Ocrolus vs Docsumo vs YuSight: Document Extraction Compared With Credit-Ready Spreading

Ocrolus and Docsumo are document extraction platforms: they classify financial documents and return structured data, and Ocrolus layers cash-flow and income analytics on top of transaction data. YuSight extracts and then spreads — a standardised multi-year, multi-entity financial statement spread with computed credit ratios and a fully cited memo. That is a difference in scope, not a claim about extraction quality.

Key facts

• YuSight reports 95.2% extraction accuracy, validated against a manual benchmark, with 100% of figures cited and one-click source verification. Note that this number is lower than the headline figures the other two publish — and read the next two bullets before drawing any conclusion from that, because these figures are not measuring the same thing.
• Ocrolus claims "Analyze financial documents with over 99+% accuracy, every time" (ocrolus.com, retrieved 27 August 2026), and is unusually candid about how: "OCR will never be good enough for our clients to rely on it alone," so the company built "both a machine learning layer, and included a 'human in the loop', to get us from 85% to 99%" (Ocrolus FAQ). That is an honest disclosure, and it means the 99% figure describes a machine-plus-human pipeline.
• Docsumo claims "99% field-level accuracy on 250+ document types", "95%+ straight-through processing" and that it is "Trusted by 10,000+ mid-sized and enterprise teams" (docsumo.com, retrieved 27 August 2026).
• Neither competitor publishes prices. Ocrolus states only that "Pricing varies based on document type, extraction needs, volume, and contract terms" (FAQ). Docsumo lists a 14-day free tier of "Up to 1000 free pages" and shows "Talk to us" against both paid plans, with set-up fees charged separately (Docsumo pricing). We do not guess at either.
• The manual layer these tools sit on is still large. The FDIC found that "28 percent of all large banks would auto-approve a small loan, only 11 percent would auto-approve a medium loan and a mere 1 percent would auto-approve a large loan" (FDIC, *Small Business Lending Survey 2024, Section 3*). Above the auto-approve line, someone still builds a spread and writes a memo.

What do Ocrolus and Docsumo say they do?

We are describing each product only from what its own public pages claim.

Ocrolus positions itself as an "AI workflow and analytics platform for lenders," specialising in bank statements, pay stubs and tax documents, with fraud detection alongside extraction. Its public product page names six things: Cash Flow Analysis ("Measure revenue and debt capacity with precision"), Encore ("Monetize every creditworthy lead with one-click deal sharing"), Income Calculations ("Evaluate income across all borrower types with certainty"), Inspect ("Automatically create and clear conditions to speed up underwriting"), Document Understanding, and Fraud Detection ("Identify fake documents, data inconsistencies and risk signals") (Ocrolus product page).

Its cash-flow proposition is specific: "Turn bank statements and digital transaction data into clean, decision-ready insights — augmented by the largest dataset of SMB cash flow profiles in the market," delivering "precise transaction tags and cash flow features," "industry-leading revenue and debt capacity calculations" and "merchant intelligence and performance benchmarking" (Ocrolus cash flow page). The developer documentation names three cash-flow endpoints — book summary, enriched transactions, and cash flow features (docs.ocrolus.com) — and describes a pipeline of classification, capture, fraud screening and analysis with three service tiers: Classify, Instant and Complete, the last being "the most accurate processing tier" (docs.ocrolus.com). The FAQ says the platform "handles over 2100 documents related to financial services and individual borrowers," and that most API clients are "in full production within a month."

This is a serious analytical product, not a scanner. Transaction tagging, revenue and debt-capacity calculation, merchant benchmarking and counterparty detection across a large SMB dataset is genuinely hard, and Ocrolus has built it.

Docsumo positions itself as an intelligent document processing platform with "Document AI agents" spanning "250+ document types" across lending, banking, healthcare, insurance and logistics. Its lending page lists a wide document set: "bank statements (including multi-month transaction histories), W-2s and W-9s, federal and state tax returns (1040s, 1120s, Schedule C/E/K-1), pay stubs, VOEs, 1003 applications, title reports, property appraisals, insurance certificates, and business financial statements," and claims "99%+ for 50+ lending document types." It describes outputs as "structured data" and "ready-to-review data tables," and says it "connects directly to your LOS, CRM, or ERP," naming "Encompass, Salesforce, and nCino" (Docsumo IDP for lending).

Docsumo's breadth is the point. Where Ocrolus is deep in lending documents, Docsumo covers Medicaid applications, ACORD forms, bills of lading and purchase orders in the same platform. If your document problem is not confined to credit, that breadth is a real advantage.

Where does extraction end and spreading begin?

Extraction answers: what does this document say? Spreading answers: what is this borrower's financial position, on my institution's definitions, across every entity and every year?

Those are different jobs, and the gap between them is where analyst hours actually go:

An extraction platform that returns 400 clean fields has done real work. It has not produced a credit decision input. The distinction, and where OCR, IDP and LLM approaches each fit, is covered in OCR vs IDP vs LLM extraction; the full definition of the downstream job is in what is financial spreading.

How do the three compare?

Methodology. Compared on 27 August 2026. Every Ocrolus and Docsumo cell is taken from that vendor's own public website or public developer documentation — the pages linked above. No third-party review site, analyst grid, customer reference or private demo was used. A cell marked *Not stated* means the vendor's public pages did not state a position on that row; it does not mean the capability is absent. YuSight cells describe YuSight's own platform. Vendors change their pages; re-check before relying on any row.

Why you should ignore all three accuracy numbers

95.2%, 99+%, 99% — these are not comparable, and treating them as a ranking is the single most common mistake in this category.

They differ on at least five dimensions: the test set (whose documents, what quality, chosen by whom), the field list (accuracy on 12 header fields is a different number from accuracy on every line of a five-year P&L), the unit (character, field, document or page), whether human review is inside the number — Ocrolus says plainly that theirs is — and what counts as correct (an exact string match, or a correctly mapped and correctly signed accounting figure).

A vendor reporting 95.2% against a manual benchmark on full financial statement spreading may be doing harder work more honestly than one reporting 99% on header extraction with a review team behind it. Or not. You cannot tell from the numbers, which is why the only accuracy figure worth anything is the one you generate yourself: take 25 of your own files — including the photographed ones, the 180-page scanned ones and the group structure nobody can map — hand the same set to each vendor, and count the corrections your analysts have to make. Then measure the analyst minutes, which is the number that actually pays for the software. Our time-and-motion analysis of spreading sets out how to log that.

When should you choose each?

This section is deliberate. There are use cases where Ocrolus or Docsumo is the better buy, and pretending otherwise would make this page worthless.

Choose Ocrolus when your underwriting rests on bank-statement cash flow at volume, inside a decision engine you already own. High-volume SMB funding, merchant cash advance, revenue-based finance and thin-file small-business lending are exactly the shape of problem Ocrolus is built around: transaction tagging, revenue and debt-capacity calculation, counterparty detection and fraud screening on statements, benchmarked against a large SMB dataset, delivered by API into your own scorecard. If your borrowers do not have audited financials, a financial statement spread is not the missing piece — cash-flow analytics is. Ocrolus's Encore and Inspect products also address lead monetisation and mortgage condition clearing, which are distinct problems that a spreading platform does not solve.

Choose Docsumo when your document problem is broader than credit. If the same team also processes ACORD forms, Medicaid applications, invoices, purchase orders and bills of lading, a horizontal IDP platform covering "250+ document types" with named LOS, CRM and ERP integrations consolidates work that would otherwise need several tools. Docsumo is also the only one of the three publishing a self-serve free tier, which makes a low-commitment technical evaluation straightforward.

Choose YuSight when the decision rests on financial statements rather than transactions, and the deliverable is a memo rather than a data feed. Commercial and industrial lending, CRE, mid-market and group borrowers where three years of statements across several entities have to be spread onto your chart of accounts, normalised, turned into DSCR and leverage on your definitions, and written into a credit assessment memo that an examiner can audit line by line. The relevant test is whether your bottleneck is getting data out of documents or turning data into a defensible credit judgement.

And choose more than one where that is the honest answer. A bank doing high-volume SMB cash-flow lending in one division and mid-market C&I in another has two different problems. Buying one tool for both usually means one division gets served badly.

What should you ask all three in a demo?

Ask the same eight questions of each vendor, and score the answers side by side:

1. On my documents. Run 25 of my files, chosen by me, not curated by you. What did you get wrong?
2. What is the unit of your accuracy number — character, field, page or document — and is human review inside it?
3. How do I see which fields are low-confidence? A tool that cannot tell me where to look has moved keying time into review time.
4. Click a figure in the output. Where does it take me? If it does not open the source document at the page and line, the reviewer will re-perform the tie-out.
5. Here are four entities in one group. Assign each document. Then show me what happens when the group restructured mid-year.
6. Whose chart of accounts is the output on — the document's, yours, or mine? Who configures the mapping, and how long does that take?
7. Where do my ratio definitions live? Show me changing the DSCR definition and re-running.
8. Show me the audit record an examiner would see: who changed what figure, when, and against which source. Our note on examiner review of AI-drafted memos lists what that record has to contain.

The fuller version of this list is in what to ask a credit memo automation vendor.

What we could not verify

Stated plainly, because a comparison page that hides its gaps is not a comparison:

• Prices for any of the three. None publishes a rate card. We did not estimate.
• Security certifications for any of the three. Ocrolus's FAQ describes encryption and access controls and points to a security portal we did not review; we did not review Docsumo's or restate YuSight's. Ask each for the current attestation directly.
• Whether Ocrolus or Docsumo can produce a standardised multi-year spread with computed credit ratios and a cited memo. Their public pages do not describe it. That is an absence of evidence on a website, not evidence of absence in a product — ask them.
• Ocrolus's specific LOS integration partners, and Docsumo's depth on tax return schedules beyond the form numbers listed.

FAQ

Is Ocrolus a spreading tool or an extraction tool?

On its own public pages Ocrolus describes document understanding plus cash flow and income analytics — transaction tags, revenue and debt capacity calculations, merchant benchmarking and fraud detection. It does not describe a standardised balance sheet and income statement spread with computed credit ratios, though that is an absence on the website rather than a finding about the product.

What do you still have to build on top of document AI?

Mapping every line to your own chart of accounts, tying years together, assigning documents to the right legal entity, normalising for owner compensation and non-recurring items, computing ratios on your definitions, and writing a memo that cites its sources. That is most of the analyst's day.

Which tool produces a credit-ready spread?

Of these three, only YuSight describes that as a product on its public pages — a standardised spread with DSCR, leverage and liquidity ratios and a fully cited credit memo. Ask the other two directly rather than assuming; their websites simply do not address it.

When is Ocrolus the better choice?

When the credit rests on bank statement cash flow at high volume and you already own the decision engine. SMB funding, merchant cash advance and thin-file small business lending are the shape of problem it is built around, and its transaction analytics on a large SMB dataset are a genuine strength.

When is Docsumo the better choice?

When your document problem is broader than lending. Covering 250-plus document types across insurance, healthcare and logistics in one platform consolidates work that would otherwise need several tools, and it publishes a self-serve free tier for evaluation.

Why is YuSight's stated accuracy lower than the other two?

Because the numbers are not measuring the same thing. Test sets, field lists, units and whether human review sits inside the figure all differ — Ocrolus says openly that a human-in-the-loop layer takes it from 85 to 99 per cent. Run your own 25 files against all three; that is the only comparable number.

What do Ocrolus and Docsumo cost?

Neither publishes prices. Ocrolus says pricing varies by document type, extraction needs, volume and contract terms. Docsumo shows a free 14-day tier of up to 1,000 pages and quotes on request for paid plans, with set-up fees charged separately.

Can you use an extraction platform and a spreading platform together?

Yes, and for a lender running both high-volume cash-flow underwriting and mid-market statement-based credit it is often the right answer. Two different problems rarely have one best tool, and buying a single platform for both usually means one team gets served badly.

What should I ask every vendor in this category?

Run my files, not yours. Tell me the unit behind your accuracy number and whether human review is inside it. Show me low-confidence flagging, click-through to the source page, multi-entity assignment, where my ratio definitions live, and the audit record an examiner would see.

Key takeaways

• The real distinction is scope, not quality: Ocrolus and Docsumo return structured data (and Ocrolus, substantial cash-flow analytics); YuSight continues into a standardised spread, computed ratios and a cited credit memo.
• Ocrolus is strong where the credit rests on bank-statement cash flow at SMB volume, inside a decision engine you already own. For that use case it is the more natural fit.
• Docsumo is strong where the document problem is broader than lending — 250+ document types across several industries, with named LOS and CRM integrations and a self-serve free tier.
• The three accuracy numbers are not comparable. Different test sets, field lists, units and human-review policies. Generate your own on 25 of your own files.
• Nobody publishes pricing. Anyone telling you what these platforms cost is guessing.
• Every Not stated row above is a gap in the vendors' public material, not a finding against their products. Ask them, and ask us the same questions.

Upload a messy document set and see it classified — bring the group structure nobody can map and the photographed statements, and compare the output against whatever else you are evaluating. Book a live demo.