Mastering the FRTB
data challenge

Banks that tackle data concerns are poised for FRTB action.


Banks should expect to tackle a number of data challenges in implementing Fundamental Review of the Trading Book (FRTB).

The final rules for the market risk framework for capital requirements, published in January 2016 by the Basel Committee on Banking Supervision (BCBS), go live for banks with a capital market presence in December 2019. Known as the Fundamental Review of the Trading Book (FRTB), it asks banks to build an objective boundary between their trading book and banking book, shifting their internal model approach from Value-at-Risk (VAR) to an Expected Shortfall (ES) measure of risk, thus gaining a better grasp on “tail risk” and capital adequacy when financial markets are under stress.

Meeting FRTB’s challenges should mean higher cost for rules implementation and for conducting business as usual. Banks should expect to invest in more technology infrastructure to manage needed risk calculation efforts. They should also expect to tackle a number of data challenges in implementing FRTB.

How can banks transform their market risk processes to meet regulations, despite these hurdles?

Read on, and see Accenture’s paper, Fundamental Review of the Trading Book - from Theory to Action.


Most—if not all—FRTB implementation rules are directly or indirectly tied to a bank’s data management practices. So, for banks beginning to tackle FRTB changes, finding and resolving data challenges can be a top priority.

We’ve identified three data challenges that, if mastered, can give banks a big lead on their FRTB implementation journey.

  1. Risk sensitivities sourcing:
    Under FRTB, banks will need to conduct at least 79 different calculation inputs for each risk computation sensitivity class. New prescribed risk factors and liquidity computation may lead to 12,000 calculations per trade—a big increase from the 250 to 500 calculations per trade under Basel 2.5. A new concept, curvature risk, could require banks to update infrastructure, data availability and IT capacity to run revaluation for all products that have optionality.

  2. Market data sourcing:
    Banks will need to source pricing information for risk factors, using “real” and “observable” market prices. This may be a high hurdle for banks, given certain restrictions and limited availability of pricing information. Up-front costs for a pooled market data utility can run up to $15 million. Implementation challenges can include risk factor pricing, P&L attribution and market data quality issues.

  3. Risk calculator data gaps:
    Under FRTB, it is critical for banks to grasp incremental data requirements versus existing data calculation models and calculators. Some broad data gaps can affect risk calculators across risk factors and asset classes. These data gaps can be tied to broader themes, such as maturity mismatch, data sourcing gaps, assumptions and data taxonomy.


With a sound data sourcing, calculation and management strategy, banks may be good to go with their FRTB strategy. Pinning down data challenges can bring flexibility and agility. To get there, banks can take these action steps:

Benefits include:
  • Consistent treatment of data across the bank.

  • Front office and risk management teams have the same calculations and sensitivity data.

Benefits include:
  • Golden source of risk data across the bank.

  • Ease of data quality management.

  • Availability of data across the organization as per service level agreement needed.

  • Support approval process and supervisory auditing.

Benefits include:
  • Support to individual desk approval for IMA.

  • Flexibility in switching to a standardized approach (SA) in case of rejection by supervisors.

  • Reduced capital charges due to IMA.

Benefits include:
  • Approval for use of IMA to compute capital charges.

  • Successful P&L attribution tests.

Benefits include:
  • Consistent calculation of risk sensitivities across the front office applications.

  • Identification of sensitivity gaps, which can be corrected.

  • Up to date SA calculators.

Benefits include:
  • Data quality management.

  • Efficient communication for reporting.

Benefits include:
  • Identification of strategic tools within the bank.

  • Avoiding duplicative work and cost savings due to sharing of processes and infrastructure across multiple programs.

  • Permits compliance across all regulatory regimes.

Most banks already possess the elements they need to begin their FRTB transformation. The next action? Putting things together—the right way—to create a comprehensive approach to market risk management.

For more detail about these steps, and for insight into the FRTB journey, see Accenture’s paper, Fundamental Review of the Trading Book – From Theory to Action.


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