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Credit risk prediction method and system, terminal and storage medium

A risk prediction and credit technology, applied in terminals and computer-readable storage media, credit risk prediction methods, and system fields, can solve problems such as low accuracy

Pending Publication Date: 2020-04-24
HUNAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to propose a credit risk prediction method, system, terminal and computer-readable storage medium, aiming to solve the technical problem of low accuracy in predicting the credit risk of users in the existing credit scoring model

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  • Credit risk prediction method and system, terminal and storage medium
  • Credit risk prediction method and system, terminal and storage medium
  • Credit risk prediction method and system, terminal and storage medium

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Embodiment Construction

[0046] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0047] Please refer to figure 1 , figure 1It is a schematic diagram of a hardware structure of a terminal provided in various embodiments of the present invention. The terminal includes components such as a communication module 01 , a memory 02 , and a processor 03 . Those skilled in the art can understand that, figure 1 The terminals shown in may also include more or fewer components than shown, or combine certain components, or have different arrangements of components. Wherein, the processor 03 is connected to the memory 02 and the communication module 01 respectively, the memory 02 stores a computer program, and the computer program is executed by the processor 03 at the same time.

[0048] The communication module 01 can be connected with external devices through the network. The communication module 01 can ...

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Abstract

The invention discloses a credit risk prediction method and system, a terminal and a storage medium, and the method comprises the steps: employing the information of a user having a repayment behaviorto train a to-be-trained credit risk prediction model, and obtaining a preliminarily trained credit risk prediction model; predicting the credit risk grades of the users who do not pass the loan audit by adopting the preliminarily trained credit risk prediction model to obtain the credit risk prediction grades of the users who do not pass the loan audit; and training the preliminarily trained credit risk prediction model according to the user information of the user with the repayment behavior, the corresponding actual credit risk level, the user information of the user with loan audit failure and the corresponding credit risk prediction level to obtain a final credit analysis prediction model. According to the invention, the problem of low accuracy of predicting the credit risk of the user in the existing credit scoring model is solved.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a credit risk prediction method, system, terminal and computer-readable storage medium. Background technique [0002] In recent years, with the continuous development of Internet finance, the online P2P loan market has gradually integrated into human daily life. The online P2P lending market provides convenient services that allow direct lending transactions between users. But this convenience also brings huge potential risks for users, especially investors. Therefore, how to predict the credit risk of borrowers has become an urgent problem to be solved in the online P2P loan market. [0003] The emergence of the credit scoring model has alleviated this problem to a certain extent, but the traditional credit scoring model is constructed based on the information of users who are allowed to take loans, and lacks the information of other users who have been...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06Q40/02
CPCG06Q40/03G06F18/23G06F18/24
Inventor 李心儿刘彦张在美谢国琪
Owner HUNAN UNIV
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