Credit Risk Modeling & Analysis Mastery
About this course
This specialization provides a comprehensive pathway to mastering credit risk modeling from theory to practical application. Learners will explore key concepts such as Probability of Default (PD), Loss Given Default (LGD), and Expected Loss (EL), progressing to advanced frameworks like the Altman Z-Score and Merton’s Model. Through sector-specific and real-world case studies, participants will learn to assess financial statements, assign credit ratings, and build robust risk models aligned with banking and regulatory standards. Designed for finance professionals and analysts, this specialization bridges data-driven analysis with decision-making proficiency in corporate and institutional credit risk.
75/100
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- 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
- Calculate and interpret Probability of Default (PD), Loss Given Default (LGD), and Expected Loss (EL)
- Apply the Altman Z-Score model to assess corporate bankruptcy risk
- Use Merton's Model for credit risk evaluation
- Analyze financial statements to inform credit risk assessments
- Assign credit ratings using structured methodologies
- Build credit risk models aligned with banking and regulatory requirements
Course objectives
- Master core credit risk concepts and metrics used in financial institutions
- Develop proficiency in applying established credit risk modeling frameworks
- Gain practical experience through sector-specific and real-world case studies
- Build decision-making skills for corporate and institutional credit risk management
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