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Automate high-volume transaction matching across bank, payroll, clearing, and intercompany accounts-without manual rules or spreadsheets. Taxilla uses AI-assisted and rules-based matching to reconcile millions of transactions faster, more accurately, and continuously-reducing dependency on manual effort during close.
Finance teams spend thousands of hours manually matching transactions that ERPs cannot reconcile automatically.
ERPs rely on exact match logic that fails with real-world data variations.
Minor timing, rounding, or reference mismatches create large unmatched backlogs.
Teams match transactions line-by-line during month-end pressure.
Matching becomes a bottleneck for account reconciliation and close.
Inconsistent matching logic and manual overrides weaken audit confidence.
Taxilla provides a centralized transaction matching engine that works across banks, sub-ledgers, and intercompany data-feeding clean results directly into reconciliations.
Fully Automated End-to-End Process
Seamlessly ingest transaction data from bank statements, AR/AP sub-ledgers, payment gateways, and multiple ERPs into a unified reconciliation-ready data model.
Leverage AI-driven matching using fuzzy logic, tolerances, date and amount patterns to automatically identify and pair transactions with high accuracy.
Configure flexible matching scenarios-including one-to-one, one-to-many, and many-to-many-using business-defined rules without custom coding.
Unmatched or partially matched items are automatically flagged, prioritized, and routed for review with AI-suggested matches and explanations.
Approved and matched transactions seamlessly flow into Account Reconciliation, ensuring clean balances and faster period-end close.
Dramatically reduce manual matching effort through AI-driven automation.
Clean transaction sets accelerate balance-sheet substantiation and close timelines.
AI continuously learns matching patterns and improves accuracy over time.
Every match is fully traceable, explainable, and auditor-friendly.
Shift from reactive month-end processing to proactive, ongoing reconciliation.
Enforce consistent reconciliation controls across ERPs, entities, and shared services.
Ingest transactions from bank statements, AR/AP ledgers, payment gateways, lockboxes, and multiple ERPs into a unified matching layer.
Combine machine learning with configurable business rules to achieve high auto-match rates without manual intervention.
Match transactions using amount tolerances, date ranges, reference similarity, and pattern recognition to handle real-world data inconsistencies.
Support one-to-one, one-to-many, and many-to-many matching scenarios across high-volume transaction sets.
Unmatched or partially matched items are automatically routed into prioritized exception queues with reviewer actions.
Seamlessly integrates with SAP, Oracle, NetSuite, Dynamics, and hybrid ERP landscapes without disrupting existing accounting systems.
Transactions are matched and reconciled continuously eliminating month-end spikes and enabling a true continuous close.
Business users configure matching rules, tolerances, and workflows without ERP customization or IT dependency.
Every transaction, match decision, override, and approval is fully traceable from source to close.
All logic runs in a secure sub-ledger layer-keeping ERPs clean while enabling enterprise-grade automation.
Taxilla integrates with:
Automated shared services chargebacks across 30+ legal entities, reducing disputes by 80% and accelerating close by 5 days.
Standardized high-volume transaction matching across banks, AR/AP, and payment systems-achieving 75-85% auto-match rates and reducing manual effort by 60%.
Automated bank and payment reconciliation across stores, regions, and gateways-shortening cash visibility cycles and cutting close by up to 4 days.
Matched complex one-to-many and many-to-many transactions across customers, vendors, and plants-improving audit confidence and reducing reconciliation exceptions.
Enabled continuous transaction matching across multiple entities and currencies, supporting faster monthly closes and scalable growth.
Taxilla pricing for AI Transaction Matching scales based on transaction volume, matching complexity, and entity count, ensuring predictable costs and rapid ROI-without spreadsheet dependency or ERP customization.
Mid-market teams
Multi-entity Operations
Global Enterprise
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