Key Takeaways
- The Federal Reserve's 2025 survey confirms MCA adoption has held steady at 7% since 2017, but flat adoption does not mean flat volume; the SMB population itself has grown significantly.
- Funders processing more applications through the same manual verification workflows are hitting capacity walls that kill deal speed and margin.
- Investment-grade capital is flowing into MCA platforms, raising the bar for operational rigor and making outdated bank verification processes a competitive liability.
- Bank verification software for funders must handle asynchronous document collection, AI-powered extraction, and audit-ready record-keeping to keep pace with institutional expectations.
- Let's Submit provides the async verification infrastructure that helps funders scale without proportionally scaling headcount.
A Flat Percentage Hides a Growing Problem
The Federal Reserve's 2025 Small Business Credit Survey landed with a seemingly unremarkable headline: 7% of small businesses with fewer than 500 employees regularly use merchant cash advances, unchanged from the same survey conducted in 2017. At first glance, it looks like the MCA market has plateaued. Dig a little deeper, and the picture is very different.
Between 2017 and 2025, the number of employer firms in the United States grew by roughly 400,000, according to Census Bureau data. Non-employer businesses, the sole proprietors and gig operators who increasingly seek working capital, expanded even faster. Seven percent of a larger base means more deals, more bank statements, and more pressure on underwriting teams that have not fundamentally changed how they process applications. For funders still relying on manual bank statement review, that growing absolute volume creates a verification crisis hiding behind a flat percentage.
This article breaks down why the Fed's static number actually signals escalating operational risk, how recent institutional capital raises are compounding the pressure, and what bank verification software for funders needs to deliver in 2026 to keep pace.
Institutional Capital Is Raising the Bar
What Investment-Grade Notes Mean for Operations
When Fund Street Technologies, the parent company of One Park Financial, closed a $45.5 million investment-grade corporate note in June 2026, it sent a clear signal. Institutional investors are not just entering the MCA space; they are demanding the same operational discipline they expect from traditional lending platforms. Investment-grade capital comes with covenants, reporting requirements, and audit expectations that manual spreadsheets cannot satisfy.
As we discussed in our analysis of how Fund Street's note raises the bar for bank verification software, the shift toward institutional funding sources forces funders to demonstrate process consistency. Every bank statement must be collected, parsed, and stored in a way that an auditor can trace from submission to funding decision. That is not a nice-to-have. It is a precondition for accessing the kind of capital that fuels growth.
Volume Growth Without Proportional Headcount
The math is unforgiving. If a funder's origination volume increases by 20% but its underwriting team stays the same size, something has to give. Either deal speed slows, accuracy drops, or both. The traditional solution, hiring more analysts, runs into its own constraints: recruiting takes time, training takes longer, and labor costs erode the margin gains that higher volume should deliver.
This is where the Fed's flat adoption percentage becomes deceptive. Funders looking at 7% and concluding the market is static are misreading the data. The market is growing in absolute terms, and the funders winning that volume are the ones whose bank verification infrastructure can absorb it without breaking.
Anatomy of the Verification Bottleneck
Document Collection Is Still the Biggest Friction Point
Before a single bank statement gets analyzed, it has to arrive. This is where most MCA operations lose time. Applications come in through email, brokers forward documents in mismatched formats, and merchants upload partial files that require follow-up. Each back-and-forth exchange adds hours or days to the timeline.
The bottleneck is not extraction. It is collection. A funder can have the most sophisticated AI parsing engine in the world, but if it takes three days to get a complete set of bank statements from the merchant, the technology advantage evaporates. Asynchronous document collection, where the merchant receives a secure link and uploads everything on their own schedule, eliminates the email ping-pong that kills deal velocity.
Manual Review Creates Inconsistency at Scale
When two different analysts review the same bank statement, they often extract slightly different numbers. One might catch an NSF fee pattern; the other might miss it. At low volume, this inconsistency is manageable. Supervisors can spot-check. At higher volume, the variance compounds into real underwriting risk.
Consistency matters for two reasons. First, inconsistent data leads to inconsistent funding decisions, which means either approving deals that should have been declined or declining deals that should have been funded. Both outcomes cost money. Second, when institutional capital partners audit the portfolio, inconsistency in source data raises red flags that can jeopardize future funding rounds.
AI-powered extraction solves this by applying identical logic to every document. The same fields get pulled, the same calculations get run, and the same anomalies get flagged, regardless of whether it is the first application of the day or the five hundredth. As Lightspeed Capital's recent 73% MCA revenue growth demonstrates, the funders scaling fastest are those whose bank verification workflows can absorb surging volume without proportional headcount increases.
Audit Trail Gaps Become Liability
Every MCA funder operating in New York, Virginia, Connecticut, or any other state with active commercial financing disclosure requirements needs a defensible record of what documents were received, when they were reviewed, and what data was extracted before the funding decision. Manual processes create gaps. Emails get deleted. Spreadsheets get overwritten. Analysts leave and take institutional knowledge with them.
A purpose-built verification platform maintains an immutable audit trail automatically. Every document upload, every extraction result, every human edit is timestamped and logged. When a regulator or capital partner asks to see the underwriting file for a specific deal, the funder can produce a complete record in minutes rather than scrambling to reconstruct it from email chains.
What Modern Bank Verification Software Must Deliver
The requirements have shifted. Five years ago, bank verification software for funders meant basic OCR that could pull numbers off a PDF. That is table stakes now. The 2026 landscape demands a more complete solution, one that addresses the full lifecycle from document collection through underwriting review.
Asynchronous collection. Merchants and brokers should be able to submit documents through a secure portal on their own time, without requiring a live interaction with the funder's team. This single change can compress application intake from days to hours.
AI-powered extraction with human review. Machine learning models should handle the initial parsing, identifying account holders, calculating average daily balances, flagging negative balance days, and categorizing transaction types. But the output should route to a human reviewer who can verify, edit, and approve before it reaches the underwriting queue. Full automation without human oversight creates a different kind of risk.
Structured data output. Extracted data needs to flow cleanly into the funder's CRM or underwriting platform. If an analyst has to re-key numbers from one system into another, the efficiency gains from automated extraction are partially lost. One-click sync to Salesforce or equivalent systems eliminates that last mile of manual work.
Fraud surface coverage. Fabricated bank statements are a growing concern in SMB lending. Verification software should flag common manipulation indicators: mismatched fonts, inconsistent running balances, duplicate transaction patterns, and metadata anomalies in PDFs. This does not replace dedicated fraud investigation, but it provides an early warning layer that catches the most obvious attempts before they consume underwriting time.
Complete audit trails. Every action, from document upload to data extraction to human edit to final approval, must be logged with timestamps and user attribution. This is non-negotiable for funders seeking institutional capital or operating in regulated states.
A Real-World Scenario: What Happens Without the Infrastructure
Consider a mid-size funder processing 150 applications per week. Each application requires three months of bank statements, typically six to twelve PDF pages. The intake team spends most of its day chasing brokers for missing documents. When statements arrive, two analysts split the review work, manually entering average balances, identifying existing MCA positions, and calculating net deposits into a shared spreadsheet.
On a good week, they fund 40 deals. On a bad week, when a broker sends incomplete files or a merchant is slow to respond, throughput drops to 25. The funder's capital partner notices the inconsistency and asks for documentation on three specific deals. It takes two days to locate all the original bank statements and reconstruct the review notes.
Now consider the same funder using a platform like Let's Submit. Brokers and merchants receive a secure upload link. Documents arrive in a centralized dashboard. AI extracts business information, financials, and owner details automatically. An underwriter reviews the extracted data, makes any corrections, and approves it for the next stage. The entire intake-to-review cycle compresses from days to hours. When the capital partner asks for deal documentation, every file and every extraction result is available in the application timeline with a full audit trail.
The difference is not marginal. It is structural. One workflow scales linearly with volume. The other hits a ceiling and forces the funder to choose between speed and accuracy.
Frequently Asked Questions
Why is MCA adoption flat at 7% but origination volume still growing?
The 7% figure from the Federal Reserve survey represents the share of small businesses that regularly use MCAs, not the absolute number of MCA deals. Because the total small business population in the United States has expanded since 2017, a flat percentage applied to a larger base produces more total originations. Funders experience this as higher application volume even though market penetration has not changed.
How does asynchronous bank verification speed up MCA underwriting?
Asynchronous bank verification allows merchants and brokers to upload documents through a secure portal at any time, eliminating the back-and-forth email exchanges that typically delay application intake. Instead of waiting for a live handoff, the funder's team receives complete document packages in a centralized dashboard, ready for AI-powered extraction and human review. This can compress the intake timeline from several days to a matter of hours.
What should funders look for in bank verification software?
Funders should prioritize five capabilities: asynchronous document collection via secure upload links, AI-powered data extraction with configurable fields, human-in-the-loop review workflows, CRM integration for structured data output, and immutable audit trails that log every action from upload to approval. Platforms that deliver all five, such as Let's Submit, provide the infrastructure needed to scale originations without proportionally increasing headcount.
Does flat MCA adoption mean the market is saturated?
No. Flat adoption as a percentage of all small businesses does not indicate saturation. It means that MCA products serve a consistent segment of the market, primarily businesses that cannot access traditional bank financing or need faster capital deployment. Growth in this segment comes from the expanding small business population, deeper broker distribution networks, and platform-based lending partnerships that introduce MCAs to new merchant categories.
Conclusion
The Federal Reserve's steady 7% MCA adoption figure tells a story of market stability on the surface. Underneath, absolute deal volume is climbing, institutional capital is demanding higher operational standards, and funders that rely on manual bank verification are running out of room to grow. The verification bottleneck is not a future problem. It is a current one, and it widens with every new application that hits a crowded inbox.
Let's Submit was built for exactly this moment. One secure link for document collection, AI-powered extraction that handles the heavy lifting, and a complete audit trail from submission to approval. Visit letssubmit.ca to see how async bank verification fits into your workflow and start processing applications at the speed your capital partners expect.