Small businesses drive local economies, but too many still struggle to access timely, right-sized credit. For financial institutions, this is no longer just a demand issue. It is a structural mismatch between how small businesses need financing and how banks underwrite it.
That mismatch is widening the credit gap. Increasingly, AI-driven underwriting is the most practical way to close it.
Small business credit demand remains strong, but the nature of that demand has shifted. Businesses are not just borrowing to grow, they are borrowing to manage rising costs, uneven cash flow, and economic uncertainty.
Federal Reserve data shows that 60% of employer firms applied for financing, yet only 42% received all the funding they sought, leaving 58% with unmet or partially met demand¹. Operating expenses, not expansion, are the most common reason for borrowing¹.
Traditional underwriting was built for expansion lending. It relies heavily on historical financials, tax returns, and static ratios. In today’s environment, those tools often miss what matters most: current cash flow.
The result is a growing disconnect. A rising share of denied applicants cite excessive existing debt, 41% in 2024, up from 22% in 2021, even as many businesses face temporary cash-flow strain rather than structural decline¹. Lenders can see stress. They cannot always see whether it is temporary or structural. That is the core problem.
Why Traditional Underwriting Breaks Down
The limitations of legacy underwriting are most visible in small-balance lending.
These challenges make small loans difficult to justify economically. As a result, many banks either avoid them or process them inefficiently.
The Small-Loan Opportunity Banks Can’t Ignore
Demand is shifting toward smaller credits. SBA data shows that loans under $150,000 have doubled since 2020 and continue to grow, while Federal Reserve data indicates that 40% of applicants seek less than $50,000³¹. Historically, banks have underserved this segment because the economics did not work. Manual underwriting made small loans nearly as expensive to originate as larger ones².
Fintechs stepped in, offering faster decisions and simpler experiences. Borrowers followed, even when costs were higher. For banks, the trade off is clear: continue to lose share or find a way to serve this segment profitably.
How AI Enabled Underwriting Changes the Math
AI enabled underwriting improves both speed and decision quality by using real-time data and automation.
This is the real unlock: better decisions at a lower cost per loan.
Why Acting Now Matters
The urgency is growing across three fronts.
Without change, banks face a losing equation: decline small loans and lose relationships or book them at high cost.
Responsible AI Is the Differentiator
AI enabled underwriting must meet the same standards as any credit process: transparency, fairness, and control. Regulators require explainable decisions, accurate adverse-action reasons, and active fair-lending oversight. There is no exemption for AI-driven models⁶.
The most effective approach combines automation with human oversight: automate straightforward approvals and declines, route complex cases to underwriters, and monitor outcomes and model performance⁵. This ensures speed without sacrificing governance.
Turning Strategy into Execution
Closing the credit gap starts with focus: target existing small business customers, prioritize loans between $25,000 and $250,000, use cash-flow data as the foundation, and build hybrid workflows that combine automation and human review.
From there, institutions can scale, expanding to new customers and integrating lending into broader relationship strategies.
How Baker Hill Helps
Many institutions recognize the need to modernize underwriting but face execution challenges. Baker Hill enables this transition with integrated loan origination and underwriting workflows, AI-driven cash-flow analysis, automated data ingestion, configurable credit policies, and explainable decisioning. These capabilities help institutions improve speed, consistency, and cost efficiency while maintaining strong governance.
Small business lending is becoming a technology-enabled relationship business. Speed, data, and precision now define competitiveness. Banks that modernize can turn small-balance lending into a scalable growth engine. Those that do not risk losing both market share and customer relationships. The opportunity is clear, and time sensitive.
To learn how your institution can close the small business credit gap with AI underwriting, explore Baker Hill’s solutions or request a demo today.
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