One of the most significant impacts of the FRTB is the reform of the internal models framework.
The FRTB framework seeks to address several weaknesses in the previous internal models approach identified by regulators, including:
- Underestimation of credit risk.
- Inadequate capture of market risk, particularly for structured credit products.
- Unintended incentives for excessive tail-risk taking.
- A high frequency of backtesting exceptions, highlighting significant discrepancies between actual losses and modelled losses.
Key Revisions to the Framework
Transition from Value at Risk to Expected Shortfall
Expected Shortfall replaces Value at Risk (VaR) to provide a more comprehensive measure of tail risk by estimating the average loss beyond the 97.5% confidence threshold.
By comparison, Value at Risk (VaR) estimates the potential loss in the market value of a portfolio at a given confidence level and over a specified time horizon. Under the previous market risk framework, VaR was generally calibrated at a 99% confidence level.
Introduction of Multiple Liquidity Horizons
Differentiated liquidity horizons account for the time required to exit or hedge positions, thereby providing a more realistic representation of market liquidity. Unlike the previous framework, the FRTB does not assume that all positions can be liquidated within a uniform 10-day horizon.
Strengthened Controls and Internal Model Validation
The FRTB introduces more stringent requirements for internal model approval and ongoing validation, notably through the Profit and Loss Attribution (PLA) test and enhanced requirements concerning the modellability of risk factors.
Conclusion
The FRTB provides a more robust framework for measuring market risk by incorporating tail losses, differences in the liquidity of financial instruments, and more stringent standards for model governance.
For banks, a key challenge is to demonstrate, on an ongoing basis and using sufficiently reliable market data, that their internal models adequately reflect the underlying risks. Where risks cannot be appropriately modelled, this may directly affect the resulting regulatory capital requirements.
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