The Same Application, Different Verdicts
A merchant declined by one funder and approved days later by another is not unusual, and it is not evidence that either funder made a mistake. Per Forbes’s August 2026 reporting on algorithmic small-business lending decisions, a rejection from an underwriting model optimized for one risk profile says relatively little about how a differently built underwriter will read the same business’s application. Different funders are, in a real sense, asking different questions of the same numbers.
The Fed’s Own Numbers Show How Wide the Gap Already Is
The same Forbes reporting cites Federal Reserve data showing small banks fully approved 57% of applicants, the highest full-approval rate of any lender category tracked, well above MCA’s 48% and business lines of credit’s 45%, both already established figures in this research base. That is a meaningful gap before any individual funder’s specific quirks even enter the picture, driven by lender category alone: a community bank’s underwriting model is simply built differently than an MCA funder’s or another bank’s.
If categories that broad produce a 12-point swing on their own, funder-to-funder variance within the MCA category specifically is a genuinely reasonable thing to expect, not a red flag when it shows up on a specific file.
Borrowing a Concept From Mortgage Lending: The Overlay
Mortgage lending has a well-documented version of this exact phenomenon, called an overlay, per Bluefield Group’s explanation of why two mortgage lenders can give different answers to the same borrower. An overlay is a lender’s own additional, stricter criteria layered on top of a baseline program’s published guidelines, meaning two lenders working from the identical underlying loan program can still reach different decisions because each has quietly added its own extra filter on top.
No MCA funder publishes its own overlay criteria the way this gets documented in mortgage lending, so this comparison should be read as an explanatory parallel for the underlying mechanism, not a specific claim about how any individual MCA funder’s process works. The concept, a baseline standard plus an individual lender’s own added filter, is the useful part, even without an MCA-specific dataset to point to directly.
What This Means for Building a Funder Panel
A decline from one funder is data about that funder’s specific model, not a verdict on the merchant. That is the practical reason a broker working a panel of several funders, rather than relying on a single relationship, has a real structural advantage: a merchant who does not fit one underwriter’s model may fit another’s cleanly, for reasons that have nothing to do with the merchant’s actual creditworthiness changing between submissions.
How to Talk to a Merchant Who Got Declined Once Already
A merchant who hears a decline once often assumes the door is closed everywhere, and a broker who explains the overlay-style concept honestly, different underwriters weigh the same numbers differently, is giving that merchant a genuinely more accurate picture than either blind resubmission with no context or simply giving up after one no. The honest version of this conversation treats a single decline as information about one funder’s model, not a final verdict on the deal.
Sources
The external data in this article draws on the sources below. Figures described in the text as estimates or industry triangulations are directional and are not attributed to a single dataset.
- Forbes, An Algorithm Is Reading Your Loan Application. You Can Still Ask Why
- Bluefield Group, Understanding Lender Overlays: Why Two Mortgage Lenders Give You Different Answers