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Celonis Product Documentation

User guide for Duplicate Invoice Checker
User Profile

The Duplicate Invoice Checker Module Action View is configured to be used by accounts payable specialists responsible for removing duplicate invoices.

Purpose of the Action View
  • Presents potential duplicate invoices detected using Celonis fuzzy matching algorithms

  • Notifies AP clerks and enables them to take action on potential duplicates in time.

  • Gathers feedback on duplicate detection precision based on user actions and tracks value realization.

User Interface and Functionalities
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The Action View gives the responsible AP clerk an overview of duplicates currently detected by Celonis and KPIs reflecting value realization. At a glance, the following figures are presented:

  • Duplicate Value (open): Indicates the total value of potential duplicates discovered by the Machine Learning-Sensor (ML-Sensor)

  • # Duplicates (open): Indicates the number of duplicate groups discovered by the ML-sensor

  • Duplicate pairsDuplicate Value (valid): Indicates the value of confirmed duplicates by the AP clerk

  • # Duplicates (valid): Indicates the number of duplicate groups confirmed by the AP clerk

* The ML-Sensor is the back-end tool that searches your invoice backlog for duplicates.

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Using filters, the AP clerk can narrow down the duplicate backlog to specific company codes, vendors, or other fields, customizable by the user.

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In the Action View, the AP clerk can switch between the ‘Open Duplicates’-tab which lists potential duplicates identified by the ML-sensor, and the ‘Resolved Duplicates’-tab which contains past verified cases.

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The Action View displays potential duplicates grouped and summarizes the most important information about a duplicate group, such as its total value and the detection patterns used.

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Each duplicate group can be displayed in a detailed view, showing the details of the potential duplicate invoices.

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After reviewing the duplicate case, the AP clerk can manually assign a status to the whole duplicate group by either marking it as a real 'Duplicate' case or a 'No Duplicate' case.

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In the ‘Resolved Duplicates' tab, the user can evaluate past duplicate patterns and algorithm classification quality.