Small businesses have many funding avenues, but many are rejected for the wrong reasons
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Small business loan rejection rates in the United States remain stubbornly high, which is a lose-lose scenario. Denial of credit prevents capital-starved firms from growing and deprives lenders of revenue: they literally leave money on the table.
In 2024 (the most recent full year for which data are available), 41% of applicants received all the financing they sought, 36% received just some, and 24% received none, according to the Small Business Credit Survey (SBCS). Compared to 2019, significantly fewer companies in 2024 were fully approved for financing: 51% compared to 62%. Among loan types, Small Business Administration (SBA) loan or line of credit (LOC) applicants experienced a 45% denial rate in 2024—more than double the 21% rate across all types.
Despite increasing demand for small business loans from large banks, the Federal Reserve Bank of St. Louis notes that there has been a steady decline in the supply of bank-provided capital to small businesses in recent years. Nationally, between 2019 and 2023, bank lending by real dollar amount declined by 18%.
High Bar to Clear
In theory, banks should be willing to provide SBA loans given the reduced risks entailed. SBA loans (primarily 7(a)) provide funding up to $5 million with competitive, capped interest rates, long repayment terms, and lower down payments. The SBA covers a significant portion of the loan if the borrower defaults. For most SBA 7(a) loans, the SBA guarantees up to 85% for loans of $150,000 or less and 75% for loans over $150,000.
Many bankers view SBA 7(a) loans as an important part of their toolkit to serve their small business customers. A 7(a) loan can help a bank get to a “yes” to make a loan for a borrower who doesn’t qualify or is on the margin of qualifying for a conventional loan.
Yet banks’ SBA loans also entail a high administrative burden, long processing times (60–120 days), and complex paperwork. Interest rates are often capped. Larger banks sometimes find that processing smaller SBA loans is not as profitable as larger corporate loans, as the administrative cost of underwriting a $100,000 loan is similar to a $1 million loan.
Further, the SBA has distinct requirements for eligibility. Its credit elsewhere rule mandates that small businesses must be unable to obtain necessary financing on reasonable terms from conventional, non-governmental sources to qualify for an SBA-guaranteed loan. This rule ensures federal support assists truly underserved businesses, requiring lenders to document why the borrower cannot secure conventional credit.
Applicants for SBA loans are often rejected because they cannot meet the SBA Debt Service Coverage Ratio. The DCSR measures a business’s ability to repay loans, calculated as net operating income / total debt service, with lenders typically seeking 1.25x or higher—meaning $1.25 income for every $1 of debt—to ensure sufficient cash flow.
Money Left on the Table
Banks that make SBA 7(a) loans can sell the guaranteed portion (75% to 85%) on the secondary market for a premium. By rejecting these loans, they forgo this immediate fee income. They lose out on the interest income from the portion of the loan they retain (typically 15% to 25%) and the fee income generated from servicing the loans.
Rejecting an SBA loan often means losing a small business client entirely. These clients often require other services. These include checking accounts, payroll services, and credit cards, and they represent solid cross-selling opportunities that are lost when an SBA loan is rejected.
At the same time, when traditional banks reject SBA loans, they cede market share to non-bank lenders—especially fintech firms—that are increasing their share of small business lending. Industry estimates have found that fintech firms now generate 10% to 15% of small business loan volume in the United States. While this represents a relatively small share of total dollars compared to traditional banks, fintechs serve nearly double the number of small business borrowers.
AI Can Help
While by no means a panacea for reducing SBA loan rejection rates, artificial intelligence (AI) nonetheless brings much to the table. Deployed effectively, AI can streamline the application process, provide more accurate risk assessments using alternative data, and significantly shorten loan approval time.
Traditional lending models often overlook businesses with limited credit histories. AI analyzes a broader range of data sources, including cash flow patterns, accounting software data, and invoice payment history. By doing so, it offers a more holistic view of a borrower’s creditworthiness, helping lenders identify otherwise creditworthy businesses that might be denied using a less rigorous analysis of data sources.
SBA loans involve extensive paperwork and a high administrative burden, while manual data entry and document review are prone to human error. AI-powered systems automate the collection, processing, and verification of financial documents like tax returns and bank statements, reducing errors and ensuring that applications are complete and accurate.
By automating time-consuming tasks like initial screening and data analysis, AI can potentially shorten the loan approval timeline from weeks to days or even minutes. Faster processing means businesses receive quicker decisions and can reapply or seek alternative funding sooner if rejected, reducing overall delays.
AI models can also help ensure consistent, objective decisions based purely on data, which may mitigate human bias in lending decisions and expand access to credit for underserved populations.
Capitalizing on a Growing Market
Despite the challenges small businesses face in getting approved for loans, the overall market remains large and continues to grow. The U.S. Treasury Department estimates that the small business loan market in the United States is valued at over $1.4 trillion. From Jan. 2020 to Jan. 2025, new small business formation jumped 50%, with a record 430,000 new business applications each month in 2024 and creating 70% of net new jobs.
During the first quarter of fiscal year 2025, the SBA reached its second-largest 7(a) lending volume since 1991. Brisk growth in the program’s smallest loans, those under $150,000, is driving portfolio expansion. Among the almost 45,000 7(a) loans approved as of April 10, the vast majority (81%) are $500,000 or less, and more than half are for amounts of $150,000 or less.
To best capitalize on this opportunity—and not cede more ground to tech-savvy fintechs—banks should judiciously use AI solutions. AI can make the most difference when it comes to data analysis and initial screening.
There might be a temptation to automate as much of the loan application process as possible, but we advise banks to tread cautiously. Relying too much on chatbots can be detrimental in loan applications because they struggle to handle the complexity, nuances, and high-stakes nature of financial decisions. The result is often user frustration and sometimes even security risks.
Ultimately, banking is a people-centered business built on trust, client relationships, and personalized advisory services. While AI is increasingly important for enhancing performance, human interaction remains paramount for important decision-making, such as whether or not to approve a small business loan.
