Credit Data and Scoring: The First Triumph of Big Data and Big Algorithms

Credit Data and Scoring: The First Triumph of Big Data and Big Algorithms illuminates the often-hidden practice of predicting an individual’s economic responsibility. Written by a leading practitioner, it examines the international implications of US leadership in credit scoring and what other countries have learned from it in building their own systems. Through its comprehensive contemporary perspective, the book also explores how algorithms and big data are driving the future of credit scoring. By revealing a new big picture and data comparisons, it delivers useful insights into legal, regulatory and data manipulation.

1. When Our Reputation Became our Score 2. The Credit Industry 3. CRAs - Losing Battles to Win the War 4. My Credit Report 5. Historic Complaints about Credit Accuracy 6. Differences in Credit Data Between Bureaus 7. Differences in Credit Scores between Bureaus 8. The Mystery of Credit Scores 9. Making a Credit Score 10. Picking the y Variable, Picking the x Variables 11. Calculating Weight of Evidence and Information Value 12. Regressions 13. Getting a Good Model 14. Data Flows: The Road to Attributes and Scores 15. The War Between Individuals and Algorithms 16. Protecting Data 17. About the Authors

Appendix 1. Credit Laws / Data Laws 2. My Credit Report