1. SAP Glossary
  2. Claims Management
  3. statistical reserve


What is statistical reserve in SAP FS-CM - Claims Management?


SAP Term: statistical reserve

  • Component: FS-CM

  • Component Name: Claims Management

  • Description: Reserves that are estimated and set by the system. Within the claim: These may be configurable default values, or they can be determined on the basis of a configurable rule tool that evaluates the claim data. Outside the claim data: Adjustment and enhancement of reserves based on facts that are not captured in the claim itself IBNR, ULAE, or supplemental reserves.


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  • Key Concepts: 
    Statistical reserve is a feature of the FS-CM Claims Management component of SAP. It is used to calculate the expected cost of claims that have not yet been reported. This calculation is based on historical data and statistical models. The statistical reserve is used to ensure that the company has sufficient funds to cover the expected costs of future claims. 
    
    How to use it: 
    The statistical reserve can be used to help companies plan for future claims costs. Companies can use the reserve to determine how much money should be set aside for future claims and adjust their budget accordingly. The reserve can also be used to monitor the performance of the company's claims management system and identify areas where improvements can be made. 
    
    Tips & Tricks: 
    When setting up a statistical reserve, it is important to ensure that the data used for the calculation is accurate and up-to-date. Companies should also consider using a variety of different statistical models in order to get a more accurate picture of their expected claims costs. 
    
    Related Information: 
    The FS-CM Claims Management component of SAP also includes features such as claim processing, reporting, and analytics. These features can be used in conjunction with the statistical reserve to help companies better manage their claims costs. Additionally, companies may want to consider using other tools such as predictive analytics or machine learning algorithms to further improve their claims management process.
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