Credit limit prediction method and device based on deep fusion and medium
A credit and in-depth technology, applied in the field of machine learning, can solve problems such as low accuracy of evaluation results, achieve the effects of ensuring diversity, improving capital utilization, and reducing the amount of data processing
Active Publication Date: 2019-05-24
SUZHOU UNIV
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Problems solved by technology
In the prior art, the applicant's loan amount is evaluated through short-answer machine learning, and the accuracy of the evaluation result is often not high
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[0070] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0071] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0072] Next, a credit line prediction method based on deep fusion provided by an embodiment of the present invention is introduced in detail. figure 1 A flow chart of a method for predicting credit l...
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The embodiment of the invention discloses a credit limit prediction method and device based on deep fusion and a computer readable storage medium. The credit limit prediction method comprises the steps of obtaining credit data of each user; carrying out dimension reduction processing on the credit data to obtain a dense vector; and through dimension reduction processing, reducing the data processing amount of model training on the premise that the model training accuracy is not influenced;training the dense vectors by using a preset multi-path residual network to obtain a depth fusion model meeting convergence requirements; and processing the input to-be-evaluated data by using the depth fusion model to obtain a credit limit prediction value. According to the technical scheme, a multi-pathprocessing mode is set for the residual network, so that the diversity of feature extraction is ensured, the prediction accuracy of the deep fusion model is improved, an appropriate amount is distributed to a user with a borrowing demand as much as possible, and the fund utilization rate of a credit platform is improved.
Description
technical field [0001] The present invention relates to the technical field of machine learning, in particular to a credit limit prediction method, device and computer-readable storage medium based on deep fusion. Background technique [0002] With the popularity of credit platforms, there are more unsecured cash loan products. Applicants only need to fill in the required personal information on the application page to apply for cash loans. [0003] When carrying out credit business, in addition to assessing the risks of users, it is also necessary to predict the borrowing needs of users. Only by allocating an appropriate amount to users with borrowing needs as much as possible can the utilization rate of funds be maximized and costs reduced. and increase earnings. Usually, the credit platform evaluates the applicant's economic ability and repayment ability based on the personal information filled in by the applicant, so as to determine the applicant's initial credit line. ...
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IPC IPC(8): G06Q10/04G06Q40/02
CPCY02D10/00
Inventor 倪志文马小虎孙霄边丽娜
Owner SUZHOU UNIV