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.
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