Transaction matching compares records that may describe the same business event: an invoice, a ledger entry, and a bank movement. Good automation can reduce repetitive review, but it should make the evidence and uncertainty visible to the person responsible for the books.
Normalize before comparing
Imported records often use different date formats, descriptions, identifiers, and currency conventions. A workflow first preserves the original files, then structures relevant fields consistently so candidate records can be compared. Original source values should remain available for audit and correction.
Use multiple signals
Potential matches can be evaluated using amount, currency, date range, reference number, counterparty, and transaction description. A single coinciding amount is not enough to establish a match. Transfers, partial payments, fees, and currency conversion can require separate treatment.
Keep exceptions in the loop
When evidence is incomplete or conflicting, the record belongs in an exception queue for review. A reviewer should be able to inspect both source records, understand why a candidate was suggested, correct the result, and leave an explanation for later review.
Measure quality transparently
Useful quality checks include unresolved-item counts, duplicate detection, balance comparisons against statements, and sampled review of accepted matches. Automation metrics should not be confused with a guarantee that every classification or tax treatment is correct.
People remain accountable
Automation can organize evidence; it does not replace professional judgment or the customer’s responsibility to verify financial records. The right workflow makes review easier and keeps approvals explicit.
This product explainer is general information, not a description of a guarantee or tax advice. Confirm product capabilities and review important outputs before use.
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