Convert Chase Bank Statements to CSV

Upload your Chase bank statement PDF to BankStmtConverter.com, and the converter extracts transaction dates, descriptions, debits, credits, and running balances into a clean CSV file. You download the file and import it directly into your accounting software, spreadsheet application, or reconciliation tool without retyping a single row.

CSV works across platforms—Windows, Mac, Linux—and opens in Excel, Google Sheets, LibreOffice, and virtually every accounting package. For Chase customers managing business accounts or preparing tax records, CSV offers a portable format that preserves transaction structure while letting you control exactly how data maps to your existing workflows.

How do I convert a Chase statement to CSV?

1. Download your Chase statement PDF from chase.com (Personal Banking or Business Banking, Statements & Documents section).
2. Go to BankStmtConverter.com and upload the PDF file.
3. The converter processes the statement, extracting date, description, debit, credit, and balance columns.
4. Download the CSV file to your computer.
5. Open the CSV in your software or import it into your accounting system.

The entire process takes under a minute for statements up to 50 pages. Chase statements from checking, savings, and business accounts all follow a consistent tabular layout that the converter parses reliably.

What data gets extracted from Chase statements?

The converter pulls these columns from your Chase PDF:

• Transaction Date: the date the transaction posted to your account, formatted MM/DD/YYYY.
• Description: payee name and transaction details as they appear on the statement (check numbers, ACH descriptions, merchant names).
• Debit: withdrawals, payments, and fees in dollars and cents.
• Credit: deposits, transfers in, and refunds.
• Balance: running account balance after each transaction.

Chase lists debits and credits in separate columns on most personal and business statements, which the converter preserves in the CSV. For statements showing a single signed amount column, the converter splits transactions into debit and credit fields based on the sign.

Working with CSV files: import and analysis workflows

CSV is a plain-text format where each line represents one transaction and commas separate the fields. This simplicity makes it the universal import format for accounting software, but you must map columns correctly during import to match your chart of accounts.

In Excel or Google Sheets, open the CSV and use column filters to isolate specific payees or date ranges. A formula like =SUMIF(B:B,"AMAZON*",C:C) totals all debits to Amazon across the statement period. Create pivot tables to break down spending by category after you add a classification column. Save the file as .xlsx to preserve formatting, or keep it as CSV for portability.

For accounting software (Xero, Wave, FreshBooks, Zoho Books), use the built-in bank import or CSV upload feature. During import, you map the CSV columns to the software's expected fields: transaction date → Date, description → Description or Narration, debit → Money Out, credit → Money In. Most tools let you save these mappings so repeat imports take two clicks. After import, the software matches transactions to existing entries or flags duplicates.

QuickBooks Desktop and QuickBooks Online both accept CSV through their bank feed import. In Desktop, go to Banking → Bank Feeds → Import Transactions, choose CSV, and map columns. Online users upload via Banking → Upload Transactions. Map the date, description, and amount fields, then assign accounts and categories during the review step before adding to the register.

For Python or R analysis, read the CSV with pandas.read_csv() or read.csv(). Parse the date column into datetime objects, convert debit and credit strings to floats, and run aggregations or time-series plots. The consistent column structure across Chase statements makes scripting reliable month after month.

Does it work with scanned or photographed Chase statements?

Yes. If your Chase statement is a scanned image or photograph saved as PDF, the converter applies OCR to extract text before parsing transactions. The process takes slightly longer than text-based PDFs—typically 15-30 seconds for a 10-page scanned statement—but produces the same CSV structure.

After extraction, the converter checks that the sum of all debits and credits reconciles to the statement's printed beginning and ending balances. If totals mismatch by more than a few cents, the converter flags the discrepancy so you can review the CSV before importing. This catches OCR misreads on smudged or low-resolution scans.

Example: Chase business checking CSV output

A three-transaction excerpt from a Chase business checking statement converted to CSV looks like this:

Open this CSV in Excel, and you can filter the Description column for