GL Outlier Detection
AI-powered GL Outlier Detection automatically identifies potential errors and inconsistencies in the general ledger.
By analyzing historical data, it helps uncover anomalies that may indicate coding mistakes or missed transactions, ensuring greater accuracy and reliability in financial reporting.
How Kaunt Outlier Detection Works
Kaunt's GL Outlier Detection leverages advanced AI models to analyze historical general ledger (GL) data and identify anomalies that could suggest potential errors and inconsistencies.
The system scans vast amounts of invoices and postings, looking for outliers in patterns such as unexpected account assignments, or inconsistencies in financial classifications. By comparing current data with historical trends, Kaunt’s AI identifies these discrepancies, allowing finance teams to focus on high-risk areas.
The AI continually refines its detection capabilities as new data is processed, learning from past corrections to improve its accuracy over time. This provides a dynamic, real-time safeguard against financial inaccuracies and helps maintain the integrity of your customers' GLs without requiring manual effort or extensive audits.