Interest Rate Risk Isn’t About Prediction—It’s About Preparation

Why Model Integrity and Scenario Discipline Matter More Than Ever

In today's dynamic interest rate environment, managing interest rate risk (IRR) isn't about making perfect predictions - it's about preparing for uncertainty. For banks and credit unions, the tools you use to manage this risk are only as effective as the assumptions behind them and the integrity of their implementation.

Assumptions Matter: Deposit Behavior and Loan Prepayments

Accurate modeling starts with well-supported assumptions. Assumptions around deposit betas, average life, early withdrawal behavior, and loan prepayments have a material impact on simulated outcomes. Yet in many cases, these assumptions are carried over from historical norms without regular challenge or validation.

For example, deposit behavior has shifted significantly over the past two years. Customers are more rate-sensitive, and funding pressures have grown. Relying on outdated decay assumptions or static beta inputs can lead to material misrepresentation of interest rate exposure. Likewise, loan prepayment models that don't reflect the current rate environment or borrower psychology can skew cash flow projections.

The Purpose of Scenario Analysis: Risk Discovery, Not Rate Forecasting

One of the most common misconceptions in IRR modeling is the belief that scenario analysis is about predicting where rates are headed. It’s not. The goal is to understand how your balance sheet behaves across a range of plausible environments - rising rates, falling rates, rate shocks, yield curve twists, and more.

Stress testing your model across multiple scenarios reveals vulnerabilities you might otherwise overlook. Are you overexposed to long-duration assets in a rising rate environment? Are deposit assumptions overly optimistic if rates decline? Scenario discipline gives management the insight needed to evaluate strategy, pricing, and risk appetite with confidence.

Model Governance: Getting Implementation and Validation Right

Even the best models can fail if they're poorly implemented or not configured correctly. We’ve seen everything from incorrect account mapping to outdated assumptions hardcoded into models, producing outputs that look polished but mislead decision-makers.

A rigorous validation process is essential—not just to meet regulatory expectations, but to protect your institution from avoidable errors. Validation should assess the accuracy and consistency of assumptions, evaluate the integrity of the model’s logic and calculations, and ensure results are clearly explained and understood by stakeholders.

Bottom Line

Interest rate risk is complex, especially in a volatile market. But with sound assumptions, scenario-driven insight, and disciplined model governance, your institution can not only meet regulatory expectations but make more confident strategic decisions.