Recent Methods from Statistics and Machine Learning for Credit Scoring

Anne Kraus

ISBN 10: 3954047365 / ISBN 13: 9783954047369

Published by Cuvillier, Cuvillier Jul 2014, 2014

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Credit scoring models are the basis for financial institutions like retail and consumer credit banks. The purpose of the models is to evaluate the likelihood of credit applicants defaulting in order to decide whether to grant them credit. The area under the receiver operating characteristic (ROC) curve (AUC) is one of the most commonly used measures to evaluate predictive performance in credit scoring.The aim of this thesis is to benchmark different methods for building scoring models in order to maximize the AUC. While this measure is used to evaluate the predictive accuracy of the presented algorithms, the AUC is especially introduced as direct optimization criterion.Books on Demand GmbH, Überseering 33, 22297 Hamburg 166 pp. Englisch.

Seller Inventory # 9783954047369

Bibliographic Details

• Title: Recent Methods from Statistics and Machine Learning for Credit Scoring
• Publisher: Cuvillier, Cuvillier Jul 2014
• Publication Date: 2014
• Language: English
• ISBN 10: 3954047365
• ISBN 13: 9783954047369
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 10D millimeters 210 millimeters width by 148 millimeters height by 10 millimeters depth
• Weight: 224 grams

About this title

Synopsis

Credit scoring models are the basis for financial institutions like retail and consumer credit banks. The purpose of the models is to evaluate the likelihood of credit applicants defaulting in order to decide whether to grant them credit. The area under the receiver operating characteristic (ROC) curve (AUC) is one of the most commonly used measures to evaluate predictive performance in credit scoring. The aim of this thesis is to benchmark different methods for building scoring models in order to maximize the AUC. While this measure is used to evaluate the predictive accuracy of the presented algorithms, the AUC is especially introduced as direct optimization criterion.