Credit Intelligence & Modelling: Many Paths through the Forest of Credit Rating and Scoring

Credit Intelligence & Modelling: Many Paths through the Forest of Credit Rating and Scoring – Ebook Instant Download/Delivery ISBN(s): 9780192844194,0192844199,9780192658159, 0192658158

Product detail:

• ISBN 10: 0192658158
• ISBN 13: 9780192658159
• Author: Raymond A. Anderson

Credit Intelligence and Modelling provides an indispensable explanation of the statistical models and methods used when assessing credit risk and automating decisions. Over eight modules, the book covers consumer and business lending in both the developed and developing worlds, providing the frameworks for both theory and practice. It first explores an introduction to credit risk assessment and predictive modelling, micro-histories of credit and credit scoring, as well as the processes used throughout the credit risk management cycle. Mathematical and statistical tools used to develop and assess predictive models are then considered, in addition to project management and data assembly, data preparation from sampling to reject inference, and finally model training through to implementation. Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines, whether for academic research or practical use. The book assumes little prior knowledge, thus making it an indispensable desktop reference for students and practitioners alike. Credit Intelligence and Modelling expands on the success of The Credit Scoring Toolkit to cover credit rating and intelligence agencies, and the data and tools used as part of the process.

Table of contents:

1. 1: Credit Intelligence
2. 2: Predictive Modelling Overview
3. 3: Retail Credit
4. 4: Business Credit
5. 5: Side Histories
6. 6: Credit—A Microhistory
7. 7: The Birth of Modern Credit Intelligence
8. 8: The Dawn of Credit Scoring
9. 9: Front-Door
10. 10: Back-Door
11. 11: Stats & Maths & Unicorns
12. 12: Borrowed Measures
13. 13: Practical Application
14. 14: Predictive Modelling Techniques
15. 15: Project Management
16. 16: Data Acquisition—Observation
17. 17: Data Acquisition—Performance
18. 18: Target Definition
19. 19: File Assembly
20. 20: Sample Selection
21. 21: Data Transformation
22. 22: Segmentation
23. 23: Reject-Inference
24. 24: Model Training
25. 25: Scaling and Banding
26. 26: Finalization

People also search: