Bank Parser

About Bank Parser

Bank Parser is an accounting data infrastructure product built by engineers for accountants.

We treat bank statements as transaction systems — not documents to OCR. Every supported bank has a dedicated parser hand-tuned to that bank's exact statement format. The output is a structured 17-field transaction model designed for accounting workflows, not generic data extraction.

Why Bank Parser Exists

The accounting profession has lived for decades with a structural gap: banks issue PDF statements for human reading, but accounting systems require structured transaction data. Generic PDF-to-table tools handle the first 80% of that gap well — and break down on the last 20%, which is where reconciliation, categorization, and audit-readiness happen.

Bank Parser was built to close that last 20%. Not as a general-purpose document processor, but as a category-specific tool with deep knowledge of how each major bank formats its statements, how those formats change over time, and how the resulting data needs to be structured for downstream accounting use.

The product is opinionated: it cares about balance reconciliation, categorical consistency across files, and producing the same column structure every time. That opinion comes from talking to bookkeepers and CPAs whose workflows broke when generic tools produced inconsistent output across clients.

Engineering Principles

Specialized over generic

Each supported bank has a dedicated parser built around that bank's actual PDF format — including format changes spanning a decade. No generic OCR. No heuristic table detection. Format-specific logic, validated against real statements.

Balance reconciliation as primitive

Every parser includes balance verification. Opening balance plus transactions must equal closing balance to within $0.01. Extraction errors are caught before they reach the accounting system, not after.

Structured 17-field output

Every transaction is reconstructed with the same 17 fields — date, type, amount, original description, balance, counterparty, payment code, IRS Schedule C category, channel, normalized description, EIN, merchant ID, transaction ID, source bank, account type, account number. Consistent across all files, all clients.

Pay-as-you-go, not subscription

Pricing matches usage: per-transaction billing without monthly minimums. Built for the seasonal patterns of real bookkeeping — heavy in tax season, lighter mid-year.

Who Bank Parser Is Built For

The product is built around workflows specific to the accounting profession:

  • Bookkeepers handling multi-client cleanup, monthly close cycles, or catch-up engagements where consistency across clients is the bottleneck.
  • CPAs preparing historical financial data for audits, tax filings, or remediating books from prior years.
  • Small business owners reconstructing financial records — typically during tax season, after a bookkeeping lapse, or for audit defense.
  • Accounting firms standardizing onboarding across 20+ clients where each client's bank export is structurally different.

Meet the Founder

BZ

Baurzhan Zhetenov

Founder & Developer

I built Bank Parser after watching bookkeepers spend hours on manual data entry — a problem that software should have solved years ago.

My background is in software development with a focus on document processing and automation. Bank Parser uses pdfjs-dist with bank-specific parsing logic — no OCR, no generic table extraction. Every parser is hand-tuned to ensure maximum accuracy.

Data Security

256-bit encryption

Auto-deleted after processing

No data stored or shared

SOC 2 aligned practices

By the Numbers

17
Data Fields Extracted
30s
Average Processing Time
95-100%
Extraction Accuracy
4+
US Banks + Credit Cards

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