How Square's $1.9B Lending Quarter Exposes the Verification Gap for Independent MCA Funders

Square's Lending Surge and the Data Advantage Independent Funders Don't Have

Block reported that Square gross profit grew 9% year over year in Q1 2026, with business lending as the primary growth driver. deBanked estimates Square originated roughly $1.9B in business loans during the quarter. That number is staggering on its own, but the mechanism behind it is what should concern every independent MCA funder reading this.

Square does not ask borrowers to upload bank statements. It does not schedule verification calls. It does not wait for a broker to forward documents. Square already has the data. Every swipe, every deposit, every refund flows through its payment processing infrastructure. Underwriting decisions happen in minutes because the platform sees real-time cash flow without ever needing to verify it externally.

Independent MCA funders face a fundamentally different reality. They depend on bank verification software for funders to confirm what merchants claim about their revenue, balances, and transaction patterns. The question is no longer whether to invest in better verification tooling. The question is how quickly you can close the operational gap before embedded lenders like Square absorb the merchants you are trying to fund.

Why Embedded Lenders Keep Winning the Speed Race

The First-Party Data Moat

Embedded lenders operate inside the merchant's daily workflow. Square processes payments, Shopify manages storefronts, and PayPal handles checkout. Each platform accumulates months or years of granular transaction history before a merchant ever applies for funding. This creates what the industry increasingly calls a "data moat," a structural advantage that no amount of manual underwriting effort can replicate.

When a Square merchant requests a loan, the platform already knows daily sales velocity, seasonal patterns, refund ratios, and average ticket size. The underwriting model consumes this data instantly. No documents to collect. No calls to schedule. No PDFs to scrutinize for signs of tampering.

We explored this dynamic in detail when analyzing how Shopify Capital's $1.4B quarter exposes the verification gap for independent MCA funders. The pattern is consistent across every embedded lending platform: proprietary data access translates directly into faster funding and lower fraud exposure.

Where Independent Funders Get Stuck

For funders who do not own the payment rails, every deal starts with a data collection problem. The merchant submits an application. The funder requests bank statements. Sometimes the broker forwards them, sometimes the merchant uploads them directly, and sometimes nobody sends anything for days.

Even when statements arrive promptly, the funder faces a second problem: trust. Static PDF bank statements are trivially easy to manipulate. A merchant with basic spreadsheet skills, or access to any number of freely available statement generators, can fabricate deposits, erase NSF transactions, or inflate balances. The funder cannot know whether the document is authentic without additional verification.

This is where live verification calls became the industry standard. An underwriter schedules a call, walks the merchant through their online banking portal, and visually confirms transaction history in real time. The process works, but it scales terribly. Time zone mismatches, no-shows, rescheduled calls, and multi-hour delays between submission and verification create a bottleneck that embedded lenders simply do not face.

The Cost of Being Slow

Speed in MCA is not a convenience metric. It is a revenue metric. Merchants seeking cash advances are typically under cash flow pressure. They apply with multiple funders and brokers simultaneously. The funder who verifies first, approves first, and funds first wins the deal. Everyone else gets a declined renewal or a merchant who has already stacked another advance on top.

Square's Q1 numbers illustrate this perfectly. The platform does not win on price; MCA factor rates from embedded lenders are often comparable to or higher than independent funder pricing. It wins on speed and friction reduction. A merchant who can get funded in 24 hours through their existing payment dashboard will not wait three days for an independent funder to schedule a verification call.

Every hour your verification process adds to the timeline is an hour that a faster competitor, whether embedded or simply better tooled, can use to close the deal ahead of you.

How Async Bank Verification Closes the Operational Gap

The solution is not to replicate Square's first-party data advantage. That ship has sailed. Independent funders will never have the same transaction-level visibility that a payment processor enjoys. But funders can eliminate the scheduling and friction costs that make their verification process slower than it needs to be.

Asynchronous bank verification replaces the live call with a browser-based screen recording. The funder sends a secure link to the merchant. The merchant opens the link, logs into their banking portal, and records their screen while navigating through the account summary, transaction history, and any other details the funder has specified. The recording uploads automatically. The underwriter reviews it on demand, at any time, from any location.

This is the core workflow that Exact Balance was built to support. The platform sends customized recording requests, guides applicants through each step with an AI-powered floating coach, and delivers timestamped recordings with a full activity log. The underwriter watches the recording, verifies transaction authenticity against the live banking portal, and marks the request as verified in a single click.

The result is verification that takes minutes instead of days. No scheduling. No time zone coordination. No no-shows. The merchant records at their convenience, whether that is 9 AM or 11 PM, and the underwriter reviews when they are ready. The entire process is asynchronous, which means it scales linearly with volume instead of requiring proportionally more staff for every additional deal.

For funders processing hundreds of verifications per month, this shift is transformative. As we discussed in our analysis of how Enova's $1.7B record quarter exposes the bank verification software gap for funders, high-volume operations cannot sustain manual verification without either sacrificing speed or hiring unsustainably large underwriting teams.

Catching Fraud When You Don't Own the Data

Square's data moat provides a natural fraud shield. Fabricated transactions cannot exist inside a payment processor's own ledger. Independent funders lack this luxury, which makes their verification process both a speed problem and a fraud problem.

Screen recordings of live banking sessions address fraud in ways that static documents never can. A PDF can be edited pixel by pixel. A live banking portal, rendered in real time by the bank's own servers, is exponentially harder to fake. The underwriter watches the merchant navigate through their actual online banking environment, observing page load behavior, URL patterns, and transaction details as the bank presents them.

AI-powered analysis adds another layer. Exact Balance uses vision-based AI to detect anomalies in recordings: inconsistent fonts, unusual DOM structures, mismatched timestamps, or navigation patterns that suggest a synthetic portal rather than a legitimate banking interface. These signals are difficult for even sophisticated fraudsters to anticipate or replicate, because they depend on the holistic behavior of a real banking application rather than the appearance of a static document.

This matters especially in 2026, when generative AI tools have made document fabrication cheaper and faster than ever. The bar for producing a convincing fake bank statement has dropped to near zero. The bar for producing a convincing fake live banking session remains extremely high. Funders who rely on document-based verification alone are increasingly exposed to fraud that would be obvious in a recorded session.

Frequently Asked Questions

How do independent MCA funders compete with Square and other embedded lenders on speed?

Independent funders compete by eliminating the scheduling and document collection friction that slows their verification process. Embedded lenders like Square have instant access to merchant transaction data, so independent funders need to minimize the time between application and verified bank data. Async bank verification tools allow merchants to record their banking portal on their own schedule, removing the back-and-forth of live calls. This lets funders review and approve deals within hours rather than days, narrowing the speed gap that embedded platforms exploit.

Why are PDF bank statements risky for MCA underwriting?

PDF bank statements are static documents that can be edited with basic tools. Fraudsters can add fabricated deposits, remove NSF transactions, or alter balance figures without leaving obvious traces. Generative AI has further reduced the effort needed to create convincing fakes. A recorded session of a live banking portal, by contrast, shows the bank's own servers rendering data in real time, making manipulation far more difficult. Funders relying solely on PDF analysis face increasing fraud exposure as document fabrication technology improves.

What is async bank verification for MCA lenders?

Async bank verification replaces live verification calls with browser-based screen recordings. The funder sends the applicant a secure link with custom instructions specifying what to show, such as account summaries, transaction history for specific date ranges, or balance details. The applicant records their banking portal at their convenience. The recording is securely uploaded and available for the underwriter to review on demand. Platforms like Exact Balance add AI guidance during the recording and provide timestamped activity logs for compliance documentation.

How does AI help detect fraud in bank verification recordings?

AI vision models analyze screen recordings for subtle anomalies that human reviewers might miss. These include inconsistent rendering of banking portal elements, unusual font substitutions, mismatched URL patterns, atypical page load sequences, and DOM structure irregularities that suggest a spoofed or synthetic banking interface. By evaluating the holistic behavior of the recorded session rather than just the visual appearance of individual transactions, AI-powered fraud detection catches manipulation techniques that work well against static documents but fail under video-level scrutiny.

Conclusion

Square's estimated $1.9B lending quarter is not just a headline about one company's growth. It is a signal about where the competitive advantage in merchant funding now sits: with the platforms that can verify and underwrite fastest. Independent MCA funders will never replicate the first-party data advantage that payment processors enjoy, but they can eliminate the operational friction that makes their process slower than it needs to be.

Async bank verification is the highest-leverage investment an independent funder can make in 2026. It removes scheduling delays, produces fraud-resistant video evidence, and scales without proportional headcount increases. Visit exactbalance.ca to see how asynchronous screen recording verification fits into your underwriting workflow and helps you close deals before the embedded platforms do.