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

Table of Contents

1. When Our Reputation Became our Score2. The Credit Industry3. CRAs Losing Battles to Win the War4. My Credit Report5. Historic Complaints about Credit Accuracy6. Differences in Credit Data Between Bureaus7. Differences in Credit Scores between Bureaus8. The Mystery of Credit Scores9. Making a Credit Score10. Picking the y Variable, Picking the x Variables11. Calculating Weight of Evidence and Information Value12. Regressions13. Getting a Good Model14. Data Flows: The Road to Attributes and Scores15. The War Between Individuals and Algorithms16. Protecting Data17. About the Authors

Appendix1. Credit Laws / Data Laws2. My Credit Report

Authors

Eric Rosenblatt Fannie Mae, Washington DC, USA. Eric Rosenblatt has worked in the mortgage industry, mainly the credit side, for thirty years, most of it (since 2000) as a Vice President at Fannie Mae. He received a Ph.D. in Finance in 1994. At Fannie Mae he was known for his management of Credit Risk analytics (including credit report models), his correct call of the housing recession, and for what Fannie called Innovation: applications and models which integrated data and made credit, fraud, and home valuation decisions. One of these applications, Collateral Underwriter, is used by all lenders and appraisal management companies. Another is a credit scoring model that treats people that pay their credit card balances (transactors) differently than people that do not (revolvers). While at Fannie Mae he published 19 papers and was granted 13 patents.