Import a Bank Statement Into Lunch Money (CSV)

Lunch Money maps a CSV on import

Lunch Money, the indie budgeting app, brings transactions in by mapping a CSV: you upload the file and tell it which column is which. That mapping step is where a clean file pays off, because a messy export means fixing columns and re-reading amounts before anything imports. Converting your statement to a well-structured CSV first, with each field in its own column and the numbers right, means the mapping is a quick confirmation rather than a repair job. When your bank hands you a PDF, converting it to that clean CSV is the step that gets the month into Lunch Money's importer in a shape it can read on the first pass.

The four columns it reads

Lunch Money's CSV importer works with four fields: date, payee name, amount, and category. You map them by clicking each column header in the upload and choosing the matching field from a dropdown, and each column maps to exactly one field. Date, payee, and amount are the ones that carry a transaction; category is optional. A converted statement provides the date, payee, and amount cleanly, and any column Lunch Money does not need can be set to Do Not Import, so nothing extra clutters the mapping.

Three ways to show debits and credits

Lunch Money is unusually flexible about how a CSV expresses direction, which is worth knowing before you convert. If your file has one signed amount column, you map it to Amount. If it splits money in and money out into two columns, you map them to inflow and outflow. And if it has a separate column that labels each row as a debit or a credit, you map that to Amount Type. Because a converter can output whichever of these you prefer, you can match the layout Lunch Money handles most cleanly for your setup rather than reshaping the file after the fact.

Auto-detection, Do Not Import, and validation

The importer tries to help. It attempts to match columns automatically from their header names, which works best when the file uses clear, recommended headers, and you confirm or override each guess. Columns you do not want become Do Not Import in a click. And Lunch Money validates as it goes, flagging any line missing a required field, a date, a payee, or an amount, so you catch a bad row before it imports rather than after. A converted CSV with clean headers and complete rows sails through that validation.

Migrating in, and privacy

Lunch Money took in a wave of users from Mint and YNAB, and the same CSV path handles those migrations and a plain bank statement alike. A converted statement fills whatever a migration export misses, an account it did not cover or older history. Because the statement holds real account activity, the file is processed to build the CSV and then deleted automatically, with nothing retained on a server afterward, so the transactions end up only in your own Lunch Money account and the source file does not linger.

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