Logistic Regression or Neural Network? Which Provides Better Results for Retail Loans?

Kitti Fodor

doi:10.18096/TMP.2023.01.05

Authors

Kitti Fodor University of Miskolc https://orcid.org/0000-0003-1815-8159

DOI:

https://doi.org/10.18096/TMP.2023.01.05

Keywords:

statistics, logistic regression, neural network, loan default

Abstract

While there is a large literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in our country, where there is not much scientific work on this topic. Recognising who is becoming a bad debtor is not easy. There are several ways to analyse the data, which may even show different results. In this paper, my aim is to predict the default of household loans using logistic regression and neural networks. The question is, which method produces the better results?

Author Biography

Kitti Fodor, University of Miskolc

Assistant Lecturer

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