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Editorial Cuvillier

Publicaciones, tesis doctorales, capacitaciónes para acceder a una cátedra de universidad & prospectos.
Su editorial internacional especializado en ciencias y economia

Editorial Cuvillier

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Recent Methods from Statistics and Machine Learning for Credit Scoring

Impresion
EUR 32,80 EUR 31,16

E-Book
EUR 22,96

Recent Methods from Statistics and Machine Learning for Credit Scoring (Tienda española)

Anne Kraus (Autor)

Previo

Indice, PDF (45 KB)
Lectura de prueba, PDF (160 KB)

ISBN-13 (Impresion) 9783954047369
ISBN-13 (E-Book) 9783736947368
Idioma Inglés
Numero de paginas 166
Laminacion de la cubierta mate
Edicion 1. Aufl.
Lugar de publicacion Göttingen
Lugar de la disertacion München
Fecha de publicacion 08.07.2014
Clasificacion simple Tesis doctoral
Area Matemática
Palabras claves Credit Scoring, AUC, optimization, Banking
Descripcion

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.