Common Mistakes New MCA Companies Make With Bank Verification and Underwriting

Why New MCA Companies Keep Repeating the Same Mistakes

A recent analysis from Better Accounting Solutions, published by deBanked, laid out the operational and financial pitfalls that trip up new merchant cash advance companies. The list will feel painfully familiar to anyone who has worked the funder side of the business: sloppy accounting, mismanaged syndicator relationships, poor cash flow planning, and disorganized operations. What the article touched on but didn't fully unpack is that many of these problems trace back to a single root cause: weak MCA underwriting best practices, especially around bank verification and document intake.

The MCA industry is scaling rapidly. Stripe Capital alone originated 81,000 merchant cash advances and business loans in 2025, while Square Loans funded a staggering $7 billion to merchants in the same year. The market is clearly massive. But volume without discipline is a recipe for losses. New funders who rush to deploy capital without building a reliable underwriting backbone end up bleeding money to fraud, stacking, and deals that never should have been funded in the first place.

This article breaks down the specific bank verification and underwriting mistakes that sink new MCA companies, and provides a practical playbook for avoiding every one of them.

The Bank Verification Mistakes Killing New MCA Funders

Relying on Manual Bank Statement Review

The most common and most costly mistake new MCA companies make is reviewing bank statements by hand. An underwriter opens a PDF, scans through three to six months of transactions, manually calculates average daily balances, and enters numbers into a spreadsheet. This process is slow, error-prone, and impossible to scale.

When you're funding five deals a week, manual review feels manageable. At fifty deals a week, it collapses. Underwriters start skipping pages, misreading figures, or rushing through statements to keep up with volume. Fraud slips through. Stacking goes undetected. And the funder wonders why their portfolio performance deteriorated so quickly.

AI-powered bank statement analysis has moved past the experimental phase. In 2026, automated extraction tools can parse deposited amounts, identify NSF patterns, flag unusual transaction spikes, and calculate key metrics like average daily balance and monthly revenue in seconds rather than hours. Platforms like Let's Submit use AI-powered extraction to pull financials, business info, and owner details directly from uploaded documents, cutting the manual review burden dramatically. The question is no longer whether to automate bank statement review. It's how much you're losing every month by not doing it.

Inconsistent Document Collection From Brokers

New MCA companies typically rely heavily on ISO and broker channels for deal flow. That's normal. What's not normal, but extremely common, is having zero standardization around how documents arrive. One broker emails a scanned application as a JPEG. Another sends bank statements in three separate emails over two days. A third forwards an entire email thread with the actual documents buried in attachments from the fourth reply.

This chaos means underwriters waste time hunting for documents before they can even start reviewing them. Worse, incomplete submissions sit in limbo. The deal gets cold. The merchant signs with a faster funder. We've written extensively about why MCA lenders lose deals to slow application intake, and broker document chaos is one of the primary drivers.

The fix is straightforward: give every broker and applicant a single, secure upload link. All documents land in one place, organized and timestamped. Let's Submit was built specifically around this workflow. One link, all documents collected, no more chasing brokers for missing pages.

No Audit Trail for Verification Decisions

Early-stage MCA companies often operate informally. An underwriter reviews bank statements, gives a verbal thumbs up, and the deal moves to funding. There's no record of what was reviewed, what flags were identified, or why the deal was approved at a specific amount.

This becomes a serious problem in three scenarios. First, when portfolio losses spike and leadership needs to understand what went wrong. Second, when a syndicator or institutional partner audits your underwriting files. Third, when regulatory scrutiny intensifies, which the Consumer Financial Protection Bureau has signaled will continue expanding into alternative lending.

Building an audit trail from day one is not bureaucracy. It's survival. Every document received, every data point extracted, every decision made should be logged with timestamps and user attribution. This is table stakes for any funder that plans to be around in three years.

Ignoring Stacking Signals in Bank Statements

MCA stacking, where a merchant takes multiple cash advances simultaneously without disclosure, remains one of the industry's biggest sources of loss. New funders are especially vulnerable because they lack the pattern recognition that experienced underwriters develop over time.

The signals are in the bank statements: multiple daily ACH debits from different companies, sudden balance drops at predictable intervals, or deposits that immediately flow out to what appear to be other funder payments. Manual reviewers miss these patterns regularly, especially under volume pressure. AI-based transaction categorization can flag these automatically by recognizing common funder payment patterns across thousands of merchants. For a deeper look at how technology addresses this problem, our piece on preventing MCA stacking fraud with smarter bank verification covers the specific detection techniques that work.

Operational Workflow Gaps That Compound Over Time

Bank verification mistakes don't exist in isolation. They're usually symptoms of broader workflow problems that compound as the company grows.

Treating Underwriting as a Cost Center Instead of a Competitive Advantage

New MCA companies often view underwriting as overhead: something you do because you have to, not something you invest in strategically. This mindset leads to underfunding the underwriting function, hiring junior staff without proper training, and resisting technology investments that would pay for themselves within weeks.

The companies dominating this market understand that underwriting speed and accuracy are competitive advantages. Square Loans' near-zero non-performing loan rate didn't happen by accident. It happened because their underwriting infrastructure, built on proprietary data from millions of merchant transactions, is extraordinarily precise. Smaller MCA companies can't match that data scale, but they can close the gap by deploying AI extraction tools that handle the mechanical work and freeing their underwriters to focus on judgment calls.

Failing to Standardize Before Scaling

The deBanked article on common MCA mistakes highlights a pattern that every industry veteran recognizes: companies that grow fast without building operational infrastructure collapse under their own weight. In underwriting, this means establishing clear procedures for document intake, extraction, review, and decisioning before you scale your broker network or increase your funding capacity.

What does standardization look like in practice? It means every application follows the same journey: documents arrive through a defined channel (upload link or dedicated email inbox), AI extracts key data fields automatically, an underwriter reviews the extracted data against established criteria, and the decision is logged with full attribution. Platforms like Let's Submit provide this structure out of the box, with real-time tracking from submission through approval and AI-powered extraction that ensures consistency regardless of volume.

Poor Communication Loops With Applicants

Another pattern that kills new funders is the communication gap between document request and document receipt. An underwriter identifies missing bank statement pages and emails the broker. The broker emails the merchant. The merchant doesn't respond for three days. By then, the underwriter has moved on to other deals, and the original application sits in a forgotten queue.

Smart funders eliminate this friction by providing applicants with a self-service portal where they can see exactly what's needed and upload it directly. This removes the broker as a communication bottleneck for document collection and dramatically reduces time-to-complete. Building a scalable MCA application pipeline requires these kinds of structural fixes, not just more headcount.

What the Current Market Is Telling New MCA Companies

The 2026 MCA landscape is sending clear signals. On one end, massive platforms like Stripe Capital and Square Loans are proving that technology-driven underwriting at scale produces excellent portfolio performance. On the other end, the Saul Shalev fraud case, which prosecutors say involved lavish spending funded by industry fraud, reminds us that weak verification processes create openings for bad actors.

For new MCA companies sitting between these extremes, the path forward is clear. You don't need a $159 billion valuation to underwrite effectively. You do need a system that collects documents consistently, extracts data accurately, flags risks automatically, and creates an auditable record of every decision. These aren't nice-to-haves. They're the minimum requirements for sustainable operation in this market.

The funders who figure this out early, who build their underwriting infrastructure before they need it rather than after something goes wrong, are the ones that will still be around in five years. The ones who don't will join the long list of MCA companies that burned bright and flamed out because they confused deal flow with operational maturity.

Frequently Asked Questions

What are the biggest mistakes new MCA companies make?

The most damaging mistakes center on operational infrastructure rather than deal sourcing. Manual bank statement review that can't scale, inconsistent document collection from brokers, missing audit trails, and failure to detect MCA stacking are the top issues. These problems feel manageable at low volume but become existential as the company grows. Establishing standardized underwriting workflows and investing in automated document extraction early prevents the majority of these failures.

How do MCA lenders verify bank statements effectively?

Effective bank statement verification combines AI-powered extraction with human oversight. Automated tools parse PDF bank statements to extract average daily balances, monthly deposit totals, NSF counts, and transaction patterns. The AI flags anomalies like potential stacking activity or inconsistent cash flow patterns. An underwriter then reviews the flagged items and makes the final decision. This hybrid approach is faster and more accurate than purely manual review.

Why does document intake matter so much for MCA funders?

Document intake is the first bottleneck in every MCA deal. If bank statements, applications, and ID documents arrive through scattered channels in inconsistent formats, underwriters spend more time organizing files than analyzing them. Slow intake directly causes lost deals because merchants often sign with whichever funder responds first. A structured intake process with a single upload link and automated data extraction removes this bottleneck completely.

What should new MCA companies look for in underwriting software?

New MCA companies should prioritize four capabilities: structured document collection (secure upload links or dedicated email forwarding), AI-powered data extraction from bank statements and applications, real-time application tracking with status visibility, and a complete audit trail for every action. Integration with CRM systems is also valuable for keeping sales and underwriting teams aligned. Let's Submit offers all of these features in a platform designed specifically for MCA lenders.

Conclusion

Every MCA company starts small. The ones that survive are the ones that build strong operational habits before they need them. Bank verification, document intake, and underwriting workflow are not glamorous topics, but they're the foundation that separates funders who scale from funders who implode.

The mistakes outlined here are avoidable. Automated document extraction, structured applicant portals, real-time tracking, and audit-ready records are all accessible today without enterprise budgets or months of implementation. Let's Submit was built to solve exactly these problems for MCA lenders who want to process applications faster without sacrificing accuracy or compliance. Visit letssubmit.ca to see how a streamlined intake and verification workflow fits into your operation.