Introduction to Credit Risk Modeling
This course provides a foundational overview of the quantitative techniques and regulatory frameworks used to assess and manage credit risk. It covers the end-to-end process of developing, validating, and implementing credit risk models, from initial application scoring to the management of defaulted assets. The curriculum emphasizes the transformation of raw financial data into actionable risk metrics, bridging the gap between financial theory and practical data science applications.
- Level: intermediate
- Duration: 6 weeks
- 8 sections
- Price: $20
Topics: Credit Risk, Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), Scorecard Development, Basel Regulations, Machine Learning, Model Validation, Expected Credit Loss, Risk Management, Financial Data Science, Survival Analysis
What's inside
- Introduction to Credit Risk Modeling
- Chapter 1: Foundations of Credit Risk
- Chapter 2: Data Preprocessing & Feature Engineering
- Chapter 3: Scorecard Development & Logistic Regression
- Chapter 4: Advanced Modeling & Machine Learning
- Chapter 5: Model Validation & Performance Metrics
- Chapter 6: Stress Testing & Expected Credit Loss (IFRS 9 / CECL)
- Chapter 7: Synthesis, Applications & Future Directions