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Finance · Transaction Matching

Transaction Matching Agent

Matches transactions accurately to ensure financial integrity and reporting accuracy.

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The work it takes off your plate

The Transaction Matching Agent resolves the issue of discrepancies in financial transactions that can lead to inaccurate reporting and compliance risks. Manual matching is labor-intensive and prone to human error, which can compromise financial integrity.

How it works

The Transaction Matching Agent connects to financial systems, banking feeds, spreadsheets, and payment platforms to collect general ledger, subledger, bank statement, invoice, and settlement transactions. It standardizes dates, currencies, signs, descriptions, account identifiers, and reference fields before applying configurable exact, tolerance-based, and fuzzy matching rules. The agent compares amounts, dates, payees, document numbers, and descriptions, then assigns match confidence and reasons. It automatically clears high-confidence matches, groups related transactions, and routes exceptions for review. Finally, it produces reconciliation reports, discrepancy worklists, audit evidence, and summary metrics for finance and controllership teams.

  1. 1Gather Transaction DataPrepares transaction data for matching.
  2. 2Match TransactionsAccurately matches transactions to ensure consistency.
  3. 3Report FindingsProvides insights into transaction accuracy and integrity.

  1. Step 1: Gather Transaction Data

    • Collect data from various financial sources
    • Standardize transaction formats

    Result: Prepares transaction data for matching.

  2. Step 2: Match Transactions

    • Apply matching algorithms to identify pairs
    • Flag unmatched transactions for review

    Result: Accurately matches transactions to ensure consistency.

  3. Step 3: Report Findings

    • Generate reports on matched and unmatched transactions
    • Highlight discrepancies for further investigation

    Result: Provides insights into transaction accuracy and integrity.

Why use it

  • Faster Reconciliation. Automates high-volume transaction matching across ledgers, bank feeds, invoices, and settlements.
  • Higher Accuracy. Combines exact, tolerance-based, and fuzzy logic to reduce false matches and missed exceptions.
  • Stronger Controls. Records match rules, confidence scores, reasons, and reviewer actions for auditability.
  • Lower Manual Effort. Routes only material or ambiguous discrepancies to finance teams for investigation.