Automated Accounting Reconciliation
ReconIQ is a cutting-edge AI-powered solution that revolutionizes financial operations by automating invoice matching, payment reconciliation, and general ledger validation. By seamlessly integrating advanced AI, Machine Learning (ML), and data analytics, ReconIQ is engineered to handle millions of transactions with over 99% accuracy.
This high precision empowers finance teams to eliminate bottlenecks and prevent errors, giving your business real-time cash flow visibility and enabling a faster, more accurate financial close every month. Ultimately, ReconIQ allows your team to make faster, data-driven decisions with confidence.
ReconIQ is more than just a matching tool; it's an intelligent automation solution that replaces tedious manual cross-checking with streamlined, reliable operation.
Manual reconciliation is costly, time-intensive, and prone to errors that impact financial reporting and cash flow. ReConIQ mitigates these risks by drastically cutting manual labor, accelerating the close process, and providing consistent, audit-ready reconciliation results.
ReConIQ automates the matching of invoices, payments, and ledger entries, handling complex scenarios such as partial payments, multiple invoice matching, and adjusting entries with precision. It intelligently learns from historical reconciliation patterns, continuously improving its matching accuracy and exception handling capabilities over time.
ReconIQ brings the power of AI to every stage of the reconciliation process, from data ingestion to discrepancy resolution.
Uses AI and machine learning models to match complex transaction patterns including partial payments, multi-invoice settlements, and cross-currency transactions.
Flags unmatched or suspicious transactions instantly, providing actionable insights and recommended resolutions to speed up issue resolution.
Supports a wide range of reconciliation needs, including Bank, General Ledger (GL), Accounts Payable (AP), and Accounts Receivable (AR), and can be configured for complex Intercompany Reconciliation.
Allows your finance team to define and apply highly specific, custom matching rules and tolerance levels to align perfectly with your unique financial policies.
Fully integrates with your existing ERP, accounting, and banking platforms (including Tally) and automatically maintains detailed, unchangeable logs of all activities for full compliance.
Learns from user feedback and historical data to improve accuracy and reduce manual overrides over time.
ReconIQ transforms the finance function from a historical data entry process into a strategic, forward-looking operation.
Stop relying on tedious spreadsheets and gain confidence in your financial data with AI precision.
ReconIQ is versatile, automating critical types including Bank Reconciliation, General Ledger (GL), Accounts Payable (AP), and Accounts Receivable (AR) matching, plus complex Intercompany Reconciliation.
ReConIQ uses AI and machine learning to intelligently match complex transactions, detect anomalies, and handle exceptions, accelerating reconciliation cycles and improving accuracy compared to manual methods.
Yes, ReConIQ supports multi-currency transactions and reconciles accounts across different geographies with complex payment scenarios.
ReconIQ achieves accuracy rates over 99% for high-volume, repetitive matching tasks. The system uses Machine Learning to look beyond simple identifiers, inferring matches even with inconsistencies in data formats.
The system excels at Exception Management. If a match cannot be made with 100% confidence, the AI flags the item immediately and routes it to the designated user for quick review and manual justification.
The system excels at Exception Management. If a match cannot be made with 100% confidence, the AI flags the item immediately and routes it to the designated user for quick review and manual justification.
Yes. By analyzing patterns and comparing data across multiple sources in real-time, ReconIQ is highly effective at Anomaly Detection. It flags unusual patterns, duplicate entries, or suspicious transaction types that manual processes often overlook.
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