| Reviews |
| - 'This is an extremely valuable and timely book on a very important topic ... Anderson has provided a great service to all who use Credit Scoring techniques.' - Barry Scholnick PhD, Eric Geddes Associate Professor of Business, University of Alberta
- 'It is a superb mixture of a practical how to do guide for those wanting to use and develop credit scoring together with a way of putting the decisions it supports in context and the techniques it uses in a general modelling framework.' - Professor Lyn Thomas, Professor of Management Science, Scholl of Management, University of Southampton
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| Description | | - Highly-accessible guide to Credit Scoring
- Assumes little prior knowledge
- Comprehensive, up-to-date and wide-ranging
- Extensive glossary and bibliography
- Numerous examples and illustrations
| The Credit Scoring Toolkit provides an all-encompassing view of the use of statistical models to assess retail credit risk and provide automated decisions.
In eight modules, the book provides frameworks for both theory and practice. It first explores the economic justification and history of Credit Scoring, risk linkages and decision science, statistical and mathematical tools, the
assessment of business enterprises, and regulatory issues ranging from data privacy to Basel II. It then provides a practical how-to-guide for scorecard development, including data collection, scorecard implementation, and use within the credit risk management cycle.
Including numerous real-life examples and an extensive glossary and bibliography, the text assumes little prior knowledge making
it an indispensable desktop reference for graduate students in statistics, business, economics and finance, MBA students, credit risk and financial practitioners. |
Readership: Masters level students in statistics, business, economics and finance, MBA students, and credit risk and financial practitioners.
| Contents |
Preface
A Setting the scene
1.
Credit scoring and the business
2.
Credit micro-histories
3.
The mechanics of credit scoring
B Risky business
4.
The theory of risk
5.
Decision science
6.
Assessing enterprise risk
C Stats and Maths
7.
Predictive statistics 101
8.
Measures of separation/divergence
9.
Odds and ends
D Data!
10.
Data considerations and design
11.
Data sources
12.
Scoring structure
13.
Information sharing
14.
Data preparation
E Scorecard development
15.
Transformation
16.
Characteristic selection
17.
Segmentation
18.
Reject inference
19.
Scorecard calibration
20.
Validation
21.
Development management issues
F Implementation and use
22.
Implementation
23.
Overrides, referrals, and controls
24.
Monitoring
25.
Finance
G Risk management cycle
26.
Marketing
27.
Application processing
28.
Account management
29.
Collection and recoveries
30.
Fraud
H Regulatory environment
31.
Regulatory concepts
32.
Data privacy and protection
33.
Anti-discrimination
34.
Fair lending
35.
Capital adequacy
36.
Know your customer (KYC)
37.
National differences
Z Reference materials
38.
Glossary / Dictionary
39.
Bibliography
40.
Appendices
Index
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| Authors, editors,
and contributors |
Raymond Anderson, Standard Bank Group, Johannesburg
|
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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