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.
Applied Learning Project
Learners will complete hands-on projects that simulate real-world credit risk evaluation and modeling scenarios. Using actual corporate financial data, participants will construct and interpret credit risk models, compute key risk metrics, and prepare internal credit assessments and recommendations. These applied projects reinforce analytical and decision-making skills vital for risk management roles in banks and financial institutions.
