Ce cours apparaît dans les formations suivantes :
• IÉSEG > MSc in Big Data Analytics for Business > Semester 2 > 2,00 ECTS

Pré requis

•- Basic statistical knowledge
- Introduction to predictive analytics
- Introduction to banking and finance
- Introduction to databases
- Introduction to business informatics

Objectifs du cours

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

Contenu du cours

- 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

Modalités d'enseignement

Organisation du cours

Méthodes pédagogiques

• Case study
• Interactive class
• Project work
• Tutorial

Évaluation

Individual assignment, applying the taught techniques to a case study, reporting and discussing the results.
Short paper discussing a topic related to the contents of the course. Feedback on the case is provided by providing a basic outline of the solution, and students can request individual feedback with regards to the report they submitted.

Bibliographie

• Credit riks management: basic concepts, Van Gestel and Baesens, Oxford University Press, 2008 -

• Credit Scoring and Its Applications, Thomas, Edelman and Crook, Siam Monographs on Mathematical Modeling and Computation, 2002 -

• Developing credit risk models using SAS Enterprise Miner and SAS/STAT, Brown, SAS -

Ressources internet

• Default Risk: credit risk modeling website

• Bank for International Settlements

• European Central Bank