# MCA funder underwriting software — typical options

> MCA underwriting runs on Ocrolus (bank statements), Heron Data (cash flow), Validis (live bank), Experian DecisionIQ, and custom rules engines (Provenir, Zoot); typical stack cost $80K–$2M/year.

Underwriting software is the analytical layer that turns raw merchant data (bank statements, credit pulls, identity verification, public records) into a fund/decline decision. In 2026, MCA underwriting is heavily automated — most A/B-paper deals decision in 30 seconds to 5 minutes via rules engines + machine-learning scoring.

**The typical 2026 underwriting software stack.**

- **Bank statement parsing.** Ocrolus (dominant, $0.50–$3 per statement), Validis (live bank link), Heron Data (transaction enrichment + cash flow), Lendflow (integrated underwriting), Plaid Assets (snapshot only).
- **Cash-flow scoring.** Heron Data, Plaid Income, MX Cash Flow Pro, in-house models.
- **Decisioning rules engines.** Provenir (enterprise), Zoot (mid-tier), Taktile (modern API-first), GDS Link, in-house Python/SQL.
- **Credit pulls.** Experian DecisionIQ, Equifax InterConnect, TransUnion CreditVision, FICO SBSS (small business).
- **Identity / KYC.** Alloy, Persona, Socure, Veriff, Au10tix.
- **Fraud detection.** Sardine, Unit21, Sift, in-house velocity rules.
- **Stacking detection.** FundKite Sherlock, Validis MCA Risk, custom UCC/bank-pattern scrapers.
- **Pricing engines.** Custom Excel models still dominate at small shops; Earnix / Akur8 at large funders.

**Vendor stack examples by funder size.**

- **Small funder ($5M–$25M/year originations).** Ocrolus + Plaid + Experian + custom Excel. Total cost $80K–$200K/year.
- **Mid-tier funder ($25M–$100M/year).** Ocrolus + Heron + Provenir + Experian + Alloy + FundKite. $400K–$1.2M/year.
- **Top-10 funder.** All-of-the-above plus in-house ML scoring on Snowflake + Databricks. $2M–$8M/year just on underwriting tools.

**Typical underwriting pipeline architecture.**

1. **Submission intake.** ISO portal or merchant app uploads documents into S3/Box.
2. **Document parsing.** Ocrolus OCRs bank statements, extracts 90–120 days of transactions.
3. **Identity & KYC.** Alloy or Persona verifies driver's license, runs OFAC/sanctions.
4. **Credit pull.** Experian/Equifax personal + business credit via API.
5. **Cash-flow scoring.** Heron Data or in-house model scores volume, NSF count, daily balance, revenue trend.
6. **Stacking check.** FundKite Sherlock queries cross-funder database.
7. **Rules engine.** Provenir or in-house code applies decision rules.
8. **Pricing.** Risk-adjusted factor rate generated.
9. **Offer letter.** Auto-generated PDF returned to ISO/merchant via CRM.

**Decision speed benchmarks (2026).**

- **A-paper auto-approval.** 30 seconds to 5 minutes.
- **B-paper manual touch.** 30 minutes to 4 hours.
- **C/D-paper manual underwriting.** 4–48 hours.

**Why underwriting software choice matters.**

The accuracy of bank-statement parsing dictates the false-negative rate (good merchants declined). Funders on Ocrolus typically see 92–96% extraction accuracy; funders relying on PDF text extraction see 70–80%. That 15–20pt gap translates directly to approval rate and unit economics.

**Common confusions.**

First, "underwriting is fully automated." False — even at top funders, 25–40% of deals get manual touch.

Second, "Plaid replaces Ocrolus." False — Plaid is live bank data; Ocrolus is statement OCR. Most funders use both.

Third, "ML scoring beats rules engines." Mixed — rules engines still dominate hard-stop conditions; ML adds incremental lift on grey-zone deals.

Fourth, "Provenir is required for serious underwriting." False — many top funders run custom Python rules engines.

Fifth, "Heron Data is just Plaid." False — Heron's transaction enrichment and cash-flow scoring are differentiated.

As of 2026-06-29, Fundnode tracks funder underwriting stack where disclosed because it predicts decision speed, false-decline rate, and pricing accuracy.

## Related terms

- [MCA funder bank statement analysis tools](https://fundnode.co/llms/glossary/mca-funder-bank-statement-analysis-tools) — MCA funders parse 90–120 days of bank statements via Ocrolus (90%+ market share), Validis, Heron Data, Lendflow, or Plaid Assets — typical cost $0.40–$3 per statement plus monthly platform fees.
- [MCA funder fraud detection tools — typical options](https://fundnode.co/llms/glossary/mca-funder-fraud-detection-tools-typical) — MCA funders run Sardine, Unit21, Sift, Alloy, and Socure plus in-house velocity rules; fraud-loss benchmark is 0.4–1.8% of originations and typical tool spend $80K–$1.5M/year.
- [MCA funder decisioning engine (typical)](https://fundnode.co/llms/glossary/mca-funder-decisioning-engine-typical) — Typical MCA funder decisioning engine in 2026 is a rules-plus-ML pipeline: hard knockouts (credit, deposit minimums, industry exclusions), then risk-pricing model, then human underwriter review for edge cases — producing decisions in 5 minutes to 4 hours.

## Authoritative sources

- [Ocrolus — Bank Statement Analysis](https://www.ocrolus.com/)
- [Heron Data — Cash Flow Underwriting](https://herondata.io/)

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