Other parts of this series:
- Internal Model Method (IMM) Helps Banks Measure Capital Requirements
- Defining Materiality is Key First Step in Internal Model Method (IMM) Process
- Setting Progress Metrics for Internal Model Method (IMM)
- A Robust Control Framework for Internal Model Method (IMM) Implementation
- Internal Model Method Solution Design: Seeking Efficiencies in Regulatory and Business Initiatives
- Self-Assessment Considerations in Internal Model Method Compliance Programs
- A Coherent Target Operating Model for Internal Model Method Compliance Programs
- Establishing an Effective Regulatory Communications Strategy for Internal Model Method Compliance Programs
We previously reviewed the importance of clear, effective progress metrics for a successful IMM transformation process. The next key consideration in the process is the implementation of a robust control framework, one that can provide evidence for the lineage of data and the quality of inputs used within the IMM model.
The IMM process requires multiple data inputs, such as market data, trade data, counterparty and reference data, and collateral information; all which will come from different sources and leveraged throughout the bank by various functions. Regulators need to see that data inputs are high quality, comprehensive and consistent with inputs into other related models and reported figures. This means that, wherever possible, the IMM model should take data directly from “golden sources” subject to robust data governance practices. If this is not possible, reconciliations should be performed for consistency of data used within the IMM model.
To confirm data integrity, controls should certify data inputs as “fit for use” prior to processing and confirm outputs as “effectively modeled.” Controls should also be accompanied by appropriate break management tools and well-documented remediation governance processes.
In addition, if any data is adjusted prior to official month-end reporting, the adjustments should be done in a controlled manner and executed as far upstream in the data chain as possible. These month-end IMM runs should include all adjustments to allow alignment with official reporting and bank ledgers. Finally, it is essential that processes for adjusting, and the timing and location of adjusted data, be well understood within the IMM target state solution. Clearly documented data and system architectures can provide transparency into the reconciliation, controls and adjustments that take place within the IMM process chain.
In the next blog in this series, we will look at how banks can seek efficiencies within regulatory and business initiatives as part of the IMM solution design.
For more information, see SlideShare deck: “Considerations for an Effective Internal Model Method Implementation”
Visit www.accenture.com/RegulatoryCompliance for latest insights on regulatory remediation and compliance transformation.
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