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AI Poised to Drive Small Business Lending Decisions

AI Poised to Drive Small Business Lending Decisions

Small- to medium-sized businesses (SMBs) are, by definition, firms with the most potential to grow.

But, somewhat counterintuitively, SMBs also represent a category most likely to suffer from a lack of financial inclusion within the broader landscape. This leaves them shut out from the lending, working capital solutions and financing products they could increasingly use as their businesses scale and their operational needs evolve.

With the cost of doing business only growing more top of mind for Main Street SMBs, given the state of the macro environment and prevailing headwinds, something has to give.

Traditional approaches to SMB lending are undergoing a profound and fundamental shift driven by the emerging era of artificial intelligence-driven decision frameworks.

New digital lending and financing products being offered by FinTechs, and savvy traditional financial institutions are democratizing access to working capital amounts that are often small for the issuer, but potentially transformative for SMB owners.

It represents a potential bright spot in a starkly challenging landscape.

Read also: Young SMBs Can’t Find Enough Business Financing

What the Rise of AI-based Lending Means for SMBs

Traditionally, the banks and credit unions that extended loans to local SMBs based their lending decisions on the five C’s of a business owner’s character, capacity, conditions, capital and collateral.

“Character” originally referred to the relationship between the individual banker and the individual borrower, and character-based lending was a cornerstone of business banking — in the 19th and 20th centuries, at least.

Nowadays, credit scores are commonly turned to as a stand-in for the borrower’s character, but as AI-powered loan decisioning tools are becoming the new norm, they are revolutionizing the way working capital and financing are extended to SMBs.

AI has introduced a data-driven paradigm into the lending landscape, replacing subjective evaluations with objective analyses of vast amounts of information. Machine learning algorithms now assess a multitude of factors, including financial history, credit scores and business performance metrics, to make lending decisions. The shift has, in many ways, relegated character-based lending to a dying art.

“It’s not simple for small businesses to get a loan, even if it’s a small loan,” Galileo Financial Technologies Chief Product Officer David Feuer told PYMNTS in an interview posted in October.

“Banks are becoming increasingly sophisticated in their use of data and their use of AI to make intelligent decisions about who to make their offers to,” he added.

One of the advantages of AI-powered loan decisioning tools is their efficiency and speed. Traditional character-based lending often involved lengthy evaluations and personal interactions, leading to delays in accessing much-needed working capital. AI enables quick and automated assessments, providing SMBs with timely financing solutions to support their growth and operations.

As a result, loan products, and their approval rates, look different today than they did a few years back. The onus is on the financial institution or FinTech to modernize their systems to adapt to this new reality.

See also: Leveraging Data to Close the Small Businesses Targeting Gap

Driving a More Inclusive Financial Landscape Forward With Data

PYMNTS Intelligence found that nearly 34% of SMBs do not use credit but want to start doing so this year. The question is whether they’ll find an embrace among the marquee names in banking or have to tap alternative financing routes.

“We went through one of the most volatile macro environments … and I think many [SMBs] are now starting to think about going on the offensive,” Charles Zhu, vice president of product at Enigma, told PYMNTS in an interview posted in December.

For financial platforms used to simply calling up a credit bureau, this shift in the landscape of small business lending means that they will need to onboard technology and tools capable of evaluating SMB financial health and performance through the lens of alternative data.

When PYMNTS CEO Karen Webster spoke with Matt Baker, head of small business at Visa, last year about the need for small business lenders to look past their standard considerations for loans, Baker explained that the traditional processes by which small businesses apply for credit, and the metrics by which financial institutions gauge risk and make decisions are both time-consuming and less than efficient.

“What small business owners want is a fast ‘yes’ or a fast ‘no,’” he said. “What they hate is a slow ‘maybe,’ and then a ‘no.’”

Increasingly, AI systems can help analyze and manage SMB risk, informing underwriting structures and loan schedules.

But while purely character-based lending may be fading, there is still room for the human touch in the lending process. Relationship building, understanding unique business challenges, and providing personalized advice can complement AI-driven analyses. Striking the right balance between technology and human expertise is crucial for ensuring responsible and inclusive lending practices in the evolving financial landscape.

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