How to Map CSV Columns

How to Map CSV Columns

Mapping tells the converter which column in your CSV file contains which piece of information. Because every bank and app creates its own CSV layout, you need to match your file's columns to the fields the converter understands.

The table above shows a preview of your file. Use the dropdown at the top of each column to assign it a role.

Fields you must always map

At minimum, every conversion requires:

  • Date — the date the transaction occurred. If your file uses a specific date format (DD/MM/YYYY, MM/DD/YYYY, etc.) choose the matching date field. Use the country selector to help the converter detect the right format automatically.
  • Amount — the value of the transaction. Positive numbers are deposits or credits; negative numbers are payments or debits.

Without a date and an amount, the converter cannot produce a valid output file.

When your file has separate Debit and Credit columns

Some bank exports split transactions across two columns: one for money going out (debit) and one for money coming in (credit), leaving the other column empty on each row. For example:

Date,Description,Debit,Credit
15/01/2024,Salary,,2500.00
16/01/2024,Rent,850.00,

In this case, map the debit column to Debit Amount and the credit column to Credit Amount instead of using the single Amount field. The converter will combine them automatically, making debits negative and credits positive.

When your file has a "Type" column

Some exports include a column that says whether each row is a debit or a credit — for example with values like DEBIT, CREDIT, DR, CR, D, or C. Map this column to Transaction Type. The converter will use the type to set the correct sign on the amount automatically.

Splitting one file into multiple accounts (Account / Splitter)

If your CSV contains transactions for more than one account — for example a combined export with both a current account and a savings account on the same rows — you can use the Account / Splitter field.

Map the column that contains the account name (or account number) to Account / Splitter. The converter will group all rows by the unique values in that column and produce a separate output file for each account. You can then import each file independently into your accounting software.

For example: a column containing "Checking" and "Savings" will produce checking.qif and savings.qif.

OFX-only fields

Some fields are only meaningful for OFX output and are ignored when converting to QIF:

  • Balance — the running account balance after each transaction.
  • Transaction Number / Check Number — a reference number assigned by the bank.

Investment fields

If your CSV contains stock or fund transactions rather than bank transactions, investment-specific fields are available: Security Name, Price per Unit, Number of Shares, Commission, and Investment Action. These produce QIF investment-type output.

Custom fields — adding a fixed value to every transaction

Custom fields let you attach the same value to every transaction in the output — without that value existing in your CSV. This is useful for categorising imports by source.

PayPal example — separating sales from fees:

  1. Export your PayPal CSV. Map the gross amount column to Amount.
  2. In a custom field, set the type to Category and type the value PayPal:Sales. This adds "PayPal:Sales" as the category on every transaction.
  3. Save this mapping as PayPal Sales.
  4. Export the same PayPal CSV again. This time, map the fee column to Amount instead.
  5. Set the custom field category to PayPal:Fees and save the mapping as PayPal Fees.

You now have two separate QIF/OFX files — one for sales, one for fees — each correctly categorised, from the same original export. Import them both into your accounting software to keep fees and sales in separate categories.

Saving mappings for reuse

Once you have mapped your columns, you can save the mapping with a name (on the next steps). The next time you download a CSV from the same bank, load your saved mapping and all columns will be assigned instantly. If you bank with multiple institutions, you can keep a saved mapping for each one.