FRTB – Now that the future is written, and the ink is dry

May 23, 2019

by John Carroll

Following numerous revisions in the form of 2016’s initial draft, two further FAQ’s and 2018’s consultation document, the Basel Committee on Banking Supervision (BCBS) issued its final amendments to FRTB in January 2019, providing national regulators with a conclusive effective date of January 2022 for minimum capital requirements.[1]

While January’s revision eases the overall impact on banks’ capital allocations (the revised ruling to allow “real” price observations as part of the Risk Factor Eligibility Test (RFET) for modellability being a prime example), the overall data-management challenge it presents remains considerable with the impact of non-compliance substantial.

Although the regulation itself incorporates a number of distinct components (the Trading Book / Banking Book Boundary, the treatment of credit, Expected Shortfall vs VaR etc.), within First Derivatives we have observed one predominant theme across our global customer base and partner network – the need for a robust data infrastructure. That is to say, a data infrastructure designed to meet the historical data requirements that drive capital calculations as well as the need to integrate with 3rd party data providers to bridge the gaps in their internal Non-Modellable Risk Factors? (NMRFs) data and avoid an over-reliance on proxies.

While individual banks approaches to various aspects of the regulation will naturally vary (just as the preparedness of the domestic regulators Federal Reserve, PRA, EBA etc. continues to differ), the below sets out the 3 principal data management[2] challenges posed by the regulation:

  • Expected Shortfall (ES) replacing VaR: The introduction of ES as a replacement for VaR mandates the need for increased histories of market data, with the observation horizon for determining the most stressful 12 months required to extend to 2007 at a minimum.
  • Revised Liquidity Risk Horizon Schedules: The replacement of the historic 10-day VaR calculation window with a per-asset liquidity horizon scaling factor based on its liquidity profile (i.e., the ease of unwinding the positions in the market without significant impact on transaction prices).
  • The need for real price observation data: In order for a risk factor to be considered modellable, firms must produce a minimum of 24 observations of either executed prices or committed quotes per year, per risk factor. Whilst this may not pose a data challenge for on-exchange trading, the fragmented OTC markets pose a serious challenge in terms of periodicity and liquidity.

According to some regulators (EBA for example), market participants reported preparedness in certain areas, namely the Expected Shortfall calculations and standard model adoption is mature. Other areas, namely addressing the proof of modellability and the identification of ‘non-modellable’ risk factors (NMRFs), continue to pose a problem however.

Whilst the final rule has responded to concerns around seasonality (particularly relevant in the case of commodity and energy markets) and new issues, the RFET remains challenging, so much so that many banks will require data from external sources for Internal Model Approaches (IMA) to guarantee capital relief.  As before, we have observed some differences in design approaches. For example, with regard to proving modellability and identifying non-modellable risk factors we have observed:

  • Efforts made in the general direction of data pooling services (e.g. DTCC).
  • Data providers such as Bloomberg/Refinitiv developing comprehensive aggregated offerings with risk and back-testing tools providing the ability to created expected shortfall scenarios.
  • That is not to mention the numerous attempts being made to use solely internal trade and price data which is unlikely to provide sufficient coverage.

In each case, it is essential that firms resist the temptation to solve only one aspect of the regulation (e.g. RFET/NMRF), and instead focus attention on developing a holistic risk management approach that simultaneously addresses the data requirements for related regulations e.g. BCBS 239, Prudential Valuations, MiFID II, PRIIPS and the Comprehensive Capital Analysis and Review regulatory framework.

As our Capital Markets Consulting division continues to work closely with customers and partners in addressing the process, methodology and evidence of FRTB compliance (including but not limited to enforcing practitioner approaches for trading book diversification, portfolio risk diversification and SA/IMA adoption) our message is clear; Banks must work to address FRTB strategically and in its entirety. To do so, they must begin with the data in mind, evaluating their overall data infrastructure to ensure a complete approach to risk management regulation comprising data sourcing, governance, timelines, infrastructure and risk reporting.

[1] Sources expect reporting under the standardised approach to begin in December 2020.

[2] As against the organisational challenges of the trading book boundary, P&L attribution etc.