ALM Modeling, Measurement & Risk Analysis builds on foundational banking principles to introduce the practical tools and frameworks used by financial institutions to model risk and evaluate exposure to interest rate movements.
The course begins with a deep dive into the core assumptions underlying ALM modeling, including asset sensitivity, liability sensitivity, and their impact on net interest income (NII) across various rate scenarios. You'll examine key gap analysis techniques—such as Price/Maturity Gaps versus Rate/Reset Gaps—and evaluate how repricing assumptions shift across time buckets and financial instruments. The concept of Market Value of Equity (MVE) is also introduced, offering a long-term perspective on how rate changes affect a bank’s economic value.
From there, the focus turns to essential risk measurement tools. These include metrics like Earnings at Risk, Cost to Close, and multiple gap types—rate-sensitive, price-sensitive, and liquidity. Learners gain a firm grasp on how to calculate Net Interest Income at Risk and apply duration gap analysis to quantify interest rate exposure over different time horizons.
A central theme of the course is duration and convexity as sensitivity measures of interest rate risk. The curriculum covers Macaulay and modified duration, effective duration, and convexity—each critical for measuring sensitivity on both sides of the balance sheet. More advanced techniques, such as Monte Carlo simulations and Value-at-Risk (VaR) applied to MVE, prepare learners for complex modeling environments.
The course concludes with an in-depth case study of the Silicon Valley Bank collapse—a real-world example of how flawed ALM assumptions and weak measurement practices can lead to institutional failure. Through analysis of SVB’s balance sheet and risk posture, learners bridge the gap between technical theory and real-world application.
This course is part of the New York Institute of Finance’s Asset Liability Management Professional Certificate program.
