Reconcile Banks, Realize Efficiency.
This AI agent automates the often tedious and time-consuming process of matching transactions from bank statements with entries in the company's general ledger (GL), identifying discrepancies and exceptions.
The Problem
Problem Solved:
Manual bank reconciliation is a labor-intensive, error-prone task, especially for companies with high transaction volumes or multiple bank accounts. Delays in reconciliation can impact the accuracy of financial reporting and hide errors or fraudulent activity.
Key Features & Benefits
Key Features & Benefits:
- Drastically Reduces Manual Reconciliation Time: Frees accountants from hours of manual matching.
- Improves Accuracy: Minimizes human error in the reconciliation process.
- Enables Daily Reconciliation: Allows for more frequent checks, improving financial control.
- Faster Month-End Close: Speeds up a critical component of the financial closing process.
- Highlights Exceptions: Clearly identifies unmatched items and potential errors for investigation.
How It Works
How It Works:
The agent uses Machine Learning (ML) for advanced matching algorithms, including fuzzy matching logic, to compare bank transaction details (dates, amounts, descriptions) with GL entries. It learns matching rules from historical data and user feedback. RPA can automate the import of bank statements and GL data.
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