How to use FNVCOMPRESSION - Loans: Document Data Summarization


SAP Transaction Code - Details

  • Transaction Code: FNVCOMPRESSION

    Description: Loans: Document Data Summarization

    Release: S/4HANA and ECC 6

    Menu Path:

    • Accounting > Bank Applications > Loans Management > Position Management > Periodic Processing > Reorganization > Summarization
  • Show technical details Hide technical details
    • Program: RFVD_COMPRESSION_01

      Screen: 1000

      Authorization Object: F_T_TRANSB

    • Development Package: FVVD

      Package Description: Treasury Loans

      Parent Package: FVVD_ZBASIS

    • Module/Component: FS-CML

      Description: Loans Management


Smart SAP Assistant

  • SAP Tcode: FNVCOMPRESSION - Loans: Document Data Summarization
    
    Overview:
    FNVCOMPRESSION is an SAP transaction code used to summarize loan document data. It is used to reduce the amount of data stored in the system, making it easier to manage and access. 
    
    Functionality: 
    FNVCOMPRESSION allows users to compress loan document data into a single record. This reduces the amount of data stored in the system, making it easier to manage and access. The transaction code also allows users to view the summarized data in a graphical format, making it easier to understand and analyze. 
    
    Step-by-step How to Use: 
    1. Enter the transaction code FNVCOMPRESSION into the command field. 
    2. Select the loan document data that you want to summarize. 
    3. Select the fields that you want to include in the summary. 
    4. Click “Execute” to generate a summary of the selected data. 
    5. View the summarized data in a graphical format for easy analysis and understanding. 
    
    Other Recommendations: 
    It is recommended that users regularly use FNVCOMPRESSION to keep their loan document data up-to-date and organized. This will help ensure that all relevant information is easily accessible when needed. Additionally, users should be aware of any changes or updates made to the summarized data, as this could affect their analysis and understanding of the loan document data.
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