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Credit Scoring and Its Application : Siam Monographs on Mathematical Modeling and Computation - L. Thomas

Credit Scoring and Its Application

By: L. Thomas, D. Edelman, J. Crook

Paperback | 1 May 2002

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Tremendous growth in the credit industry has spurred the need for this book, the only one that details the mathematical models that help creditors make intelligent credit risk decisions. Creditors of all types make risk decisions every day, often haphazardly. This groundbreaking book addresses the two basic types of decisions and offers sound mathematical models to assist with the decision-making process. Creditors must decide whether to grant credit to a new applicant (credit scoring), and how to adjust the credit restrictions or the marketing effort directed at a current customer (behavioral scoring). Currently, only the most sophisticated creditors use the models contained in this book to make these decisions, but all creditors can know these aids to successful lending. The book contains a comprehensive review of the objectives, methods, and practical implementation of credit and behavioral scoring. The authors review principles of the statistical and operations research methods used in building scorecards, as well as the advantages and disadvantages of each approach. The book also describes practical problems encountered in building, using, and monitoring scorecards and examines some country-specific problems caused by bankruptcy, equal opportunities, and privacy legislation. This important feature addresses the increasingly international nature of the credit lending industry. Also included in this book is a discussion of economic theories of consumers' use of credit. The reader will gain an understanding of what lending institutions seek to achieve by using credit scoring and the changes in their objectives. Despite their widespread use in business, no other book details credit scoring variations that should be used with standard statistical and operations research techniques such as discriminant analysis, logistic regression, linear programming, neural nets, and genetic algorithms. Other unique features include methods of monitoring scorecards and deciding when to update them, as well as different applications of scoring, including direct marketing, profit scoring, tax inspection, prisoner release, and payment of fines. Focusing on small data problems is useful pedagogically; therefore, the authors have included a CD-ROM containing a database, mainly to emphasize the data analysis aspects of credit scoring.

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