Postgraduate Course: Credit Risk Management (CMSE11122)
Course Outline
School | Business School |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
SCQF Credits | 15 |
ECTS Credits | 7.5 |
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 core courses during Semester 1 of the programme, therefore complementing the other courses and minimising overlap of materials.
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Course description |
This course builds upon core 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.
This course relies on the knowledge students gain in the core courses during Semester 1 of their programme, therefore complementing the other courses and minimising the overlap of material.
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | For Business School PG students on MSc in Banking & Risk and MSc in Accounting & Finance. |
Information for Visiting Students
Pre-requisites | Business School Postgraduate Students Only |
High Demand Course? |
Yes |
Course Delivery Information
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Academic year 2020/21, Available to all students (SV1)
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Quota: 80 |
Course Start |
Semester 2 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 20,
Supervised Practical/Workshop/Studio Hours 15,
Summative Assessment Hours 2,
Revision Session Hours 1,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
109 )
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Assessment (Further Info) |
Written Exam
80 %,
Coursework
0 %,
Practical Exam
20 %
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Additional Information (Assessment) |
Coursework (weighted 80%) - assess Learning Outcomes 1,2 and 3.
Practical exam (weighted 20%) - assesses Learning Outcomes 1 and 3 |
Feedback |
Students will gain feedback on their understanding of the material when they perform computer lab exercises. Students should ask questions in lectures to assess their knowledge. |
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
Main:
Thomas, L., Edelman, D. and Crook, J. (2017) Credit Scoring and its Applications. SIAM: Philadelphia.
Additional:
Anderson, R. (2007) The Credit Scoring Toolkit. Oxford University Press: Oxford.
Baesens, B. (2014) Analytics in a big data world : the essential guide to data science and its application. Hoboken, New Jersey : Wiley
Crook, J., Edelman, D. and Thomas, L. (2007) "Recent Developments in Consumer Risk Assessment" European Journal of Operational Research. Vol. 183, No. 3, pp.1447-1465.
Mays, E. (2001) Handbook of Credit Scoring. Glenlake: London.
Siddiqi, N. (2006) Credit risk scorecards : developing and implementing intelligent credit scoring. Wiley: New Jersey.
Thomas, L. (2009) Consumer Credit Models. Oxford University Press: Oxford.
Thomas, L., Edelman, D. and Crook, J. (2004) Readings in Credit Scoring. Oxford University Press: Oxford.
Van Gestel, T. and Baesens, B. (2009) Credit Risk Management. Oxford University Press: Oxford.
Resource List: https://eu01.alma.exlibrisgroup.com/leganto/public/44UOE_INST/lists/18387580740002466?auth=SAML
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Additional Information
Graduate Attributes and Skills |
Cognitive Skills:
After completing this course, students should gain:
- the ability to quantitatively interpret and understand the methodology and outputs of classification algorithms;
- the ability to quantitatively evaluate the predictive performance of classification algorithms;
- the ability to select appropriate quantitative methods to model repayment performance by individuals and companies.
Subject Specific Skills:
After completing this course, students will gain:
- a basic ability to model the probability of default for a sample of loans;
- the ability to assess the performance of credit scoring models;
- the ability to understand, speak and write the language of credit risk analysis.
By the end of the course students will be expected to:
- be able to communicate technically complex issues coherently and precisely;
- be able to advance reasoned and factually supported arguments in written work;
- have acquired lifelong learning skills and personal development so as to be able to work with self-direction;
- have skills in time management and prioritisation. |
Keywords | Mark-CRM |
Contacts
Course organiser | Dr Galina Andreeva
Tel: (0131 6)51 3293
Email: Galina.Andreeva@ed.ac.uk |
Course secretary | Ms Rachael Tring
Tel: (0131 6)51 5467
Email: Rachael.Tring@ed.ac.uk |
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