Abstract
With the economic development, loan business has rapidly developed in China. The risk that customers can’t repay their loans on time has increased. Therefore it is an important problem for financial organizations to approve the customers’ loan application or not. Typical machine learning methods for classification can be employed to mine customers’ financial information and give valuable judgments. However, these learning methods rely on shallow features, and the relationships between these features are not well studied. We investigate the function of Convolutional Neural Network (CNN) in this work, as it is successful in field of image recognition, speech recognition and natural language processing. We investigate four different CNN models. Experiments show that the fourth model with stochastic gradient descent algorithm and momentum achieves the best performance. Its accuracy and recall are 0.95 and 0.26 respectively.
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Acknowledgement
This work is partially supported by the National Natural Science Foundation of China (61672040 and 61972003).
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Wu, M., Du, C., Huang, Y., Cui, X., Duan, J. (2021). Investigation on Loan Approval Based on Convolutional Neural Network. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1422. Springer, Cham. https://doi.org/10.1007/978-3-030-78615-1_18
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