Recent Methods from Statistics and Machine Learning for Credit Scoring
Author | : Anne Kraus |
Publisher | : Cuvillier Verlag |
Total Pages | : 166 |
Release | : 2014-07-08 |
ISBN-10 | : 9783736947368 |
ISBN-13 | : 3736947364 |
Rating | : 4/5 (68 Downloads) |
Download or read book Recent Methods from Statistics and Machine Learning for Credit Scoring written by Anne Kraus and published by Cuvillier Verlag. This book was released on 2014-07-08 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.