A Deep Neural Network (DNN) based classification model in application to loan default prediction

In this study, we applied a Deep Neural Networks (DNN) based classification model along with the conventional classification methods (Logistic Regression, Decision Tree, Naïve Bayes and Support Vector Machines) on a two distinct datasets containing characteristics of the loan clients in a medium-siz...

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Main Authors: Selçuk BAYRACI, Orkun SUSUZ
Format: Article
Language:English
Published: General Association of Economists from Romania 2019-12-01
Series:Theoretical and Applied Economics
Subjects:
Online Access: http://store.ectap.ro/articole/1421.pdf
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author Selçuk BAYRACI
Orkun SUSUZ
author_facet Selçuk BAYRACI
Orkun SUSUZ
author_sort Selçuk BAYRACI
collection DOAJ
description In this study, we applied a Deep Neural Networks (DNN) based classification model along with the conventional classification methods (Logistic Regression, Decision Tree, Naïve Bayes and Support Vector Machines) on a two distinct datasets containing characteristics of the loan clients in a medium-sized Turkish commercial bank. Python programming language and libraries (Sklearn, Tensorflow and Keras) have been used in data cleaning, data preparation, feature engineering and model implementation processes. Our empirical findings document that the accuracy of the deep learning classification model increases with the size of the dataset, implying that the deep learning models might yield better results than regression-based models in more complex datasets.
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spelling doaj.art-278dcf4faec04f29942d89f6c7f272002022-12-22T02:00:28ZengGeneral Association of Economists from RomaniaTheoretical and Applied Economics1841-86781844-00292019-12-01XXVI4758418418678A Deep Neural Network (DNN) based classification model in application to loan default predictionSelçuk BAYRACI0Orkun SUSUZ1 R&D Center, C/S Information Technologies, Istanbul, Turkey R&D Center, C/S Information Technologies, Istanbul, Turkey In this study, we applied a Deep Neural Networks (DNN) based classification model along with the conventional classification methods (Logistic Regression, Decision Tree, Naïve Bayes and Support Vector Machines) on a two distinct datasets containing characteristics of the loan clients in a medium-sized Turkish commercial bank. Python programming language and libraries (Sklearn, Tensorflow and Keras) have been used in data cleaning, data preparation, feature engineering and model implementation processes. Our empirical findings document that the accuracy of the deep learning classification model increases with the size of the dataset, implying that the deep learning models might yield better results than regression-based models in more complex datasets. http://store.ectap.ro/articole/1421.pdf data analyticscredit scoringdeep learningrisk management
spellingShingle Selçuk BAYRACI
Orkun SUSUZ
A Deep Neural Network (DNN) based classification model in application to loan default prediction
Theoretical and Applied Economics
data analytics
credit scoring
deep learning
risk management
title A Deep Neural Network (DNN) based classification model in application to loan default prediction
title_full A Deep Neural Network (DNN) based classification model in application to loan default prediction
title_fullStr A Deep Neural Network (DNN) based classification model in application to loan default prediction
title_full_unstemmed A Deep Neural Network (DNN) based classification model in application to loan default prediction
title_short A Deep Neural Network (DNN) based classification model in application to loan default prediction
title_sort deep neural network dnn based classification model in application to loan default prediction
topic data analytics
credit scoring
deep learning
risk management
url http://store.ectap.ro/articole/1421.pdf
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AT orkunsusuz adeepneuralnetworkdnnbasedclassificationmodelinapplicationtoloandefaultprediction
AT selcukbayraci deepneuralnetworkdnnbasedclassificationmodelinapplicationtoloandefaultprediction
AT orkunsusuz deepneuralnetworkdnnbasedclassificationmodelinapplicationtoloandefaultprediction