Prevent healthcare claim denials with AI and automation

Key takeaways:

• Over the past 12 months, 25% of providers reported increased denial rates.
• Incomplete or incorrect patient registration information, inaccurate claim data and authorization issues are all top denial triggers.
• AI-powered solutions like Patient Access Curator™ (PAC) and AI Advantage™ can help healthcare organizations improve front-end data accuracy and better predict and prevent potential claims issues before submission.

Healthcare claim denials continue to remain a significant challenge for healthcare revenue cycle leaders. More than four in ten providers say at least 10% of claims are denied, according to Experian Health data. As a result, providers are rethinking how to leverage AI and automation to reduce denial rates across the revenue cycle. Improving front-end data accuracy is a top priority for many providers. Still, they also see opportunities to use technology to better predict denials before they occur and streamline claims management processes.

Why are healthcare claims denied?

Even the smallest mistakes on claims submission can trigger denials. Nearly 70% of providers say submitting clean claims is harder than it was a year ago, and 54% report an increase in claim errors, according to Experian Health’s 2025 State of Claims report.

Some common reasons for healthcare claims denials include:

1. Missing patient information: Incomplete or incorrect patient data collected at registration triggers 32% of claim denials, according to Experian Health’s latest State of Claims report.
2. Inaccurate insurance data: Outdated patient insurance information, missing coverage or mistakes made when entering insurance data during registration can lead to rejected or denied claims.
3. Eligibility verification errors: Mistakes during manual eligibility checks or incomplete insurance eligibility verification are common causes of denials.
4. Prior authorization issues: 35% of claim denials are triggered when prior authorizations aren’t obtained or don’t fully meet prior authorization requirements before claims submission.
5. Coding inaccuracies: Missing medical billing codes and coding errors account for 24% of denials. Nearly half of providers say that coding errors are one of the top three most preventable claims errors in the latest Experian Health Claim Denial Management survey.
6. Coordination of benefits (COB) errors: Coordinating benefits across several payers is a complex process and mistakes that lead to denials are common, especially when COB is handled manually.
7. Incomplete registration records: 26% of providers report that at least 10% of denials stem from inaccurate or incomplete data collected during registration.

The current challenges in claims management

Providers face several key challenges when navigating claims management in today’s complex and fast-changing healthcare landscape.

Manual claims review processes

Many health systems still rely on manual claims review processes, which increase the risk of data entry errors, inaccurate claims submissions and denials. To further complicate matters, most manual claims review processes consist of disparate systems from multiple vendors. This can create communication challenges between front-end and back-end operations, resulting in additional administrative work and further slowing down claims processing.

Staffing shortages and revenue cycle workforce constraints

More than 40% of providers are understaffed, and 60% say they have fewer than 25 team members managing claims, according to Experian Health data. For 36% of providers, staffing shortages make keeping up with claims management challenging, especially when staff need to spend extra time manually reworking claims.

Inaccurate patient information and eligibility verification errors

Getting patient information and eligibility verification checks right from the start is key to submitting cleaner claims and reducing denials. However, data accuracy consistently ranks as a top concern for providers, according to Experian Health’s latest State of Patient Access survey. While providers report that data accuracy has improved since the previous year, Experian Health’s Claim Denial Management survey data shows that improving the quality of front-end data is the single biggest opportunity for providers to reduce claims denials.

Payer complexity and changing policies

Payer rules are complex and evolve frequently – sometimes with limited notice. Keeping pace with updates can be a never-ending challenge for providers. The issue is further compounded by the sheer scale of changes, inconsistent or fragmented communication channels and a growing number of payers. As a result, unexpected delays or denials are common, even when providers are confident that claims are accurate.

The hidden costs of claim denials

Healthcare claim denials carry hidden costs, including lost revenue, increased administrative burden and decreased patient satisfaction.

Here’s how denied claims commonly impact providers and patients:

– Financial: Denials can result in delayed reimbursements, cash flow issues and increased collections costs.

– Operational: Denied claims may trigger heavy appeals workloads, straining already limited resources, leading to staff burnout.

– Patient: Denials can cause billing confusion, delays in care and a poor financial experience that reduces overall patient satisfaction.

How AI and automation support proactive denial management

Here’s a closer look at how AI and automation can help providers take a more proactive approach to managing claim denials.

How AI and automation support denial management:

– Detects registration and eligibility errors: AI-powered data intake solutions can identify incomplete or inaccurate patient data before claims are submitted, supporting cleaner claims and faster reimbursement.

– Predicts denial risk: Machine learning models analyze historical claims and payment patterns to identify high-risk claims before submission, continuously learning from historical outcomes.

– Automates claim review: Automating claims management reduces manual errors, standardizes workflows, and alleviates administrative burden, freeing staff to focus on other priorities.

– Prioritizes denial recovery: Denial management tools with predictive analytics help teams focus on denials with the highest likelihood of reimbursement and prioritize work queues based on financial impact.

– Identifies denial trends: AI-powered denial prevention tools allow organizations to uncover recurring root causes, detect payer-specific denial patterns and proactively improve claims management processes.

How to implement AI in claims management

Getting ahead of the claims challenge isn’t just about fixing denials after the fact, but about preventing them in the first place. Here are two ways health systems can use AI in claims management to minimize denials:

1. Improving front-end accuracy

Comprehensive AI-based solutions like Patient Access Curator help providers gather accurate patient data during registration. PAC uses AI, machine learning and robotic process automation to verify demographics, eligibility, COB, Medicare Beneficiary Identifiers (MBI) and insurance discovery in real-time – so patient intake data is accurate from the start and remains up-to-date across the revenue cycle.

2. Predicting and preventing claim denials

AI Advantage uses historical payment data and Experian Health datasets to analyze denial patterns and surface issues before claims submission. It helps edit high-risk claims to reduce denials and eliminates guesswork by identifying high-value denials so that staff can focus on claims with the highest financial priority. And with machine learning, this solution continuously adapts and improves results over time.

Case studies and real-world applications

See how real-world health systems prevent claim denials with AI-driven and automation solutions like Patient Access Curator.

The future of healthcare claim denial prevention

As claim denials continue to evolve in both volume and complexity, healthcare organizations need to shift from reactive denial management to proactive prevention. Because many denials stem from issues that originate during patient registration, strengthening front-end data accuracy offers one of the greatest opportunities to improve claim outcomes. In fact, Experian Health data shows that 50% of providers identify improving front-end data accuracy as their top opportunity to reduce denials. AI-powered solutions such as Patient Access Curator help organizations capture and verify more accurate patient information at intake, enabling cleaner claims and reducing the risk of denials before a claim is ever submitted.

Find out how Experian Health’s Patient Access Curator helps healthcare organizations prevent claim denials by improving front-end data accuracy.

---

Contact Experian Health

Complete the form below to be connected with a member of our Sales team. For Customer Support, including password resets, please visit our Support page.