The countdown is on, and financial institutions are getting serious about preparing for new Fundamental Review of the Trading (FRTB) requirements – slated to take effect in January 2022. The new standards are expected to dramatically change the way that firms calculate, plan for, and manage market risk.
The stakes are high, the rules are complex, and banks will have to rework their models and processes to accurately capture risk. Careful planning and adequate lead time will play vital roles in FRTB compliance success and in banks’ ability to avoid excessive punitive capital charges.
There are strong indications that it hasn’t been smooth sailing for many financial services organizations on this important journey. According to Chartis Research, more than 50% of financial institutions surveyed in the firm’s 2016 FRTB study said they are not certain their bank will meet the 2019 deadline (Note, the survey was conducted prior to the revised effective date of January 2022).
FRTB readiness seems to consistently be top-of-mind for IT decision-makers, but the bulk of discussion tends to be around a handful of stubborn challenges pertaining to data collection and analysis, progress in defining methodology and general lingering uncertainty. Keeping these considerations in mind, there are four key takeaways decision makers must be privy to as they continue to revise FRTB adherence approach.
- Collecting and managing data – as well as general apprehension about data as it relates to FRTB – is a major concern. Data availability and data quality are critical issues for organizations whether they are opting to use the standardized approach (SA) or an internal model approach (IMA) to calculate their capital under FRTB. When it comes to collecting data, most say this process is significantly lacking in sophistication. Furthermore, analyzing and managing data once collected is a challenge for financial institutions due to a lack of bandwidth to make sense of all the available information at their disposal.
- Siloed (or non-existent) systems remain a culprit. The greatest challenge for their financial institution’s ability to leverage FRTB data in strategic business decisions is the fact that their data is in disparate systems. Firms even have a difficult time composing and gathering this data in the first place. Collecting the high volume of data required across multiple trading desks to comply with FRTB appears to be a monumental task for firms to undertake. They must collect this data on a daily basis and keep it for specified periods of time, which is no easy task.
- Process automation and data management (including governance) are the greatest drivers for success when undertaking FRTB projects. The new rules present big data management challenges as many banks regard sourcing required market data as a top challenge. To succeed, banks must better organize/centralize their data and ensure its accuracy. Banks must also ensure data is consistently treated—this includes ensuring consistent calculations and sensitivity data between the front office and risk management teams. Automating areas like back testing and risk reporting can reduce time, the chance of errors and the overall costs for compliance.
- Firms are making progress with methodology. Especially in the areas of expected shortfall models, stress period identification for risk factors, default risk charge and counterparty credit risk. This represents a change from a year ago when bankers were focused squarely on creating methodologies and models and reconciling front- and back-office models. Organizations, however, still have some work to do, particularly in profit and loss (P&L) attribution model development and N-MRF (non-modellable risk factors) capital calculation methodology.
The Path Forward
FRTB’s extended data demands require unprecedented alignment between front-office, risk and finance functions, especially for internal model approval. The industry has increasingly understood the growing need for this alignment in the years since the financial crisis, but progress in individual institutions has varied widely. Firms can no longer drag their feet as risk and finance alignment is essential to FRTB compliance.
With these findings in mind and the need for greater alignment between front-office, risk, and finance, banks should factor several considerations and best practices into their decisions about FRTB process automation and data management.
FRTB is an extremely complex regulation with fundamental changes to the capital adequacy process. While P&L attribution and N-MRF continue to be challenges, banks are starting to look at implementation and automation of the entire process. Firms must prepare today to create a foundational system for the future that gives them the visibility and flexibility required to comply with the FRTB standards. By seeking an architecture that encompasses a unified data foundation, expanded data modeling and governance capabilities, next-generation model validation and governance, advanced predictive analytics, and extensive automated reporting capabilities, financial institutions will be well positioned for the new world ahead.