Banking never sleeps and neither does risk. With both interest rate volatility and credit spread movements putting pressure on bank balance sheets, it’s no longer enough to focus solely on one side of the equation.
The evolving regulatory landscape and real-world events have shown that effective balance sheet management requires a clear view of how these risks interact and how they can compound or offset each other.
Same Book, Interacting Pressures
Interest rates and credit spreads move for different reasons, but their effects are often felt at the same time, and in the same areas of the balance sheet. One shift can amplify the impact of the other, especially in times of market stress.
For example, when interest rates rise sharply, the value of fixed-income assets will fall. If, at the same time, credit spreads widen due to deteriorating sentiment or liquidity concerns, the decline in asset value will accelerate. We’ve seen this play out in recent bank failures. What starts as a valuation problem can quickly become a liquidity or capital one.
Understanding this interplay is no longer optional. It’s core to managing risk in the banking book.
Regulation is Already There
The EBA’s IRRBB 2022 guidelines pushed credit spread risk more firmly into the spotlight. Since then, banks have been expected to develop more detailed measurement, modelling and governance frameworks that reflect the reality of credit spread risk alongside interest rate exposure.
With increased regulatory focus on IRRBB and CSRBB and their integration into forecasting and stress testing, banks are under pressure to improve how they estimate NII and calculate EVE, including credit spread risk.
Regulators aren’t just asking if you’ve measured the risks. They’re asking if you understand how the risks, and the models behind them interact and influence each other.
The Practical Challenges and Opportunities
Managing these risks together isn’t simple. Most frameworks were built with interest rate sensitivity at the core, and retrofitting spread risk into them can be messy. Banks face challenges such as:
- Consistent behavioural assumptions for NMDs and customer behaviour
- Forecasting rate and spread scenarios under different market conditions
- Modelling fair value changes driven by spread movements
- Avoiding capital inefficiencies or double-counting
- Explaining assumptions and methodologies to supervisors
But those that get it right don’t just tick boxes, they gain strategic clarity. Better hedging. Smarter pricing. A more resilient balance sheet.
Measuring What Matters: NII and EVE Still Rule
Most banks manage interest rate risk through a combination of Net Interest Income (NII) sensitivity (NII) —also referred to as Earnings at Risk (EaR), and Economic Value of Equity (EVE). These are the twin pillars of IRRBB measurement.
- NII captures the short-term, P&L impact of rate movements, how much income could fluctuate over the NII horizon.
- EVE looks more longer-term, focusing on the present value of all future cash flows across the balance sheet, typically fixed flows and floating flows up to their next reset date.
The EBA’s current Supervisory Outlier Tests (SOTs) are applied to both NII and EVE, with thresholds based on their impact on the institution’s Tier 1 capital. Incorporating CSRBB adds complexity, particularly as spread volatility affects both mark-to-market valuations (impacting EVE) and forward-looking income projections (impacting EaR).
What Banks Should Be Doing Now
- Refresh your modelling. Capture both rate and spread sensitivities in your risk engine, under real-world and stress scenarios.
- Clarify assumptions. Make sure behavioural and market inputs are consistent across interest rate and spread scenarios, recognising where and why they diverge.
- Integrate your view. Your ALM, treasury and risk teams should be working from the same playbook, literally.
- Engage early. Keep your regulator in the loop about your methods, interpretations, and any challenges you’re facing.
Bottom Line: Focus on the Connection
The interaction between rate and spread risks isn’t theoretical; it’s showing up on balance sheets, in capital buffers, and in supervisory reviews.
Getting ahead means recognising how these risks combine, modelling them accurately, and embedding them into decision-making.
Because this isn’t just about risk avoidance, it’s about building a balance sheet that performs under pressure.