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Are banks going to miss the FRTB Standardised Approach deadline?

Fausto Marseglia
Fausto Marseglia
Head of Product Management, FRTB and Regulatory Propositions, Refinitiv
Attika Raj
Attika Raj
Regulatory Analytics Product Lead Manager, LSEG

For many small and medium-sized banks, the implementation of the Fundamental Review of the Trading Book (FRTB) regulation is proving to be a significant headache. Under the Standardised Approach’s (SA) Sensitivities Based Method (SBM), banks must perform new analytics using large quantities of data. Projects to source data and build analytics internally can be complex and expensive, leaving firms at risk of overrunning the implementation deadline.

  1. FRTB SA compels banks to implement SBM
  2. SBM requires significant quantities of data, which many small and medium-sized banks are struggling to deliver internally
  3. Working with Refinitiv and Yield Book for data and analytics can enable banks to implement the FRTB SA with confidence

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Small and mid-sized banks around the globe are facing enormous data and analytics challenges as they move towards the Fundamental Review of the Trading Book (FRTB) deadline to implement the SA.

FRTB is a set of regulations developed by the Basel Committee on Banking Supervision, to improve the way banks calculate and hold regulatory capital for market risk. The new framework replaces a pre-existing one, incorporating lessons learned from the Global Financial Crisis of 2008.

One of the biggest changes in the new rules is that they are being applied at the individual trading desk level, rather than at the enterprise level. This delivers more granularity to the risk charges and capital requirements for regulators, but for banks, it means that their data and the analytics need to be much more granular, too.

Another big change for banks implementing the SA is that the capital requirement calculation now requires measuring the risk sensitivity of the positions, quantifying the impact of fluctuations in risk impacts on the portfolio and on asset valuations.

Refinitiv FRTB Data Solutions: Obtain the data you need for the Standardised and Internal Models Approaches

Understanding the FRTB Standardised Approach

While international and large regional banks will likely implement some desks via the Internal ModelsApproach (IMA) – using their market risk models for regulatory capital allocation – all banks will have to implement SA anyway for a number of their desks. The SA approach applies the same rules for calculating capital to all the banks using it, and is considered less resource-intensive to use, which makes it more palatable to smaller banks, to the expense of generally higher capitals charges compared to the IMA.

That doesn’t mean that Standardised Approach banks get off lightly – they need to implement the Sensitivities Based Method (SBM). Individual desks have to perform sensitivity calculations that focus on identifying risk factors for various risk classes and measuring the impact of these risk factors on asset and portfolio positions. The desks also need to complete the aggregation of risk charges, which incorporates correlations between risk factors and risk buckets into the overall calculations for regulatory capital.

Bank trading desks need large quantities of data to undertake these Sensitivities Based Method calculations. For example, in addition to a range of market data fields, desks will need the risk class, risk bucket, and risk weight information. They will also need an up-to-date and high-quality inventory of T&Cs data for relevant financial instruments representing their trading positions, which is a prerequisite to correctly classify trading positions to the relevant risk buckets.

There are other SA Sensitivities Based Method elements that trading desks will need information on, too. For the Funds Look-Through Approach, the FRTB rules say that equity investments in funds will need to be teased apart so that the underlying positions of the fund are transparent. Then, these underlying positions will need to be treated as if they were held directly by the bank for the purpose of calculating the relevant sensitivities. So, trading desks will need all the data on each position, and related SBM data such as risk weights.

Trading desks also have to contend with the Index Look-Through Approach. This is similar to the Funds Look Through Approach, but designed for index instruments. Trading desks will need to access individual constituents of an index, to treat the underlying positions as if they were held directly by the bank.

Standardised Approach Challenges

Given the complex data and analytics requirements of the SA it’s not a surprise that firms are facing some substantial challenges, including:

  • Obtaining and managing all the needed data to perform the calculations, including market data such as yield/credit curves, prices and volatility information. They also need holdings and transaction data.
  • Meeting SBM risk bucketing requirements
  • Performing the necessary sensitivity calculations
  • Aggregating the risk charges within and across the risk buckets, and analysing these for potential correlations

The data requirements, computational costs and complexity of these challenges are pushing banks to work with a partner for SBM data and calculations.

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Solving the SBM data issues

Banks using the SA for trading desks are turning to Refinitiv for data, analytics, or both – solving this knotty compliance challenge so their teams can focus on other, more value-generating activities.

For example, Refinitiv Datascope and Datascope Plus today provide firms with:

  • Risk Class – specifies the class of risk the instruments belong to
  • Risk Bucket – specifies the set of risk factors which the instrument relates to
  • Risk Weight – measures how much that instrument is impacted by the relevant risk factor

To deliver full transparency as to how buckets and weights have been calculated, Refinitiv also provides new fields for the data it uses to calculate risk class, risk weight, and risk bucket, including FRTB Economy Type, FRTB Sector, FRTB Market Cap, and Credit Quality.

In addition, Refinitiv enables firms to fulfil the Funds Look-Through requirements by using DataScope Select and DataScope On Site. Firms can access their current list of individual constituents and weights for the relevant funds in their portfolio, including the identification of UCITs and alternative investment funds.

To meet the Index Look-Through requirements, firms can use the DataStream solution. There, they can access the current list of individual constituents and weights for listed equity and credit indices.

How can banks meet their SBM analytics needs?

Many Standardised Approach banks are also outsourcing analytics for the capital requirements calculation, to reduce the burden on trading desks and their IT teams. Yield Book – part of London Stock Exchange Group’s Information Services Division – is a market leader in fixed income analytics.

Through Yield Book’s FRTB SBM FI engine, firms will be able to perform analytics for interest rate and credit spread asset classes. These may be used alongside Yield Book’s fixed income valuation engine for a seamless user experience.

Along with this, Refinitiv FRTB SA data is being integrated into Yield Book’s FRTB engine. For firms, this will make Yield Book a one stop FRTB SA solution for fixed income, with data availability, risk factor mapping, sensitivities calculations and risk charge determinations for FRTB’s GIRR and CSR risk classes. Yield Book can also provide various risk factor data components like risk-free yield curves and volatilities.

So, for banks seeking to implement the SA, the challenges can be large, and time is growing short. Working with Refinitiv and Yield Book to solve critical SBM compliance challenges can enable firms to meet their regulatory capital calculation obligations with confidence, freeing teams to focus on other, value-generating activities.


What are the Fundamental Review of the Trading Book (FRTB)?

FRTB is a set of regulations developed by the Basel Committee on Banking Supervision, to improve the way banks calculate and hold regulatory capital for market risk.