Extract payee, amount, date, MICR, memo, and routing number from bank checks automatically—no templates, no manual keying.
Upload scanned batches, connect a cloud folder that receives lockbox images, or set up email auto-forwarding from your bank. Accepts PDFs, JPEGs, PNGs, and TIFFs in any combination.
The AI pulls payee name, date, written and numeric amounts, check number, memo, bank name, and full MICR line data. Each field gets a confidence score so exceptions surface automatically.
Route extracted check data to Excel, Google Sheets, CSV, or JSON. Use the REST API to feed records directly into your ERP, accounting platform, or reconciliation workflow.
“We receive 400 checks a week from different payers. Manually keying payee, amount, and check number into our AR system was a full-time job. Now it’s automatic.”
“The MICR parsing is what we needed most. Our old system couldn’t separate routing numbers from account numbers reliably. Lido nails it every time.”
“Reconciliation used to take three days at month-end. With structured check data flowing directly into our ledger, we close the books in one afternoon.”
Audited controls over a sustained period, not a point-in-time check.
Bank-grade encryption at rest and TLS 1.2+ in transit.
Documents deleted within 24 hours. No copies retained.
Check data extraction is the process of reading a bank check—whether scanned, photographed, or received as a digital image—and converting every meaningful field into a labeled, structured record. A complete extraction captures the payee name, courtesy amount (numeric), legal amount (written), check date, check number, memo or reference line, payer name and address, issuing bank, and the full MICR line broken into routing number, account number, and check serial number. The result is a database-ready row, not raw text.
The persistent challenge for accounts receivable teams, treasury departments, and payment processors is that checks arrive from hundreds of different banks with no standardized digital format. Each bank prints checks with different fonts, layouts, security patterns, and field placements. A template-based extraction system requires a separate configuration for every bank’s check layout, which is impractical when you process checks from dozens or hundreds of issuers. AI-based extraction reads each check contextually, identifying the payee field by its label and position relative to other elements rather than by fixed coordinates.
The downstream value of structured check data extends beyond simply digitizing the payment amount. When every field is captured—including the memo line and check number—teams can automate payment reconciliation against open invoices, build searchable check registers without manual data entry, and flag duplicate check numbers before they reach the ledger. Lido outputs these structured records to Excel, Google Sheets, CSV, or JSON, making it straightforward to feed the data into accounting systems, ERP platforms, or custom reconciliation workflows.
For organizations still keying check data manually, the cost is not just labor hours. Manual entry introduces transposition errors in amounts and routing numbers—errors that propagate through the ledger and surface as reconciliation discrepancies days or weeks later. Automated extraction with per-field confidence scoring catches ambiguous values at the point of entry, before they contaminate downstream records.
A complete check data extraction captures the payee name, numeric amount (courtesy amount), written amount (legal amount), check date, check number, memo or reference line, payer name and address, bank name, and the full MICR line including routing number, account number, and check serial number. Lido extracts all of these fields automatically and returns them as labeled columns in a spreadsheet or structured JSON.
Payment reconciliation requires matching incoming check payments against open invoices or expected receivables. Check data extraction automates the first step by converting each check into a row with payee, amount, date, and reference fields that can be matched programmatically against your accounts receivable ledger. This eliminates manual keying of check details and reduces the reconciliation cycle from days to hours.
Yes. The MICR (Magnetic Ink Character Recognition) line contains the routing number, account number, and check serial number encoded in a specialized font. Lido’s AI extraction engine reads the MICR line from scanned images and photographs, parsing it into separate routing number, account number, and serial number fields. This works even when the MICR line is partially obscured or the image quality is low.
Generic OCR converts an image into raw text without understanding what each piece of text means. Check data extraction applies domain-specific intelligence to identify and label each field on a check: it knows the difference between the payee name and the bank name, the courtesy amount and the check number. The output is a structured record with named fields, not a block of unstructured text.
Once check data extraction produces structured records with check number, date, payee, amount, and memo fields, those records can be exported directly to a spreadsheet that serves as a check register. Lido outputs to Excel, Google Sheets, or CSV in a format that mirrors standard check register columns. For ongoing use, email auto-forwarding lets you send check scans to Lido automatically, keeping the register updated without manual uploads.
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Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine