# How columns are matched automatically

> Three signals — the header, the shape of the values, and whether the values are already names in your books.

Section: Importing and exporting · Canonical: https://intubu.intuitivecapital-dai.com/docs/csv-column-matching

The hard part of an import is knowing that the column headed **Supplier** is your vendor and **Net GBP** is the amount. Three things work that out.

**1. The header.** Matched against the words people actually use — *supplier*, *payee*, *merchant*, *nominal*, *category*, *trans date* — with fuzzy comparison, so "Trans  Date" and "Transaction date" are the same thing.

**2. The shape of the values.** A column whose entries all parse as dates is a date column whatever it is called. This is what rescues files with no useful headers at all, or headers in another language.

**3. Your own records.** A column containing your actual vendor names is a vendor column — because those *are* your vendors. The same goes for account names and numbers, which is how a column headed only "Nominal" still finds its way to Account.

**Every field shows how sure we are:** *confident*, *likely* or *unsure*. Anything marked unsure is worth a glance. Nothing is inferred silently, and you can change any row of the mapping.

**One column is never used for two fields.** The whole grid of possibilities is scored at once and assigned best-first, so a column that fits one field poorly and another well goes where it belongs.

**What it cannot guess** is the genuinely ambiguous: 03/04/2026 is March 4th to an American bank and April 3rd to a British one. If any value in the column is above 12 we settle it from the data; otherwise you set the convention, and a saved format remembers it.

**Amounts** are read in the conventions spreadsheets actually use: currency symbols, thousands separators, parenthesised negatives, a trailing minus, and the European decimal comma. A bank file with separate Debit and Credit columns is recognised as such.