As we have discussed, the effective implementation of a Fundamental Review of Trading Book (FRTB) program calls for banks to have a sound data sourcing, calculation and management strategy.  Addressing the data challenges provides the foundation for flexible, agile FRTB compliance efforts. 

Some additional concerns—to identifying a consistent set of sensitivities, defining a centralized architecture for sourcing risk data, and managing Internal Model Approach (IMA) risk factors and liquidity horizons—include: 

  1. Planning for profit and loss (P&L) attribution.  The bank should define the factors governing the portfolio which is to be considered for P&L attribution and communication protocols to different departments (such as Finance) to integrate the desks which are eligible for the internal model.
  2. Managing Standardized Approach (SA) risk sensitivities.  This requires documentation of the existing data from front office systems.  The data should be periodically reviewed and updated to confirm the existing risk factors and identify any new risk factors affecting the models.
  3. Enhancing market data process for data quality management.  The concern here is the integration of the IT processes which warn and/or alert the users regarding data issues in the repository.  Both users and affected functions should know about data issues and possible delays. 
  4. Identifying technology synergies with other regulatory initiatives.  Banks should identify synergies with other strategic regulatory initiatives such as BCBS 239 and UMR (Uncleared Margin Regulation).  This can help leverage the existing infrastructure for supporting FRTB. UMR in particular has strong parallels with FRTB regulations.

In the final blog in this series, we will summarize what banks should do to undertake an effective transformation of their market risk processes in response to the FRTB challenge. 

For more information see SlideShare deck: “Fundamental Review of the Trading Book (FRTB) – Data Challenges


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