Sovetta.

Underwriting intelligence for working-capital finance

Every statement, read like evidence.

Sovetta parses a merchant's bank statements natively, verifies the math to the penny, screens every page for tampering, and maps each existing advance — a complete decision file in minutes.

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560+bank statement formats parsed natively
350+visual fingerprints of genuine statements
490+funders tracked for position detection
Minutesfrom submission to decision file
The platform

Five gates. Nothing gets waved through.

Every deal runs the same sequence. A failure at any gate stops the line and tells you exactly why — no black-box scores, no maybes.

GATE 01

Document forensics

Before a single number is read, every PDF is authenticated — producer chain, creation history, editing software traces, and file structure. A statement that has been touched by a consumer editor never reaches underwriting.

GATE 02

Statement integrity

Deposits, withdrawals, and daily balances must reconcile to the penny — within each statement and across months. Numbers that don't add up are a finding, not a rounding error.

GATE 03

Collections screen

Collection agencies, payment reversals, and legal-action signals surface immediately — the deal-killers you'd otherwise find three weeks after funding.

GATE 04

Merchant underwriting

Liquidity, real revenue, existing positions, stacking behavior, and payment burden — measured from the transactions themselves, not from what the application claims.

GATE 05

Credit risk

Owner and business credit read with the same discipline — trade lines, inquiries, and derogatory records folded into the same decision file.

We never auto-approve.  Sovetta's rules are rejection criteria. A deal that clears every gate lands with your underwriter, alongside the evidence — pricing stays a human decision.

Fraud defense

Edited statements look perfect. Until they're measured.

Modern statement fraud passes the eye test — matching fonts, rewritten totals, untouched layout. Sovetta doesn't use the eye test.

Metadata forensics

The file remembers what happened to it

Producer signatures, creation-vs-modification history, and tool chains are checked against how each bank actually generates statements. Re-exports, editor traces, and spoofed producers all leave marks.

TELL — bank PDF “printed” from a consumer editor
Mathematical proof

Forged numbers don't reconcile

Change one deposit and the daily balances, section totals, and month-to-month chain all have to be rewritten consistently. Almost nobody manages it. The math gate catches the ones who try.

TELL — summary says $48,210, ledger sums to $52,105
Visual fingerprinting

Compared against the genuine article

Each statement is measured against a library of 350+ fingerprints of authentic bank layouts — glyph positions, grid alignment, spacing. A rebuilt page never sits on the bank's own baseline grid.

TELL — amounts drift 0.4px off the bank's grid
Structural analysis

Fonts and structure under the microscope

Replaced fonts, injected text objects, mixed generation pipelines inside one document — character-level inspection finds surgery that visual review never will.

TELL — three fonts where the bank uses one
Industry intelligence

Built by people who price deals, not demos.

Position detection, stacking behavior, and payment burden aren't bolt-on features — they're the reason the platform exists.

Every position, mapped

Daily and weekly pulls from 490+ tracked funders are recognized in the transaction stream — including truncated descriptors, wire aliases, and renewals — and resolved into active positions with real burden math.

Revenue you can believe

Transfers, advance deposits, and pass-through activity are stripped out before revenue is computed. What's left is money the business actually earned.

Behavior, classified

Withdrawals are sorted into 26 categories — payroll, fuel, food, gambling, crypto — so character shows up in the file, not just cash flow.

An audit trail for every decision

Each finding traces back to the exact transaction, page, and rule that produced it. When a funder asks why, the answer is one click, not an investigation.

Security & sovereignty

Your deal flow is nobody's training data.

Sovetta runs on infrastructure we own. Statements are processed in-house, end to end — not shipped to a mosaic of third-party APIs.

Self-hosted by design

Parsing, fraud analysis, and underwriting run on dedicated hardware under our control. Merchant files aren't used to train third-party models — yours or anyone else's.

Deterministic, not vibes

The same statements produce the same decision, every time. Rules are versioned, thresholds are explicit, and every change is recorded.

Documented and accountable

Encrypted transport, scoped seats, immutable audit logs. The full picture is public in our Data Processing & Security Statement.

Try Sovetta

See your next deal through Sovetta's eyes.

Send us a live file. We'll walk you through the decision it produces — every gate, every finding, line by line.

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