The Credit Scoring Toolkit

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,...

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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.

List of figures
List of tables
List of equations
Preface
Acknowledgement
Outline
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List of figures
List of tables
List of equations
Preface
Acknowledgement
Outline
Module A Setting the scene
1 Credit scoring and the business
2 Credit micro-histories
3 The mechanics of credit scoring
Module B Risky business
4 The theory of risk
5 Decision science
6 Assessing enterprise risk
Module C Stats and maths
7 Predictive statistics 101
8 Measures of separation/divergence
9 Odds and ends
10 Minds and machines
Module D Data!
11 Data considerations and design
12 Data sources
13 Scoring structure
14 Information sharing
15 Data preparation
Module E Scorecard development
16 Transformation
17 Characteristic selection
18 Segmentation
19 Reject inference
20 Scorecard calibration
21 Validation
22 Development management issues
Module F Implementation and use
23 Implementation
24 Overrides, referrals, and controls
25 Monitoring
26 Finance
Module G Credit Risk management cycle
27 Marketing
28 Application processing
29 Account management
30 Collections and recoveries
31 Fraud
Module H Regulatory environment
32 Regulatory concepts
33 Data privacy and protection
34 Anti-discrimination
35 Fair lending
36 Capital adequacy
37 Know Your Customer (KYC)
38 National differences
Glossary
Bibliography
Appendices
Index
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