Credit Data and Scoring
eBook - ePub

Credit Data and Scoring

The First Triumph of Big Data and Big Algorithms

  1. 274 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Credit Data and Scoring

The First Triumph of Big Data and Big Algorithms

About this book

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.- Provides insights into credit scoring goals and methods- Examines U.S leadership in developing credit data and algorithms and how other countries depart from it- Analyzes the growing influence of algorithms in data scoring

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Yes, you can access Credit Data and Scoring by Eric Rosenblatt in PDF and/or ePUB format, as well as other popular books in Economics & Development Economics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Preface
  6. Chapter One. I used to have a reputation. Now I have a score.
  7. Chapter Two. The credit industry in the United States
  8. Chapter Three. My credit report—some of it is right
  9. Chapter Four. Credit reporting agencies: playing the long game
  10. Chapter Five. Data errors to keep money renters happy
  11. Chapter Six. Historic complaints about credit accuracy
  12. Chapter Seven. Differences in data between credit reporting agencies
  13. Chapter Eight. Can credit errors be fixed? Probably not
  14. Chapter nine. The mystery of credit scores
  15. Chapter Ten. Making a credit score: it starts with data
  16. Chapter Eleven. Picking the Y variable, picking the X variables
  17. Chapter Twelve. Calculating weight of evidence and information value
  18. Chapter Thirteen. Regressions
  19. Chapter Fourteen. Getting a sensible model
  20. Chapter Fifteen. Credit scores on the same borrower differ between CRAs
  21. Chapter Sixteen. The credit industry outside the United States
  22. Chapter Seventeen. List of practices by country
  23. Chapter Eighteen. Data security
  24. Chapter Nineteen. Algorithms and individuals
  25. Chapter Twenty. Something like a conclusion
  26. Appendix 1. U.S. (and a little bit of European) law
  27. Appendix 2. Final rule on credit scores from FHFA
  28. Appendix 3. Attachment: My credit report
  29. Appendix 4. A summary of your rights under the Fair Credit Reporting Act
  30. Appendix 5. Your rights under State law
  31. Index