FRTB (Fundamental Review of the Trading Book)
FRTB is a Basel Committee regulatory framework that fundamentally revises how banks calculate market risk capital requirements for their trading books. It replaces the previous Basel 2.5 market risk framework with a more risk-sensitive approach, introducing a clear boundary between the trading book and banking book,ζ°η standardized approach and internal models approach for capital calculation, and stricter requirements for model approval and backtesting. FRTB also introduces the concept of Profits and Losses Attribution testing to verify that banks' risk models accurately reflect actual trading P&L.
In Financial Services
Real-World Example
A global investment bank prepares for FRTB implementation by deploying a new market risk platform that calculates sensitivities across all trading book positions daily. The bank implements a Profit and Loss Attribution testing framework that compares daily risk-theoretical P&L against actual P&L for each trading desk, with thresholds set at 10% for the first PLAT test. Trading desks that fail PLAT tests must use the standardized approach for capital calculation, increasing their capital requirements by an average of 30%. The bank invests $50 million in new risk infrastructure, including a real-time risk data warehouse, sensitivity calculation engines, and automated regulatory reporting.
Why It Matters for Finance
FRTB represents the most significant change to market risk capital requirements in decades. For finance professionals in trading, risk management, and capital planning, understanding FRTB is essential because it directly impacts trading profitability, capital allocation, and the cost of maintaining trading book positions. AI solutions that automate sensitivity calculations and PLAT testing are increasingly critical for FRTB compliance.
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Frequently Asked Questions
What is FRTB and how does it affect trading books?
FRTB is a Basel framework that revises market risk capital requirements for trading books. It introduces stricter boundaries between trading and banking books, new capital calculation approaches, and Profit and Loss Attribution testing for model approval.
How is AI used for FRTB compliance in investment banks?
AI automates sensitivity calculations across thousands of positions, enables real-time Profit and Loss Attribution testing, and streamlines regulatory reporting. Machine learning models help identify trading books likely to fail PLAT tests before they occur.
What are the key FRTB capital requirements for market risk?
FRTB introduces a Standardised Approach using prescribed risk weights and sensitivities, and an Internal Models Approach requiring regulatory approval. Banks must pass PLAT tests to use internal models, or face higher capital charges under the standardized approach.