Credit prediction overdue method and system fused with machine learning

Abstract

The invention provides a credit overdue prediction method and system fused with machine learning, and the method comprises the steps: collecting a plurality of credit factor data, carrying out the preprocessing, carrying out the calculation and sorting of the importance of the credit factor data in a preprocessing result, and deleting redundancy, and obtaining the selected credit factor data; andconstructing a training sample based on the credit factor data, establishing and training a credit overdue prediction model by using LSTM based on the training sample, determining an optimal parameter, and performing credit overdue prediction after the optimal model is obtained. According to the invention, credit factor data is widely collected to improve comprehensiveness of credit overdue prediction; the missing training data is classified to improve the data quality; the class imbalance condition of the user is processed by using an oversampling method, and data distribution is balanced; all factors influencing credit expiration is sorted, and redundancy is eliminated, and then the reasonability of factor selection is improved; and a credit overdue prediction model is comprehensively established based on bidirectional LSTM in combination with timing sequence factors, optimal model parameters are determined through S-fold intersection, and the optimal model quality is improved.

Description

technical field [0001] The invention relates to a credit overdue prediction method and system based on machine learning. Background technique [0002] In recent years, with the convenience and speed of credit application and the gradual change of user consumption habits, the amount of credit has continued to increase, and the business risk of credit has also continued to increase. As of the end of the first quarter of 2018, the total amount of credit card credit was 13.14 trillion yuan, maintaining a rapid growth trend; the total outstanding credit card credit card overdue for half a year accounted for 1.21% of the total credit payable at the end of the period, and the bad debt rate was relatively high. Credit is an important part of commercial bank profits, but it is currently facing relatively high risks, so commercial banks need to pay attention to this issue in the field of risk prevention and control. [0003] When a user applies for credit, predicting the user's credi...

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Problems solved by technology

[0005] The present invention provides a credit overdue prediction method and system integrated with machine learning, which is used to solve the problem of low efficiency and inaccurate prediction results of credit overdue prediction due to lack of original data, unbalanced data distribution, and more reliance on manual experience in the prior art. The problem

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