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The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation, by Raymond Anderson
Free PDF The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation, by Raymond Anderson
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Credit scoring aims to quantify the likelihood of a prospective borrower defaulting on payment over a specified period of time. The credit score is calculated using increasingly sophisticated statistical models, which vary considerably between individual cases. This clearly-written and comprehensive text covers the scorecard development process and provides a practical how-to guide for those wanting to use and develop credit scoring techniques.
Assuming little prior knowledge, the text includes the relevant statistical and mathematical tools, numerous real-life examples, and discussion of the credit risk management cycle and the importance of credit scoring in business and regulatory environments, including Basel II.
An extensive glossary and bibliography make this an indispensable desktop reference for graduate students in statistics, business, economics and finance, MBA students, credit risk and financial practitioners.
- Sales Rank: #710797 in Books
- Published on: 2007-08-30
- Original language: English
- Number of items: 1
- Dimensions: 7.30" h x 1.90" w x 9.70" l, 3.70 pounds
- Binding: Hardcover
- 731 pages
Review
This is an extremely valuable and timely book on a very important topic ... Anderson has provided a great service to all who use Credit Scoring techniques. Barry Scholnick PhD, Eric Geddes Associate Professor of Business, University of Alberta It is a superb mixture of a practical how to do guide for those wanting to use and develop credit scoring together with a way of putting the decisions it supports in context and the techniques it uses in a general modelling framework. Professor Lyn Thomas, Professor of Management Science, Scholl of Management, University of Southampton
From the Author
If you've written the thing, of course you're going to brag. This work was took four years, and involved thousands of hours reading and research, to provide a view of the topic from practically every possible angle: statistics, economics, finance, law, history, and so on. And even though I already had several years experience in the field, its creation took me on a journey of learning.
Although written by a practitioner, the book is extremely well referenced and suited for academic environments (the bibliography and glossary are 15 and 40 pages long, respectively). It takes a non-geocentric approach, and strives present broad principles instead of focussing upon the situation in any one country. Even so, it is most relevant to the UK and USA environments, for which the most information is available.
Comments received from colleagues have thus far have included "awesome", "art", and "bible", as I really tried to draw upon my writing abilities to create something that "is in a totally different league" to other works. If you have any interest in retail credit, whether as a bank, retailer, or service provider, I am sure you will find this book of value.
From the Back Cover
"This is an extremely valuable and timely book on a very important topic... Anderson had provided a great service to all who use Credit Scoring techniques."
Barry Scholnick PhD, Eric Geddes Associate Professor of Business, University of Alberta
"It is a superb mixture of a practical how to do guide for those wanting to develop credit scoring together with a way of putting the decisions it supports in context and the techniques it uses in a general modelling framework."
Professor Lyn Thomas, Professor of Management Science, School of Management, University of Southampton.
The Credit Scoring Toolkit provides an all-encompassing view of the use of statistical models to assess retail credit risk and provide automated decisions, and in eight modules it provides frameworks for both theory and practice. The book first explores the economic justification and history of Credit Scoring, risk linkages and decision science, statistical and mathematical tools, the assessment of business enterprises, and regulatory issues ranging from data privacy to Basel II. It then provides a practical how-to-guide for scorecard development, including data collection, scorecard implementation, and use within the credit risk management cycle.
Including numerous real-life examples and an extensive glossary and bibliography, the text assumes little prior knowledge making it an indispensable desktop reference for graduate students in statistics, business, economics and finance, MBA students, credit risk and financial practitioners.
- Highly-accessible guide to Credit Scoring
- Comprehensive, up-to-date, and wide ranging
- Assumes little prior knowledge
- Numerous examples and illustrations
- Extensive glossary and bibliography
Most helpful customer reviews
5 of 5 people found the following review helpful.
Amazing contents..
By Kbcard
I have experiance of developing scoring models over 11 years. But I never have seen like this reference book which has most important things. It contains from the start of scoring models to the end of scoring models, so if you have interest in scoring models and retail credit risk management then never miss this oppertunity for you..
0 of 0 people found the following review helpful.
Four Stars
By Felipe Llaugel Emiliano
excelent!
12 of 17 people found the following review helpful.
Overpriced and Overrated
By Limorkil
This is by no means a bad book, but do not let the high price tag fool you into thinking this is the best out there. It is very comprehensive, although everything is either at an annoyingly high level or an unhelpful low level, with nothing much between. You can get a feel for WHAT people do when they create scoring models, but not necessarily WHY or HOW they do it.
I think the worst feature is that the book is very uneven, almost like it was written by two people: one experienced and non-technical, the other highly technical but working in a different field. The non-technical parts are highly readable, if somewhat wordy and slightly vague. Then, in parts, the book switches to "statistics 101" mode and throws a lot of jargon at you which - even for those who can understand it - is not terribly enlightening. Maybe the author had someone else write those parts, or maybe he copied heavily from some statistical papers without really understanding what he was writing.
Don't get me wrong: this book is a pretty good overview. It is certainly no worse than 90% of the subject matter out there and the high level parts are very engaging. But if you were thinking paying >$150 would get you something more in depth or a different perspective or approach then you will probably be disappointed.
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