Turn check images into CSV files that import directly into QuickBooks, Sage, Xero, and any system that accepts structured data—no reformatting needed.
Drag and drop scanned check images or PDFs. Process a single check or hundreds at once—the batch converter handles JPEG, PNG, TIFF, and multi-page PDF files.
Each check becomes a row with columns for payee, date, amount, check number, memo, routing number, and account number. The AI reads handwritten and printed text without templates.
Get a clean CSV file formatted for direct import into QuickBooks, Xero, Sage, or any system that accepts comma-separated data. No reformatting or column mapping needed.
“We deposit 200 checks a month and used to type each one into QuickBooks manually. Now we scan the batch, download the CSV, and import it in two minutes.”
“The column mapping feature was the deciding factor. We needed date in MM/DD/YYYY, amount split into debit and credit, and a custom reference field. It handled all of that.”
“Bank reconciliation went from a two-day ordeal to a 30-minute task. We match the CSV against our bank statement and discrepancies surface instantly.”
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Check-to-CSV conversion is the process of scanning or photographing bank checks, extracting the key fields—payee, amount, date, check number, memo, and routing information—and outputting them as a CSV file with columns that match the import format of accounting software like QuickBooks, Sage, Xero, or NetSuite. The CSV acts as a bridge between the physical check and the digital ledger, eliminating the manual data entry step that introduces errors and delays into the accounts receivable workflow.
Every accounting platform supports CSV import, but each one expects a slightly different column order, date format, and field naming convention. QuickBooks Online wants “Date, Payee, Amount, Memo” while Sage 50 expects “Reference, Date, N/C, Details, T/C, Debit, Credit.” The practical challenge is not just extracting data from checks but formatting that data to match the target system’s expectations. This is where customizable column mapping becomes essential—the extraction tool needs to let you rename, reorder, and transform columns without writing code.
Batch processing is the other critical requirement for check-to-CSV workflows. Accounting teams do not process checks one at a time; they accumulate a stack of deposited checks and enter them as a batch during the reconciliation cycle. A useful check-to-CSV tool must accept dozens or hundreds of check images at once and produce a single CSV file where each check becomes one row. Lido handles this natively—upload a batch, review the extracted data in a spreadsheet view, adjust any flagged fields, and download the CSV formatted for your specific accounting system.
For teams that process checks on a recurring schedule, email auto-forwarding eliminates the upload step entirely. Forward check images to a dedicated Lido inbox and they are extracted and appended to your running dataset automatically. When reconciliation day arrives, the CSV is already populated and waiting for download.
Yes. Lido’s check-to-CSV output uses column headers and date formats that align with the import templates used by QuickBooks Desktop, QuickBooks Online, Sage 50, Sage Intacct, and Xero. You can map extracted fields to your accounting system’s expected columns using AI columns, so the CSV file is ready for import without manual reformatting.
The default CSV output includes check number, date, payee name, numeric amount, memo or reference line, routing number, and account number. You can add, remove, or rename columns using Lido’s AI column feature to match whatever format your accounting system or ERP expects. Custom columns can also compute derived values, such as splitting a single amount into debit and credit columns.
Upload a stack of check scans or photos at once and Lido processes each one individually, appending the results as separate rows in a single CSV file. You can also set up email auto-forwarding so that check images arriving by email are automatically processed and added to a running CSV export. Batch processing supports hundreds or thousands of checks per upload.
Lido’s AI extraction handles both printed and handwritten check fields. Handwritten amounts, dates, payee names, and memo lines are recognized using contextual AI that understands check layout conventions. Accuracy on clearly written handwriting typically exceeds 95 percent, with confidence scoring that flags ambiguous characters for human review.
Absolutely. The CSV output includes check number, date, and amount fields that map directly to the columns needed for bank reconciliation. Import the CSV into your accounting system or reconciliation spreadsheet to match deposited checks against your bank statement. This replaces the manual process of keying each check’s details into a reconciliation worksheet.
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Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine