Credit Risk Modeling & its Application in Banks
About this course
Build a practical foundation in credit risk modeling and learn how banks and financial institutions measure, interpret, and evaluate credit risk. Designed for learners interested in banking and financial services, this course introduces the concepts, calculations, and challenges that support risk-based decision-making. You’ll explore the purpose and structure of credit risk frameworks and examine why credit risk has become increasingly important following financial crises. Through step-by-step explanations and real-world examples, you’ll analyze Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD). You’ll calculate expected credit loss, distinguish between settlement and pre-settlement risk, and evaluate how model assumptions and data limitations affect risk assessments. The course also connects modeling outputs with capital adequacy and regulatory requirements, helping you understand their role in institutional risk management. Its focused progression from foundational concepts to quantitative estimation and practical evaluation makes complex risk metrics easier to apply. Enroll to build the knowledge needed to interpret credit risk measures, assess model limitations, and evaluate credit risk models in real-world banking contexts.
75/100
CourseAsk score
- What the provider tells you
- 39/45
- Who stands behind it
- 20/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- analyze Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD)
- calculate Expected Loss and distinguish between settlement and pre-settlement risk
- evaluate the impact of model assumptions and data limitations on risk assessment
Course objectives
- build a strong foundation in credit risk modeling
- support risk-based decision-making in banking
- interpret credit risk metrics effectively
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