Handbook of Credit Scoring
| Author | : | |
| Rating | : | 4.74 (739 Votes) |
| Asin | : | 081440619X |
| Format Type | : | paperback |
| Number of Pages | : | 370 Pages |
| Publish Date | : | 2014-09-06 |
| Language | : | English |
DESCRIPTION:
Her area is responsible for building credit risk models for first and second mortgages, student loans, and other consumer loan products. She was previously with Freddie Mac where she worked in the area of automated underwriting, and spent eight years with the Office of Thrift Supervision building models to measure interest rate risk. She has published a number of articles on risk management and is the edi- tor of Credit Risk Modeling: Design and Application and co-editor of
Very helpful book As someone who is not familiar with how credit scoring models are built, I have found this book to be extremely helpful and informative. Our institution has hired a number of vendors to build scorecards in the past but none has explained how the point weights were derived or how it was determined which variables should enter the scorecard. This book provided a very insightful discussion of these issues. It also includes two chapters discussing things you need to keep in mind when implementing scorecard. Tea Bag said not worth the money. this book doesn't cover any theoretical aspect of credit scoring. for example, almost every authoer is still using K-S statistics, which is no better than just eye-balling the difference between any "not worth the money" according to Tea Bag. this book doesn't cover any theoretical aspect of credit scoring. for example, almost every authoer is still using K-S statistics, which is no better than just eye-balling the difference between any 2 curves. the book provides no useful information to someone who wants to learn how to do the scoring. this book has 1/not worth the money this book doesn't cover any theoretical aspect of credit scoring. for example, almost every authoer is still using K-S statistics, which is no better than just eye-balling the difference between any 2 curves. the book provides no useful information to someone who wants to learn how to do the scoring. this book has 1/3 of overlap with the editor's last book. are the editor and authors just lazy? or the articles are just too good?. of overlap with the editor's last book. are the editor and authors just lazy? or the articles are just too good?. curves. the book provides no useful information to someone who wants to learn how to do the scoring. this book has 1/not worth the money this book doesn't cover any theoretical aspect of credit scoring. for example, almost every authoer is still using K-S statistics, which is no better than just eye-balling the difference between any 2 curves. the book provides no useful information to someone who wants to learn how to do the scoring. this book has 1/3 of overlap with the editor's last book. are the editor and authors just lazy? or the articles are just too good?. of overlap with the editor's last book. are the editor and authors just lazy? or the articles are just too good?. "I need a copy of it as soon as possible" according to Hussien Ali. Why yuo stopped the publishing of this item , I need a copy of it soon for any price
She has published a number of articles on risk management and is the edi- tor of Credit Risk Modeling: Design and Application and co-editor of a book on interest rate risk measurement and modeling, Interest Rate Risk Models: Theory and Application. She holds a Ph.D. . in Economics from the University of Cincinnati. About the Author Elizabeth Mays is the Director of Risk Modeling for Citigroup's Consumer Asset Division. Her area is responsible for building credit risk models for first and second mortgages, student loans, and other consumer loan products. She was previously with Freddie Mac where she worked in the area of automated underwriting
HANDBOOK OF CREDIT SCORING offers the insights of experts on credit scoring systems. Topics include: statistical techniques * generic and customized credit scoring models * credit scorecards, and more.. Bankers and lenders depend on credit scoring to determine the best credit risks--and insure maximum profit and security from their loan portfolios