Credit Risk Modeling & its Application in Banks

Overview

This course provides a structured and practical introduction to credit risk modeling with a focus on its application in banking and financial institutions. Designed for learners seeking to analyze, calculate, and evaluate core credit risk components, the course begins by establishing a conceptual foundation for credit risk and its growing importance post-financial crises. Through real-world examples and step-by-step breakdowns, learners will gain a strong grasp of key modeling inputs such as Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD). They will also learn how to compute expected loss, differentiate between settlement and pre-settlement risk, and assess the practical challenges that arise due to model assumptions and data limitations. By the end of the course, learners will be equipped to interpret and apply credit risk metrics, support risk-based decision-making, and align modeling outputs with capital adequacy and regulatory requirements in a financial services context.

Syllabus

Foundations and Core Concepts of Credit Risk

This module introduces the essential building blocks of credit risk modeling, focusing on its purpose, components, and practical implications in banking and financial institutions. Learners will explore definitions, frameworks, risk estimation metrics, and the challenges associated with real-world credit risk measurement. By understanding core concepts such as Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), learners will gain a structured foundation for analyzing and quantifying credit risk within institutional settings.