In the United States, microbusinesses — defined as firms with fewer than 10 employees — form the very bedrock of economic innovation, local employment and community resilience. Yet despite their foundational role, these enterprises are consistently denied access to the financial fuel they need to scale.
The PYMNTS Intelligence report “Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms,” a collaboration with Markaaz, found that a systemic crisis of data quality is increasingly shaping lending decisions in ways that sideline the smallest players.
While banks and other financial institutions are eager to lend to small businesses, drawn in part by high demand and the potential for strong returns, most are paralyzed by a persistent gap in verifiable data. The report found that nearly 3 in 10 microbusiness loan applications in the U.S. and the United Kingdom are rejected not due to credit risk, but due to unverifiable legitimacy.
That’s five times the rejection rate of larger businesses.
The Opaque Frontier of Micro-SMB Lending
It’s not a matter of unwillingness. Six in 10 U.S. banks surveyed said they want real-time access to business data that could help them approve more loans and reduce delinquency. Yet only 30% of institutions reported having truly comprehensive assessment capabilities for microbusinesses.
This disconnect — between institutional aspiration and technological capability — is stifling credit access, stunting job creation and starving the early-stage firms that drive America’s entrepreneurial engine.
Microbusinesses often operate in the shadows of traditional financial visibility. They typically lack audited financials, have short or fragmented credit histories, and submit inconsistent or self-reported data that lenders struggle to trust. For the average bank or credit union, underwriting these businesses becomes a high-friction, low-confidence exercise.
The economic logic of lending is that good data drives good decisions. Yet for microbusinesses, the data infrastructure is broken or missing altogether. The report revealed that 22% of large U.S. banks and 25% of credit unions consider lending to microbusinesses profitable.
Compare that to 84% of banks that offer comprehensive credit assessments for small businesses — those with better data inputs — that consider this segment highly profitable, and the financial penalty of informational opacity becomes clear. In practical terms, many of these businesses are not rejected for being risky. They are rejected for being unknowable.
Get the report: Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms
Lenders fundamentally trust what they can independently verify. According to the study, confidence in underwriting soared to 96% when debt repayment histories came from a credit bureau, and to 94% when financials were audited. That confidence dropped to 82% when reviewing self-reported bank account statements.
In the U.K., the disparity is less severe thanks to Companies House, which standardizes and centralizes business filings. There, nearly half of banks said audited financial statements were their most essential input. In the U.S., only one-third did, reflecting cultural differences and systemic data fragmentation.
The absence of a U.S. equivalent to Companies House means that banks must piece together financial narratives from tax returns, owner disclosures and incomplete statements — each one a potential red flag in the absence of corroboration.
Solving the microbusiness lending challenge requires more than just goodwill or regulatory nudges. It demands a data strategy that is as entrepreneurial as the businesses it aims to serve, the report found.
Financial institutions need low-cost, scalable ways to verify the fundamentals — ownership, revenue, debt obligations and payment history. Tools like Markaaz, which aggregate and refresh global business records in real time, are offering promising pathways.