Better Data Turns Small Business Loans From Problem to Profit

For decades, small business lending was banking’s problem child.

Loans to mom-and-pop shops and mid-size firms were seen as marginally profitable at best, and too risky at worst. At the same time, loan sizes were small, origination costs high, and default rates volatile.

But with rising rates, inflationary pressures, and regulatory scrutiny putting lenders under strain, small business lending is quietly emerging as a profit center for institutions that enforce discipline at the gate.

According to recent data from PYMNTS Intelligence in the report “ Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms ,” a collaboration with Markaaz , 84% of lenders surveyed with robust underwriting standards now report that their small business loans are “highly profitable.”

By contrast, among banks with weaker credit practices, only 39% say the same. The lesson may be an attractive one: When underwriting meets data discipline, risk can turn into return.

SMB Market Hiding in Plain Sight

Small and mid-sized businesses (SMBs) represent the backbone of the U.S. economy, accounting for nearly half of private-sector employment and a substantial share of GDP. Yet, their access to credit is notoriously fragile. During downturns, banks often retreat, fearing defaults. Conversely, when standards loosen, lenders can face surging losses.

At first glance, SMB lending looks unattractive. But headline metrics can conceal three structural advantages.

The first is that SMB loans often carry higher interest rates than the equivalent large corporate facilities. And once onboarded, small businesses tend to bring along deposits, payments and treasury services.

At the same time, a lending relationship creates a foothold for additional products — merchant services, credit cards, insurance, even payroll solutions.

In servicing the SMB and micro-business market, robust underwriting means more than running models through legacy systems. It means plugging into third-party data ecosystems that can validate the accuracy and timeliness of small business information.

The PYMNTS Intelligence data illustrates just how decisive underwriting rigor is. Institutions that insist on comprehensive credit assessments report double the profitability rate of peers that cut corners. In other words, profitability in SMB lending tracks directly with underwriting discipline, and with the quality of the data underpinning it.

Read the report: Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms

FinTechs were early to spot the SMB opportunity, marketing themselves as faster and more flexible than traditional banks. But speed without discipline has limits. Many FinTech lenders are now grappling with rising default rates, prompting a pivot toward partnerships with banks that can provide the infrastructure and verified data streams to stabilize credit risk.

Meanwhile, scale matters. PYMNTS found that 100% of international and national banks now leverage third-party data sources, compared with just 32% of institutions with under $1 billion in assets. Smaller community lenders, ironically, those most dependent on SMB clients, are often the least equipped to adopt modern verification. The report warns that many are “flying blind at scale,” exposing themselves to both credit losses and competitive erosion.

The next phase may be one of convergence: FinTechs bringing speed and user-friendly experiences, banks contributing verification and balance-sheet strength. Together, they may define the future of small business credit.

As credit markets evolve, SMB lending may become the proving ground for a new era of data-driven banking. The lesson is not just about avoiding losses, it is about strategically turning blind spots into bankable opportunities.