Interest Rate Risk in the Banking Book: Stress Testing and Scenario Analysis
Economic → Interest Rate Shocks
RAI Insights | 2025-11-02 22:20:52
RAI Insights | 2025-11-02 22:20:52
Introduction Slide – Interest Rate Risk in the Banking Book: Stress Testing and Scenario Analysis
Assessing Bank Resilience Against Rate Volatility
Overview
- Interest Rate Risk in the Banking Book (IRRBB) stress testing evaluates how banks withstand adverse movements in interest rates, focusing on risks not captured by static models.
- Understanding IRRBB is crucial for financial stability, as excessive risk can threaten bank earnings and capital, especially in volatile environments.
- This deck covers the principles of stress testing, scenario construction, behavioral challenges, regulatory expectations, and practical implementation.
- Key insight: Stress testing reveals vulnerabilities hidden by standard calculations, especially around behavioral assumptions and tail events.
Key Discussion Points – IRRBB Stress Testing and Scenario Analysis
Beyond the Standard: Drivers and Insights
Main Points
- Standard IRRBB calculations use predefined rate shocks (e.g., ±200 bps parallel shifts) but may miss tail-risk events and behavioral surprises.
- Stress testing explores severe scenarios, including non-linear rate jumps, market disruptions, and shifts in customer behavior (e.g., mass withdrawals, accelerated prepayments).
- Risk considerations include non-maturity deposit behavior, prepayment risk, basis risk, option risk, and credit spread risk, all amplified under stress.
- Takeaway: Effective stress testing requires collaboration across treasury, risk, and finance teams to challenge assumptions and uncover material risks.
Graphical Analysis – Yield Curve Stress Scenarios
Visualizing Rate Shock Impact
Context and Interpretation
- This layered chart illustrates the impact of different stress scenarios on a bank’s net interest income (NII) and economic value of equity (EVE) across yield curve shapes.
- Trends show how parallel, steepening, and flattening shocks affect risk metrics differently, with severe stress scenarios (tail events) causing disproportionate losses.
- Risk considerations include the bank’s ability to reprice assets and liabilities, hedge effectiveness, and behavioral adjustments.
- Key insight: Tail-risk scenarios expose vulnerabilities not visible under normal or moderate stress.
Figure: Impact of Yield Curve Stress Scenarios on NII and EVE
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{"Scenario": "Steepening", "NII_Impact": -8, "EVE_Impact": -20, "Prepayment_Rate": 30},
{"Scenario": "Flattening", "NII_Impact": -3, "EVE_Impact": -8, "Prepayment_Rate": 10},
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}Graphical Analysis – IRRBB Stress Testing Project Timeline
Context and Interpretation
- This Gantt chart outlines the typical phases of an IRRBB stress testing project, from scenario design to results analysis and management action.
- Trends show that effective stress testing requires iterative refinement, especially as new risks and behavioral patterns emerge.
- Risk considerations include the need for timely responses to adverse scenarios and the integration of findings into risk appetite frameworks.
- Key insight: A structured, phased approach ensures comprehensive coverage and actionable outcomes.
Figure: IRRBB Stress Testing Project Timeline
gantt title IRRBB Stress Testing Project Timeline dateFormat YYYY-MM-DD section Preparation Scenario Design :a1, 2025-11-01, 14d Data Collection :after a1, 7d section Execution Model Calibration :a2, after a1, 10d Stress Test Run :after a2, 7d section Analysis Results Review :a3, after a2, 7d Management Reporting :after a3, 5d section Action Risk Mitigation Planning :a4, after a3, 10d
Analytical Summary & Table – Scenario Impact Comparison
Quantitative and Qualitative Stress Test Outcomes
Key Discussion Points
- Stress testing outcomes vary significantly by scenario type, with tail events and behavioral shifts causing the most severe impacts.
- Contextual interpretation emphasizes the importance of scenario selection, including historical, hypothetical, and reverse stress tests.
- The significance of metrics like NII and EVE lies in their ability to capture both earnings and capital risk under stress.
- Assumptions around deposit stability and prepayment behavior are critical limitations; real-world outcomes may diverge from models.
Illustrative Scenario Impact Table
| Scenario | NII Impact (%) | EVE Impact (%) | Behavioral Shift |
|---|---|---|---|
| Parallel Up | -6 | -15 | Moderate |
| Parallel Down | 4 | 10 | Low |
| Steepening | -8 | -20 | High |
| Flattening | -3 | -8 | Low |
| Tail Event | -15 | -35 | Extreme |
Analytical Explanation & Formula – Core IRRBB Metrics
Quantifying Interest Rate Risk
Concept Overview
- The core of IRRBB stress testing lies in projecting changes in Net Interest Income (NII) and Economic Value of Equity (EVE) under various rate scenarios.
- These metrics depend on the repricing behavior of assets and liabilities, optionality, and customer behavior, all modeled under stress.
- Key parameters include the shock size, repricing gaps, behavioral adjustments, and hedge effectiveness.
- Practical implications: Accurate modeling requires robust data, sound assumptions, and regular validation against actual outcomes.
General Formula Representation
The change in Economic Value of Equity under a rate shock can be expressed as:
$$ \Delta EVE = \sum_{t=1}^{T} \frac{CF_t^{assets} - CF_t^{liabilities}}{(1 + r_t + \Delta r)^t} - \sum_{t=1}^{T} \frac{CF_t^{assets} - CF_t^{liabilities}}{(1 + r_t)^t} $$
Where:
- \( CF_t^{assets}, CF_t^{liabilities} \) = Cash flows from assets and liabilities at time \( t \)
- \( r_t \) = Base discount rate at time \( t \)
- \( \Delta r \) = Interest rate shock
A similar approach applies to NII, focusing on periodic income rather than present value.
Graphical Analysis – NII and EVE Sensitivity Over Time
Tracking Risk Evolution
Context and Interpretation
- This line chart tracks the sensitivity of NII and EVE to interest rate shocks over multiple years, highlighting how risk profiles evolve with market conditions and balance sheet changes.
- Trends may show increasing sensitivity during periods of low rates or high optionality, and decreasing sensitivity following hedging or balance sheet repositioning.
- Risk considerations include the potential for sudden shifts in sensitivity due to behavioral changes or macroeconomic shocks.
- Key insight: Continuous monitoring and scenario updating are essential for proactive risk management.
Figure: NII and EVE Sensitivity to Rate Shocks (2020–2025)
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{"Year": 2021, "NII_Sensitivity": 110, "EVE_Sensitivity": 90},
{"Year": 2022, "NII_Sensitivity": 130, "EVE_Sensitivity": 120},
{"Year": 2023, "NII_Sensitivity": 120, "EVE_Sensitivity": 110},
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}Conclusion
Strengthening Bank Resilience Through Stress Testing
- IRRBB stress testing is a critical tool for identifying vulnerabilities that standard calculations miss, especially around behavioral risk and tail events.
- Next steps include integrating reverse stress testing, refining behavioral models, and aligning with evolving regulatory expectations.
- Remember: Scenario design, cross-functional collaboration, and continuous model validation are key to effective IRRBB management.
- For further insights, explore macroeconomic scenario linkage and advanced behavioral modeling techniques.
