The Fundamental Review of the Trading Book is set to further increase data demands on banks, despite potential synergies between this new market risk framework and MiFID II.
Of all the new incoming regulations, few will have a greater impact on a financial institution’s business than the Fundamental Review of the Trading Book (FRTB).
FRTB is an update to the current Basel 2.5 framework and it introduces stricter rules for the treatment of market risk and addresses some of the weaknesses of the current framework. The scope of this regulation is global and covers rates, credit, FX, equity, and commodity asset classes.
In practice, it could result in higher capital requirements.
The rules, which were finalized in January 2016, will come into effect in 2019 and are in the process of being adopted. However, more recently some jurisdictions have chosen to announce delays to the timelines defined in January 2016.
Watch: Fundamental Review of the Trading Book (FRTB) — Market Developments, Trends and Requirements
FRTB key points
FRTB introduces a stricter separation of the trading book and the banking book in order to reduce the possibility of arbitrage between the two and to ensure a more consistent application across banks.
Banks will need to review their portfolios to determine if existing classifications of instruments as trading book or banking book are correct and whether any revisions are required.
In addition to the stricter separation of the trading book and banking book FRTB also increases the risk sensitivity of standardized approach, makes material changes in the IMA approval process, has lead to the adoption of Expected Shortfall (ES) and amendments to the Default Risk Charge (DRC).
The culmination of these changes is an increased burden on banks for data and analytics.
The need for data
Most large banks will likely use the internal models for their capital calculations — and hence will require three sources of external data: time-series market data, reference data and “real” price data.
In addition, large quantities of internal data are also required.
For banks using internal models, time-series data is a critical input into the capital models.
For example, Expected Shortfall (ES) and Default Risk Charge (DRC) calculations should be based on datasets that go back to 2007 and 10 years, respectively.
Many banks don’t currently have access to time-series data back this far. These banks will have extra work to do in order to collect high quality time-series data.
Irrespective of whether a bank is using internal models or the standardized approach, accessing the right reference data is a critical requirement of its FRTB response.
High quality and complete instrument reference data allows banks to accurately classify their instruments within the regulatory framework.
Another data challenge results from the introduction of the NMRF (Non-Modellable Risk Factor) requirements.
This specifies that banks using internal models must pass the NMRF test if they want to calculate their capital based on an ES calculation.
For this test, banks are required to determine whether they have continuously available “real” prices for a sufficient set of representative transactions.
The requirement to conduct the NMRF test creates two challenges for banks.
Firstly, for many OTC markets executed trade and committed quote data may not be readily available.
Secondly, once the data has been sourced, it needs to be organized into a consistent set of data models to be mapped into risk factors in order to determine whether they pass.
Fundamental Review of the Trading Book Modellable Risk Factors, Obligations, Variances & Governance
MiFID II synergies
FRTB compliance will have certain synergies with the upcoming EU’s MiFID II, which comes into effect in January 2018.
MiFID II mandates that trading platforms as well as buy and sell-side firms have obligations to publish trade details. It is this extensive source of information that could be used as a source of “real” price data under FRTB.
However, MiFID II post-trade data is not a complete solution for two reasons.
Data models in MiFID II are not necessarily aligned with those proposed for use within FRTB, so banks seeking to use MiFID II post-trade data for their “real” price observations may need to map the data into a new data model.
In addition, post-trade rules require each trading firm to publish trades that they execute, and each buy or sell-side firm to report through a new type of regulated entity called an APA (Approved Publication Arrangement).
The splintered nature of OTC markets in combination with the competition between different APA providers mean that the MiFID II post-trade data will be fragmented.
Avoiding negative impact
The comprehensive data that banks will be required to collect for this regulatory purpose is unprecedented.
Financial institutions are responding by participating in Quantitative Impact Study and industry working groups, as well as undertaking proof of concepts.
Long-term, banks will require a high-quality data vendor that can provide a broad range of market data, reference data and “real” price data.
Taking these necessary actions to remain compliant will help banks avoid a negative impact on their business.