Fields Extracted from Bank Statements
Zera Books extracts every meaningful data point from a bank statement — not just the transaction rows. This includes metadata about the statement period, account identifiers, and opening/closing balances that are essential for proper reconciliation.
| Field | Description | Notes |
|---|---|---|
| Transaction Date | Date the transaction posted to the account | Normalized to YYYY-MM-DD regardless of source format (MM/DD/YYYY, DD-MMM-YYYY, etc.) |
| Description | Full merchant name or transaction reference | Multi-line descriptions merged; bank reference codes preserved |
| Debit Amount | Money leaving the account | Standardized to positive values; parenthetical negatives handled |
| Credit Amount | Money entering the account | Separate column from debits in all output formats |
| Running Balance | Account balance after each transaction | Extracted where present; calculated where not shown |
| Account Number | Full or masked account number | Extracted from header; matched to correct transactions in multi-account PDFs |
| Statement Period | Start and end dates of the statement | Extracted from header; used for duplicate detection across overlapping periods |
| Opening Balance | Balance at period start | Used to validate extraction completeness |
| Closing Balance | Balance at period end | Cross-checked against sum of transactions + opening balance |
Format and Input Handling
Bank statement PDFs come in two fundamentally different forms: digital (text-layer) and scanned (image-only). Each requires a different processing approach. Zera Books handles both automatically — it detects the input type and routes accordingly without requiring manual flags.
Digital PDFs (Text Layer)
PDFs with an embedded text layer are processed directly by Zera AI. No OCR step required. 99.6% field-level accuracy. Handles any column layout, any page structure.
Scanned PDFs and Images
Scanned statements are processed by Zera OCR at 95%+ accuracy. Handles blurry scans, low resolution, rotated pages, and skewed images that generic OCR engines fail on.
Password-Protected PDFs
Enter the password once during upload. The platform decrypts, processes, and stores extracted data — not the raw PDF — for security compliance.
Multi-Page Statements
Statements spanning 50+ pages are processed as a single unit. Page breaks in the middle of transactions are handled correctly — no split transactions.
Multi-account PDFs: A single PDF containing checking, savings, and credit card data is detected and split into separate output files automatically. See multi-account detection for how the boundary detection works.
Any bank. Any format. No templates.
Upload a PDF from any institution and get clean, categorized transactions ready for QuickBooks or Xero in under 60 seconds.
Try for one weekOutput Formats and Accounting Software Compatibility
The output format determines how much work you do after conversion. A generic CSV requires column mapping in your accounting software. A QBO file imports directly with no configuration. Zera Books supports both, plus pre-formatted exports for every major platform.
| Format | Best For | What's Included |
|---|---|---|
| Excel (XLSX) | Firms that do their own import or review before uploading | All extracted fields, AI category column, confidence scores, standardized dates |
| CSV | Custom imports, data analysis, internal accounting systems | UTF-8 encoded, standardized field names, configurable delimiters |
| QBO | QuickBooks Online direct import | OFX-based format, bank ID mapped, transactions dated correctly |
| IIF | QuickBooks Desktop | Account type, split transactions, vendor names pre-mapped |
| Xero-formatted CSV | Xero bank feed import | Reference numbers, descriptions, amounts in Xero column order |
| Sage / Wave / Zoho / NetSuite | Those specific platforms | Each export matches the exact import spec of the target platform |
Accuracy Benchmarks
Accuracy claims without methodology are meaningless. Here's what the 99.6% figure means and where it comes from:
Field-Level Accuracy — How It's Measured
What 99.6% means: Field-level accuracy measures each individual extracted value (date, amount, description) against the source document. At 99.6%, a statement with 100 transactions and 400 field values has an average of 1.6 errors. In practice, amount fields have higher accuracy than description fields because amounts are numerically validated against opening/closing balance checks.
Frequently Asked Questions
What fields does Zera Books extract from bank statements?
Date, description, debit, credit, running balance, account number, account holder name, opening balance, closing balance, and statement period. Multi-line descriptions are merged correctly. All date formats are normalized.
Does Zera Books handle scanned bank statement PDFs?
Yes. Zera OCR handles scanned PDFs at 95%+ accuracy. It processes blurry scans, rotated pages, and low-resolution images. Scanned statements are automatically detected and routed through the OCR pipeline.
Can Zera Books process statements from any bank?
Yes. Zera AI dynamically processes any bank format without template setup — trained on 2.8 million statements from hundreds of institutions. It adapts to format changes automatically. See Zera AI reference for model details.
What output formats are available?
Excel, CSV, QBO, IIF, and pre-formatted exports for Xero, Sage, Wave, Zoho, NetSuite, FreshBooks, MYOB, and Oracle. All exports include AI-categorized transactions. See zerabooks.com/products/bank-statements for full details.