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Readings in Credit Scoring
Foundations, Developments, and Aims
Lyn C. Thomas, David B. Edelman, and Jonathan Crook
338 pages
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numerous line drawings
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240x168mm
978-0-19-852797-8
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Hardback
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08 July 2004
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This item is printed to order. Items which are printed to order are normally despatched and charged within 5-10 days.
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- Unique collection of papers on one of the most successful techniques in finance
- Well-known and experienced author team
- Highly topical with a broad appeal
Credit scoring is one of the most successful applications of statistical and management science techniques in finance in the last forty years. This unique collection of recent papers, with comments by experts in the field, provides excellent coverage of recent developments, advances and aims in credit scoring. Aimed at statisticians, economists, operational researchers and mathematicians working in both industry and academia, and to all working on credit scoring and data mining, it is an invaluable source of reference.
Readership: Statisticians, economists, operational
researchers and mathematicians working in industry. Graduate and undergraduate students in statistics studying credit scoring and data mining.
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Lyn C. Thomas, School of Management, University of Southampton, David B. Edelman, Direct Line Financial Services, and Jonathan Crook, Professor in Business Economics School of Management, University of Edinburgh Contributors:
R W Johnson
R Eisenbeis
M A Hopper and E M Lewis
A D Wilkie
G Wilkinson and J Tingay
R L Keeney and R M Oliver
A Lucas
R M Oliver and E Wells
D J Hand and W E Henley
G A Overstreet Jr., E L Bradley, and R S Kemp Jr.
J N Crook, L C Thomas, and R Hamilton
G Bennett, G
Platts, and J Crossley
K J Leonard
G Platts and I Howe
A Lucas and J Powell
B Narain
P Sewart and J Whittaker
M B Yobas, J N Crook, and P Ross
J Ho, L C Thomas, T A Pomrey, and W T Scherer
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A: Historical development of credit and behavioural scoring
R W Johnson: Legal, social and economic issues in implementing scoring in the US
R Eisenbeis: Problems in applying discriminant analysis in credit scoring models
M A Hopper and E M Lewis: Behaviour scoring and adaptive control systems
B: Objectives and measures in credit scoring
A D Wilkie: Measures for comparing scoring systems
G Wilkinson and J Tingay: The use of affordability data - does it add real value?
R L Keeney and R M Oliver: Improving lender offers using consumer preferences
C: Practical implementation of scoring systems
A Lucas: Updating scorecards: Removing the mystique
R M Oliver and E Wells: Efficient frontier cut-off policies in credit portfolios
D: Features of scoring
D J Hand and W E Henley: Can reject inference ever work?
G A Overstreet Jr, E L Bradley, and R S Kemp Jr: The flat-maximum effect and generic linear scoring models: a test
J N Crook, L C Thomas, and R Hamilton: The degradation of the scorecard over the business cycle
G Bennett, G Platts, and J Crossley: Inferring the inferred
E: Other applications of scoring in credit risk
K J Leonard: Detecting credit card fraud using expert systems
G Platts and I Howe: A single European scorecard
A Lucas and J Powell: Small sample scoring
F: Alternative approaches to scoring systems
B Narain: Survival analysis and the credit granting decision
P Sewart and J Whittaker: Graphical models in credit scoring
M B Yobas, J N Crook, and P Ross: Credit scoring using neural and evolutionary techniques
J Ho, L C Thomas, T A Pomrey, and W T Scherer: Segmenting in Markov chain consumer credit behaviour models
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The specification in this catalogue, including without limitation price, format, extent, number of illustrations, and month of publication, was as accurate as possible at the time the catalogue was compiled. Occasionally, due to the nature of some contractual restrictions, we are unable to ship a specific product to a particular territory. Jacket images are provisional and liable to change before publication.
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