The PYMNTS Intelligence report “Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms” revealed a challenge for financial institutions. Banks, particularly in the United States and the United Kingdom, are keen to finance small businesses but frequently lack the verified data needed to confidently assess a company’s risk.
The study, based on a survey conducted from March 4 to April 2, gathered insights from 350 banking executives in the U.S. and U.K., encompassing leaders from credit unions, community banks, regional banks, large national banks and digital-only institutions. These executives, involved in commercial lending, credit underwriting, customer acquisition or compliance, offered direct visibility into their firms’ data practices for small business loan applications.
The report highlighted that incomplete, outdated or missing records impeded approvals, raised rejection rates and narrowed credit access for the smallest firms. This led financial institutions to either apply higher risk pricing or reject applicants outright, even if the business was fundamentally creditworthy.
A core problem was that micro-sized firms were often “too small for manual review and too opaque for automated scoring,” rendering them unscored and underserved, the report found.
While robust credit assessment provided a competitive edge, leading to more approvals and increased profitability for lenders, pervasive data gaps fostered conservative lending patterns. Despite interest from 60% of U.S. banks and 64% of U.K. banks in real-time data access for small- to medium-sized business (SMB) lending, only 3 in 10 financial institutions in both countries possessed comprehensive credit assessment tools for micro-businesses, largely due to inaccurate, incomplete and outdated data.
Key findings from the report include:
- Nearly 3 in 10 micro-business loan applications were rejected because data on the business’s identity or legitimacy could not be verified, a rejection rate five times higher than that for larger enterprise applications. This suggests that the smallest firms were often penalized for data deficits rather than their actual risk profile.
- The perceived profitability of SMB lending was directly correlated with the quality and comprehensiveness of a bank’s credit assessment. Among banks with very or extremely comprehensive SMB underwriting, 84% reported this segment as highly profitable, a contrast to 39% of less-equipped banks. The profitability gap was wider for micro-businesses, with only 22% of large banks, a quarter of credit unions, and fewer than 3 in 10 digital-only banks stating that lending to these firms was profitable.
- Financial institutions prioritized real-time access to third-party data over API integration solutions for faster decision making. Six in 10 U.S. banks expressed high interest in providers offering live access to micro- and small-business data, a figure that climbed to 70% among large banks and existing third-party data users. This emphasis on immediate utility over system design aimed to accelerate underwriting and approvals.
The report further detailed that data quality failures, including inaccurate, incomplete, inconsistent and outdated information, were the primary obstacles in underwriting small businesses. Financial institutions exhibited higher confidence in data verified by independent third parties, such as credit bureau data on debt repayment history (96% confidence) or audited financial statements (94% confidence), compared to self-reported information from businesses.
Paradoxically, the study found an inverse relationship between the proportion of micro-SMB clients in a bank’s portfolio and its use of third-party data. Half of institutions with 60% or more micro-SMB customers used external data, versus 83% of banks with lower micro-SMB exposure. This suggests a “scale problem,” where banks heavily focused on SMBs may face budget constraints for external validation, potentially operating with less visibility into their borrowers.
Ultimately, the report concluded that addressing data reliability, prioritizing real-time access, linking profitability to assessment quality, and scaling data strategy with SMB penetration were critical for banks aiming to effectively serve and profit from this essential business segment.
