Executive Education

APPLIED CREDIT RISK MANAGEMENT

This course introduces to some modern credit risk methodologies. It will not only introduce the theoretical concepts of default models that are used in banking practice, but will also use computer-based applications and software (Microsoft Excel) to implement the theoretical concepts into practice.

The course will cover different approaches to determine individual probabilities of default. Examples of these approaches comprise credit scoring models, rating transitions (credit migration approach), or the Merton model as an approach to default modeling based on option pricing theory. The course will also cover some concepts of the regulation of credit risk as outlined in the Basel accords, and will discuss portfolio credit risk. Finally, students will become familiar with the products used in today’s credit markets such as internal and external ratings or credit default swaps (CDS), an insurance contract against default.

The course will not only present the theoretical concepts but also deepen the knowledge of the different credit risk management tools by a hands-on implementation in Microsoft Excel. Any pre-knowledge in MS Excel is useful, but not necessarily required for this course.

 

Any questions?

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Ludmila Ketterer

 +49 69 798 33512

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Course Format

This course is offered in the part-time Master in Finance program and may be attended on a “no credit” basis by individuals not enrolled in the program. Course participants are visitors who are not responsible for assignments and do not take an exam or earn academic credits. As the number of seats in the course is limited, we recommend to register online early.

Learning Objectives

Upon completion of this course, you will be able to:

  • Perform simple regression analyses of non-linear models to model default probabilities as a function of observable characteristics
  • Evaluate single claim credit risk applying different methodologies such as structural models, credit migration approach, or scoring models
  • Estimate the risk of a credit portfolio using default-mode models
  • Understand and estimate the price of credit risk
  • Understand structured portfolio credit risk and be aware of the implied risks
Key Concepts
  • Scoring Models
  • Structural Pricing Models
  • Ratings and Rating Transition Matrices
  • Prediction of Default Probabilities
  • Portfolio Risk (e.g. Value-at-Risk, Expected Shortfall)
  • Credit Default Swaps (CDS)
  • Regulation
Faculty

Assist. Prof. Dr. Andreas Barth

Andreas Barth is Assistant Professor of Digital Transformation in Finance and Accounting at Saarland University Saarbrücken. Before joining Saarland University, he was Assistant Professor at the Chair of Banking and Finance at Goethe University Frankfurt. He graduated with Prof. Dr. Isabel Schnabel at Gutenberg University Mainz. Andreas did various research stays at the European Systemic Risk Board and the European Central Bank. His teaching specializes inter alia in financial modeling and risk management and applied econometrics. His research focusses mainly on financial intermediation, banking regulation and financial markets.

Key Facts

Course materials

Course materials will be provided in electronic form.

Language

English

Venue

Campus Westend of Goethe University Frankfurt.

Certificate of participation

A GBS certificate of participation is awarded upon completion of the course.

Course Fee

€ 950 (fee is exempt from VAT). The fee for GBS students or alumni amounts to € 400.

Course Schedule
Date Session
Fri., June 14, 2024 13:00-15:00, 15:30-17:30
Fri., June 28, 2024 13:00-15:00, 15:30-17:30
Fri., July 5, 2024 13:00-15:00, 15:30-17:30
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There are two main things which make returning for Open Programs such a valuable and worthwhile experience. The first is being back on campus – meeting the current students, returning to campus again, the whole experience was just so pleasant. The second is the level of quality in the courses – the faculty teaching are absolute experts.

Stephan KieneDuke-Goethe Executive MBA Class of 2009
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