Credit Risk Analytics: Predictive Modeling Techniques Comparison: Automated comparison of various predictive modeling techniques on credit card data - Couverture souple

Singh, Ravinder

 
9783659300868: Credit Risk Analytics: Predictive Modeling Techniques Comparison: Automated comparison of various predictive modeling techniques on credit card data
Couverture souple
ISBN 10 : 3659300861 ISBN 13 : 9783659300868
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

Credit Scoring studies are very important for any financial house. Both traditional statistical and modern data mining/machine learning tools have been evaluated in the credit scoring problem. Predictive modeling defaulter risk is one of the important problems in credit risk management. There are quite a few aggregate models and data driven models available in literature But very few of the studies facilitate the comparison of majority of the commonly employed tools in single comprehensive study. Additionally no study assesses the performance on more then two data sets and reports the results at the same time. So a macro or a simulator is designed which would work on multiple data sets and make the process of credit scoring transparent to the novice user. In initial stage, tools were compared using Dtreg predictive modeling software. Subsequently a SAS macro is developed to evaluate the effectiveness of tools available in SAS enterprise miner. The results revealed that support vector machine and genetic programming are superior tools for the purpose of classifying the loan applicant as their misclassification rates were least as compared to others. Also cross validation is essentia

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Présentation de l'éditeur

Credit Scoring studies are very important for any financial house. Both traditional statistical and modern data mining/machine learning tools have been evaluated in the credit scoring problem. Predictive modeling defaulter risk is one of the important problems in credit risk management. There are quite a few aggregate models and data driven models available in literature But very few of the studies facilitate the comparison of majority of the commonly employed tools in single comprehensive study. Additionally no study assesses the performance on more then two data sets and reports the results at the same time. So a macro or a simulator is designed which would work on multiple data sets and make the process of credit scoring transparent to the novice user. In initial stage, tools were compared using Dtreg predictive modeling software. Subsequently a SAS macro is developed to evaluate the effectiveness of tools available in SAS enterprise miner. The results revealed that support vector machine and genetic programming are superior tools for the purpose of classifying the loan applicant as their misclassification rates were least as compared to others. Also cross validation is essentia

Biographie de l'auteur

Ravinder Singh, ME(Master of Engineering), Data Analyst/Predictive Modeler/SAS consultant at Knowledge Business solutions,Bangalore, SAS advance certified

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659300861
ISBN 13 
9783659300868
Reliure
Broché
Nombre de pages
156
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
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