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Consumer Credit ModelsPricing, Profit and Portfolios$
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Lyn C. Thomas

Print publication date: 2009

Print ISBN-13: 9780199232130

Published to Oxford Scholarship Online: May 2009

DOI: 10.1093/acprof:oso/9780199232130.001.1

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Introduction to consumer credit and credit scoring

Introduction to consumer credit and credit scoring

Chapter:
(p.1) 1 Introduction to consumer credit and credit scoring
Source:
Consumer Credit Models
Author(s):

Lyn C. Thomas

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199232130.003.0001

This chapter outlines what is meant by a credit score, why it is an integral part of the decision process in lending to consumers, and how credit scoring systems are built. After describing the historical development of consumer credit and credit scoring, decision trees are used to model the credit granting process. In particular, return on capital based models and their connection with the tradition expected profit model are introduced. The chapter defines what is meant by a credit score, why log odds scores have such useful properties, and how one can extend the definition of a credit score to time dependent scores. It then goes through the development process of building a scorecard, discussing sample construction, reject inference, coarse classification, and variable selection. It concludes by looking at the different methodologies for building a scorecard such as logistic regression, linear regression, classification tress, and linear programming.

Keywords:   credit score, default probability, logistic regression, scorecard building methodologies, return on capital, decision trees, coarse classification

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