![](https://www.univ-catholille.fr/wp-content/uploads/2024/06/Pole-HDC-scaled.jpg)
CREDIT SCORING
Année du cours : 1 année(s)
Etablissement : IÉSEG School of Management
Langue : English
Formation(s) dans laquelle/lesquelles le cours apparait :
Période : S2
•- Basic statistical knowledge
– Introduction to predictive analytics
– Introduction to banking and finance
– Introduction to databases
– Introduction to business informatics
At the end of the course, the student should be able to:
– understand and explain the role of credit scorecards as essential tools for financial institutions to make data-driven, effective and efficient decisions
– understand and explain the goals, working, principles and underlying models of the Basel regulation and the requirements towards financial institutions in developing risk management systems
– discuss and apply different data preparation steps for building credit scorecards
– develop a credit scorecard using different predictive analytical techniques
– explain the role of PD, LGD and EAD modeling in the Basel framework
– understand the effect of the economic cycle on credit risk and explain the approaches adopted by financial institutions to address this effects in terms of capital calculation and modeling
These competencies and/or skills contribute to the following learning objectives
– 2.C Generate sustainable solutions for organizations
– 3.A Breakdown complex organizational problems using the appropriate methodology
– 5.A. Predict how business and economic cycles could affect organizational strategy
– 5.D. Make effectual organizational decisions
– Introduction to credit scoring
– Introduction to Basel I,II and III regulation, and PD, LGD and EAD modeling
– Data preprocessing for PD modeling
– Building PD models
– Postprocessing PD models
– Developing a credit rating system