- Docente: Enrico Supino
- Credits: 6
- SSD: SECS-P/07
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Rimini
- Corso: Second cycle degree programme (LM) in Statistical, Financial and Actuarial Sciences (cod. 8877)
Learning outcomes
At the end of the course, the students will know the main financial performance measures and the most used techniques to build credit scoring models.
Course contents
- Financial performance indicators to evaluate profitability and solvency;
- Linear discriminant analysis for credit scoring models;
- Logistic regression for credit scoring models;
- Artificial neural networks for credit scoring models.
Assessment methods
Written test - Multiple choice questions (23 points out of 30)
Oral test - Group project work, groups of up to 5 people (8 points out of 30)
Class tests during the course (up to 2 points)
Teaching tools
Book chapters, slides and other study material will be made available to students at the end of each lecture
Office hours
See the website of Enrico Supino