Underwriting intelligence for MCAs and ISOs

The true-revenue layer for MCA underwriting.

Vyaso re-underwrites every bank statement in 90 seconds. It surfaces loan stacking, account kiting, and revenue inflation before funds wire — and gives committees a number they can defend.

Runs on top of Ocrolus · Heron Data · Validis · raw PDF or CSV uploads

Your parser tells you what each transaction is.
Vyaso tells you what they add up to.

The same statement, two ways of reading it.

What your parser sees

04/03    ACH CREDIT ACME CORP                   +$48,000.00
04/12    TRANSFER FROM SAVINGS                 +$30,000.00
04/19    DEPOSIT QUICKFUND CAPITAL            +$42,000.00
04/24    DEPOSIT VELOCITY LENDING LLC          +$38,000.00

Total deposits: $158,000.00. Looks like revenue.

What Vyaso sees

04/03    ACME CORP+$48,000.00
Real customer revenue. Counterparty resolves to a known B2B client across multiple statements.
04/12    TRANSFER FROM SAVINGS+$30,000.00
Account kiting. The same money counted twice.
04/19    QUICKFUND CAPITAL+$42,000.00
Lender deposit. Not customer revenue.
04/24    VELOCITY LENDING LLC+$38,000.00
Loan stacking. A second lender in a short window.

Adjusted revenue: $48,000. One of four credits is real.

Why now

MCA underwriting got harder in 2024.

MCA default rates climbed through 2024 and into 2025 as pandemic-era expansion cohorts matured into repayment. Funders that lent against gross deposits are absorbing the delta now, in collections. Industry estimate¹

Loan stacking has gotten harder to spot. Lender deposits are routinely described to look like platform payouts or customer ACH. The keyword-only detection that worked five years ago no longer does. Industry estimate¹

AI-generated forged bank statements became trivial in 2024. Font drift, balance breaks, and metadata anomalies are signals a parser does not surface. They need a forensic layer. Industry estimate¹

The intelligence that worked five years ago does not work for the files arriving today.

Designed for how MCA portfolios actually default.

Speed

~90s✓ verified

Per file, end to end.

Replace 60–90 minutes of manual review per applicant. Industry estimate¹

Accuracy

8–25%Vyaso benchmark

Typical adjusted-revenue delta.

The amount Vyaso strips out of gross deposits to land on a number you can defend in committee.

Vyaso benchmark across the pilot corpus to date. Per-file delta varies; some files show no delta, others exceed 50%.

Coverage

9✓ verified

Detection layers.

Symmetric flows, graph cycles, window dressing, statistical anomalies, counterparty risk, loan stacking, account kiting, daisy-chain inflation, and PDF integrity. Every credit passes through all of them.

Built for both sides of the deal.

Funders re-underwrite every file. ISOs route every applicant to the funder whose box the real revenue actually fits.

For MCA funders

Re-underwrite every file in 90 seconds.

Stop funding stacks. Re-underwrite every file at the same speed: clean files clear in seconds, risky ones surface before the funds wire.

  • Adjusted revenue you can defend in committee
  • Loan-stacking and kiting flags ranked by severity
  • Executive summary, paste-ready to credit memo

For ISOs and brokers

Submit smarter. Decline less.

Pre-screen every applicant before submission. Match the file to the funder whose box the real revenue fits. Protect your reputation by never sending a stacked merchant.

  • True-revenue figure before you submit
  • Stacking and kiting visibility on first read
  • Funder-routing intelligence built on the same analysis underwriters trust

How a file moves through Vyaso.

01

Upload

Drop the bank statement PDFs or CSVs. Optional: company domain.

02

Auto-classify

Vyaso detects the merchant's industry and tunes the analysis automatically.

03

Re-underwrite

Every credit passes through nine detection layers and an agentic synthesis step.

04

Receive

Risk score, adjusted revenue, ranked flags, network graph, revenue waterfall, and an executive summary.

Median time end-to-end: ~90 seconds. ✓ verified

The five patterns we keep seeing.

Every MCA portfolio has them. Most underwriting tools don't.

PatternWhat it looks like
Loan stackingMultiple lender deposits arriving in a short window.
Account kitingSelf-transfers between the merchant's own accounts inflating deposit volume.
Circular B2B counterparty launderingMoney moving through three or more counterparties in a tight loop and returning to the merchant.
Daisy-chain inflationThe same flow stretched out over weeks, evading short-window detectors.
Forged statementsPDFs that look real but were generated outside bank software, with font drift, balance breaks, or telltale metadata.

Each pattern maps to a dedicated detection layer. See the platform page for what catches what.

Vyaso runs on the data your stack already produces.

If you already use Ocrolus, Heron Data, or Validis, Vyaso reads their output and re-underwrites it. Raw PDF and CSV upload also work today. API integrations with these parsers are available in the pilot program. Roadmap

Run Vyaso on your portfolio.

Free 30-day pilot. Bring 50–100 files. We'll show you what the model would have flagged, what would have been approved, and how the adjusted revenue compares.

No commitment. No setup fee.

Design partners

Working with funders and ISOs through the pilot program.

An East Coast MCA fund
A top-50 ISO
A regional MCA portfolio
An ISO with national footprint
A specialty-finance lender

Logos shown after pilot completion and partner approval. Currently anonymized by mutual agreement.

Frequently asked.