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Supplier financial risk prediction method and device

A risk prediction and supplier technology, applied in the field of data processing, can solve problems such as poor reproductive ability, inability to guarantee the accuracy of supplier financial risk prediction, and slow convergence speed

Pending Publication Date: 2020-06-16
INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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Problems solved by technology

The BP neural network is a shallow network. There are few layers of the neural network. Generally, there are one layer for input, implicit, and output. Therefore, the BP model has shortcomings such as slow convergence speed and poor reproductive ability, and thus cannot guarantee the financial risk prediction of suppliers. accuracy

Method used

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  • Supplier financial risk prediction method and device
  • Supplier financial risk prediction method and device
  • Supplier financial risk prediction method and device

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Embodiment Construction

[0110] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0111] Based on the theoretical research on supplier financial risk evaluation indicators, this application provides a method of deep learning convolutional neural network with self-learning ability, which can more accurately evaluate supplier risk.

[0112] The essence of deep learning is based on building a neuron mechanism with many hidden layers. The neuro...

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Abstract

Embodiments of the invention provide a supplier financial risk prediction method and device. The method comprises the steps of obtaining financial risk index data of a target supplier; inputting the financial risk index data into a preset convolutional neural network model, and taking the output of the convolutional neural network model as a financial risk prediction result corresponding to the target supplier; and outputting a financial risk prediction result corresponding to the target supplier. According to the invention, the supplier financial risk can be predicted through the deep learning convolutional neural network with the self-learning capability, and the accuracy of supplier financial risk prediction can be effectively improved, so that the potential risk of the supplier can beeffectively avoided, and the operation reliability of the enterprise can be ensured.

Description

technical field [0001] This application relates to the technical field of data processing, in particular to a supplier financial risk prediction method and device. Background technique [0002] The current research on supplier risk mainly focuses on the screening and optimization of risk indicators for supply chain and supplier risk, less emphasis is placed on theoretical research on risk indicator systems, and more use of fuzzy comprehensive evaluation, analytic hierarchy process, gray evaluation, SCOR model, risk The method of mechanism coordination and balance has systematically summarized the risk assessment and conclusion analysis. The neural network simulates the neural reflexes of the human brain to train the machine, so that the trained neural network can analyze and judge the given input value and predict the output value. [0003] At present, BP neural network is mainly used to construct the risk prediction model of supplier finance, and BP neural network has been...

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Application Information

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IPC IPC(8): G06Q10/06G06Q40/00G06N3/04G06N3/08
CPCG06Q10/0635G06Q10/06393G06Q40/125G06N3/08G06N3/045
Inventor 王茹楠邬文佳查礼
Owner INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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