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
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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
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