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Establishment
Language of instruction
English
Teaching content
FINANCE
This course occurs in the following program(s)
MSc in Big Data Analytics for Business
- Crédits ECTS: 2.00
Training officer(s)
W.VERBEKE
Stakeholder(s)
W.VERBEKE
Présentation
Prerequisite
•- Basic statistical knowledge
- Introduction to predictive analytics
- Introduction to banking and finance
- Introduction to databases
- Introduction to business informatics
- Introduction to predictive analytics
- Introduction to banking and finance
- Introduction to databases
- Introduction to business informatics
Goal
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
- 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
Presentation
- 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
- 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
Organization
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours interactif | 16,00 | ||
| Autoformation | |||
| Lecture du manuel de référence | 34,00 | ||
| Overall student workload | 50,00 | ||
Evaluation
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.
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.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| Participation | 16,00 | 1 | 20,00 |
| Autres | |||
| Projet Individuel | 34,00 | 1 | 80,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliography
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 -
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 -