LedgerMatch

How to Match a Statement CSV with Uncleared Transactions

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Uncleared ledger transactions are not automatically wrong. Use the statement period, amount, date, and description together to match them without overlooking timing differences or duplicates.

Matching a statement CSV with uncleared transactions starts with a definition: a transaction is uncleared because it has not yet been tied to the bank statement, not because it is definitely missing or incorrect. The goal is to identify supported matches and keep the uncertain rows available for review.

1. Prepare the two files

  • Export the bank statement with the full period and a transaction-level date, description, and amount.
  • Export the ledger account with uncleared and already-cleared status if the system provides it.
  • Use one sign convention and one date format in the working copy, while preserving the original files unchanged.

2. Match exact amounts first

An exact amount is a strong signal, but it is not enough by itself. Check that the dates are in the same period and that the description or reference is plausible. If multiple uncleared rows share the amount, leave the match unresolved until the other fields distinguish them.

3. Review timing and description differences

  1. Allow a small date window for weekends, bank processing, and posting delays.
  2. Compare normalized descriptions rather than requiring the bank and ledger text to be identical.
  3. Treat fees, transfers, and card settlements as their own categories because one statement row may represent several ledger rows.
  4. Return ambiguous candidates to a reviewer instead of assigning the first plausible row.

4. Handle one-to-many matches deliberately

A deposit may combine several invoices, and a card settlement may combine many sales minus fees. Compare the sum of candidate ledger rows with the statement amount, then review the date and reference context. Do not force these cases through a one-row lookup.

5. Recalculate the remaining difference

  1. Mark only supported matches as cleared or matched.
  2. Keep missing bank rows, missing ledger rows, duplicates, and timing differences in separate exception groups.
  3. Recalculate the statement-to-ledger difference after each correction.
  4. Export the matched result and the unresolved list for review or follow-up.

Frequently asked questions

Can I match uncleared transactions from a CSV?

Yes. Export the statement and the ledger transactions, normalize the fields, and compare exact matches before reviewing timing, descriptions, duplicates, and split activity.

What if several uncleared transactions have the same amount?

Use the date, description, reference, and period context to distinguish them. If those signals are not enough, keep the candidates unresolved for a reviewer rather than choosing arbitrarily.

Should I clear every transaction that has a matching amount?

No. Amount alone can create false positives, especially for recurring payments and duplicates. A supported match should also make sense by date and description or reference.

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