FRTB implementation – Covid-19 and Libor pressure

Industry leaders discuss the pressures Fundamental Review of the Trading Book (FRTB) is placing on banks’ data infrastructure and systems, how FRTB may constrain banks’ ability to manage future volatility, and the potential complications to implementation caused by such factors as the Covid‑19 pandemic and the transition away from Libor

The panel

• David Cassonnet, Director of Business Development, ActiveViam
• Essan Soobratty, Product Manager, Regulatory Data, Bloomberg
• Eugene Stern, Head of MARS Market Risk, Bloomberg
• Risk modelling lead at a European global banking group

What impact has the Covid-19 pandemic had on banks’ FRTB preparations?

Essan Soobratty. Bloomberg

Essan Soobratty, Bloomberg: Regulators providing additional time for compliance because of the Covid-19 pandemic affords banks the flexibility to reprioritise resources in the short term where necessary without falling behind in their FRTB implementation. Despite this, banks have mostly continued along their established pre-Covid trajectories. This extension is being viewed as less of a delay and more an opportunity to continue at a pace that allows for a more strategic implementation.

Eugene Stern, Bloomberg: It is useful to separate risk modelling issues from operational ones. On the one hand – the operational side – the pandemic has resulted in a one-year delay to Basel III implementation and delays to many national supervisors’ FRTB deadlines. Banks that may have fallen behind on the original dates now have time to catch up.

On the other hand, some banks that were close to being on schedule have been able to pause and address the issues arising out of the Covid-19 pandemic. These banks will now need to ensure they refocus on FRTB to meet the new deadlines. In a few years, we may find the legacy of the crisis to be on the risk modelling side, through immediate issues such as negative commodity prices, or more long-term questions about improving our risk models to handle the market volatility we have seen this quarter.

David Cassonnet, ActiveViam: Institutions with FRTB projects in their current and near-future pipelines have kept them because they do not want to lose budget for this year – especially those that need to meet the December 2020 revised Capital Requirements Regulation (CRR II) deadline. Since regulators had already delayed the FRTB implementation by a year, some banks had a late start. For example, to be ready for January 2022, a parallel run in 2021 will be required for one year – which means development of the systems during 2020 – so it has to be started now.

Some banks have already chosen their risk/valuation engines or are migrating their existing solutions to handle sensitivities/profit-and-loss (P&L) computations and see FRTB as something to be tackled using the lowest-cost solution. We see this as a mistake and a missed opportunity. The extra time can be used to create a holistic approach, inclusive of everyday risk management. While a cheaper solution may tick the box, one that provides the ability to combine internal risk management – which a bank needs to do anyway – with regulatory compliance will provide the most cost savings and benefits in the long run. 

Risk modelling lead at a European global banking group: On one hand, Covid‑19 led to a change in the regulatory agenda with a postponement of activities related to the updated CRR II at least to year-end. This slippage is adding even more complexity to an approval process that, since the outset, has always been aimed at moving targets, while the European Central Bank has currently not communicated any postponement to the Q3 2021 deadline for applications. This would clearly put any project management office under severe strain – even before the Covid‑19 pandemic. On the other hand, banks will need to rethink priorities and redirect resources. While the reporting requirement will apply in EU form in Q3 2023, uncertainty as to how the ‘own funds requirement’ implications of the reform are applied might de-prioritise FRTB-related implementations to avoid sunk costs in the absence of clear and crystallised regulatory guidance.

 

Considering the requirement for value-at-risk (VAR)-based backtesting, to what extent will FRTB constrain banks’ abilities to manage future volatility?

David Cassonnet, ActiveViam

David Cassonnet: VAR backtesting requirements should not impact banks’ ability to manage future volatility. Capital requirements governance and processes should be run in parallel with actual business risk management governance and processes. This means implementation of VAR backtesting is not mutually exclusive, with the ability to manage future volatility. If the two processes are robust and well established, one should support the other. 

Eugene Stern: FRTB is a capital model, and managing capital is not the same as managing volatility. Capital models should be asking what sort of event a bank needs to be able to survive (or not), and the position in which it might find itself after the deadline. Market risk capital models have been moving away from straight volatility forecasting at least since the financial crisis that began in 2007–08, after which we saw the introduction of stressed VAR. FRTB is another step in this direction, with stressed expected shortfall (SES) for internal models, as well a standardised approach (SA), serving as either a floor or a binding capital calculation, with no volatility model at all. The VAR backtesting requirement should be seen as incentivising banks to avoid resting their market risk capital frameworks on volatility models that might not be very robust.

Risk modelling lead: The CRR II transposition of the Basel Committee on Banking Supervision text contains a definition of VAR to be used for backtesting purposes that is much more restrictive than the Basel 16 and the Basel 19 versions of the standard. In particular, the requirement is for such VAR not to include any non-modellable risk factors (NMRFs). The corresponding actual and hypothetical P&Ls are inclusive of both modellable risk factors and NMRFs, which is like comparing apples with pears. However, a bank is allowed to disregard any exception that might be induced by the missing risk factors in case there is sufficient SES capital set aside for NMRFs. While such a set-up – despite its statistical incoherence – can ensure sufficient capitalisation across all types of risk factors, it is difficult to see how such VAR could be used for business steering or for risk management purposes. A metric used to measure risks and manage market volatility must be based on the full set of risk factors moving jointly according to their interrelationship in the market.

 

The Basel Committee on Banking Supervision’s Basel III April monitoring report sparked debate over banks’ varying assessments of capital requirements. What can regulators do to ensure a level playing field?

Risk modelling lead: They should approach banks perceived as outliers and conduct a deep-dive on the reasons for such divergence.

 

What are the pros and cons of the different FRTB approaches to calculating market risk capital, and how have these changed in the current environment?

Eugene Stern, Bloomberg

Eugene Stern: The first thing to note is that both the SA and internal models approach (IMA) to FRTB are quite prescriptive, certainly compared with most banks’ capital modelling under Basel 2.5. In both tracks, a tension can be observed between the pros of best practices and the cons of higher costs, as well as potential over-standardisation. Bloomberg tries to help banks attain best practices in risk modelling without having to bear the full cost of building the data and analytics platforms in-house, while also giving them the flexibility to make their own choices on model configuration and data mappings.

David Cassonnet: From our FRTB working group in Europe, the Middle East and Africa, clients have told us the decision to perform the SA or the IMA may have been influenced by a local regulator, so not all banks are able to choose freely. Generally speaking, whether IMA is preferable to SA is a desk-driven decision, contingent on the composition of the underlying portfolio. The ability to take out or insert a set of trades, change values and test the capital charge is key here. Banks may opt for the SA if they have not laid the groundwork – quantitative analysis and backtesting – for the IMA. While this may work operationally, it may not be the best way to optimise the FRTB calculations and therefore the bank’s capital.  

Risk modelling lead: The IMA is applied at desk level, and quantitative standards such as the P&L attribution test and backtesting need to be met on a permanent basis. Failure to meet them means downgrading to a typically more punitive SA. Market events such as those experienced throughout the Covid‑19 pandemic can easily lead to the failure of both tests with subsequent aggravation of risk-weighted asset (RWA) density with all the problems induced by RWA procyclicality.

The new default risk capital seems an improvement over the Basel 2.5 incremental risk charge, removing most of the double‑counting it embedded.

 

What pressures does FRTB place on banks’ data infrastructure and systems?

David Cassonnet: Institutions with global operations and numerous front-office systems and risk management processes will need to be mindful of finding a way to bind them altogether. 

A ‘de-siloed’ approach is the way to go here, as each bank function (front office, risk, finance) needs to examine something different, but all of the pieces impact the capital charge. A risk manager would want the ability to drill down into the sensitivities and examine the impact. A desk manager may want to perform what-if analysis on how the addition or subtraction of new business lines would impact a portfolio. A tool that affords the ability to isolate a slice of risk; change a book, desk or set of trades; refresh data on the fly so only the most recent data points are updated; and provide a real-time view into risk provides all of these things. For its part, a regulator would want to see real-time reports. 

To provide the most up-to-date information, you need those departments to effectively communicate with one another. In the IMA, for example, banks need to match risk-theoretical P&L with the hypothetical, and actual P&L to maintain their IMA status. This involves a number of complex tasks including aligning different data models and data sources and sourcing NMRFs. This places enormous pressure on the entire banking ecosystem from the front office through to risk and finance. Even institutions that aim at proactively managing, explaining and optimising FRTB calculations will encounter difficulties without an overlay across their systems that aggregates all the necessary data and makes it visible in one place. 

Essan Soobratty: The quantity and variety of data required for effective FRTB implementation introduces a number of governance and operational challenges, especially if banks are to achieve the necessary alignment required for many FRTB workflows. 

Adding to these data management challenges is the need to implement the large volume of desk-level calculations required across both SA and IMA. These data management and computing challenges have forced banks to accelerate upgrades to their systems and the underlying technology. 

Banks continue to explore a mix of on-premises development, third-party cloud deployment and, increasingly, hybrid implementation.

Eugene Stern: Every bank is facing challenges, as all are being pushed beyond their comfort zones by some aspect of the new rules. The key for all to realise is that solving for FRTB requires having access to a risk platform that ensures consistency, scalability and accuracy across all asset classes. From this point of view, particular business challenges are simply requirements for that platform, and banks that frame the question that way should be well positioned to decide whether they are best positioned to build out the required platform themselves or to integrate components provided by a vendor or strategic partner.

 

What complications does the transition away from Libor pose within the FRTB framework?

Essan Soobratty: From a data perspective, during the transition from interbank offered rates to new risk-free rate benchmarks, there have long been concerns around the ability of banks to evidence the necessary real price observations to satisfy the risk factor eligibility test for new benchmark rate instruments. 

In releasing their June 2020 FAQ, the Basel Committee mitigated some of those concerns by permitting banks to include observations from old and new benchmarks for one year following discontinuation of the old benchmark.

There are other requirements in FRTB where the transition from old to new rates will continue to complicate risk analytics and calibration that rely on normalised time series data. 

 

How can banks navigate the remaining implementation challenges of FRTB?

David Cassonnet: Regulatory compliance is not just about providing top-of-house or per-desk metrics. You have to explain those metrics. A bank would want a flexible solution that allows them to keep their best-of-breed calculation engines and perform predictive analytics on top. To fully satisfy regulators, it is better if business users can monitor risk intraday, as new transactions occur, so they have more time to analyse the impact of market moves, for example, and make necessary adjustments (such as data quality issues). Some analysis cases also require the ability to modify raw data – under what-if assumptions – and see the impact on official metrics, again at various levels of granularity. This requires tools that can handle not only the sheer volume of data the new regulations call for, but even more data generated by those assumptions. The point of doing all that is critical, not just a fancy optional feature, because it is the only way to understand some of the impacts of regulatory compliance, such as testing desk eligibility to the IMA over time. It also allows a bank to look at trading activity and how a series of trades would impact risk capital consumption. Running complex data analytics at scale on moving data, as business activity is occurring, is an unparalleled risk management advantage.

Essan Soobratty: Banks that have adopted a strategic approach to implementing FRTB in terms of acquiring and managing data in a way that benefits the organisation beyond FRTB already see benefits across trading, risk and back-office operations. 

An example of an area presenting continued challenges for banks is the need to analyse their positions in funds by applying the Basel Committee’s look-through criteria and treat underlying positions in funds (and index products) as if the bank held the underlying positions directly. The challenges relate to acquiring data and also in computing the risk analytics. Addressing these challenges in a timely and strategic manner benefits the trading and risk operations today, and takes the bank further along its path to FRTB compliance.

Prioritising investment in the data, systems and technology that benefit the organisation beyond FRTB will allow banks to remain on a firm trajectory towards eventual FRTB compliance. Banks with IMA decisions yet to be finalised will continue to move towards a state of IMA compatibility that provides them with flexibility to pivot as needed.

Eugene Stern: We still see a lot of variation among banks in FRTB plans and readiness. Nonetheless, we can highlight two themes. First, even with the shift in the regulatory calendar, there is still not much time left. While different banks have different key problems left to solve, in many cases the ‘low-hanging fruit’ has already been picked, and the challenges that remain are significant. Banks need to identify and prioritise the key remaining hurdles of data, analytics, technology and operations, then decide which challenges they can solve on their own and which they need help with. Second, it’s important to remember that FRTB development won’t stop with the first go-live date. Some banks initially going live with SA have plans to build out IMA in the future, while others expect to upgrade their data and modelling infrastructures over time.

 

FRTB – Special report 2020
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