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Aggregation functions in Bank Analyzer

In this post, I will talk about the main aggregation functions in Bank Analyzer:

  1. Source Data Aggregation (SDA)
  2. Preaggregation
  3. GL Connector
  1. Source Data Aggregation (SDA)
    • Process provided by SDL which allows to aggregate source data (Financial Transactions, Business Transactions and accruals).
    • Used for products which do not have to be evaluated on single transaction level. These products can be reported for accounting at their nominal value . Valuation does not need to be done for these products at the single contract level. Examples of these products are Current Accounts, simple Deposits and Loans (i.e. those without premium/discount).
    • These products typically exist in high quantities, therefore aggregation makes sense to reduce processing time and hardware cost.
    • SDA is run after “Set SDL Time stamp” step and before PEBT (Post External Business Transactions) step.
    • Aggregation is done at the level of Granularity characteristics.

   2.  Preaggregation

    • Process provided within RDL which allows to aggregate data.
    • Summarizes RDL single postings and writes totals.
    • Useful from a technical standpoint to summarize high number of AFI posting documents and store the totals; so performance can be improved.

    3.  GL Connector

    • Process provided within Analytics Layer. This process is typically run at least daily.
    • GL Connector summarizes the AFI FI-GL postings and sends them to GL. This helps build the framework for thin GL; detailed subledger.
    • Audit trail including drill through from GL to single AFI postings is available.

In my next post, I will summarize configuration and end user transactions for these Aggregation functions.

My earlier post on AFI postings derivation is here.

Comments are welcome.


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