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Final Call for Comments on FRTB Capital Requirements for Market Risk

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The January 1, 2022 implementation deadline of Fundamental Review of the Trading Book (FRTB) regulation may be three years out, but the data management challenges of compliance need to be considered now. Most importantly, a BCBS consultation paper on the standardised approach to calculating minimum capital requirements for OTC derivatives needs urgent industry input on what could become impossible requirements around non-modellable risk factors (NMRFs) under FRTB. The consultation paper – Revisions to the Minimum Capital Requirements for Market Risk – has a closing comment deadline of June 20, 2018.

The challenges of NMRFs include the requirement to provide frequent, real price observations of the risk factors if they are to be used in an internal model approach (IMA) to calculating minimum capital requirements for market risk in line FRTB. Without this evidence of market liquidity, products can’t be traded; with the evidence, capital requirements may be sky high, leading banks to withdraw non-profitable products.

The Data Management Super Bowl

Tim Lind, managing director of data services at DTCC, describes FRTB as ‘The Data Management Super Bowl’ in terms of trade data aggregation required for the risk factor eligibility test (RFET) of NMRFs, essentially the provision of at least 24 real price observations of the value of the risk factor over the previous 12 months, with no more than a one-month gap between any two observations. He adds: “Trade reporting per se proves nothing. This is all about the liquidity of underlying instruments as a proxy for risk.”

Considering, among other issues, approaches to gathering required data, the consultation paper states: “The Committee is also aware of nascent efforts to establish data pooling schemes that could improve the availability of real price observations for the RFET, but that may face confidentiality driven challenges that prohibit the sharing of actual prices to subscribers of such a service.”

Potential data pooling solutions

While many banks are working to understand whether they can meet NMRF data requirements internally, the likelihood is that they will not be able to demonstrate 24 real price observations in the required timeframe, across all relevant asset classes.

One potential solution is to pool data for wider industry use, a service that DTCC is developing for OTC credit derivatives. The organisation’s FRTB Real Price Observations Data Service uses DTCC’s global data infrastructure to pool observable transaction data, helping banks meet FRTB requirements and reduce risk capital charges.

Another potential solution is a utility-style response to the data management problems of NMRFs, which could be offered to a consortium of banks and based on the Secure Data Pooling Service (SDPS) developed by Iason Consulting, a risk consultancy, in partnership with Financial Machineries. The SDPS provides a cryptographic, blockchain-like technology that allows pooling of transacted data. A key feature of the service is that the administrator will not know or own the source data, or resultant data. The ownership of this data will be retained by participating banks, who can choose to share or commercialise the data in an open source format.

Other features include high levels of security, for example, no bank contributing data has access to any other bank’s data, and nor does the administrator see the source data. The only information made available to all parties is the final time series volume weighted average price, obtained via calculations on the contributed data. The Secure Data Pooling algorithm is public to contributing members, with open source code and readily available information. The service will be hosted in the Amazon Web Services cloud.

Antonio Castagna, founder of Iason Consulting, says: “The key differentiator we offer is that this managed utility will not own the data and Iason will not calculate and administer observable prices anonymously because it is the utility procedure itself that anonymously and secretly calculates the aggregated time series data and administers the final volume weighted average prices to the participant banks. Iason will only oversee the procedure to make sure that no glitches occur and that the data is correctly distributed.”

Whatever the level of difficulty in sourcing satisfactory data, the consultation paper does not back away from the concept of the RFET of NMRFs, and states: “The Committee proposes clarifications to the RFET and a number of principles to inform assessments of the quality of data that banks use to calibrate their internal models.”

Design flaws

On the topic of concerns expressed by market participants that the approach defined for NMRFs may be subject to design flaws that result in disproportionately high capital requirements for some risk factors relative to the risk they pose to a bank – for example, due to an arguably liquid risk factor not meeting requirements of the RFET or due to an overly conservative treatment of certain types of NMRFs – the Committee states it ‘has not received compelling evidence for these issues and seeks further feedback in response to the consultative document that could support a final decision on them. In the absence of compelling evidence, the Committee does not propose revisions to these aspects of the treatment of NMRFs’.

Damaging impact on liquidity

While banks need to consider whether their individual trading desks can pass FRTB’s rigorous approval process to use an IMA or whether they will have to fall back on the standardised approach described by the regulation, the problems of NMRFs also require them to carry out internal stress tests to see if a desk is viable from a profitability perspective. NMRFs may be a matter of FRTB compliance, but a lack of price observations, the capital costs the risk factors can generate and resulting decisions to withdraw products from the market could have a damaging impact on liquidity.

FRTB is a high stakes game, make sure you add your comments on the consultation paper here.

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