Expected Loss Formula

Expected loss is the cornerstone metric for consistent, transparent credit risk measurement. In this short video, GICP trainer Elena Pellegrini demystifies the EL formula (PD × LGD × EAD) and shows how each component works together to quantify risk, compare exposures and inform better decisions.

Read the transcript

Today, I’d like to talk to you about one of the core concepts in credit risk management—quantifying credit risk using the expected loss formula.

Understanding and managing credit risk is fundamental to the stability and profitability of our institutions, and this is a clear and consistent way to measure it. The formula is elegantly simple, but its implications are profound.
Expected Loss = Probability of Default × Loss Given Default × Exposure at Default

Let’s briefly unpack each component:

• The probability of default, or PD, represents the likelihood that a borrower will be unable to fulfill their financial obligations within a given time horizon. This probability is typically estimated using historical data, credit ratings, or advanced statistical models, and it serves as a measure of the chance that a default may occur .
• When you think about loss given default the main thing you want to understand is: “How much of the exposure is at risk of not being recovered in the event of a default?”. The loss given default parameter represents in fact the percentage of exposure that is expected to be lost if a default occurs. It considers factors such as collateral, guarantees, and recovery processes.
• Exposure at default is the total value at risk at the moment of the default. For a loan, it’s typically the outstanding balance. For more complex products, it may include potential future drawdowns or undrawn commitments.

When we multiply these three factors, we arrive at the expected loss—a single, quantified estimate that helps us make informed decisions about pricing, capital allocation, and risk appetite.

Why is this so important? Understanding and applying the expected loss framework provides a robust foundation for assessing and managing credit risk across all areas of financial decision-making. It offers a clear, consistent methodology for structuring transactions, evaluating risk exposures, and communicating risk insights both internally and externally.

By quantifying potential losses, organizations can compare credit exposures on a consistent basis, prioritize their risk mitigation efforts, and ultimately enhance risk-adjusted performance.

In essence, mastering the expected loss formula allows us to turn complex credit risk factors into actionable insights, supporting more resilient portfolios and fostering sound, informed decision-making throughout the organization.