Transaction Matching Agents

Match transactions across any ledger, entity, or system

Automated intercompany reconciliation without changing how teams record transactions.

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Finally, eliminate the reconciliation work that never seems to end

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AI-powered matching across systems and entities

Match transactions across ERPs, bank feeds, billing systems, and subledgers — even when formats, timing, or descriptions don’t line up perfectly.

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Reconciliation without process changes

Define matching logic in plain language, the same way you’d train a new team member, and automatically resolve discrepancies without changing how your team works.

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Exception-first workflows

Agents handle the bulk matching automatically and surface only the true exceptions — so your team focuses on resolving issues, not hunting for them.

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Continuous matching, not month-end fire drills

Transactions are matched throughout the month, reducing reconciliation bottlenecks and dramatically lowering close pressure.

Detection

Finds related activity automatically

Nominal continuously scans transactions across ledgers, bank feeds, and entities to identify entries that may represent the same business event.

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Matching

Transactions are linked and reconciled

When related entries are identified, Nominal links them into a single reconciled record across entities and accounts. Most reconciliation work is completed before the close begins.

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How it works

Nominal’s Transaction Matching Agents continuously match, explain, and resolve activity across your financial systems — turning reconciliation into a review and approval workflow.

  1. Transactions are continuously evaluated

    Agents analyze transactions across accounts, entities, and systems to identify related activity and reconciliation opportunities in real time.

  2. Matching happens automatically

    AI agents match transactions based on amounts, timing, descriptions, and patterns — even when records don’t perfectly align.

  3. Discrepancies are identified and explained

    Unmatched or inconsistent items are surfaced with clear explanations, so teams understand what’s wrong without digging through data.

  4. Resolution options are generated automatically

    Agents propose next steps — including matches, journal entries, or adjustments — to resolve discrepancies quickly.

  5. Your team reviews and approves

    Finance moves from preparing reconciliations to reviewing and approving agent-generated outputs with full context and confidence.

Our Knowledge Base

Insights & Updates

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    Move from doing the work to running the business.

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