Documentation of potential duplicate liabilities recorded in zapCash
The artificial intelligence (AI) within zapCash identifies potential duplicate invoices. The professional judgment is performed by business professionals to evaluate, based on the business context, if two invoices are true duplicates.
The AI learns on the basis of assessments and professional judgement. To make the quality of the assessments verifiable by an independent auditor or zapliance, the customer documents in detail how they come to the conclusion of the selected potential hits.
Since zapliance does not have access to the customer data, the conclusion must be comprehensible even without insight into the underlying SAP system.
To write good documentation, you can work along some W-questions, for example:
- What were the facts behind the two liabilities (e.g. document references like order or purchase numbers)?
- When did the process operations shown take place (e.g. posting or document dates)?
- Why is or isn't it a duplicate liability?
To identify the root causes of duplicate liabilities, it can also be helpful to use standardized wording for frequently recurring evaluations.
Each potential hit is assigned to one of the following three categories:
1. No duplicate liability
The shown liabilities are not the same.
Therefore, a double paid invoice does not exist (“False Positive”).
2. Duplicate liability
The liabilities shown are the same.
Therefore, a double paid invoice exists (“True Positive”).
For further processing by zapliance it is important to also choose the current recovery status of the duplicate liability as shown in the second picture.
3. Duplicate liability already identified
The shown liabilities are the same but have already been discovered before the zapCash data analysis. It was recovered by means of a registered correction.
In order for zapliance to track the identification and settlement of the liability, the necessary information is entered in the fields provided.