How the Fed's $600B Small Business Lending Data Impacts Bank Verification Software for Funders

The Fed Just Reminded MCA Funders Who They're Competing Against

Federal Reserve Vice Chair for Supervision Michelle W. Bowman recently stated that banks hold roughly $600 billion in business loans originated under $1 million. That single figure underscores a reality every MCA funder already feels: banks are the dominant force in small business financing, and bank verification software for funders is no longer optional for anyone who wants to compete. The figure was presented at a Consumer Bankers Association event, where Bowman emphasized that banks remain the primary financing channel for small businesses across the country.

For alternative lenders and MCA funders, this is not just a data point. It is a competitive benchmark. Banks have inherent advantages: direct access to deposit data, real-time balance visibility, and internal transaction histories that eliminate the need for manual document collection. When an MCA funder asks a merchant to upload three months of bank statements, a bank is already sitting on years of that data. The speed gap is enormous, and it costs funders deals.

This article breaks down what the Fed's data means for MCA verification workflows, why bank verification software is the equalizer, and how AI-powered extraction closes the gap between alternative lenders and the $600 billion incumbents.

Why Banks Win on Verification and How MCA Funders Can Close the Gap

The Internal Data Advantage Banks Hold

Banks do not need to verify bank statements because they generate them. When a small business applies for a line of credit at the same institution where it deposits revenue, the lender already has complete visibility into cash flow patterns, average daily balances, overdraft frequency, and deposit consistency. There is no document upload step. No waiting for PDFs. No risk of tampered statements.

MCA funders operate without this luxury. Every deal requires collecting bank statements from an external institution, parsing them for key financial metrics, and cross-referencing the data against the application. In 2026, many funders still do portions of this manually, creating delays that push merchants toward faster alternatives. The Fed's $600 billion figure is not just about capital availability; it reflects the operational efficiency that banks bring to small business lending.

Speed Is the Only Weapon That Matters

When a merchant needs capital within 48 hours, the funder who verifies bank data fastest wins the deal. Traditional bank verification workflows involve emailing the merchant, waiting for document uploads, manually reviewing PDFs, keying data into spreadsheets, and then passing findings to an underwriter. Each step introduces hours or days of delay.

Bank verification software built for funders eliminates most of these steps. AI-powered document extraction pulls revenue figures, average balances, NSF counts, and deposit patterns directly from uploaded bank statements. Instead of a human spending 20 minutes per statement, the system processes the document in seconds and presents structured data ready for underwriting review.

This matters even more when you consider that slow application intake is one of the top reasons MCA lenders lose deals. Every hour spent waiting for documents or manually parsing statements is an hour the merchant could spend accepting a competing offer.

Asynchronous Collection Eliminates the Biggest Bottleneck

The most overlooked component of bank verification is not the analysis itself. It is the document collection. Merchants are busy running their businesses. They do not respond to emails immediately. They forget attachments. They send the wrong months. They upload screenshots instead of PDFs.

Asynchronous bank verification solves this by decoupling the collection step from the underwriting step. With platforms like Let's Submit, funders send a single secure upload link to the merchant. The merchant uploads documents on their own time, from any device. Meanwhile, the funder's team works on other deals. When documents arrive, AI extraction triggers automatically, and the application moves to review without anyone chasing down paperwork.

This workflow mirrors the convenience that banks offer through their own portals, except it works for external lenders who do not hold the merchant's deposits. The result is a verification experience that feels as fast as a bank's internal process, even though the data is coming from outside.

AI Extraction That Matches Bank-Level Data Depth

Banks do not just know a merchant's balance. They know deposit velocity, seasonal revenue patterns, the ratio of card sales to ACH deposits, and whether the merchant has recently taken on new recurring debits that suggest stacking. Matching this level of data depth from PDFs alone is challenging, but modern AI extraction is closing the gap quickly.

Purpose-built AI models trained specifically on bank statements can now extract not just totals, but line-item transaction data. They categorize deposits by type, flag large irregular withdrawals, identify existing MCA payment patterns, and calculate running daily balances across multiple months. This goes far beyond basic OCR, which only captures text. AI extraction understands the structure and meaning of the data, producing output that an underwriter can act on immediately.

Let's Submit's Pro tier includes bank statement OCR with auto-extraction, along with a risk model and scoring layer. Combined with AI-powered field extraction on the Basic tier, funders get structured, verified data that rivals what banks see in their own systems.

The Competitive Pressure Is Real and Growing

The Fed's $600 billion figure exists alongside a broader trend: banks are becoming more aggressive in small business lending, not less. At the same time, alternative lending continues to scale. Pipe's $300 million in MCA originations over the past two years demonstrates that merchant cash advance is a growing asset class attracting serious capital. eBay's own capital program has crossed $1 billion in cumulative originations through partners like Liberis. The market is large and getting larger, but so is the competition.

For funders caught between bank dominance and platform-based lending, the differentiator is not capital. It is process. Merchants care about speed, simplicity, and certainty. They will go with the funder who gets them an answer fastest with the least friction. Bank verification software that automates collection and analysis is the infrastructure that makes that speed possible.

Consider the typical scenario: a merchant applies to three funders simultaneously. The funder using manual verification takes two days to get bank data reviewed. The funder using AI-powered extraction and async document collection has the data structured and in front of an underwriter within hours. That second funder is not just faster. They are more likely to catch red flags that the manual reviewer misses under time pressure, because the AI extracts every data point consistently.

This is exactly the dynamic that the deBanked coverage of the Fed's remarks highlights: banks win because of infrastructure. Alternative lenders win when they build infrastructure that compensates for not having deposit-level access. Bank verification software is that infrastructure.

Funders who still rely on email threads for document collection and manual spreadsheets for statement analysis are not just slow. They are structurally disadvantaged against both banks and tech-forward competitors. The gap compounds with volume. Processing ten deals manually is annoying but manageable. Processing a hundred is impossible without automation. As the MCA market grows, the funders who invested in verification infrastructure will absorb market share from those who did not.

Frequently Asked Questions

What is bank verification software for funders?

Bank verification software for funders is technology that automates the collection, extraction, and analysis of bank statements submitted by merchants applying for financing. Instead of manually reviewing PDF statements, the software uses AI and OCR to pull key financial data such as revenue totals, average daily balances, deposit frequency, NSF counts, and existing payment obligations. This structured data feeds directly into underwriting decisions. For MCA funders, this type of software replaces the slow, error-prone manual process that causes deal delays and missed fraud signals.

How do MCA funders compete with banks on verification speed?

MCA funders compete by using asynchronous document collection and AI-powered extraction to eliminate the manual steps that slow traditional workflows. Banks have an inherent advantage because they already hold merchant deposit data internally. Funders overcome this by deploying secure upload links that let merchants submit documents on their own schedule, combined with automated extraction that processes statements in seconds rather than hours. Platforms like Let's Submit are purpose-built for this exact workflow, giving funders speed that approaches what banks achieve through internal data access.

Why does the Fed's $600 billion small business lending figure matter for MCA lenders?

The Fed's figure quantifies the scale of bank competition in small business lending. Banks hold $600 billion in business loans under $1 million, which represents the same market that MCA funders serve. This means MCA lenders are not just competing with each other; they are competing against institutions with superior data access, lower cost of capital, and established merchant relationships. The implication is that MCA funders must invest in technology, particularly bank verification and AI extraction, to remain competitive on speed and accuracy where they cannot compete on rates.

How does AI improve bank statement analysis for MCA underwriting?

AI improves bank statement analysis by going beyond basic text extraction. Modern AI models trained on bank statement formats can categorize individual transactions, identify deposit types, flag patterns consistent with MCA stacking or existing payment obligations, calculate running daily balances, and detect anomalies that suggest document tampering. Unlike manual review, AI processes every line item consistently without fatigue or oversight errors. This produces underwriting-ready data that is both faster and more comprehensive than what a human reviewer typically captures from the same document.

Conclusion

The Federal Reserve's confirmation that banks hold $600 billion in small business loans under $1 million is a wake-up call for every MCA funder still running manual verification workflows. Banks win because they have infrastructure. Alternative lenders win when they build their own. Bank verification software that combines asynchronous document collection with AI-powered extraction is the most direct path to closing the speed and accuracy gap that separates MCA funders from traditional lenders.

Let's Submit was built for exactly this challenge. One secure link collects every document. AI extracts the data. Your team reviews and moves. No more chasing merchants for missing pages, and no more deals lost to slower verification. Visit letssubmit.ca to see how async bank verification fits into your workflow and start competing with the speed that the market demands.