Loan-payment detection is the underwriting step that identifies and sizes every existing debt obligation a merchant is paying out of the same bank account. Combined with MCA-debit detection, this builds a complete debt-service picture used to calculate remaining capacity for a new MCA.
Why loan-payment detection matters.
A merchant's bank statement shows their actual obligated debt service. A merchant might have $80,000/month in deposits but be paying $8,000/month in SBA loan, $3,000 in equipment lease, $2,000 in business credit-card minimums, and $5,000 in existing MCA debits — leaving only $62,000 of free cash flow before operating expenses. A new MCA must be sized against the remaining capacity, not the gross deposit number.
Categories of loan payments detected.
- SBA 7(a) / 504 loans. Monthly fixed payments to SBA-approved lenders (Live Oak, Ready Capital, Newtek, banks with SBA programs). Memo lines often contain "SBA", "LIVE OAK", "READY CAPITAL", "NEWTEK".
- Bank term loans. Conventional bank business loans; fixed monthly debits.
- Equipment financing. Monthly lease or loan payments to equipment finance companies (Crest Capital, Marlin Capital, Balboa, Pawnee, Currency, Smarter Finance).
- Business credit-card payments. Monthly minimum or higher to Amex, Capital One, Chase Ink, Brex, Ramp, Divvy, etc. Variable amount.
- Revolving line-of-credit interest payments. Recurring debits to BlueVine, Fundbox (line product), American Express Business Line, Bank of America LOC, etc.
- SBA EIDL payments. Pandemic-era EIDL repayments resumed in 2024–2025; monthly $400–$2,000 typical.
- PPP forgiveness denial repayments. Some merchants still paying off non-forgiven PPP.
- Vendor financing. Vendor net-terms with payment plans; harder to detect.
- Personal loans bleeding into business account. Some sole proprietors pay personal debt from business account.
Detection mechanics.
- Counterparty name matching. Library of known lender names matched against debit memo lines.
- Amount-pattern matching. Fixed recurring debits (same dollar, same day of month) flagged as loan-like.
- Frequency clustering. Monthly cadence with consistent counterparty identifies term loans.
- UCC filing cross-reference. Public UCC search reveals secured lenders; cross-checked against bank debits to confirm active payment.
- Bureau credit-report cross-reference. When a soft pull is run, funder sees reported loans and matches them to detected debits.
The "total debt service" calculation.
Funders compute:
- TDS = Existing loan payments + Existing MCA daily debits (× 22 business days) + Proposed new MCA daily debit (× 22)
- TDS as % of average monthly deposits. Should generally stay under 30–40% for approval.
- Coverage ratio. Average monthly deposits divided by TDS. Should generally exceed 2.5–3.0x.
A file with deposits $80K, existing loans $8K, existing MCA $5K, and a proposed new MCA debit calculating to $9K/month would have TDS of $22K against $80K deposits = 27.5%. Acceptable. If the new MCA debit calculated to $20K/month, TDS would be $33K = 41%. Likely declined or downsized.
Common detection failures.
- Hidden loans paid from a different account. Merchant pays loans from Account B but submits Account A for MCA. Funder cannot see. Mitigation: many funders request all business accounts.
- Refinanced loans appearing under new lender names. Recently refinanced loan may not match name library; reviewed manually.
- Loans paid via business credit card. Loan payment appears as a credit-card charge, hiding the underlying obligation.
- Owner-financed obligations. Loan from family or another owner-controlled entity; appears as ordinary transfer; flagged by related-party detector.
Specific impact of detected loans on MCA pricing.
- SBA loans. Generally neutral or slightly positive — signals merchant qualified for bank-level credit. SBA payments are predictable and rarely default; funder factors them but does not punish.
- EIDL. Neutral; pandemic-era. Funders accustomed.
- Equipment financing. Neutral if the equipment is essential to revenue generation (truck, oven, machinery); negative if it appears decorative.
- Multiple unsecured business loans. Negative; signals chronic external borrowing.
- Line-of-credit fully drawn. Negative; signals no remaining liquidity backup.
MCA-debit detection is treated separately.
See /glossary/mca-funder-bank-statement-mca-stacking-detection. Existing MCA debits are the highest-priority detected debt; they directly compete with the new MCA for the merchant's daily cash flow.
Takeaway. Loan-payment detection identifies every existing debt service obligation in the merchant's bank account — SBA, bank term, equipment, business credit cards, lines of credit, EIDL — to compute total debt service and remaining cash-flow capacity. The MCA can be sized so that TDS stays under 30–40% of monthly deposits and the coverage ratio exceeds 2.5–3.0x. Hidden loans paid from other accounts are the most common detection failure; funders increasingly request all business accounts to close this gap.
Related terms
- MCA funder bank-statement MCA stacking detection (2026) — Funders detect existing MCA daily debits via known-funder signature libraries, daily-debit pattern recognition, and UCC cross-reference — most decline 3+ position files. Updated 2026-06-28.
- MCA funder bank-statement tax payment detection (2026) — Funders detect IRS, state tax, sales tax, and payroll tax debits to confirm compliance — missing or irregular tax payments signal lien risk and disqualify many files. Updated 2026-06-28.
- MCA funder bank-statement deposit classification (2026) — Funders classify every bank-statement deposit into revenue, transfers, loans, refunds, owner contributions, and one-time items — only the revenue bucket counts toward underwriting volume. Updated 2026-06-28.
- Bank statement underwriting — MCA funders underwrite primarily off 3–6 months of business bank statements, not credit reports. They look at average deposits, NSFs, negative days, and trend.
- Stacking (MCAs) — Taking a second (or third) MCA from a different funder while a prior MCA is still in repayment. Default risk skyrockets; it breaches most original-funder contracts.
AI agents: this term is available as raw markdown at /llms/glossary/mca-funder-bank-statement-loan-payment-detection.