Bank statement processing that makes reconciliation fast

Reconciliation only moves as fast as the statements get transcribed. Bank statements come in a hundred layouts, often as scans, and every transaction has to line up against the ledger. Dynamite Docs turns the statement into rows you can reconcile instead of a PDF you squint at.

Try this workflow free or view pricing.

Statements are designed for humans, not for books

Every bank formats transactions differently. Dates, descriptions, amounts, and running balances sit in different places on every layout.
Scanned statements have no text layer, so traditional PDF tools read nothing.
Retyping transactions is error-prone in exactly the way that hides from a quick glance: transposed digits, missed fees, mis-copied balances.
A bookkeeper juggling several clients sees three or four bank layouts on a single morning.

How Dynamite Docs handles bank statement processing

01 — Upload any statement

Digital PDFs parse deterministically from their text layer; scanned or photographed statements are read by the vision model you choose.

02 — The transaction schema is inferred

Date, description, debit/credit, amount, running balance, and reference are pulled from the layout automatically, no per-bank templates.

03 — Verify the few low-confidence rows

Confidence scores flag the transactions worth a glance. Corrections become patterns, so the second statement from the same bank extracts cleanly the first time.

04 — Reconcile with clean data

Export to Excel, CSV, or JSON, or push rows into your bookkeeping workflow with the API and webhooks.

Document types this workflow handles

Bank statement PDFs — digital statements parsed from the text layer
Scanned statements — read by the vision model you choose
Multi-page statements — each page consumes one page-equivalent
Foreign-format statements — US, UK, EU, AU, and IN layouts

What gets extracted from a bank statement

Inferred per layout. A typical statement run yields:

Transaction date — 2026-07-28
Description — ACH DEP PINNACLE MARKETING
Type — Debit
Amount — $248.90
Running balance — $12,406.51
Reference — A-9901247
Opening / closing balance — $14,180.20 / $13,410.35

A realistic example

A statement extracts to rows like these, ready for reconciliation against your ledger:

Date	Description	Type	Amount	Balance
2026-07-27	DIRECT DEP PAYROLL	Credit	+$8,250.00	$14,180.20
2026-07-28	ACH DEP PINNACLE MARKETING	Debit	−$248.90	$13,931.30
2026-07-29	VISA PURCHASE COFFEE ROASTERS	Debit	−$12.75	$13,918.55
2026-07-30	ACH WITHDRAW QUARTERLY INSURANCE	Debit	−$508.20	$13,410.35

Reconciliation is where statements become books

A statement is only useful when its transactions line up against the ledger, and that matching depends on clean, complete rows: the right date, the right description, the right debit or credit, and a running balance that ties out. Retyped statements undermine that. A transposed digit or a dropped fee hides in plain sight and surfaces later as a mystery variance. Statements pile up on both sides of month-end; processing them as they arrive keeps the close from starting behind.

Statement extraction changes the shape of month-end. The statement becomes rows the moment it is uploaded; low-confidence transactions surface for a glance; and corrections are remembered, so the second statement from the same bank extracts cleanly. For a bookkeeper juggling multiple clients, that is the difference between a morning of transcribing and a morning of reviewing.

It also matters which model reads the scans. Statements are financial data your clients trust you with, so being able to lock processing to no-training providers, or run it fully local with Ollama, keeps that trust intact while the automation still happens. Clean digital statements parse deterministically for free; your own vision key handles the scans at your provider’s rate.

Begin with the accounts you reconcile most often. Once their layouts are remembered, the per-account cost drops to near zero, and month-end closes in hours instead of a weekend.

Why bring-your-own-AI matters for statements

Client statements are sensitive financial data. Dynamite Docs is explicit about which providers train on your data, locks sensitive documents to no-training providers, and can run fully local or air-gapped when your client agreement demands it.

Scanned statements are a vision-model problem and clean PDFs are a deterministic one. Pick your own model for the scans, pay your provider’s rate, and let the free deterministic path handle the rest.

Your bank-layout corrections are remembered, so statement processing gets faster across your whole client list. The knowledge stays in your workspace, not in someone else’s model.

Questions, answered

Does it handle statements from banks outside the US?

Yes. The schema is inferred from the layout, so UK, EU, AU, and IN formats work without templates, including currencies, date orders, and column arrangements.

Can it read scanned statements?

Scans and photos are read by the vision model you choose. For statements without a text layer that is the only option, and it works well.

How do I get the data into my bookkeeping software?

Export to CSV, JSON, Excel, Word, or Sheets, or push rows with API tokens and webhooks into whatever you reconcile in.

Is this different from credit-card statement processing?

Yes. Bank statements are your operating account (dates, balances, ACH). Credit-card statements have merchant names, post dates, categories, fees, and payment info. Both are supported, with separate pages.