Ongoing Model Performance Monitoring of pricing models across various asset classes for a large US Bank
Client : Large US Bank
Objective
To provide a top-tier US bank with ongoing performance monitoring of 50+ pricing models across Rates, Equity, Forex, Commodity, Credit and CVA asset classes.
CRISIL's Solution
- Using process standardization and automation techniques, developed an efficient and cost-effective solution to monitor models on a quarterly basis
- Market data used is no older than the quarter prior to the assessment
- Tests during monitoring include:
- Convergence and Stability Tests (NPV and Greeks)
- Consistency Tests (parity relationships, model limits, accuracy tests)
- Stress Tests (large volatilities, negative rates)
- PnL Attribution (30 business reports and regression tests)
- Convergence and Stability Tests (NPV and Greeks)
- Most tests have well-defined numerical outputs that are compared against predefined thresholds (Green/Yellow/Red)
- Monitoring process includes documentation/reporting of the results
- FX: Cross-Currency Swap Model
- FX Spot Rate Sensitivity
- DV01
- Consistency with Single-Currency Swap
- FX Spot Rate Sensitivity
- Credit & SP: CDS Pricer
- Monotonicity of the Price on the Hazard Curve
- 30 days PnL (R2)
- Spread01
- FX: Cross-Currency Swap Model
Process Automation
- For equity and FX models, developed common python frameworks that allow running/monitoring in a standardised manner
- Documentation performed directly from scripting
- Infrastructure allows one analyst to monitor 14 models (tests + documentation) in less than 10 working days
- Similar infrastructure being developed for other desks
Client Impact
- Solution provides effective model monitoring across asset classes, faster and at lower cost
- Test results presented in well-defined presentation with comparison to pre-defined thresholds using color coding, allowing for easy analysis and enhanced decision making