artificial intelligence (AI), machine learning (ML), and/or robotic process automation (RPA), tools that make insurance claims processing automation faster and more accurate.
Here’s how a fully automated claims lifecycle typically works:
Intake → the process starts when a customer reports a claim by phone, SMS, app, or web form.
Data extraction → tools like optical character recognition (OCR) and intelligent document processing (IDP) pull key details from documents, photos, or emails.
Validation → AI compares data against policy details, fraud databases, or repair estimates.
Adjudication → rules engines and ML models decide claim outcomes or flag exceptions for human review.
Settlement → payments are processed automatically through integrated finance systems.
These systems only work well when integrated with core insurance platforms and workflows such as policy administration, CRM, billing, and analytics. Integration ensures data flows seamlessly, keeping every department in sync.
Several platforms lead the way in insurance claims processing automation. Each offers unique tools for automation, compliance, and scalability.
To see how these tools stack up, let’s take a quick look at some of the most popular claims automation platforms and what makes each one stand out.
Platform | Core strengths | Unique features |
Strada | FNOL & communication | AI voice + SMS agents, 24/7 intake |
Conduent | Enterprise automation | Scalable claims processing |
Damco | End-to-end claims | Cloud-based, customizable modules |
Kognitos | RPA + natural language | Human-readable automation scripts |
Appian Connected Claims | Workflow orchestration | Low-code integration, analytics dashboard |
Strada stands out for its AI-powered voice and SMS agents. It handles 24/7 FNOL, capturing claim details instantly and reducing phone call workloads, so claims move faster from the first interaction.
So, claims automation isn’t just about saving time. It’s about transforming how insurance feels for everyone involved. When AI, RPA, and intelligent systems work together, you cut delays, reduce human error, and create smoother experiences for policyholders.
So what happens when everything’s done manually? What are the downsides of that approach? Let’s take a closer look.
What challenges does manual claims processing have?
Manual claims processing might feel comfortable, but it hides a maze of inefficiencies. If your team still relies on spreadsheets, paper forms, or endless phone calls, you’re likely facing some major roadblocks.
Before exploring automation, it’s key to understand why manual methods struggle to keep up.
Here are the most common pain points:
Slow resolutions → claims can take days or weeks as each manual handoff adds delay and risk.
Frequent errors → typos, missing details, and duplicate entries lead to costly rework and compliance issues.
High costs → more staff are needed for repetitive tasks, leaving little room for growth.
Disconnected systems → when data is scattered across policy, billing, and CRM tools, teams spend time searching instead of solving.
These challenges don’t just frustrate insurers. They slow down everyone involved, from customers waiting for payouts to teams managing backlogs. Manual processes also make it harder to stay compliant or detect fraud, since verification and pattern detection take too long.
Scalability is another limit. As volumes grow, manual work simply can’t keep up. That’s why many insurers now turn to Strada’s AI-powered agents, which capture claim details via natural voice or SMS and trigger automated workflows instantly — cutting delays, errors, and costs.
Next, let’s take a look at the main benefits automation brings to the insurance industry.
Why is claims automation vital for insurers today?
Insurance is changing fast. Claim volumes keep rising, driven by aging populations, chronic health conditions, and growing policyholder bases.
At the same time, customers expect faster responses, full transparency, and simple digital experiences. Manual claim handling just can’t keep up anymore.
Operational pressures are piling on. Insurers face:
Higher costs from labor and administration
Tighter regulations and compliance demands
Customer pressure for instant answers and real-time updates
That’s where insurance claims automation makes all the difference. By automating repetitive claim tasks, you cut costs and process claims faster.
AI-powered validation and data checks improve accuracy and reduce fraud. Automation ensures every claim follows consistent rules, keeping compliance tight and errors low.
The benefits go beyond efficiency. Insurance claim automation helps insurers focus on what matters most: the customer.
Faster settlements build trust. Accurate, transparent communication reduces disputes. Happy customers stay longer, renew policies, and recommend your brand.
Automation also gives insurers a competitive edge. It’s not just about doing things quicker. It's about doing them smarter, at scale, and with reliability regulators can trust.
This is where Strada makes a real impact. Strada’s AI-powered voice and SMS agents handle FNOL calls, policy servicing, and renewals, all autonomously. It engages customers 24/7, capturing accurate information instantly and triggering faster claim initiation.
By reducing manual workloads, Strada helps insurers improve reliability, response times, and customer satisfaction, all while staying compliant.
And automation delivers more than efficiency; it improves accuracy, consistency, and results. That’s exactly what insurers will need in 2025.
So what exactly lies at the core of workflow automation? Let’s break it down.
What key technologies power claims automation?
Behind every fast, accurate, and customer-friendly claim process lies a network of smart technologies.
Insurance claims automation isn’t driven by a single tool. It’s powered by several integrated systems that work together to remove manual effort, speed up decisions, and deliver better outcomes.
Before we dive into the details, here’s a simple diagram to help you visualize how these technologies work together and how each one fits into today’s insurance claims automation ecosystem
Now let’s take a closer look at each one.
AI and Machine Learning
AI and ML learn from past claims to predict outcomes, detect fraud, and guide adjusters.
They spot duplicate or suspicious activity instantly, helping teams focus on high-risk or high-value cases for faster, more accurate settlements.
Optical Character Recognition (OCR) and Intelligent Document Processing (IDP)
OCR turns scanned or handwritten forms into digital data, while IDP extracts and validates key details automatically.
Less manual typing
Faster turnaround
Fewer errors
Easy, searchable access
Robotic Process Automation (RPA)
RPA bots handle repetitive tasks like data entry, verification, and notifications — running nonstop for consistent, reliable workflows.
Natural Language Processing (NLP)
NLP powers chatbots and voice agents that understand and respond to customers 24/7, bridging automation in insurance claims processing and empathy.
Blockchain and IoT
Blockchain ensures transparent, tamper-proof transactions, while IoT devices provide real-time data (from vehicle sensors to smart homes) for faster, verified claims.
Bringing all these technologies together in a real-world solution is where Strada truly shines.
Strada’s AI-powered conversational platform is built specifically for insurance, with pre-trained models that already understand policy language, claim categories, and customer intent. It uses NLP, AI, and automation to handle the critical first steps of claims, especially FNOL.
Through voice and SMS, Strada’s AI agents collect accurate claim information, verify key details, and trigger workflows instantly within the insurer’s system.
And here’s why that matters:
Customers can report claims 24/7 without waiting on hold.
Data is captured correctly the first time, reducing follow-up calls and delays.
Claims move forward immediately, cutting days off the process.
Human agents are freed up to handle sensitive or complex cases.
Strada’s platform doesn’t just make automation smarter, it makes it conversational. By blending technical accuracy with human-like communication, it creates a smoother experience for both insurers and policyholders.
In short, each technology plays a different role in insurance claims automation, but they’re most powerful when they work together. The outcome is simple: faster claims, lower costs, and happier customers who feel heard and supported every step of the way.
Now let’s take a closer look at what you can actually hand over to automation.
What parts of claims processing can be automated?
When you look at the entire claims journey, from first notice to final payout, you’ll see dozens of steps that rely on data, rules, and repetition. That’s exactly where claims automation insurance delivers the biggest impact.
Let’s walk through which parts of the claims process are most ready for automation and how they work together to create a faster, more connected workflow.
Data capture and extraction
Every claim starts with information, often scattered across forms, photos, PDFs, or emails.
Automated data capture tools and OCR extract details like policy numbers, dates, and descriptions instantly. IDP then validates and structures that data so it’s ready for review. No manual typing, no delays.
Strada simplifies one of the most time-consuming steps, the initial claims intake. Its AI-powered voice and SMS agents work 24/7, capturing FNOL details instantly.
The moment a claim is reported, Strada automatically triggers workflows: creating a claim file, notifying adjusters, and sending required documents. No manual intervention needed.
By automating intake, Strada removes delays, reduces errors, and helps customers start their claims journey faster and with less frustration.
Validation and eligibility checks
Once data is captured, automation takes over eligibility checks. Systems like Strada can initiate a workflow that instantly compares claim details against policy coverage, prior claims, and regulatory requirements.
This ensures accuracy and consistency right from the start.
Fraud detection and anomaly flagging
AI models analyze thousands of data points in real time to flag potential fraud. By spotting unusual claim patterns or duplicate data, automation in insurance claims processing helps insurers act early, protecting both customers and the business.
Adjudication and routing
This is where robotic process automation insurance claims really shine. Here’s what it can do in practice:
Auto-approve simple claims → RPA bots handle clear-cut cases instantly.
Route complex cases smartly → the right claims go straight to the right adjusters.
Eliminate delays → routine tasks run in the background 24/7.
Keep workflows predictable → every step follows consistent, rules-based logic.
RPA bots can automatically approve straightforward claims and route more complex cases to human adjusters. Rules-based decisions mean faster resolutions, fewer bottlenecks, and a more predictable workflow.
Customer communication and self-service
Automation isn’t just about speed. It’s about better communication. Chatbots and self-service portals let customers file, track, or update claims anytime. NLP enables friendly, conversational interactions that feel personal while keeping costs low.
Payment processing and settlement
Once a claim is approved, payment workflows can run automatically. Integrated systems calculate amounts, verify banking details, and trigger payments, cutting settlement times from days to minutes.
Reporting and real-time analytics
automation of insurance claims also powers smarter decision-making. Real-time dashboards monitor claim volumes, processing speed, and performance trends, giving insurers a clear picture of efficiency and outcomes.
To make it easier to see where automation delivers the most value, the table below breaks down each step of the claims process, showing how feasible automation is and which tools are typically used.
Claims process step | Automation feasibility | Typical tools & platforms |
Data capture & extraction | Very high | OCR, IDP, AI-based document tools |
Validation & eligibility checks | High | RPA, rule engines, policy databases |
Fraud detection | High | AI/ML models, analytics platforms |
Adjudication & routing | High | RPA, decision engines, workflow tools |
Customer communication | Very high | Chatbots, NLP platforms, Strada |
Payment & settlement | Moderate to high | RPA, ERP, finance automation tools |
Reporting & analytics | High | BI dashboards, data visualization tools |
Automation touches every step of modern claims handling. By combining intelligent tools with platforms like Strada, insurers can process claims faster, reduce workloads, and keep customers informed at every stage.
The result? Fewer delays, fewer errors, and a claims experience that actually builds trust.
So how exactly does automation improve customer interactions? Let’s find out.
How does claims automation improve customer experience?
Filing an insurance claim can be one of the most stressful moments for a customer. There’s uncertainty, paperwork, and a lot of waiting.
Automation in insurance claims makes this process faster, clearer, and far more customer-friendly.
The first big benefit is speed. Automated systems use AI and pre-set workflows to process claims almost instantly. What once took days or weeks can now take hours. Faster resolutions mean customers spend less time worrying and more time getting back to normal.
It also adds transparency. Real-time status updates through digital portals and chatbots keep customers informed at every step. They can log in, check progress, or ask questions anytime, with no more wondering what’s happening behind the scenes.
Accuracy is another big win. With data automatically verified and cross-checked, errors drop dramatically. That translates into fair, consistent payouts and fewer disputes, which strengthens trust between insurers and customers.
Here’s how automation transforms the experience overall:
24/7 access → customers can submit and track claims anytime through online and mobile tools.
Personalized service → integrated analytics tailor updates and recommendations based on individual needs.
Consistent communication → automated systems ensure every customer gets timely, reliable updates.
A standout example is Strada, an AI-powered conversational platform built for insurers. Its voice and SMS agents deliver real-time support with zero hold times, answering FAQs, sharing claim updates, and securely capturing information around the clock.
Strada gives customers control and confidence while freeing human teams to handle more complex tasks.
Automation in insurance claims turns a stressful process into a smooth, transparent, and positive experience, one that builds satisfaction, loyalty, and lasting trust.
The benefits for customers are clear. But every process has its challenges. Let’s look at what you might run into and how to avoid it.
What challenges and limitations should insurers anticipate?
Even though automation of insurance claims brings major advantages, implementing it isn’t always plug-and-play. Insurers stepping into automation need to understand the practical challenges that come with new technology.
With the right planning and mindset, most of these can be managed, but it’s important to go in prepared.
Upfront сosts and training
Automation isn’t free. There’s an initial investment in software, system upgrades, and employee training.
Teams need time to learn how to use new tools and workflows effectively. But, these costs pay off quickly through faster processing, reduced manual work, and better customer satisfaction.
Integration with legacy systems
Many insurers still rely on older systems for policies and claims. Integrating automation tools, AI models, or robotic process automation insurance claims workflows with these legacy platforms can be complex.
It often requires technical support and careful change management to ensure data moves smoothly between systems. In reality, the main challenges usually come down to:
Data silos → key information locked in outdated systems or formats.
Integration gaps → new automation tools don’t “talk” easily with old software.
Change resistance → teams need time and training to trust and adopt new workflows.
Technical debt → custom patches and manual workarounds slow progress.
That said, solutions like Strada make this easier. Strada offers native integrations with leading AMS, CRM platforms, and policy or claims systems.
These ready-made connectors reduce engineering lift, speed up deployment, and minimize disruption to existing workflows.
Data quality and consistency
AI is only as good as the data it learns from. Inconsistent, incomplete, or outdated data can lead to poor decisions and inaccurate automation results.
Before rolling out automation widely, insurers should clean and standardize their data, especially if they’re using AI for claims triage or fraud detection.
Keeping humans in the loop
Not every claim can be automated. Complex or disputed cases still need human judgment and empathy.
The best approach combines automation with oversight, letting technology handle routine tasks while humans focus on nuanced decisions, negotiations, or customer reassurance.
Change management and culture
Automation often changes how teams work. That can lead to resistance if it’s not managed carefully.
Clear communication, proper training, and leadership support are essential to get everyone on board. When people understand automation is there to help, not replace them, adoption grows naturally.
Data privacy and security
Insurers handle highly sensitive information. Any automation partner must meet strict security standards.
Strada makes this a priority through SOC 2 Type 2 compliance and robust data isolation protocols. That ensures every customer interaction, from voice calls to SMS data capture, stays secure and compliant.
Automation comes with challenges, but they’re manageable. With clean data, thoughtful planning, and trusted partners like Strada, insurers can modernize their claims operations confidently and see real results faster.
Next, let’s look at how you can bring automation into your workflow.
How to successfully implement claims automation?
If you’re ready to bring automation into your claims operations, the good news is that success doesn’t require a complete overhaul overnight.
The best implementations start small, focus on measurable wins, and build momentum over time.
Insurance claim processing automation works best when it fits naturally into your existing systems and people’s daily workflows. Here’s a simple roadmap to help you do it right.
Let’s check the details.
#1 Assess your current claims process
Before diving into automation, take a close look at how claims flow through your business today. Map out each step, from intake to settlement, and identify where delays, bottlenecks, or manual tasks slow things down.
Ask questions like: Which tasks are repetitive or prone to human error? Where do customers experience the most friction or delays? What systems already work well, and which need improvement?
This clarity helps you pinpoint automation opportunities that deliver the biggest impact first.
#2 Choose the right technology and partners
Once you know what to automate, select the right tools and partners. Look for solutions that integrate easily with your existing systems and support long-term scalability.
Platforms like Appian, Kognitos, Conduent, and Damco offer strong foundations for process automation, analytics, and compliance tracking.
When evaluating technology, consider:
Ease of integration with your existing claims or policy systems
Low-code customization to adjust workflows without deep engineering
Proven industry experience in insurance and regulatory environments
Getting started with Strada doesn’t require a big IT project — it’s designed to plug right into your existing insurance operations. Here’s a quick step-by-step guide to help you launch fast and see results from day one:
Identify your use cases
Start with the highest-impact areas like renewals, claims intake (FNOL), or policy servicing. These are proven Strada workflows that deliver immediate ROI by cutting call times and reducing manual data entry.
Set up your voice AI agent
Strada’s insurance-trained conversational AI can handle inbound and outbound calls. Configure your agent to greet customers, collect key details, verify policy data, and trigger next steps automatically — all without coding.
Connect your systems
Link Strada to your CRM, AMS, billing, or policy systems. Its native integrations ensure that call outcomes (like quote updates or payment promises) instantly sync to the right place — no manual re-entry.
Design your workflows
Use Strada Workflows’ no-code automation builder to define what happens after every call.
For example, when a customer reports a claim, Strada can create a claim file, assign an adjuster, and send follow-up documents automatically.
Test and scale
Run pilot calls, review real-time reports, and adjust your workflows for accuracy. Once optimized, scale across more use cases (from renewals to customer service), with zero extra engineering lift.
With Strada Voice AI and Workflows, every call turns into instant action: faster claims, fewer errors, and a better customer experience.
#3 Take a modular, scalable approach
Avoid trying to automate everything at once. Instead, roll out automation in stages. Choose one process, like claims intake or validation, and automate that first. Measure results, make improvements, then move to the next area.
A modular approach reduces risk and allows for human collaboration at every stage. Automation should support your people, not replace them.
By combining human oversight with digital speed, you’ll maintain accuracy and trust while increasing efficiency.
#4 Train, adapt, and continuously improve
Change doesn’t stick without buy-in. Train your staff early and involve them in redesigning workflows. Encourage feedback and make it clear how automation helps them focus on more meaningful work, not just data entry.
Keep evolving. Automation is never “done.” Review processes regularly, update systems, and adopt new AI capabilities as they emerge.
A continuous improvement mindset ensures your automation strategy stays relevant and effective.
#5 Track the right KPIs
You can’t improve what you don’t measure. Monitor KPIs that reflect both efficiency and customer experience:
Processing speed → how quickly are claims resolved?
Error rates → are accuracy levels improving?
Customer satisfaction → do customers feel better served?
Compliance → are regulatory and audit requirements met automatically?
Regularly reviewing these metrics helps you see what’s working and where to fine-tune.
#6 Leverage Strada’s easy deployment model
For many insurers, one of the biggest hurdles is getting automation live quickly. That’s where Strada stands out. Its AI voice agents are designed for rapid deployment, with no long setup cycles or complex integrations required.
With Strada’s Workflows engine, you can create customizable call flows that trigger real-time business actions after customer interactions.
For example, when a caller reports a FNOL, Strada can automatically open a claim in your core system, send a confirmation text, and notify the adjuster, all within seconds.
It’s also built for flexibility. You can start with a single use case, like FNOL or policy servicing, then expand into renewals or customer follow-ups.
Strada’s platform supports incremental automation, allowing smooth human handoffs whenever needed. That means your teams stay in control while the system handles the routine tasks.
Successful insurance claim processing automation happens when technology, people, and process align.
With the right plan, the right mindset, and intelligent tools, you’ll transform your claims process from manual and reactive to automated, proactive, and customer-first.
So what ensures the success of automation implementation? Let’s take a closer look.
What best practices and frameworks ensure claims automation success?
Technology alone doesn’t guarantee success. To get real results from insurance claim process automation, you need the right frameworks, teams, and habits in place.
These best practices help insurers implement automation effectively, sustain performance, and continuously improve.
Adopt agile implementation frameworks
Forget long, rigid project plans. The best automation programs use agile frameworks like Scrum or Kanban. They focus on small, iterative releases with constant feedback.
In practice, that means:
Start small → launch one workflow or process at a time to prove quick wins.
Get feedback early → involve adjusters, agents, and ops teams from day one.
Iterate fast → refine automation steps weekly instead of waiting for a “perfect” rollout.
Measure results → track time saved, error reduction, and customer satisfaction after each sprint.
Scale what works → expand successful automations across other processes.
This approach builds momentum and ensures automation grows in the right direction.
Strengthen data governance
Automation thrives on clean, consistent, and compliant data. That’s why a strong data governance framework is essential.
Define how data is collected, validated, and stored, and make sure privacy and compliance standards like GDPR and HIPAA are followed.
Clear ownership and quality checks keep your AI models accurate and trustworthy, which is essential for both regulators and customers.
Build a center of excellence (CoE)
A CoE acts as the internal engine for innovation and continuous improvement. It brings together experts from IT, claims, and compliance to share best practices, manage automation pipelines, and ensure scalability.
This structure keeps automation aligned with business goals while avoiding duplication of effort across teams.
Foster IT–business collaboration
Successful transformation happens when IT and business units work hand in hand. Encourage joint planning, open communication, and shared KPIs.
Business teams understand workflows best, while IT ensures solutions are robust and scalable. Collaboration keeps automation practical, grounded, and value-driven.
Use process mining and workflow analytics
Tools like Celonis and UiPath Process Mining help visualize how claims actually flow through your systems. They reveal hidden bottlenecks, inefficiencies, and ROI opportunities, letting you target the right areas for automation first.
Here’s what to look for when using process mining:
Track claim cycle time → spot where delays occur most often.
Identify manual touchpoints → find steps still relying on human input or rework.
Measure volume vs. effort → see which claim types consume the most time.
Uncover exceptions → detect patterns where workflows break or loop back.
Prioritize fixes → focus automation on areas with the biggest ROI impact.
Data-driven insights mean you’re not guessing where to optimize next.
Invest in continuous training
As technology evolves, so should your teams. Offer regular upskilling programs for both claims and IT staff.
Training builds confidence, boosts adoption, and helps employees see automation as an opportunity, not a threat.
Strada takes best practices further with continuous AI model evaluation and built-in testing tools to ensure accuracy and reliability. Its platform includes real-time monitoring, data privacy safeguards, and SOC 2–compliant security, so automation runs smoothly and safely at scale.
Strada’s dedicated support teams help insurers maintain performance, adapt workflows, and fine-tune automation as business needs change.
As you can see, automation isn’t a one-time project. It’s a continuous improvement journey. By following these frameworks, you’ll build a foundation for claims automation that’s scalable, compliant, and ready for the future.
But how can you tell if automation is really delivering results for your business? Let’s find out.
How to measure ROI and business impact of claims automation?
Once you’ve rolled out insurance claim automation, the next step is figuring out if it’s really working.
Measuring ROI and business impact isn’t complicated, it’s about tracking the right mix of numbers and outcomes that clearly show progress. Let’s walk through how to do that in a practical, no-fluff way.
Identify quantifiable KPIs
Start with data that proves progress. Track average claim processing time, which should fall as automation speeds up workflows. Measure cost per claim to confirm reduced manual effort, and monitor error rate reduction to ensure fewer disputes.
Watch your straight-through processing (STP) rate: more claims handled without human touch means higher efficiency.
To visualize how these KPIs connect to business outcomes, the table below offers a simple example of an ROI dashboard you can customize for your own organization.
KPI category | Example metric | Target goal | Measured result | Impact |
Efficiency | Avg. claim processing time | < 2 days | 1.4 days | Faster settlements |
Cost | Cost per claim | -25% | -30% | Reduced expenses |
Accuracy | Error rate | < 2% | 1.3% | Fewer reworks |
Automation | Straight-through processing rate | 60% | 68% | Higher throughput |
Customer | NPS / CSAT | +15% | +18% | Better satisfaction |
Fraud | False positive rate | -20% | -25% | More accurate detection |
Operations | Audit pass rate | 100% | 100% | Full compliance |
Financial | Claim leakage | -10% | -14% | Improved profitability |
Focus on customer-centric metrics
Efficiency is great, but customer experience seals the deal. Keep tabs on NPS for loyalty and CSAT for immediate satisfaction.
A drop in complaint rates shows automation is improving clarity and reducing friction.
Evaluate fraud detection accuracy
Smart algorithms now flag suspicious claims instantly. The key is balance — higher detection rates with fewer false positives. That saves time, protects genuine customers, and prevents unnecessary payouts.
In practice, here’s what to track:
Detection rate → how many fraudulent claims your system catches.
False positive rate → how often legitimate claims get flagged by mistake.
Review time → how quickly flagged claims are investigated and resolved.
Recovered value → the amount saved by preventing fraudulent payouts.
Customer impact → whether automation reduces friction for honest policyholders.
Track operational gains
Look beyond numbers to team impact. Measure productivity gains, scalability, and compliance audit pass rates. Automation should free your people for higher-value work, not replace them.
Assess financial outcomes
Follow the money. Compare pre- vs. post-automation costs, check claim leakage reduction, and track cash-flow speed to see how fast settlements move.
Benchmark your results
Put your data in context by comparing it with industry standards. It’s the best way to identify what’s working and where to improve.
Now you know how and with which tools to automate insurance claims settlement. It’s time to start taking action, one step at a time. But before you do, let’s quickly recap.
Conclusion
Insurance claims automation is transforming how the entire industry operates. It’s changing the experience for customers, adjusters, and insurers alike, turning slow, manual workflows into fast, accurate, and transparent processes.
The result? Quicker resolutions, lower costs, and happier policyholders.
But the best outcomes don’t come from technology alone. Successful automation happens when advanced tools work hand in hand with human judgment.
Claims still need empathy, oversight, and clear communication, and automation simply gives teams more time to focus on what matters most: helping customers.
If you haven’t started your automation journey yet, now’s the time. Begin by assessing your claims operations, identifying repetitive tasks, and exploring solutions that fit your goals.
Platforms like Strada make that next step simple. Its AI-driven phone agents and Strada Workflows platform deliver powerful front-office automation that drives immediate ROI.
From managing claim intake to enabling seamless human handoffs, Strada scales effortlessly as your needs grow.
Looking ahead, insurance claim automation isn’t just a competitive advantage; it’s a necessity. Insurers that start using it will be faster, more customer-focused, and ready for the future.
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The Ultimate 2025 Guide to Claims Automation in Insurance
Amir Prodensky
CEO
Nov 21, 2025
18 min read
Learn what really works (and what doesn’t) in modern claims automation.
I still remember the first time I filed an insurance claim.
It took weeks of phone calls, emails, and waiting. Fast-forward to today, and that kind of process feels ancient. Insurance claims automation is completely changing the game.
At its core, it’s about using smart technology to handle claims faster, more accurately, and with far less manual work. Instead of people chasing paperwork and typing the same details again and again, automation takes care of those repetitive steps. Instantly.
And this shift couldn’t come at a better time. Claims are increasing, customers expect real-time answers, and insurers are under pressure to do more with less. The old way simply can’t keep up.
That’s where automation steps in. It doesn’t just speed things up. It cuts errors, reduces costs, and makes the customer experience smoother from start to finish. Take Strada, for example. It’s an AI-powered phone agent platform helping insurers transform their front-line operations. It engages customers naturally, handles routine calls automatically, and frees up human teams to focus on high-value tasks.
In this guide, you’ll get clear, actionable insights into how claims automation really works, why it matters now, and how to make it deliver measurable results for your business.
Ready to see how automation is reshaping insurance? Let’s dive in.
What is claims automation, and how does it work?
Claims automation insurance is all about using technology to replace manual, repetitive tasks in the claims process.
Instead of people keying in data, sending endless emails, or following up by phone, smart systems handle most of the work.
This is often powered by artificial intelligence (AI), machine learning (ML), and/or robotic process automation (RPA), tools that make insurance claims processing automation faster and more accurate.
Here’s how a fully automated claims lifecycle typically works:
Intake → the process starts when a customer reports a claim by phone, SMS, app, or web form.
Data extraction → tools like optical character recognition (OCR) and intelligent document processing (IDP) pull key details from documents, photos, or emails.
Validation → AI compares data against policy details, fraud databases, or repair estimates.
Adjudication → rules engines and ML models decide claim outcomes or flag exceptions for human review.
Settlement → payments are processed automatically through integrated finance systems.
These systems only work well when integrated with core insurance platforms and workflows such as policy administration, CRM, billing, and analytics. Integration ensures data flows seamlessly, keeping every department in sync.
Several platforms lead the way in insurance claims processing automation. Each offers unique tools for automation, compliance, and scalability.
To see how these tools stack up, let’s take a quick look at some of the most popular claims automation platforms and what makes each one stand out.
Platform | Core strengths | Unique features |
Strada | FNOL & communication | AI voice + SMS agents, 24/7 intake |
Conduent | Enterprise automation | Scalable claims processing |
Damco | End-to-end claims | Cloud-based, customizable modules |
Kognitos | RPA + natural language | Human-readable automation scripts |
Appian Connected Claims | Workflow orchestration | Low-code integration, analytics dashboard |
Strada stands out for its AI-powered voice and SMS agents. It handles 24/7 FNOL, capturing claim details instantly and reducing phone call workloads, so claims move faster from the first interaction.
So, claims automation isn’t just about saving time. It’s about transforming how insurance feels for everyone involved. When AI, RPA, and intelligent systems work together, you cut delays, reduce human error, and create smoother experiences for policyholders.
So what happens when everything’s done manually? What are the downsides of that approach? Let’s take a closer look.
What challenges does manual claims processing have?
Manual claims processing might feel comfortable, but it hides a maze of inefficiencies. If your team still relies on spreadsheets, paper forms, or endless phone calls, you’re likely facing some major roadblocks.
Before exploring automation, it’s key to understand why manual methods struggle to keep up.
Here are the most common pain points:
Slow resolutions → claims can take days or weeks as each manual handoff adds delay and risk.
Frequent errors → typos, missing details, and duplicate entries lead to costly rework and compliance issues.
High costs → more staff are needed for repetitive tasks, leaving little room for growth.
Disconnected systems → when data is scattered across policy, billing, and CRM tools, teams spend time searching instead of solving.
These challenges don’t just frustrate insurers. They slow down everyone involved, from customers waiting for payouts to teams managing backlogs. Manual processes also make it harder to stay compliant or detect fraud, since verification and pattern detection take too long.
Scalability is another limit. As volumes grow, manual work simply can’t keep up. That’s why many insurers now turn to Strada’s AI-powered agents, which capture claim details via natural voice or SMS and trigger automated workflows instantly — cutting delays, errors, and costs.
Next, let’s take a look at the main benefits automation brings to the insurance industry.
Why is claims automation vital for insurers today?
Insurance is changing fast. Claim volumes keep rising, driven by aging populations, chronic health conditions, and growing policyholder bases.
At the same time, customers expect faster responses, full transparency, and simple digital experiences. Manual claim handling just can’t keep up anymore.
Operational pressures are piling on. Insurers face:
Higher costs from labor and administration
Tighter regulations and compliance demands
Customer pressure for instant answers and real-time updates
That’s where insurance claims automation makes all the difference. By automating repetitive claim tasks, you cut costs and process claims faster.
AI-powered validation and data checks improve accuracy and reduce fraud. Automation ensures every claim follows consistent rules, keeping compliance tight and errors low.
The benefits go beyond efficiency. Insurance claim automation helps insurers focus on what matters most: the customer.
Faster settlements build trust. Accurate, transparent communication reduces disputes. Happy customers stay longer, renew policies, and recommend your brand.
Automation also gives insurers a competitive edge. It’s not just about doing things quicker. It's about doing them smarter, at scale, and with reliability regulators can trust.
This is where Strada makes a real impact. Strada’s AI-powered voice and SMS agents handle FNOL calls, policy servicing, and renewals, all autonomously. It engages customers 24/7, capturing accurate information instantly and triggering faster claim initiation.
By reducing manual workloads, Strada helps insurers improve reliability, response times, and customer satisfaction, all while staying compliant.
And automation delivers more than efficiency; it improves accuracy, consistency, and results. That’s exactly what insurers will need in 2025.
So what exactly lies at the core of workflow automation? Let’s break it down.
What key technologies power claims automation?
Behind every fast, accurate, and customer-friendly claim process lies a network of smart technologies.
Insurance claims automation isn’t driven by a single tool. It’s powered by several integrated systems that work together to remove manual effort, speed up decisions, and deliver better outcomes.
Before we dive into the details, here’s a simple diagram to help you visualize how these technologies work together and how each one fits into today’s insurance claims automation ecosystem
Now let’s take a closer look at each one.
AI and Machine Learning
AI and ML learn from past claims to predict outcomes, detect fraud, and guide adjusters.
They spot duplicate or suspicious activity instantly, helping teams focus on high-risk or high-value cases for faster, more accurate settlements.
Optical Character Recognition (OCR) and Intelligent Document Processing (IDP)
OCR turns scanned or handwritten forms into digital data, while IDP extracts and validates key details automatically.
Less manual typing
Faster turnaround
Fewer errors
Easy, searchable access
Robotic Process Automation (RPA)
RPA bots handle repetitive tasks like data entry, verification, and notifications — running nonstop for consistent, reliable workflows.
Natural Language Processing (NLP)
NLP powers chatbots and voice agents that understand and respond to customers 24/7, bridging automation in insurance claims processing and empathy.
Blockchain and IoT
Blockchain ensures transparent, tamper-proof transactions, while IoT devices provide real-time data (from vehicle sensors to smart homes) for faster, verified claims.
Bringing all these technologies together in a real-world solution is where Strada truly shines.
Strada’s AI-powered conversational platform is built specifically for insurance, with pre-trained models that already understand policy language, claim categories, and customer intent. It uses NLP, AI, and automation to handle the critical first steps of claims, especially FNOL.
Through voice and SMS, Strada’s AI agents collect accurate claim information, verify key details, and trigger workflows instantly within the insurer’s system.
And here’s why that matters:
Customers can report claims 24/7 without waiting on hold.
Data is captured correctly the first time, reducing follow-up calls and delays.
Claims move forward immediately, cutting days off the process.
Human agents are freed up to handle sensitive or complex cases.
Strada’s platform doesn’t just make automation smarter, it makes it conversational. By blending technical accuracy with human-like communication, it creates a smoother experience for both insurers and policyholders.
In short, each technology plays a different role in insurance claims automation, but they’re most powerful when they work together. The outcome is simple: faster claims, lower costs, and happier customers who feel heard and supported every step of the way.
Now let’s take a closer look at what you can actually hand over to automation.
What parts of claims processing can be automated?
When you look at the entire claims journey, from first notice to final payout, you’ll see dozens of steps that rely on data, rules, and repetition. That’s exactly where claims automation insurance delivers the biggest impact.
Let’s walk through which parts of the claims process are most ready for automation and how they work together to create a faster, more connected workflow.
Data capture and extraction
Every claim starts with information, often scattered across forms, photos, PDFs, or emails.
Automated data capture tools and OCR extract details like policy numbers, dates, and descriptions instantly. IDP then validates and structures that data so it’s ready for review. No manual typing, no delays.
Strada simplifies one of the most time-consuming steps, the initial claims intake. Its AI-powered voice and SMS agents work 24/7, capturing FNOL details instantly.
The moment a claim is reported, Strada automatically triggers workflows: creating a claim file, notifying adjusters, and sending required documents. No manual intervention needed.
By automating intake, Strada removes delays, reduces errors, and helps customers start their claims journey faster and with less frustration.
Validation and eligibility checks
Once data is captured, automation takes over eligibility checks. Systems like Strada can initiate a workflow that instantly compares claim details against policy coverage, prior claims, and regulatory requirements.
This ensures accuracy and consistency right from the start.
Fraud detection and anomaly flagging
AI models analyze thousands of data points in real time to flag potential fraud. By spotting unusual claim patterns or duplicate data, automation in insurance claims processing helps insurers act early, protecting both customers and the business.
Adjudication and routing
This is where robotic process automation insurance claims really shine. Here’s what it can do in practice:
Auto-approve simple claims → RPA bots handle clear-cut cases instantly.
Route complex cases smartly → the right claims go straight to the right adjusters.
Eliminate delays → routine tasks run in the background 24/7.
Keep workflows predictable → every step follows consistent, rules-based logic.
RPA bots can automatically approve straightforward claims and route more complex cases to human adjusters. Rules-based decisions mean faster resolutions, fewer bottlenecks, and a more predictable workflow.
Customer communication and self-service
Automation isn’t just about speed. It’s about better communication. Chatbots and self-service portals let customers file, track, or update claims anytime. NLP enables friendly, conversational interactions that feel personal while keeping costs low.
Payment processing and settlement
Once a claim is approved, payment workflows can run automatically. Integrated systems calculate amounts, verify banking details, and trigger payments, cutting settlement times from days to minutes.
Reporting and real-time analytics
automation of insurance claims also powers smarter decision-making. Real-time dashboards monitor claim volumes, processing speed, and performance trends, giving insurers a clear picture of efficiency and outcomes.
To make it easier to see where automation delivers the most value, the table below breaks down each step of the claims process, showing how feasible automation is and which tools are typically used.
Claims process step | Automation feasibility | Typical tools & platforms |
Data capture & extraction | Very high | OCR, IDP, AI-based document tools |
Validation & eligibility checks | High | RPA, rule engines, policy databases |
Fraud detection | High | AI/ML models, analytics platforms |
Adjudication & routing | High | RPA, decision engines, workflow tools |
Customer communication | Very high | Chatbots, NLP platforms, Strada |
Payment & settlement | Moderate to high | RPA, ERP, finance automation tools |
Reporting & analytics | High | BI dashboards, data visualization tools |
Automation touches every step of modern claims handling. By combining intelligent tools with platforms like Strada, insurers can process claims faster, reduce workloads, and keep customers informed at every stage.
The result? Fewer delays, fewer errors, and a claims experience that actually builds trust.
So how exactly does automation improve customer interactions? Let’s find out.
How does claims automation improve customer experience?
Filing an insurance claim can be one of the most stressful moments for a customer. There’s uncertainty, paperwork, and a lot of waiting.
Automation in insurance claims makes this process faster, clearer, and far more customer-friendly.
The first big benefit is speed. Automated systems use AI and pre-set workflows to process claims almost instantly. What once took days or weeks can now take hours. Faster resolutions mean customers spend less time worrying and more time getting back to normal.
It also adds transparency. Real-time status updates through digital portals and chatbots keep customers informed at every step. They can log in, check progress, or ask questions anytime, with no more wondering what’s happening behind the scenes.
Accuracy is another big win. With data automatically verified and cross-checked, errors drop dramatically. That translates into fair, consistent payouts and fewer disputes, which strengthens trust between insurers and customers.
Here’s how automation transforms the experience overall:
24/7 access → customers can submit and track claims anytime through online and mobile tools.
Personalized service → integrated analytics tailor updates and recommendations based on individual needs.
Consistent communication → automated systems ensure every customer gets timely, reliable updates.
A standout example is Strada, an AI-powered conversational platform built for insurers. Its voice and SMS agents deliver real-time support with zero hold times, answering FAQs, sharing claim updates, and securely capturing information around the clock.
Strada gives customers control and confidence while freeing human teams to handle more complex tasks.
Automation in insurance claims turns a stressful process into a smooth, transparent, and positive experience, one that builds satisfaction, loyalty, and lasting trust.
The benefits for customers are clear. But every process has its challenges. Let’s look at what you might run into and how to avoid it.
What challenges and limitations should insurers anticipate?
Even though automation of insurance claims brings major advantages, implementing it isn’t always plug-and-play. Insurers stepping into automation need to understand the practical challenges that come with new technology.
With the right planning and mindset, most of these can be managed, but it’s important to go in prepared.
Upfront сosts and training
Automation isn’t free. There’s an initial investment in software, system upgrades, and employee training.
Teams need time to learn how to use new tools and workflows effectively. But, these costs pay off quickly through faster processing, reduced manual work, and better customer satisfaction.
Integration with legacy systems
Many insurers still rely on older systems for policies and claims. Integrating automation tools, AI models, or robotic process automation insurance claims workflows with these legacy platforms can be complex.
It often requires technical support and careful change management to ensure data moves smoothly between systems. In reality, the main challenges usually come down to:
Data silos → key information locked in outdated systems or formats.
Integration gaps → new automation tools don’t “talk” easily with old software.
Change resistance → teams need time and training to trust and adopt new workflows.
Technical debt → custom patches and manual workarounds slow progress.
That said, solutions like Strada make this easier. Strada offers native integrations with leading AMS, CRM platforms, and policy or claims systems.
These ready-made connectors reduce engineering lift, speed up deployment, and minimize disruption to existing workflows.
Data quality and consistency
AI is only as good as the data it learns from. Inconsistent, incomplete, or outdated data can lead to poor decisions and inaccurate automation results.
Before rolling out automation widely, insurers should clean and standardize their data, especially if they’re using AI for claims triage or fraud detection.
Keeping humans in the loop
Not every claim can be automated. Complex or disputed cases still need human judgment and empathy.
The best approach combines automation with oversight, letting technology handle routine tasks while humans focus on nuanced decisions, negotiations, or customer reassurance.
Change management and culture
Automation often changes how teams work. That can lead to resistance if it’s not managed carefully.
Clear communication, proper training, and leadership support are essential to get everyone on board. When people understand automation is there to help, not replace them, adoption grows naturally.
Data privacy and security
Insurers handle highly sensitive information. Any automation partner must meet strict security standards.
Strada makes this a priority through SOC 2 Type 2 compliance and robust data isolation protocols. That ensures every customer interaction, from voice calls to SMS data capture, stays secure and compliant.
Automation comes with challenges, but they’re manageable. With clean data, thoughtful planning, and trusted partners like Strada, insurers can modernize their claims operations confidently and see real results faster.
Next, let’s look at how you can bring automation into your workflow.
How to successfully implement claims automation?
If you’re ready to bring automation into your claims operations, the good news is that success doesn’t require a complete overhaul overnight.
The best implementations start small, focus on measurable wins, and build momentum over time.
Insurance claim processing automation works best when it fits naturally into your existing systems and people’s daily workflows. Here’s a simple roadmap to help you do it right.
Let’s check the details.
#1 Assess your current claims process
Before diving into automation, take a close look at how claims flow through your business today. Map out each step, from intake to settlement, and identify where delays, bottlenecks, or manual tasks slow things down.
Ask questions like: Which tasks are repetitive or prone to human error? Where do customers experience the most friction or delays? What systems already work well, and which need improvement?
This clarity helps you pinpoint automation opportunities that deliver the biggest impact first.
#2 Choose the right technology and partners
Once you know what to automate, select the right tools and partners. Look for solutions that integrate easily with your existing systems and support long-term scalability.
Platforms like Appian, Kognitos, Conduent, and Damco offer strong foundations for process automation, analytics, and compliance tracking.
When evaluating technology, consider:
Ease of integration with your existing claims or policy systems
Low-code customization to adjust workflows without deep engineering
Proven industry experience in insurance and regulatory environments
Getting started with Strada doesn’t require a big IT project — it’s designed to plug right into your existing insurance operations. Here’s a quick step-by-step guide to help you launch fast and see results from day one:
Identify your use cases
Start with the highest-impact areas like renewals, claims intake (FNOL), or policy servicing. These are proven Strada workflows that deliver immediate ROI by cutting call times and reducing manual data entry.
Set up your voice AI agent
Strada’s insurance-trained conversational AI can handle inbound and outbound calls. Configure your agent to greet customers, collect key details, verify policy data, and trigger next steps automatically — all without coding.
Connect your systems
Link Strada to your CRM, AMS, billing, or policy systems. Its native integrations ensure that call outcomes (like quote updates or payment promises) instantly sync to the right place — no manual re-entry.
Design your workflows
Use Strada Workflows’ no-code automation builder to define what happens after every call.
For example, when a customer reports a claim, Strada can create a claim file, assign an adjuster, and send follow-up documents automatically.
Test and scale
Run pilot calls, review real-time reports, and adjust your workflows for accuracy. Once optimized, scale across more use cases (from renewals to customer service), with zero extra engineering lift.
With Strada Voice AI and Workflows, every call turns into instant action: faster claims, fewer errors, and a better customer experience.
#3 Take a modular, scalable approach
Avoid trying to automate everything at once. Instead, roll out automation in stages. Choose one process, like claims intake or validation, and automate that first. Measure results, make improvements, then move to the next area.
A modular approach reduces risk and allows for human collaboration at every stage. Automation should support your people, not replace them.
By combining human oversight with digital speed, you’ll maintain accuracy and trust while increasing efficiency.
#4 Train, adapt, and continuously improve
Change doesn’t stick without buy-in. Train your staff early and involve them in redesigning workflows. Encourage feedback and make it clear how automation helps them focus on more meaningful work, not just data entry.
Keep evolving. Automation is never “done.” Review processes regularly, update systems, and adopt new AI capabilities as they emerge.
A continuous improvement mindset ensures your automation strategy stays relevant and effective.
#5 Track the right KPIs
You can’t improve what you don’t measure. Monitor KPIs that reflect both efficiency and customer experience:
Processing speed → how quickly are claims resolved?
Error rates → are accuracy levels improving?
Customer satisfaction → do customers feel better served?
Compliance → are regulatory and audit requirements met automatically?
Regularly reviewing these metrics helps you see what’s working and where to fine-tune.
#6 Leverage Strada’s easy deployment model
For many insurers, one of the biggest hurdles is getting automation live quickly. That’s where Strada stands out. Its AI voice agents are designed for rapid deployment, with no long setup cycles or complex integrations required.
With Strada’s Workflows engine, you can create customizable call flows that trigger real-time business actions after customer interactions.
For example, when a caller reports a FNOL, Strada can automatically open a claim in your core system, send a confirmation text, and notify the adjuster, all within seconds.
It’s also built for flexibility. You can start with a single use case, like FNOL or policy servicing, then expand into renewals or customer follow-ups.
Strada’s platform supports incremental automation, allowing smooth human handoffs whenever needed. That means your teams stay in control while the system handles the routine tasks.
Successful insurance claim processing automation happens when technology, people, and process align.
With the right plan, the right mindset, and intelligent tools, you’ll transform your claims process from manual and reactive to automated, proactive, and customer-first.
So what ensures the success of automation implementation? Let’s take a closer look.
What best practices and frameworks ensure claims automation success?
Technology alone doesn’t guarantee success. To get real results from insurance claim process automation, you need the right frameworks, teams, and habits in place.
These best practices help insurers implement automation effectively, sustain performance, and continuously improve.
Adopt agile implementation frameworks
Forget long, rigid project plans. The best automation programs use agile frameworks like Scrum or Kanban. They focus on small, iterative releases with constant feedback.
In practice, that means:
Start small → launch one workflow or process at a time to prove quick wins.
Get feedback early → involve adjusters, agents, and ops teams from day one.
Iterate fast → refine automation steps weekly instead of waiting for a “perfect” rollout.
Measure results → track time saved, error reduction, and customer satisfaction after each sprint.
Scale what works → expand successful automations across other processes.
This approach builds momentum and ensures automation grows in the right direction.
Strengthen data governance
Automation thrives on clean, consistent, and compliant data. That’s why a strong data governance framework is essential.
Define how data is collected, validated, and stored, and make sure privacy and compliance standards like GDPR and HIPAA are followed.
Clear ownership and quality checks keep your AI models accurate and trustworthy, which is essential for both regulators and customers.
Build a center of excellence (CoE)
A CoE acts as the internal engine for innovation and continuous improvement. It brings together experts from IT, claims, and compliance to share best practices, manage automation pipelines, and ensure scalability.
This structure keeps automation aligned with business goals while avoiding duplication of effort across teams.
Foster IT–business collaboration
Successful transformation happens when IT and business units work hand in hand. Encourage joint planning, open communication, and shared KPIs.
Business teams understand workflows best, while IT ensures solutions are robust and scalable. Collaboration keeps automation practical, grounded, and value-driven.
Use process mining and workflow analytics
Tools like Celonis and UiPath Process Mining help visualize how claims actually flow through your systems. They reveal hidden bottlenecks, inefficiencies, and ROI opportunities, letting you target the right areas for automation first.
Here’s what to look for when using process mining:
Track claim cycle time → spot where delays occur most often.
Identify manual touchpoints → find steps still relying on human input or rework.
Measure volume vs. effort → see which claim types consume the most time.
Uncover exceptions → detect patterns where workflows break or loop back.
Prioritize fixes → focus automation on areas with the biggest ROI impact.
Data-driven insights mean you’re not guessing where to optimize next.
Invest in continuous training
As technology evolves, so should your teams. Offer regular upskilling programs for both claims and IT staff.
Training builds confidence, boosts adoption, and helps employees see automation as an opportunity, not a threat.
Strada takes best practices further with continuous AI model evaluation and built-in testing tools to ensure accuracy and reliability. Its platform includes real-time monitoring, data privacy safeguards, and SOC 2–compliant security, so automation runs smoothly and safely at scale.
Strada’s dedicated support teams help insurers maintain performance, adapt workflows, and fine-tune automation as business needs change.
As you can see, automation isn’t a one-time project. It’s a continuous improvement journey. By following these frameworks, you’ll build a foundation for claims automation that’s scalable, compliant, and ready for the future.
But how can you tell if automation is really delivering results for your business? Let’s find out.
How to measure ROI and business impact of claims automation?
Once you’ve rolled out insurance claim automation, the next step is figuring out if it’s really working.
Measuring ROI and business impact isn’t complicated, it’s about tracking the right mix of numbers and outcomes that clearly show progress. Let’s walk through how to do that in a practical, no-fluff way.
Identify quantifiable KPIs
Start with data that proves progress. Track average claim processing time, which should fall as automation speeds up workflows. Measure cost per claim to confirm reduced manual effort, and monitor error rate reduction to ensure fewer disputes.
Watch your straight-through processing (STP) rate: more claims handled without human touch means higher efficiency.
To visualize how these KPIs connect to business outcomes, the table below offers a simple example of an ROI dashboard you can customize for your own organization.
KPI category | Example metric | Target goal | Measured result | Impact |
Efficiency | Avg. claim processing time | < 2 days | 1.4 days | Faster settlements |
Cost | Cost per claim | -25% | -30% | Reduced expenses |
Accuracy | Error rate | < 2% | 1.3% | Fewer reworks |
Automation | Straight-through processing rate | 60% | 68% | Higher throughput |
Customer | NPS / CSAT | +15% | +18% | Better satisfaction |
Fraud | False positive rate | -20% | -25% | More accurate detection |
Operations | Audit pass rate | 100% | 100% | Full compliance |
Financial | Claim leakage | -10% | -14% | Improved profitability |
Focus on customer-centric metrics
Efficiency is great, but customer experience seals the deal. Keep tabs on NPS for loyalty and CSAT for immediate satisfaction.
A drop in complaint rates shows automation is improving clarity and reducing friction.
Evaluate fraud detection accuracy
Smart algorithms now flag suspicious claims instantly. The key is balance — higher detection rates with fewer false positives. That saves time, protects genuine customers, and prevents unnecessary payouts.
In practice, here’s what to track:
Detection rate → how many fraudulent claims your system catches.
False positive rate → how often legitimate claims get flagged by mistake.
Review time → how quickly flagged claims are investigated and resolved.
Recovered value → the amount saved by preventing fraudulent payouts.
Customer impact → whether automation reduces friction for honest policyholders.
Track operational gains
Look beyond numbers to team impact. Measure productivity gains, scalability, and compliance audit pass rates. Automation should free your people for higher-value work, not replace them.
Assess financial outcomes
Follow the money. Compare pre- vs. post-automation costs, check claim leakage reduction, and track cash-flow speed to see how fast settlements move.
Benchmark your results
Put your data in context by comparing it with industry standards. It’s the best way to identify what’s working and where to improve.
Now you know how and with which tools to automate insurance claims settlement. It’s time to start taking action, one step at a time. But before you do, let’s quickly recap.
Conclusion
Insurance claims automation is transforming how the entire industry operates. It’s changing the experience for customers, adjusters, and insurers alike, turning slow, manual workflows into fast, accurate, and transparent processes.
The result? Quicker resolutions, lower costs, and happier policyholders.
But the best outcomes don’t come from technology alone. Successful automation happens when advanced tools work hand in hand with human judgment.
Claims still need empathy, oversight, and clear communication, and automation simply gives teams more time to focus on what matters most: helping customers.
If you haven’t started your automation journey yet, now’s the time. Begin by assessing your claims operations, identifying repetitive tasks, and exploring solutions that fit your goals.
Platforms like Strada make that next step simple. Its AI-driven phone agents and Strada Workflows platform deliver powerful front-office automation that drives immediate ROI.
From managing claim intake to enabling seamless human handoffs, Strada scales effortlessly as your needs grow.
Looking ahead, insurance claim automation isn’t just a competitive advantage; it’s a necessity. Insurers that start using it will be faster, more customer-focused, and ready for the future.
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© 2025 Strada API, Inc.
Phone AI agents for insurance distribution
© 2025 Strada API, Inc.
Phone AI agents for insurance distribution
© 2025 Strada API, Inc.