Industry perspective: Overcoming FRTB data challenges

This article was written by Thomas Labbe, Regulatory Data Product Manager at Bloomberg. 

The Fundamental Review of the Trading Book (FRTB), a global set of rules designed to prevent the systemic losses seen on banks’ trading books after the 2008 financial crisis, are certainly valuable but exceedingly complex.

To get a pulse on specific data challenges in the context of FRTB implementation, Bloomberg recently hosted an interactive roundtable in London with multiple global banks to hear their views on how to address these complexities. The conversation delved into how banks are juggling implementation timelines and deviations from Basel standards, treatment of funds, and modellability of risk factors for the Internal Model Approach.

This is the first blog in Bloomberg’s series on FRTB, which overviews how banks, specifically those in Europe, are thinking through these data challenges and how Bloomberg actively incorporates industry feedback and evolving regulatory guidance into its FRTB solutions so clients are prepared.

Navigating staggered implementation timelines

As part of global regulatory reforms emanating from the Basel Committee, FRTB is being implemented at a local level by each jurisdiction. Different jurisdictions have different deadlines for compliance and managing these staggered timelines came up as a top challenge during the roundtable discussion.

Since most banks reported operating on a stop-and-go project mode over the past few years, they have had to make sure their budget would remain approved despite compliance deadline extensions and changes.

Another key concern is how much jurisdictions are deviating from the Basel standards when transposed at the national level and the knock-on effects. For example, if some rules are more lenient in one jurisdiction, would that influence other regulators to adapt their standards? This will remain a key topic of discussion as industry participants and regulators parse through the 1,000 plus pages of the recently announced U.S. Notice Purpose of Rulemaking (NPR).

The challenge of funds

Participants noted that certain ESG or private equity funds might have to be immediately allocated to the banking book, meaning they would be excluded from their trading activities. Once something is allocated to the banking book, it is nearly impossible to move it to the trading book. This is a concern as it could reduce liquidity overall in this asset class and strategic sectors like ESG could suffer as a result.

Another major talking point at the roundtable was the most punitive risk weight for funds at 70%, which could pose additional threat to the business. As such, alternative methods to bucket funds under lower risk weights have been proving difficult for example, the look-through approach which requires substantial funds holdings data that can be difficult to obtain.

Depending on the jurisdiction, a strict interpretation of the look-through approach would require banks to have access to the exact holdings of the funds–which could be interpreted as 100%. Meanwhile, other jurisdictions mention the funds’ information should be sufficient, meaning not requiring 100% of holdings data–leaving room for much needed flexibility. This would help to alleviate challenges around hedging items, such as derivatives, which are not frequently tickerized so obtaining full holdings data for an entire universe would be nearly impossible. There is also the logistical aspect of decomposing funds to examine their holdings data that requires potentially booking thousands of lines of constituents’ data for a single fund. Yet, many of banks’ risk systems would not be able to handle this.

During the discussion, banks expressed interest in sourcing funds holdings data as well as getting help with allocating the funds to the right bucket in order to save on capital charges.

Confidently meeting the Risk Factor Eligibility Test (RFET)

The final area of discussion was around the two ways for calculating capital requirements for trading risk with FRTB. The first is the Standardized Approach (SA), where every bank calculates the same way, and the second is the Internal Model Approach (IMA) where banks use their own model and get it approved by the regulator. The benefit for IMA is a bank can theoretically put less capital aside but getting this model approved by regulators is very complex.

During the roundtable, banks indicated that the biggest challenge for IMA came from the P&L attribution test (PLAT), followed by the Risk Factor Eligibility test (RFET).

Banks discussed prioritizing their own internal data to pass these tests. However, a common concern was their data may not be sufficient for every asset class they are looking to apply for IMA approval. This could increase non-modellability of risk factors and result in higher capital charges. Data vendors, like Bloomberg, are expected to play a key role supplementing banks’ observations with comprehensive asset class data. Key requirements banks cited for prospective data vendors depended on instrument coverage plus auditability criteria for third parties as prescribed by the regulator.

Upcoming FRTB deadlines

The above challenges are not only relevant for European banks but are also top of mind for American banks, especially with the recently announced U.S. Notice Purpose of Rulemaking (NPR), which noted a U.S. start date for FRTB beginning from July 2025.

To help banks manage existing FRTB requirements and meet upcoming compliance deadlines, Bloomberg provides both enterprise data and analytical solutions. Whether firms require FRTB-ready market data, a reliable risk analytics engine or a full end-to-end workflow, Bloomberg can customize a package to meet specific requirements across all major jurisdictions.

Bloomberg’s FRTB Data Solution provides scalable, enterprise access to high-quality, complete data and helps banks to gain approval for their models while minimizing add-on capital charges. This solution covers both the Standard Approach (Bucketing of Risk Factors) and the Internal Model Approach (Risk Factor Eligibility Test).

Bloomberg’s Multi-Asset Risk System (MARS) Market Risk solution offers a suite of risk analytics and calculations for the entire FRTB workflow. With market-leading data at its core, MARS Market Risk provides banks with the necessary tools to accurately model multi-asset portfolios and meet regulatory risk management and reporting needs.

To hear more FRTB implementation and data challenges, view our recent webinar, FRTB – the Final Countdown.