A personal credit default prediction method

A forecasting method and credit technology, applied in the field of artificial intelligence, can solve problems such as ignoring the intersection and fusion effects of multiple value information, not fully mining complex information features, and affecting the economic operation of lenders, so as to improve classification accuracy and information acquisition. Analyze comprehensive, individual effects with small effects

Inactive Publication Date: 2019-06-28
WUHAN UNIV OF TECH
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AI Technical Summary

Problems solved by technology

The existing credit default prediction methods are difficult to fit non-linear data, ignore the intersection and fusion effects of various value information, do not fully exploit the characteristics of complex information, and the prediction accuracy is low. Once a default occurs, the credit impact on the borrower Larger, but also affect the lender's economic operation

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  • A personal credit default prediction method
  • A personal credit default prediction method
  • A personal credit default prediction method

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Embodiment Construction

[0010] The application technical solution is described in detail below in conjunction with the accompanying drawings and embodiments. The present invention is a personal credit default prediction method, and the method includes the following steps:

[0011] S1. Collect the borrower's personal information data and credit account activity information data to establish a database, eliminate missing values ​​and outliers in the data, and preprocess the data;

[0012] S11. Collect borrower's personal information data and credit account activity information data from the personal credit platform through web crawler technology to establish a database, such as figure 1 As shown, the personal information data that needs to be collected includes customer number, gender, date of birth, contact information, place of residence, family information, education, income, risk preference, housing and vehicle conditions, industry, credit status, etc. Credit information can be queried according to...

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Abstract

The invention discloses a personal credit default prediction method which specifically comprises the following steps: S1, collecting personal information data of a borrower and credit account activityinformation data to establish a database, removing missing values and abnormal values of the data, and preprocessing the data; S2, constructing a decision-making tree, forming a random forest by a plurality of combined classifiers of the decision-making tree, constructing a random forest model, and classifying credit data samples; S3, logical regression analysis and a random forest algorithm arecombined, the classification accuracy is improved, and personal credit default prediction is completed. According to the method, the diversity of personal data is more focused, information acquisitionand analysis are comprehensive, and the defect that the prior art depends on data fitting is overcome; The method has the advantages of wide application range, small individual influence and high prediction accuracy.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a personal credit default prediction method. Background technique [0002] In personal credit lending behavior, the borrower has relatively comprehensive information, while the lender has limited knowledge of the borrower's information, and there is a serious problem of information asymmetry between the borrower and the lender. The existing credit default prediction methods are difficult to fit non-linear data, ignore the intersection and fusion effects of various value information, do not fully exploit the characteristics of complex information, and the prediction accuracy is low. Once a default occurs, the credit impact on the borrower Larger, but also affect the lender's economic operation. Contents of the invention [0003] In order to solve the above problems, the present invention proposes a method for predicting personal credit default behavior based o...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/02G06Q10/04
Inventor 谭江来徐晗茜马玎
Owner WUHAN UNIV OF TECH
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