Professional Certificate in Credit Risk Modelling with Excel

• Introduction to Credit Risk Modelling: Understanding the basics and importance of credit risk modelling, the role of a credit risk modeller, and various approaches to credit risk modelling.
• Types of Credit Risks: An in-depth analysis of different credit risks, such as default risk, migration risk, and concentration risk, and their impact on financial institutions.
• Credit Scoring Models: Overview of various credit scoring models, including logistic regression, decision trees, and neural networks. This unit will also cover the process of building a credit scoring model using Excel.
• Probability of Default (PD) Models: Detailed explanation of PD models, such as the single-point model, the binomial model, and the multinomial model, and their implementation using Excel.
• Loss Given Default (LGD) Models: Understanding of LGD models, including roll-rate models, single-point models, and the asset value model, and their application using Excel.
• Expected Credit Loss (ECL) Calculations: Comprehensive coverage of ECL calculations, including the expected loss approach, the stressed expected loss approach, and the probability of default, loss given default, and exposure at default (PD-LGD-EAD) approach, and their implementation using Excel.
• Backtesting Credit Risk Models: Explanation of backtesting techniques, including the use of loan-level and portfolio-level data, and their application to validate credit risk models using Excel.
• Communicating Credit Risk Results: Techniques for effectively communicating credit risk modelling results to stakeholders, including the use of visualization tools and clear and concise reporting.
• Best Practices in Credit Risk Modelling: An overview of best practices in credit risk modelling, including data quality control, model validation, and ongoing monitoring.