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Investigation and improvement of multi-layer perceptron neural networks for credit scoring
Citation
Zhao, Z and Xu, S and Kang, BH and Kabir, MMJ and Liu, Y and Wasinger, R, Investigation and improvement of multi-layer perceptron neural networks for credit scoring, Expert Systems With Applications, 42, (7) pp. 3508-3516. ISSN 0957-4174 (2015) [Refereed Article]
Copyright Statement
Copyright 2014 Elsevier Ltd.
DOI: doi:10.1016/j.eswa.2014.12.006
Abstract
Multi-Layer Perceptron (MLP) neural networks are widely used in automatic credit scoring systems with
high accuracy and efficiency. This paper presents a higher accuracy credit scoring model based on MLP
neural networks that have been trained with the back propagation algorithm. Our work focuses on
enhancing credit scoring models in three aspects: (i) to optimise the data distribution in datasets using
a new method called Average Random Choosing; (ii) to compare effects of training–validation–test
instance numbers; and (iii) to find the most suitable number of hidden units. We trained 34 models
20 times with different initial weights and training instances. Each model has 6 to 39 hidden units with
one hidden layer. Using the well-known German credit dataset we provide test results and a comparison
between models, and we get a model with a classification accuracy of 87%, which is higher by 5% than the
best result reported in the relevant literature of recent years. We have also proved that our optimisation
of dataset structure can increase a model’s accuracy significantly in comparison with traditional methods.
Finally, we summarise the tendency of scoring accuracy of models when the number of hidden units
increases. The results of this work can be applied not only to credit scoring, but also to other MLP neural
network applications, especially when the distribution of instances in a dataset is imbalanced.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | credit scoring, neural networks, back propagation |
| Research Division: | Information and Computing Sciences |
| Research Group: | Machine learning |
| Research Field: | Neural networks |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information systems, technologies and services |
| Objective Field: | Information systems, technologies and services not elsewhere classified |
| UTAS Author: | Zhao, Z (Dr Zongyuan Zhao) |
| UTAS Author: | Xu, S (Dr Shuxiang Xu) |
| UTAS Author: | Kang, BH (Professor Byeong Kang) |
| UTAS Author: | Kabir, MMJ (Mr Mir Kabir) |
| UTAS Author: | Wasinger, R (Dr Rainer Wasinger) |
| ID Code: | 98070 |
| Year Published: | 2015 |
| Web of Science® Times Cited: | 108 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2015-01-30 |
| Last Modified: | 2022-09-30 |
| Downloads: | 0 |
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