CCRA-L2

The AIWMI CCRA-L2 exam (Certified Credit Risk Analyst Level 2) focuses on extending the foundational knowledge from Level 1 into more advanced credit risk management concepts and techniques. The main points covered typically include:

I. Advanced Credit Risk Measurement and Modeling:

• Credit Scoring and Rating: Delving deeper into statistical models used for credit scoring and rating, including logistic regression, discriminant analysis, and more sophisticated techniques. Focus on model validation, limitations, and biases.
• Credit Risk Metrics: Advanced calculations and interpretations of metrics like Expected Loss (EL), Unexpected Loss (UL), and potential future loss distributions. Understanding the limitations and assumptions of these metrics.
• PD, LGD, and EAD Estimation: In-depth exploration of Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) estimations. Advanced techniques and the challenges associated with each.
• Concentration Risk Measurement & Management: This involves understanding how to identify and manage risks arising from concentrations of credit exposures to specific borrowers, industries, or geographical areas. Techniques include stress testing and scenario analysis.
• Model Risk Management: Understanding the importance of robust model validation, oversight, and governance frameworks to mitigate the risks associated with using quantitative models in credit risk management.

II. Advanced Credit Risk Management Techniques:

• Advanced Securitization: A deeper dive into the structure and risks of different types of securitizations, including understanding the different tranches and credit enhancements.
• Regulatory Capital Requirements: A detailed understanding of Basel regulations and other regulatory frameworks relevant to credit risk capital adequacy. This includes specific capital calculations and requirements depending on the type of institution and the risk profile.
• Stress Testing and Scenario Analysis: Advanced techniques for performing stress tests and scenario analysis to assess the resilience of a credit portfolio under adverse economic conditions. This often involves the use of macroeconomic models.
• Credit Portfolio Management: Techniques for managing and optimizing a credit portfolio, including diversification strategies, concentration risk management, and portfolio optimization techniques.
• Recovery Rate Modeling: Focus on estimating and modeling recovery rates in the event of default, influencing LGD calculations.

III. Credit Risk in Specific Industries or Sectors:

The exam may dedicate some portion to the application of credit risk management principles to specific industries (e.g., financial institutions, retail banking, corporate lending).

IV. Practical Application and Case Studies:

The exam will test the ability to apply the concepts learned to real-world scenarios through case studies and problem-solving questions.

It's crucial to review the official AIWMI syllabus for the most up-to-date and precise information on the exam's content. The specific weighting of each topic may vary from year to year.