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The Data Deficit Holding Back Main Street’s Smallest Businesses | PYMNTS.com

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Small and micro businesses don’t want to stay that way. They want to grow.

In the United States, microbusinesses — defined as firms with fewer than 10 employees — form the very bedrock of economic innovation, local employment and community resilience. Yet despite their foundational role, these enterprises are consistently denied access to the financial fuel they need to scale.

The PYMNTS Intelligence report “Keeping Score: Why Data Quality Determines Lending Decisions for the Smallest Firms,” a collaboration with Markaaz, found that a systemic crisis of data quality is increasingly shaping lending decisions in ways that sideline the smallest players.

While banks and other financial institutions are eager to lend to small businesses, drawn in part by high demand and the potential for strong returns, most are paralyzed by a persistent gap in verifiable data. The report found that nearly 3 in 10 microbusiness loan applications in the U.S. and the United Kingdom are rejected not due to credit risk, but due to unverifiable legitimacy.

That’s five times the rejection rate of larger businesses.

The Opaque Frontier of Micro-SMB Lending

It’s not a matter of unwillingness. Six in 10 U.S. banks surveyed said they want real-time access to business data that could help them approve more loans and reduce delinquency. Yet only 30% of institutions reported having truly comprehensive assessment capabilities for microbusinesses.

This disconnect — between institutional aspiration and technological capability — is stifling credit access, stunting job creation and starving the early-stage firms that drive America’s entrepreneurial engine.

Microbusinesses often operate in the shadows of traditional financial visibility. They typically lack audited financials, have short or fragmented credit histories, and submit inconsistent or self-reported data that lenders struggle to trust. For the average bank or credit union, underwriting these businesses becomes a high-friction, low-confidence exercise.

The economic logic of lending is that good data drives good decisions. Yet for microbusinesses, the data infrastructure is broken or missing altogether. The report revealed that 22% of large U.S. banks and 25% of credit unions consider lending to microbusinesses profitable.

Compare that to 84% of banks that offer comprehensive credit assessments for small businesses — those with better data inputs — that consider this segment highly profitable, and the financial penalty of informational opacity becomes clear. In practical terms, many of these businesses are not rejected for being risky. They are rejected for being unknowable.

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

Lenders fundamentally trust what they can independently verify. According to the study, confidence in underwriting soared to 96% when debt repayment histories came from a credit bureau, and to 94% when financials were audited. That confidence dropped to 82% when reviewing self-reported bank account statements.

In the U.K., the disparity is less severe thanks to Companies House, which standardizes and centralizes business filings. There, nearly half of banks said audited financial statements were their most essential input. In the U.S., only one-third did, reflecting cultural differences and systemic data fragmentation.

The absence of a U.S. equivalent to Companies House means that banks must piece together financial narratives from tax returns, owner disclosures and incomplete statements — each one a potential red flag in the absence of corroboration.

Solving the microbusiness lending challenge requires more than just goodwill or regulatory nudges. It demands a data strategy that is as entrepreneurial as the businesses it aims to serve, the report found.

Financial institutions need low-cost, scalable ways to verify the fundamentals — ownership, revenue, debt obligations and payment history. Tools like Markaaz, which aggregate and refresh global business records in real time, are offering promising pathways.

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Coupa Adds Tariff Impact Planning to Supply Chain Tool | PYMNTS.com

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The Tariff Impact Planning app, part of the spend management platform’s supply chain solution, is designed to help businesses navigate global trade policy, Coupa said in a Wednesday (Aug. 6) news release.

“A lasting trade war could be a black swan event with seismic impacts to supply chains, the likes of which we haven’t seen since the COVID-19 pandemic,” Dean Bain, Coupa senior vice president and general manager of supply chain, said in the release.

“As we’ve seen before, supply chains are extremely fragile, and the potential for severe disruptions create dramatic downstream business challenges for each of our customers.”

The release notes that more than half of CEOs say trade wars are the top geopolitical risk. To ease those concerns, Coupa says it’s designed the tool to let companies design supply chains that assess “current networks, future implications, and alternate strategies” to balance tariff reduction and operational efficiency, and safeguard their bottom lines.

As PYMNTS wrote Wednesday, tariff levels may fluctuate, but a lack of “visibility into future policy has become a binding constraint on strategic planning.”

Data from PYMNTS Intelligence’s June 2025 edition of The 2025 Certainty Project, “Tariff Uncertainty Craters Confidence to Zero at Exposed Consumer Goods Companies,” shows an eye-opening number: not one chief financial officer — zero percent — in the exposed goods sector had any confidence in their company’s ability to navigate the current tariff environment.

The report points to an increasing imbalance between operational execution and strategic development. Rapid shifts in tariffs — sometimes implemented on short notice or as part of wider diplomatic disputes — can hinder the planning cycles that mid-sized firms rely on for capital budgeting and contract negotiation.

More than half of all finance chiefs across industries said they have delayed or canceled capital investments because of tariff policy volatility. The figure was even higher — 63% — among consumer goods firms with large levels of import exposure. These delays affect initiatives ranging from expansion into new markets to supply chain digitization and product innovation.

The report found that a growing number of CFOs are implementing software systems that support scenario planning and tariff exposure modeling. These tools aim to help firms assess how cost structures may shift under various policy outcomes — and to tweak their sourcing, pricing and inventory strategies accordingly.

“At the same time, companies themselves are rethinking what resilience means,” PYMNTS wrote. “Increasingly, strategic agility is replacing efficiency as the core operational objective — a shift that may ultimately make mid-market firms more robust, but also more conservative.”

For all PYMNTS B2B coverage, subscribe to the daily B2B Newsletter.

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AWS Offers OpenAI’s Models on Its Platform for the First Time | PYMNTS.com

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For the first time, OpenAI’s artificial intelligence models are available on a cloud computing platform outside of Microsoft, its largest investor to date.

AWS, in competition with Microsoft Azure for cloud market share, announced in a Tuesday (Aug. 5) press release that it will offer OpenAI’s two new open-weight models on its Bedrock platform.

OpenAI is considered the marquee brand in AI, but its models have only been available in the cloud on Microsoft Azure. All of OpenAI’s proprietary AI models are contractually exclusive to Microsoft, its early and largest investor.

OpenAI released its gpt-oss models in 120 billion and 20 billion parameters Tuesday. These open-weight models are available to anyone, including AWS. OpenAI has not had an open model since GPT-2 in 2019.

AWS’ celebratory tone at getting access to OpenAI models was apparent in the Tuesday blog post of its chief evangelist, Danilo Poccia.

“I am happy to announce the availability of two new OpenAI models with open weights” are now available on two of AWS’ platforms, he wrote in the post.

AWS created a landing page image featuring their two logos side by side, usually reserved for partners jointly announcing an alliance.

While anyone can access all of OpenAI’s models directly through its API rather than going through Microsoft Azure or AWS, enterprises need the robust compliance, security and expertise that hyperscalers provide.

However, OpenAI’s open-weight models are not truly open source in the sense that users cannot access the code and see what dataset was used to assess it for bias and other harms. OpenAI offered them under the Apache 2.0 license that lets anyone use, modify and distribute the models if there is proper attribution and a built-in grant of patent rights.

“OpenAI’s open-weight models may not represent the ‘leading-edge’ models” with capabilities “more similar” to a lightweight version of the flagship GPT-4 model, but they “do fit well with Amazon’s cost savings strategy,” wrote BofA analyst Justin Post in a research note shared with PYMNTS.

AWS said in its Tuesday blog post that OpenAI’s larger open-weight model gives enterprises 10 times more value for the price versus a comparable Gemini model, 18 times more than DeepSeek R1, and seven times over OpenAI’s o4 model. (Gemini and OpenAI o4-mini are proprietary; DeepSeek is open source.)

Poccia said in his blog post that the models “excel at coding, scientific analysis and mathematical reasoning, with performance comparable to leading alternatives.” The models also work with external tools and can be used in an “agentic workflow.”

AWS, a subsidiary of Amazon, already offers open models such as Meta’s Llama, DeepSeek and Mistral. It also offers Claude from Anthropic, in which Amazon has invested $8 billion. Claude, a main rival of OpenAI’s AI models, was not mentioned in the AWS press release.

“We see the addition of OpenAI to the AWS platform, while far from a comprehensive deal, as a positive initial step in the relationship, suggesting the companies are interested in working together,” Post said.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

Read more:

OpenAI Targets $500 Billion Valuation in Share Sale

Anthropic Unveils Claude Opus 4.1 in Dueling Releases With OpenAI

Anthropic Yanks OpenAI’s Access to Claude Model

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New Data Shows Women Decide When and How to Cut Back | PYMNTS.com

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When it comes to escaping the paycheck-to-paycheck grind, men are more likely than women to think they can simply tighten their belts.

However, women, who are responsible for managing daily expenses, have a better sense of what can and can’t be cut when it comes to improving the monthly cash flow.

A PYMNTS Intelligence “Paycheck-to-Paycheck” analysis of 1,475 U.S. consumers found that the gender gap is wide enough to drive a budget spreadsheet through. Asked whether they could stop living paycheck to paycheck if their earnings stayed flat but their spending changed, nearly 1 in 3 men said “absolutely.” Fewer than 1 in 5 women said the same.

The split persisted even after leveling the family expense playing field. Married men maintained their conviction in the money makeover, and dads with kids under 18 were no less bullish than bachelors.

However, optimism must often crash up against reality, especially in an environment where inflation is stubborn and price increases are fueled by tariffs. The data showed that more than two-thirds of consumers live paycheck to paycheck, so finding some way to improve the ebb and flow of cash flow is paramount.

Women often quarterback day-to-day household finances and caregiving budgets, so they see the hard limits on discretionary cuts. Men, by contrast, may underestimate fixed costs.

PYMNTS Intelligence researchers drilled down into two statistically subsamples: 804 married respondents and 541 parents with children under 18. In each sample, participants answered the same core question: “If your income stayed the same, could you stop living paycheck to paycheck by changing how you spend?” Response options were a simple “Yes” or “No,” enabling a clean measurement of financial self-assessment.

Key Data Highlights:

  • Overall Consumers Living Paycheck to Paycheck: Twenty-eight percent of men said they could break the cycle through spending changes alone, compared with 19% of women — an optimism gap of nine percentage points.
  • Married Consumers: Thirty-six percent of husbands said belt-tightening would do the trick, versus 21% of wives — showing that shared mortgages and grocery bills don’t do much to erase women’s views that cash flow pressures persist.
  • Parents With Children Under 18: Thirty-six percent of fathers living paycheck to paycheck were sure that spending tweaks would suffice, but only 23% of mothers agreed, underscoring that caretaking costs — tied to everything from school to recreation — weighed more heavily on women’s calculations.

The disparity is not merely about who shoulders more fixed expenses. Instead, respondents’ commentary suggested a behavioral explanation. Women more often manage family budgets and caregiving outlays, giving them a clearer view of non-negotiable costs. Men, who are less likely to run the household balance sheet, may assume more wiggle room than actually exists.

For banks, FinTechs and payments players, there’s a key takeaway and an opportunity to work with their customers to shore up the status of the household finances. Financial wellness tools, including budgeting apps, must account for gendered perceptions, not just gendered pay gaps, to improve cash flow and financial security.

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