Readings in Credit Scoring Foundations, Developments, and Aims

by Thomas, Lyn C.; Edelman, David B.; Crook, Jonathan N.

• ISBN13: 9780198527978
• ISBN10: 0198527977
• Format: Hardcover
• Copyright: 2004-09-09
• Publisher: Oxford University Press

Summary

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 sims 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.

Table of Contents

List of Contributors	xiii
Part I. Historical Development of Credit and Behavioural Scoring
1. Legal, social, and economic issues in implementing scoring in the United States	5	(12)
R.W. Johnson
In Credit Scoring and Credit Control, (eds. Thomas, Crook, and Edelman), pp. 19-32. OUP, Oxford 2002.
2. Problems in applying discriminant analysis in credit-scoring models	17	(16)
Robert A. Eisenbeis
Journal of Banking and Finance, 2, 205-19, 1978.
3. Behaviour scoring and adaptive control systems	33	(18)
M.A. Hopper and E.M. Lewis
In Credit Scoring and Credit Control, (eds. Thomas, Crook, and Edelman), pp. 257-76. OUP, Oxford 2002.
Part II. Objectives and Measures in Credit Scoring
4. Measures for comparing scoring systems	51	(12)
A.D. Wilkie
In Credit Scoring and Credit Control, (eds. Thomas, Crook, and Edelman), pp. 123-38. OUP, Oxford 2002.
5. The use of affordability data-does it add real value?	63	(10)
George Wilkinson and Jon Tingay
Proceedings of Credit Scoring and Credit Control VII, Credit Research Centre, University of Edinburgh, 2001.
6. Improving lender offers using consumer preferences	73	(20)
Ralph L. Keeney and Robert M. Oliver
Proceedings of Credit Scoring and Credit Control VIII, Credit Research Centre, University of Edinburgh, 2003.
Part III. Practical Implementation of Scoring Systems
7. Updating scorecards: removing the mystique	93	(18)
Alan Lucas
In Credit Scoring and Credit Control, (eds. Thomas, Crook, and Edelman), pp. 179-96. OUP, Oxford 1992.
8. Efficient frontier cut-off policies in credit portfolios	111	(22)
Robert M. Oliver and E. Wells
Journal of Operational Research Society, 52, 1025-33, 2001.
Part IV. Features of Scoring
9. Can reject inference ever work?	133	(14)
David J. Hand and William E. Henley
IMA Journal of Mathematics Applied in Business and Industry, 5, 45-55, 1993/4.
10. The flat-maximum effect and generic linear scoring models: a test	147	(14)
George A. Overstreet, Jr, Edwin L. Bradley, Jr:, and Robert S. Kemp, Jr.
IMA Journal of Mathematics Applied in Business and Industry, 4, 97-109, 1992.
11. The degradation of the scorecard over the business cycle	161	(16)
Jonathan N. Crook, Lyn C. Thomas, and Robert Hamilton
In Credit Scoring and Credit Control, (eds. Thomas, Crook, and Edelman), pp. 111-23. OUP, Oxford 2002.
12. Inferring the inferred	177	(12)
Gaynor Bennett, Graham Plata, and Jane Crossley
IMA Journal of Mathematics Applied in Business and Industry, 7, 327-38, 1996.
Part V. Other Applications of Scoring in Credit Risk
13. Detecting credit card fraud using expert systems	189	(6)
Kevin J. Leonard
Computers and Industrial Engineering, 25 (1-4), 103-6, 1993.
14. A single European scorecard? Does data predict differently across Europe: An Experian Scorex investigation	195	(10)
Graham Platts and Ian Howe
Proceedings of Credit Scoring and Credit Control V, Credit Research Centre, University of Edinburgh, 1997.
15. Small sample scoring	205	(30)
Alan Lucas and Joanna Powell
Proceedings of Credit Scoring and Credit Control V, Credit Research Centre, University of Edinburgh, 1997.
Part VI. Alternative Approaches to Scoring Systems
16. Survival analysis and the credit-granting decision	235	(12)
B. Narain
In Credit Scoring and Credit Control, (eds. Thomas, Crook, and Edelman), pp. 109-22. OUP, Oxford 2002.
17. Graphical models in credit scoring	247	(30)
Pete Sewart and Joe Whittaker
IMA Journal of Mathematics Applied in Business and Industry, 9, 241-66, 1998.
18. Credit scoring using neural and evolutionary techniques	277	(18)
Mumine B. Yobas, Jonathan N. Crook, and Peter Ross
IMA Journal of Mathematics Applied in Business and Industry, 11, 111-25, 2000.
19. Segmentation in Markov chain consumer credit behavioural models	295	(14)
Joseph Ho, Lyn C. Thomas, T.A. Pomroy, and William T. Scherer
Proceedings of Credit Scoring and Credit Control VII, Credit Research Centre, University of Edinburgh, 2001.
Index	309