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AI-driven collaborative enterprise multi-dimensional credit feature extraction and evaluation method

A feature extraction and evaluation method technology, applied in the field of data processing, can solve problems such as insufficient accuracy, low accuracy, and insufficient corporate image characterization, and achieve the effect of solving data imbalance and improving accuracy.

Active Publication Date: 2022-04-15
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

[0007] (1) The financial indicators considered by the method based on expert experience are not comprehensive enough, the dependence on experience is too strong, and the accuracy rate is not high
[0008] (2) The method model of machine learning is single, unable to process text comment data, the image of the enterprise is not comprehensive enough, and the accuracy rate is not high enough

Method used

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  • AI-driven collaborative enterprise multi-dimensional credit feature extraction and evaluation method
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  • AI-driven collaborative enterprise multi-dimensional credit feature extraction and evaluation method

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Embodiment Construction

[0026] In order to facilitate those skilled in the art to understand the technical content of the present invention, the content of the present invention will be further explained below in conjunction with the accompanying drawings.

[0027] The method of the present invention comprises:

[0028] (1) Financial data preprocessing: the financial data of the present invention comes from the Wande database, and the principal component analysis is carried out to the financial data;

[0029] (2) Text data preprocessing: the text data of the present invention comes from Han’s Laser, and the text is mainly a record of the buyer’s credit, repayment, and historical breach of contract, and the text is sequentially denoised, stop words removed, and word vectors of the text treatment;

[0030] (3) Generating minority category data: Using generative confrontation network to train and generate financial data and text comment data respectively;

[0031] (4) Enterprise credit evaluation mode...

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Abstract

The invention discloses an AI-driven collaborative enterprise multi-dimensional credit feature extraction and evaluation method, which is applied to the field of enterprise credit evaluation and aims to solve the problem of low enterprise credit evaluation accuracy in the prior art. According to the method, more financial data indexes are adopted, text data indexes for enterprise credit comments are added, enterprise images are described from multiple dimensions, multiple models are adopted to extract features, and the accuracy of enterprise credit evaluation can be effectively improved.

Description

technical field [0001] The invention belongs to the field of data processing, in particular to an enterprise credit evaluation technology. Background technique [0002] Since the 1960s, enterprise credit risk assessment has been an important research topic in the international academic and financial circles. A large number of market investigations and long-term practice have shown that the main reason for the default of accounts receivable in my country's enterprises is that they did not fully evaluate the credit of enterprises beforehand. The same problem also exists in the Kingdee Cloud·Kingqiong ecosystem. To evaluate the credit of cooperative enterprises in the ecosystem, reduce the probability of corporate default events, and provide technical support for reasonable sales of enterprises is the key to Kingdee Cloud·Kangqiong enterprise collaboration and ecosystem construction Foundation. Taking the enterprises in the Kingdee Cloud·Kingqiong ecological circle as the res...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/00G06Q10/06G06N20/20G06K9/62G06F16/35
Inventor 廖伟智黄鹏伟
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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