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Enterprise financial service risk prediction method and device

A risk prediction and enterprise technology, applied in the field of data processing, can solve problems such as large labor costs, difficulty in obtaining enterprise information, and inability to cover all enterprises in financial institutions, so as to improve accuracy and intelligence, solve insufficient training samples, The effect of reducing labor costs

Pending Publication Date: 2020-11-13
INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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Problems solved by technology

[0004] However, the existing applied machine learning models require experts to label a large amount of data, so it requires a lot of labor costs. It is very difficult to obtain a sufficient amount of corporate information as training samples at this stage, and the historical corporate users of financial institutions cannot objectively cover all companies within the financial institution's service scope. Accuracy and intelligent requirements for risk forecasting by enterprises that have not registered with the bank

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  • Enterprise financial service risk prediction method and device
  • Enterprise financial service risk prediction method and device
  • Enterprise financial service risk prediction method and device

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Embodiment Construction

[0078] 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.

[0079] Considering that a successful model needs to rely on a large amount of data labeling training, and the bank's small and micro enterprise customers cannot cover all small enterprises, nor can they score all small enterprises through expert evaluation, this application provides a risk prediction for enterprise financial services The method, enterprise fin...

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Abstract

The embodiment of the invention provides an enterprise financial service risk prediction method and device. The method comprises the steps that operation state information of a target enterprise whichis not authorized by financial service currently is acquired; inputting the operation state information of the target enterprise into a weak supervision scoring model for financial service risk prediction, and taking the output as a financial service risk prediction level of the target enterprise to determine whether to provide financial service for the target enterprise or not; wherein the weaksupervision scoring model is obtained by scoring a plurality of enterprises by applying a fusion model in advance, the fusion model is obtained based on a marking model and historical enterprise datawith unknown labels, and the marking model is obtained by training historical enterprise data with known labels in advance. According to the invention, the accuracy and the intelligent degree of the financial service risk prediction process of an enterprise without financial service authorization can be effectively improved, the enterprise financial service risk prediction efficiency can be effectively improved, and the operation reliability and safety of a financial institution can be improved.

Description

technical field [0001] This application relates to the technical field of data processing, in particular to a method and device for risk prediction of corporate financial services. Background technique [0002] With the rapid development of science and technology, banks and other financial institutions usually have internal evaluation systems and indicators for corporate users, especially for large and medium-sized enterprises that have opened corporate accounts or credit files in financial institutions. With big data, AI With the development of technology, financial institutions can use machine learning models to predict the financial service risks of these enterprises, thereby improving the risk control capabilities of financial institutions. [0003] At present, the existing methods of applying machine learning models to predict the risks of enterprises usually need to obtain a large amount of enterprise information in advance, and experts mark a large amount of data and ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q20/40G06Q40/02
CPCG06Q20/4016G06Q40/03
Inventor 倪灵
Owner INDUSTRIAL AND COMMERCIAL BANK OF CHINA
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