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Credit Risk Modeling for Basel/IFRS 9 using R/Python/SAS
📅 October 27-28
About This Course
In this course, students learn how to develop credit risk models in the context of the Basel and IFRS 9 guidelines. The course extensively reviews the 3 key credit risk parameters: Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD). Modeling methods, performance measurement and benchmarks are discussed into great detail. The course provides a sound mix of both theoretical and technical insights, as well as practical implementation details. These are illustrated by several real-life case studies and examples. The course also features code examples in R, Python and SAS. Throughout the course, the instructors also extenisvely report upon their research and industry experience. A certificate signed by the instructors is provided upon successful completion.
Before subscribing to this course, you should have business expertise in credit risk and a basic understanding of descriptive statistics (e.g., mean, median, standard deviation, etc.) and inference (e.g., confidence intervals, hypothesis testing). Previous R, Python and SAS experience is helpful but not necessary.
Price and Registration
This course is in the past, registration is no longer possible.