Fodor, Kitti (2023) Logistic Regression or Neural Network? Which Provides Better Results for Retail Loans? THEORY METHODOLOGY PRACTICE: CLUB OF ECONOMICS IN MISKOLC, 19 (1). pp. 53-62. ISSN 1589-3413
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Abstract
While there is extensive literature on the prediction of corporate bankruptcies, there is little literature on the classification of retail borrowers. This is also true in Hungary. Recognising who is at risk of becoming a bad debtor is not easy. There are several ways to analyse the data, which may yield 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?The analyses show that the neural network model produced the best and most favourable results. The accuracy of the best method was found to be 81.5%.
| Item Type: | Article |
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| Uncontrolled Keywords: | statistics; logistic regression; neural network, loan default |
| Subjects: | H Social Sciences / társadalomtudományok > HB Economic Theory / közgazdaságtudomány > HB4 Dynamics of the economy / gazdasági folyamatok H Social Sciences / társadalomtudományok > HG Finance / pénzügy |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 21 Jul 2023 08:29 |
| Last Modified: | 21 Jul 2023 08:29 |
| URI: | http://real.mtak.hu/id/eprint/170314 |
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