gl-recon

To reconcile general ledger data against subledger entries, you provide both extracts with relevant fields. The Skill normalizes the data and performs precise matching at the transaction or position level to highlight breaks.

Ledger matching identifies and categorizes discrepancies such as amount, quantity, or timing differences. This break classification facilitates targeted investigation of mismatches across asset classes and trade dates.

Yes, you can use this for daily trade reconciliations and month-end closing. It performs differential analysis of extract data at the transaction level, quickly spotting breaks caused by timing differences or data quality issues.

The best way to classify reconciliation breaks automatically is to provide normalized general ledger and subledger extracts. The Skill matches the data and categorizes discrepancies by probable causes like timing differences.

You do not need to manually normalize different ledger extracts before matching. The Skill normalizes the provided general ledger and subledger data internally and performs precise matching to produce a reconciliation report.

General ledger reconciliation shows mismatches across asset classes due to amount, quantity, or timing differences. The Skill identifies these discrepancies and explains potential breaks caused by data quality issues.