Scenario Computation Models to compute the profit or loss (P&L) under scenarios defined in terms of shocks to various Market Risk factors for a large Global Bank
Client : European Global Bank
Objective
To test and validate scenario computation models used by a European Global Bank to compute PnL under shocks to various market factors.
CRISIL's Solution
- Assessed methodology documents quality in accordance with the SR 11-7 requirements
- Conducted input data assessment spanning data quality, data fit-for-purpose, data governance, and data assumptions and limitations
- Verified model implementation at the risk-factor level, product level, and book level
- Identified 32 material products across asset classes, and conducted performance testing using GMAG FO-RMS pricers
- Performance testing included comparing the three computation approaches (full reval., partial reval., and SBA). This was done using a range of hypothetical shocks to various risk factors encompassing regulatory scenarios
- Verified the appropriateness and adequacy of model governance and ongoing monitoring activities
- Validated associated models, such as error correction models for IR, FX, and equity, along with de-arbitrage models, such as FX skew de-arb model and IR smoothing model
- Conducted the annual revalidation of material risk factors, such as equity spot and vol., FX spot, and credit spot risk factors
- Established minimum standard guidelines and acceptance thresholds for model use
Client Impact
- Conducted the first comprehensive validation of all the market-risk stress-testing models across the bank's legal entities
- Established minimum standard guidelines for the use of partial revaluation and sensitivity-based approaches for different asset classes, product types, risk factors, and scenarios
- Successfully conducted IT regression testing of the Excel-based pricers with front office systems for 35 material products