AI, Big Data, and the Future of Small Business Lending

Kim Sullivan owns The Health Spot, a fitness center in Brunswick, ME. When her business grew, she went to the bank and filled out a stack of paperwork, seeking a loan to finance an expanded site. Kim didn’t hear back from the bank for over a month. When she finally did, she was shocked to find that her application had been rejected. Kim repeated the process at two more banks before receiving approval.

“I didn’t know if I should keep trying,” she said. “But clients were counting on me.” Her perseverance paid off, and with the expanded business, she paid back the loan on time and in full.

Some might ask: Why is this a problem? The banking system is working as it should—perhaps Kim simply isn’t a creditworthy borrower. But for others, Kim’s story encapsulates the precarious position of small businesses in a lending landscape filled with stresses, frictions, and gaps. Many creditworthy small business owners like Kim struggle to access bank capital because of factors over which they have no control. And with 30 million small businesses in the United States—accounting for half of the country’s private sector employment[1]—the resulting credit gap threatens economic growth and opportunity across the country.

In Fintech, Small Business & The American Dream, we describe two major frictions that contribute to this credit gap: information opacity and heterogeneity. Information opacity refers to the idea that it’s extremely difficult for a lender to look inside a small business and gauge its creditworthiness. Whereas determinations can be made for consumers with relative ease using several data points like credit scores, the relevant financial information for small businesses is often spread across tax filings, bank account statements, and other paperwork. Because of this, bankers (and small business owners themselves) often struggle to understand cash flow and profitability.

Heterogeneity is an issue because small businesses vary widely in financial profile, kind of business, and customers served (dry cleaners are different from parts suppliers or veterinarians). Since each type of business has a unique credit file, loan officers often don’t see enough cases to develop expertise for each sector.  

Big data and financial technology have the power to address each of these issues in ways that can change the game for small business lending.

Imagine Annie, the owner of a café in Washington, DC. Like other small business owners, Annie spends her evenings wrestling with a bevy of paper records and online accounts to manage her payroll, banking, and accounting. But if all of this information were seamlessly integrated into a single application, she could view and manage it from a central dashboard. Annie could then quickly and easily track the café’s current and forecast cash flows. With access to that information (and to comparative data on thousands of like businesses), Annie’s bank could preapprove her for loans that she could draw down at the push of a button.  

This new landscape—where data-driven insights are directly available to both small business owners and lenders—would be so transformative that we call it “Small Business Utopia.” Recent technological developments have made such a Utopia not only possible, but imminent.

In the late 2000s, financial technology firms, or ‘fintechs,’ flooded the small business lending market. They improved customer experience for loan application, automated the process of determining creditworthiness, and notified applicants of decisions in days. To achieve this unprecedented speed and efficiency, they used vast quantities of nontraditional data—like daily transactions—gathered from customers. Application programming interfaces (APIs) allowed for the integration of multiple data streams, and machine learning algorithms were deployed to generate insights into cash flow.

Although many industry observers initially proclaimed that the fintechs’ technological advantages would render banks obsolete, that hasn’t been the case. The new entrants lacked the banks’ established customer bases and low-cost capital, and in recent years, many banks have begun to partner with or purchase innovative services from fintechs. Meanwhile, platform players like Amazon and Square also entered the small business lending scene, bringing their technological might, extensive data, and a focus on customer experience. In short, the small business lending market today is more dynamic and competitive than it has ever been.  

This rapidly changing landscape may well bring about Small Business Utopia—but not without raising challenging questions. In this new environment, debates around “more” versus “less” regulation must be replaced with a different conversation about how we make decisions in a world governed by Big Data and AI. How should we deal with potential discrimination in lending algorithms? Who owns the financial data that is shared across different companies? What role should government play? At a minimum, regulatory agencies must develop the technological expertise necessary to engage on these issues, to ensure that the advancements bring positive change instead of creating new disparities or deepening the ones that already exist.

We can’t be sure what the future of small business lending will bring. But one thing is certain: with “smart” regulation, and with technology-driven innovation creating more customer-friendly options, it’s small business owners who stand to benefit most of all.

Karen G. Mills was a member of President Barack Obama’s Cabinet and served as the Administrator of the U.S. Small Business Administration from 2009 to 2013. She received the U.S. Department of the Navy’s Distinguished Public Service Award for her contribution to U.S. competitiveness, entrepreneurship, and innovation. She is the President of MMP Group and has a long history of building companies as a venture capital investor.