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Bank Statement to General Ledger Reconciliation
An AI agent that retrieves bank statements, matches transactions with entries in the general ledger, identifies discrepancies, suggests matching rules, and prepares a reconciliation report.
Process Details
Inputs
- Bank statements
- General ledger transaction data
Outputs
- Bank reconciliation report
- List of outstanding items and discrepancies
- Suggested journal entries for bank fees/interest
Systems
Describe it in English.
It runs deterministically.
This use case solution follows these general steps at a high level.
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01
It retrieves bank statements (Excel) and transaction data from the ERP System's General Ledger
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02
Applies pre-defined rules to match bank transactions with GL entries based on amount, date, reference numbers, and descriptions
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03
Identifies unmatched items, outstanding checks, deposits in transit, bank fees, and interest. Categorizes discrepancies (e.g., timing differences, errors, unrecorded transactions).
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04
For identified bank fees or interest, the AI agent can suggest journal entries to be posted in the ERP System
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05
Generates a reconciliation report highlighting matched items, outstanding items, and exceptions. Routes the report and exceptions to an accountant via email for review and approval
Frequently Asked Questions
Which ERP systems and bank formats can this agent work with?
The agent is designed for flexibility. It can natively integrate with major ERP systems (e.g., SAP, Oracle NetSuite, Microsoft Dynamics 365) via APIs. For data acquisition, it can process files like Excel, CSV, and PDFs from any banking institution, and it can be configured to retrieve them from secure FTP sites, email inboxes, or network drives.
How customizable are the transaction matching rules?
The matching logic is highly customizable. While it comes with pre-built rules for matching by amount, date, and reference numbers, you can easily configure more sophisticated, multi-tiered logic.
How does this solution support auditability and compliance (e.g., SOX)?
The agent enhances your audit and compliance posture. Every action taken by the agent—from data retrieval to a matched transaction to a generated report—is logged in an immutable audit trail. The final reconciliation reports provide clear documentation of matched items, outstanding items, and all exceptions, giving auditors a complete and easily verifiable record of the process.
Does the agent automatically post journal entries to our ERP?
No, it does not. To ensure strict financial governance and maintain a human-in-the-loop control, the agent suggests journal entries for items like bank fees and interest. These suggestions are then sent to a designated accountant for review and approval before anything is posted to the General Ledger. This maintains the principle of segregation of duties.
What is the typical implementation timeline and what is required from our team?
A standard implementation/configuration can be completed in as little as 2-4 weeks. The process involves an initial discovery session to understand your specific ERP, chart of accounts, and bank statement formats. The primary requirement from your team will be access to a subject matter expert from your finance department and light support from IT for system access and credentials.
How does the solution scale as our business and transaction volume grows?
The agent is built on a cloud-native architecture, making it highly scalable. It can process tens of thousands without a degradation in performance. You can run reconciliations for multiple legal entities or bank accounts in parallel, ensuring the solution grows seamlessly with your business needs.
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