Postgraduate Course: Credit Scoring and Data Mining (MATH11040)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 10 |
| Home subject area | Mathematics |
Other subject area | Operational Research |
| Course website |
https://info.maths.ed.ac.uk/teaching |
Taught in Gaelic? | No |
| Course description | Large scale databases - data warehouse and data archives; statistical approaches (clustering, discrimination, regression); non statistical approaches, including neural networks and genetic algorithms; commercial software; applications such as clustering, segmenting and scoring. Introduction to credit scoring. Setting up a scoring system. Statistical techniques used in credit scoring. Other approaches to credit scoring. Use of behavioural scoring. Techniques used in behavioural scoring systems. Monitoring and updating scoring systems. Developments in scoring systems. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
|
| Delivery period: 2011/12 Block 4 (Sem 2), Not available to visiting students (SS1)
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WebCT enabled: Yes |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| No Classes have been defined for this Course |
| First Class |
First class information not currently available |
| No Exam Information |
Summary of Intended Learning Outcomes
| Understanding of statistical and alternative methods of constructing scoring rules. Understanding how to process data prior to model building. Ability to assess and monitor a scorecard. Awareness of current and new applications of credit scoring techniques. Understanding of real life application of data mining, including clustering, segmentation and scoring. |
Assessment Information
| Continuous Assessment 100% |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | CSDM |
Contacts
| Course organiser | Dr Julian Hall
Tel: (0131 6)50 5075
Email: J.A.J.Hall@ed.ac.uk |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk |
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© Copyright 2011 The University of Edinburgh - 16 January 2012 6:25 am
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