20249 - CREDIT RISK MANAGEMENT
CLMG - M - IM - MM - AFC - CLAPI - CLEFIN-FINANCE - CLELI - ACME - DES-ESS - EMIT
Course taught in English
Go to class group/s: 31
The course focuses on the state of the art of methodologies and practices of credit risk management in financial institutions, as well as in finance departments of large non-financial corporations. Risk measurement models and management policies are constantly linked in order to provide a comprehensive picture of key methodologies and tools that are currently under implementation in banks, non-financial institutions, and rating agencies. The course capitalizes on large real-world data-bases and statistical software tools such as SPSS, in order to learn how to build, manage and validate risk models; lectures are held in computer room. There are no particular prerequisites of statistics and/or SPSS software for those attending the course; SPSS will be downloaded on students’ lap tops.
- Introduction: concepts, methodologies and tools of credit risk management
- Building statistical-based scoring systems of probability of default: definition of default to be used
- Sampling, data mining and transformations (Case study based on SPSS)
- Univariate analysis. Monotonicity, statistical requirements and predictive power of individual financial ratios (Case study based on SPSS)
- Transformations of financial ratios in order to maximize their predictive power (Case study based on SPSS)
- Models estimation (Case study based on SPSS)
- Models performance measurements, comparability of different models; from scorings to ratings: choosing cut-offs. Scoring calibration and rating quantification (Case study based on SPSS)
- Internal validation and regulatory validation. Quantitative and qualitative model validation; benchmarking
- Credit risk measures taxonomy and their impacts on portfolio models structure
- Portfolio models for large and small portfolios. Securitisation and credit risk.
- Credit risk pricing and risk adjusted performance measures. Internal data and market data.
Written exam (essay). The final mark is expressed in thirties (X/30). A group assignment is optional; each student in a group may earn from 0/30 to 4/30 additional points to those earned in the written exam.
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DE LAURENTIS, MAINO, MOLTENI, Developing, Validating, and Using Internal Ratings. Methodologies and case studies, Wiley, 2010 (this book also has an Italian translation: De Laurentis, Maino, I rating a base statistica. Sviluppo, validazione, funzioni d’uso per la gestione del credito, Bancaria Editrice, 2009)
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R. DE SERVIGNY, Measuring and managing credit risk, McGraw-Hill 2004, chapter 6
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Slides sets, SPSS print-outs and case studies (available on the course web site)