How the RBF Coalition's Midterm Statement Reshapes AI Document Verification for Lending

A Political Signal MCA Funders Cannot Afford to Ignore

When the Revenue Based Finance Coalition issued its statement following the 2026 midterm elections, the language was diplomatic but the subtext was clear: a new legislative chapter is opening, and the coalition intends to shape it. Executive Director Mary Donohue congratulated victors across the aisle and signaled the coalition's readiness to engage incoming lawmakers on issues central to revenue-based financing and merchant cash advance regulation.

For MCA funders and ISO brokers, the statement is less about any single election outcome and more about trajectory. State-level commercial financing disclosure laws have already passed in Virginia, New York, California, and Utah. Federal interest has followed. Every new legislative session brings fresh proposals, and newly elected officials arrive with fresh agendas. The coalition's proactive posture suggests it expects accelerated activity, not a slowdown.

What does this have to do with AI document verification for lending? Everything. Each new disclosure rule, documentation requirement, or underwriting transparency mandate raises the bar on what funders must prove about their process. The days of reviewing bank statements on a screen and keying numbers into a spreadsheet are ending, not because the technology demands it, but because regulators and capital markets partners will.

This article breaks down what the coalition's signal means for document verification workflows, how AI-powered extraction creates the audit trail that regulation rewards, and why the funders moving fastest on automation will be the ones best positioned when new rules arrive.

Why the Legislative Landscape Is Tightening Around Verification

State-Level Disclosure Momentum

The pattern is unmistakable. Since New York passed its commercial financing disclosure law in 2020, a cascade of states has followed with their own versions. Virginia now has 229 registered MCA providers navigating its regulatory framework. California's SB 1235 created APR-equivalent disclosure obligations for commercial financing. Connecticut introduced its own commercial financing bill in 2026. Each law differs in detail, but the common thread is a demand for documentation: what was disclosed, when it was disclosed, and what data supported the underwriting decision.

For funders operating across multiple states, the compliance surface area grows with every new law. A deal funded in New York requires different documentation than one funded in Virginia or California. The merchant's bank statements, the extracted revenue figures, the calculated repayment burden: all of it must be captured, stored, and retrievable. As we explored in our analysis of Connecticut's commercial financing bill and its impact on bank verification software, the trend is toward more documentation, not less.

Federal Attention Is Building

The RBF Coalition's midterm statement did not exist in a vacuum. The CFPB's Section 1071 rulemaking, while currently excluding MCAs from its small business data collection mandate, established the infrastructure for future expansion. The coalition's engagement with incoming lawmakers suggests it anticipates federal proposals that could touch revenue-based financing directly, whether through disclosure requirements, data collection mandates, or consumer-protection-style rules applied to commercial transactions.

Funders who treat verification as an afterthought will find themselves scrambling when federal rules arrive. Those who have already built automated, auditable workflows will simply point to their existing systems.

Capital Markets Are Asking the Same Questions

Regulation is not the only force pushing funders toward better documentation. Capital markets participants, from warehouse lenders to securitization investors, increasingly demand granular data on underwriting quality. KBRA's recent ratings on OnDeck securitization tranches scrutinize origination practices. Investment-grade note offerings from firms like Fund Street and Fundworks require demonstrable rigor in how merchant cash flows are assessed. The message from every direction is the same: show your work.

How AI Document Verification Creates the Audit Trail Regulators Want

From Manual Review to Machine Extraction

Traditional MCA underwriting relies on a human reviewing four months of bank statements, identifying deposits, flagging NSFs, estimating average daily balances, and typing numbers into a spreadsheet or CRM. This process is slow, error-prone, and nearly impossible to audit at scale. When a regulator or capital markets partner asks "how did you arrive at this revenue figure," the answer is often "someone looked at it."

AI document verification replaces that ambiguity with structured, repeatable output. When a merchant uploads bank statements through a platform like Let's Submit, AI extraction parses the documents automatically. Revenue, deposits, average daily balance, NSF counts, and time-in-business indicators are pulled into a clean application record. Every field traces back to a specific page and line in the source document. That traceability is exactly what compliance teams need when regulators come asking.

Async Collection Reduces Friction Without Sacrificing Rigor

One of the practical challenges funders face is getting documents from merchants in the first place. A merchant running a contracting business or auto shop does not have time to sit on hold, email scanned PDFs, or fax bank statements. The result is friction, and friction kills deals.

Asynchronous document collection solves this by letting merchants upload bank statements, IDs, void cheques, and signed applications from their phone or computer at any time. Let's Submit generates a secure upload link that Sabbie, the platform's AI sales rep, can text directly to the merchant during the initial conversation. The merchant uploads on their schedule. The AI extracts the data. The funder's team reviews a clean, structured record without ever having to chase paperwork.

This async model does not just improve speed. It improves compliance posture. Every upload is timestamped, encrypted in transit and at rest, and stored with role-based access controls. When a state regulator asks for the documentation behind a specific deal, the funder can produce it in seconds, not days.

Fraud Detection as a Compliance Layer

Regulatory scrutiny does not stop at disclosure. Legislators and enforcement agencies are increasingly focused on whether funders are doing enough to detect fraud in the applications they approve. A competitor in the document verification space recently reported that one in eight SMB loan applications contain suspicious documents. That statistic will not go unnoticed by regulators crafting new rules.

AI-powered document verification catches inconsistencies that human reviewers miss: font mismatches in bank statement PDFs, deposit patterns that do not align with stated revenue, balances that reset too cleanly at month boundaries. These are the signals that separate a legitimate merchant from a fabricated application. As we detailed in our piece on how MCA lenders detect fabricated bank statements with AI document verification, the technology exists today to flag these anomalies automatically.

A Lending Recovery Colliding With Regulatory Pressure

LendingTree's Q3 earnings call added an important data point to this picture. CEO Scott Peyree confirmed that Q2 2026 was a trough for small business lending performance and that the company saw strong sequential growth heading into Q3, with a path back toward the all-time highs of late 2025 and early 2026. That recovery means higher application volumes flowing to MCA funders and ISO brokers in the months ahead.

Higher volume arriving at the same moment that regulatory scrutiny intensifies creates a stress test for every funder's operations. Manual verification workflows that barely kept up during the Q2 slowdown will buckle under Q4 and Q1 demand. The funders who automated their document collection and extraction during the slower months will process the surge cleanly. Those still relying on manual review will face a choice between speed and rigor, and either choice costs them.

Square Loans offers a useful benchmark here. The platform has consistently beaten its 4% loss target for over a decade, a feat that depends on disciplined, data-driven underwriting applied at massive scale. Independent MCA funders do not have Square's embedded transaction data advantage, but they can close the gap with AI-powered document verification that extracts the same cash flow signals from bank statements. The alternative is falling further behind platform lenders who automate by default, a dynamic we examined in our analysis of Square's sub-4% loss rates and what they prove about AI underwriting for merchant cash advance.

The convergence is stark. Regulation is demanding better documentation. Capital markets are demanding auditability. Application volumes are rising. And the technology to meet all three demands is already available. The question for every MCA funder in late 2026 is not whether to adopt AI document verification, but how quickly they can get it running.

Frequently Asked Questions

How does AI document verification help MCA lenders with compliance?

AI document verification creates a structured, auditable record for every merchant application. When bank statements are parsed by machine learning models rather than reviewed manually, each extracted data point (revenue, deposits, NSFs, daily balances) traces back to a specific location in the source document. This traceability allows funders to respond quickly to regulatory inquiries, produce documentation for state disclosure requirements, and demonstrate to capital markets partners that underwriting decisions are grounded in verifiable data rather than subjective judgment.

What does the RBF Coalition's midterm statement mean for MCA funders?

The statement signals that the Revenue Based Finance Coalition expects increased legislative activity around commercial financing in the coming sessions. New lawmakers bring new priorities, and the coalition is positioning itself to influence those conversations. For funders, this means preparing for potential new disclosure, documentation, or data collection requirements at both state and federal levels. Building automated verification workflows now is the most practical way to prepare for rules that have not yet been written.

Can async document collection improve MCA deal speed?

Yes. Asynchronous document collection lets merchants upload bank statements, IDs, and signed applications on their own schedule through a secure link sent via text or email. This eliminates the back-and-forth of phone calls, faxes, and email attachments. Platforms like Let's Submit pair async collection with AI extraction so that by the time a funder's team reviews a file, the data is already structured, cleaned, and ready for underwriting. The result is faster time-to-funding without sacrificing verification quality.

Why is this a critical moment for MCA verification automation?

Three forces are converging. First, state-level commercial financing disclosure laws continue to expand, with new legislation introduced in multiple states during the 2026 cycle. Second, small business lending volumes are recovering from their mid-year trough, meaning funders face rising application counts. Third, capital markets investors are demanding greater transparency in origination data as securitization activity grows. Funders who automate document verification now position themselves to handle all three pressures simultaneously.

Conclusion

The Revenue Based Finance Coalition's midterm statement is a signal, not a surprise. Regulation of MCA and revenue-based financing has been building for years, and the next legislative chapter will bring new documentation and disclosure demands. Funders who rely on manual bank statement review will find themselves exposed: unable to scale with recovering volumes, unable to produce audit trails for regulators, and unable to meet the data standards that capital markets partners require.

AI document verification for lending is the infrastructure that meets all of these challenges at once. Automated extraction, async collection, encrypted storage, and structured output turn every merchant file into a compliance-ready record.

Let's Submit gives MCA funders and ISO brokers the tools to collect documents by upload link, extract key fields with AI, and push clean applications to funders or CRMs. Visit letssubmit.ca to see how async verification fits into your workflow before the next wave of regulation arrives.