CFPB Complaints Show Credit Reporting System Under Pressure

In data released Tuesday (March 31) by the agency in its 2025 Consumer Response Annual Report, of the more than 6.6 million complaints filed in 2025, roughly 5.8 million were tied to credit or consumer reporting, accounting for 88% of all submissions.

“Since [2023], the number of complaints have roughly doubled each year,” the CFPB said in its report.

The level of what we might term “complaint concentration” indicates that the primary interface consumers have with the credit system, namely the reporting and scoring infrastructure, has become a significant source of dissatisfaction.

Within that structure, identity-related breakdowns and data inaccuracies appear repeatedly. The report notes that hundreds of thousands of complaints receive administrative responses when companies cannot confirm a consumer relationship due to fraud, scams or identity theft.

In 2025 alone, companies issued administrative responses to approximately 540,800 complaints under such conditions. Identity uncertainty interrupts the credit reporting process and leaves consumers without clear remediation.

Consumers Monitor Credit Closely

The rise in complaints coincides with a more attentive consumer base. PYMNTS Intelligence data shows that improving credit scores is the most common reason consumers seek new credit products, cutting across cards, mortgages and installment options. Credit scores are thus a central financial objective.

Yet the same data reveals a disconnect between perception and reality. Forty-two percent of consumers believe they would be denied for a new credit card, a figure nearly three times higher than actual denial rates among those without cards. Consumers self-select out of credit opportunities, and when they do engage, they scrutinize outcomes more closely, particularly when scores do not align with their expectations.

Inaccuracies and Identity

The scale of the CFPB’s reporting complaints implies recurring issues with incorrect account information, outdated records and misattributed activity, often linked to identity theft or data mismatches.

Synthetic identities, account takeovers and fragmented data sources introduce errors that propagate across credit files. When those errors occur, the remediation process is neither immediate nor always complete. Administrative responses tied to fraud or identity uncertainty can close a complaint without restoring the integrity of the underlying credit profile.

PYMNTS Intelligence research done in collaboration with Trulioo quantifies the broader cost of these identity failures. Firms report losing an average of 3.1% of annual revenue due to gaps in identifying legitimate users and detecting fraudulent actors, translating to approximately $95 billion in aggregate losses across surveyed industries.

At the same time, firms exhibit a notable confidence gap in the age of artificial intelligence. While 96% report confidence in detecting harmful AI bots, 9 in 10 acknowledge challenges from bot-driven activity, and 59% report difficulty managing that fraud. That disparity mirrors the credit reporting environment, where systems appear functional yet fail under the complexity of real-world identity and transaction patterns.

Legacy Scoring Models Struggle to Reflect Real-Time Realities

Traditional credit scoring systems were designed for a slower cadence of financial activity. They rely on periodic data updates, stable employment patterns and relatively static identity markers.

Consumers now generate financial signals continuously. Income may arrive from multiple sources, spending occurs across platforms and financial obligations can shift within short timeframes. Static scoring models, updated at intervals and dependent on aggregated historical data, cannot fully capture that variability.

The CFPB complaint data reflects the consequences of that mismatch. When nearly 9 out of 10 complaints are tied to credit reporting, it suggests that the system is misaligned with how financial behavior is recorded and evaluated.

Continuous Identity and Real-Time Underwriting

The convergence of complaint data and identity risk points toward a different architecture for credit evaluation. Continuous identity verification treats identity as an evolving signal rather than a fixed credential. It integrates behavioral data, device signals and transaction patterns to maintain an updated view of the consumer.

When paired with real-time underwriting, that approach allows lenders to assess risk based on current conditions rather than historical approximations. It reduces reliance on disputed data, too.