## Credit Scoring and Its ApplicationsTremendous growth in the credit industry has spurred the need for Credit Scoring and Its Applications, the only book 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 book addresses the two basic types of decisions and offers sound mathematical models to assist with the decision-making process. The first decision creditors face is whether to grant credit to a new applicant (credit scoring), and the second is how to adjust the credit restrictions or the marketing effort directed at a current customer (behavioral scoring). The authors have filled an important niche with this groundbreaking book. 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. |

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### Contents

MM06_ch1 | 2 |

MM06_ch2 | 9 |

MM06_ch3 | 19 |

MM06_ch4 | 41 |

MM06_ch5 | 63 |

MM06_ch6 | 89 |

MM06_ch7 | 107 |

MM06_ch8 | 121 |

MM06_ch9 | 151 |

MM06_ch10 | 169 |

MM06_ch11 | 179 |

MM06_ch12 | 187 |

MM06_ch13 | 209 |

MM06_ch14 | 219 |

MM06_bm | 233 |

### Other editions - View all

Credit Scoring and Its Applications L. C. Thomas,David B. Edelman,Jonathan N. Crook Limited preview - 2002 |

Credit Scoring and Its Applications Lyn C. Thomas,David B. Edelman,Jonathan N. Crook No preview available - 2002 |

### Common terms and phrases

acceptance rate accounts amount analysis application approach arrears assess assets assume attributes bad rate bank behavioral scoring Bernanke beta distribution borrowers build calculate Chapter characteristics classification tree coarse classifying consider consumer credit costs countries credit bureau credit card credit extended credit limit credit reference credit scorecards credit scoring cutoff score decision default define demand development sample discrimination distribution error estimate example expected expert system Figure function good:bad odds graph groups identify income increase interest rate layer lender lending linear programming loans logistic regression look Mahalanobis distance Markov chain matrix maximize measure minimize months mortgage node output outstanding parameters payments percentage performance period population portfolio predict probability problem profit repayment risk risk-based pricing ROC curve scoreband scorecard development scoring system securitization split statistical strategy strings survival analysis techniques variables