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    The final sprint for FRTB… are you prepared?

    Hector Fontaine
    Hector Fontaine

    • The Minimum Capital Requirements for Market Risk, also known as the Fundamental Review of the Trading Book (FRTB), is a revised market risk capital framework developed by the Basel Committee on Banking Supervision (BCBS), which was finalised in January 2016.  Since then, the clock has begun ticking and banks are battling to implement FRTB over the next few years, with regulatory reporting set to begin from December 31st 2019. FRTB will require a major overhaul of current risk management practices and will have a profound effect on cost structure and strategy. This blog highlights the key changes to the existing market risk framework and analyses the challenges in deciding whether or not to use internal models for regulatory compliance. The blog also provides general recommendations to help financial institutions successfully implement FRTB.

    What are the main changes in FRTB?

    • A revised boundary between trading and banking book which limits the ability to move products across books, restricting a common method of capital savings (arbitrage) used by banks to date
    • A new rigorous desk level approval regime for banks that seek to use their own internal models[1] to measure market risk
    • A revised standardised approach for market risk measurement[2] which can also serve as a fall-back[3] and capital floor for internal models
    • The replacement of “Value at Risk” (VaR) for the more conservative “Expected Shortfall”(ES) as the market risk metric under stress[4]
    • The introduction of liquidity horizons for risk factors, in an attempt to improve the current framework which inadequately assumes that trading book positions can be hedged or exited over a 10-day period

    Overall FRTB will result in significantly higher capital requirements and may continue to shrink profit margins, particularly for financial institutions with substantial market risk exposure and activity in complex financial products. As such, it is imperative that banks are able to implement risk models that are both compliant and cost efficient.

    A major implementation challenge for FRTB: using internal modelling or relying exclusively on the standardised approach?

    Generally large banks are eager to gain approval for internal modelling due to the expected less punitive capital charges. A recent industry study[5] – featuring 21 banks- found that regulatory capital under the standardised approach would be 2.4 times that of current levels, while the rise in internal models would be 1.5 times current levels. Thus, the increases are substantial with FRTB rules for both approaches, yet internal models should in theory provide significant savings compared to the standardised approach.

    Unfortunately gaining and maintaining internal model approval is by no means an easy or costless task, it will require individual trading desks to pass the FRTB P&L attribution test, which assesses the ability of a model to forecast actual P&L results. Several banks have commented that the test demands a forecasting precision that is extremely difficult to achieve[6]. Furthermore, internal models under FRTB require considerable calibration of risk factors, which may result in a laborious and potentially expensive maintenance task, increasing dependence on granular data for effective model maintenance. [7]

    In short, the choice for banks between applying and maintaining internal modelling approval or relying exclusively on standard modelling is not easy; the standardised approach results in the highest capital requirements. On the other hand, internal modelling demands significant time and effort in calibrating sophisticated models, potentially resulting in a costly operational process. Until banks have completed detailed analysis of the work required to implement both approaches the choice will remain unclear.

    Recommendations for banks

    FRTB will become a key priority in the Risk and Finance space over the coming years for banks with substantial market risk exposure. The regulation will impact a number of bank activities such as Front Office valuations and trade decision support, product control, limit setting, financial reporting, treasury management and capital planning.

    Banks seeking to comply with FRTB should perform the following critical activities:

    • Gathering, documenting and interpreting FRTB implementation requirements –risk modelling groups, IT developers, policy teams, front office and senior management in Risk and Finance will need to be connected to collectively understand these changes and their expected impact
    • Completing process, organisation, model and technology impact assessments – including a thorough review of risk methodologies to comprehend the modifications that are required to implement FRTB in the current infrastructure
    • Developing integrated current and target state operational models with other related BCBS initiatives (e.g. SA-CCR, Leverage Ratio) to avoid duplication of effort and to identify potential synergies
    • Establishing and operating robust programme management to drive the delivery of calculation model enhancements, model governance structure, organisational change and IT delivery
    • Enhancing data management for market risk (data dictionaries, data gap assessments)
    • Planning for reporting submissions and conducting test runs to identify areas of challenge ahead of the regulatory submission timelines
    • Assessing the expected impact of revised capital requirements on business and trading strategies and associated limits structures

    Although FRTB rules were finalised in January, BCBS has acknowledged that further adjustments might be required in certain areas, such as refining the P&L attribution test thresholds, considering the impact of BCBS Pillar 3 disclosure requirements (not included in final FRTB rules) and, once finalised, incorporating BCBS proposals for Credit Valuation Adjustment standards.

    Final thoughts

    FRTB is clearly an extremely demanding regulation, which requires intensive effort and planning to be effectively implemented in any organisation. Banks trading book costs may surge and market risk modelling will face unprecedented supervisory scrutiny. However, despite these challenges, there is an opportunity for banks to gain competitive advantage by devoting sufficient time not just to comply with the regulation but also to assess the strategic impact of this new capital framework. Thinking ahead on how best to adjust trading strategy and product portfolio, more closely align front office activity and capital planning, and challenge current operational models, will give institutions the best chance to maximise competitive advantage in an increasingly cost pressured environment.

     

    [1] The revised internal models approached (IMA) sets constraints on the benefits of hedging and diversification for capital reductions and attempts to more accurately identify and capitalise material risk factors
    [2] The standardised approach is known as the Sensitivity Based Approach (SBA), the rules are based on the sensitivities of instruments to underlining risk factors
    [3] Banks with internal model approval will still need to use the revised standardised approach as a fall back in the event that an internal model is deemed inaccurate by regulators
    [4] Expected Shortfall considers average losses beyond the confidence level set for VaR. It is a more a conservative statistical measure that evaluates expected returns or losses in the most adverse outcomes predicted by the models
    [5] The impact study was carried out by three industry groups: the Global Financial Markets Association (GFMA), Institute for International Finance (IIF) and the International Swaps and Derivatives Association
    [6] See Fundamental Review of the Trading Book, CFP Summit
    [7]In FRTB banks using internal models approach (IMA) will need to apply a stressed capital add-on for risk factors deemed non-modellable, in other words, factors for which there is limited data for accurate modelling. Enhancing data pooling can help banks classify more risk factors as modellable to reduce capital requirements, however this may require investment in sophisticated data solutions.

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