Postgraduate Course: Credit Risk Management (CMSE11644)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course introduces students to theory and practice in credit risk management. Students will consider the application of credit scoring and the methods for credit scoring using scorecards. In particular, students will learn certain techniques required by a lender for effective loan management and for compliance with capital requirement regulations.
This course builds on students' knowledge gained in the compulsory courses during Semester 1 of the programme, therefore complementing the other courses and minimising overlap of materials. |
| Course description |
This course builds upon compulsory courses of the programmes. The course introduces basic concepts and techniques of risk assessment and risk management in consumer credit. The course demonstrates major forms of risk modelling which retail financial lenders experience. Credit risk is considerably topical given the difficulties throughout the world economies that were precipitated by excessive lending to high risk borrowers.
The teaching objectives are to teach the students the theoretical background and practical implementation of risk management in retail credit risk. The course will teach the application of credit scoring and the methods for credit scoring using scorecards. This course introduces students to the theory and practice in credit risk management. Students will consider the application of credit scoring and the methods for credit scoring using scorecards. In particular, students will learn certain techniques required by a lender for effective loan management and for compliance with capital requirement regulations.
Outline Content
- Stages in Scorecard Construction
- Data Preparation and Variable Transformation
- Measuring Performance
- Logistic Regression
- Practical Issues
Student Learning Experience
The approaches studied will be illustrated by means of practical examples in lectures and computer labs. The students will be taught to critically evaluate advantages and limitations of the methods taught.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | Students MUST also take:
Statistics for Analytics (CMSE11624)
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| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
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Quota: 80 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 9,
Seminar/Tutorial Hours 6,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
83 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
100% Project report (Individual) - Assesses all course Learning Outcomes
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| Feedback |
Formative: Feedback will be provided throughout the course.
Summative: Feedback will be provided on assessment within agreed deadlines. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Estimate, implement and evaluate credit risk assessment methods for individual loans to corporate and retail borrowers.
- Understand and critically discuss methods of monitoring and tracking model performance.
- Understand and critically discuss methods of measuring and assessing the credit risk of portfolios of loans.
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Reading List
Core Text:
Thomas, L., Edelman, D. and Crook, J. (2017) Credit Scoring and its Applications. SIAM: Philadelphia. |
Additional Information
| Graduate Attributes and Skills |
Communication, ICT, and Numeracy Skills
After completing this course, students should be able to:
Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts.
Knowledge and Understanding
After completing this course, students should be able to:
Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.
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| Keywords | Credit risk,Predictive modelling,Credit scoring,Lending |
Contacts
| Course organiser | Dr Galina Andreeva
Tel: (0131 6)51 3293
Email: Galina.Andreeva@ed.ac.uk |
Course secretary | |
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