Customer risk feature screening method based on SVM-RFE and application thereof

A feature screening and customer-based technology, applied in the level field, can solve the problem of redundant information not learning from the training feedback results of the learner, and achieve the effect of ensuring adaptability and simplicity

Active Publication Date: 2021-01-05
SHANGHAI UNIV OF ENG SCI +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to overcome the defect that the existing technology does not consider redundant information between features and does not refer to the training feedback results of the learner, and provides a method that can use machine learning to complete automatic screening and quantitative identification of customer risk features

Method used

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  • Customer risk feature screening method based on SVM-RFE and application thereof
  • Customer risk feature screening method based on SVM-RFE and application thereof
  • Customer risk feature screening method based on SVM-RFE and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0095] A method for screening customer risk characteristics based on SVM-RFE, the steps are as follows figure 1 As shown, specifically:

[0096] (1) Acquiring customer risk characteristic data including multiple customer characteristics;

[0097] Customer risk characteristic data can be obtained through the following channels: financial institutions’ own data platforms, third-party data platforms, and the use of web crawlers and text data analysis to collect customer risk characteristic data;

[0098] Using web crawlers and text data analysis to collect customer risk characteristic data specifically includes the following steps:

[0099] Collect customer risk cases → analyze customer risk cases → mine customer risk characteristics;

[0100] Specifically, the collection of customer risk cases can be done by using web crawler technology to crawl customer risk cases on mainstream websites, or using manual channels such as public publications to further collect customer risk cas...

Embodiment 2

[0160] an electronic device such as figure 2 As shown, including one or more processors, one or more memories, one or more programs, data collection devices and display devices connected to the processors;

[0161] The data collection device is used to obtain customer risk characteristic data including multiple customer characteristics, the display device is used to display the finally obtained customer risk characteristic set, one or more programs are stored in the memory, and when the one or more programs are processed by the processor During execution, the electronic device is made to execute the method for screening customer risk characteristics based on SVM-RFE as described in Embodiment 1.

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Abstract

The invention discloses a customer risk feature screening method based on SVMRFE and application thereof. The method comprises the following steps: acquiring customer risk feature data comprising a plurality of customer features; for the customer risk feature Xj, calculating an importance comprehensive measurement index of the customer risk feature Xj based on the Gini coefficient, the informationgain, the information gain ratio, the mutual information and the feature weight of the optimal classification result of the SVM classifier; after importance comprehensive measurement indexes of all customer risk characteristics are calculated in sequence, sorting is carried out in sequence from large to small according to the indexes, and the first k characteristics are selected to form a customer risk characteristic set. According to the method, the correlation between the selected feature subset and the target variable and the redundancy of the feature subset are considered, the defect thatthe customer risk features are screened by using a single index is overcome, and the training result of the SVM classifier is introduced in the feature screening process, so that the screened customer risk features are more suitable for the characteristics of the SVM classifier, and application prospects are good.

Description

technical field [0001] The invention belongs to the technical field of customer risk rating (CRR), and relates to a customer risk feature screening method based on SVM (Support vector machine)-RFE (Recursive feature elimination, recursive feature elimination) and its application. Background technique [0002] With the continuous development of Internet technology, more and more financial institutions, enterprises, merchants and ordinary users are becoming more and more accustomed to using Internet finance to realize various financial transactions, such as inter-bank transfers, online payments, online investment and wealth management, digital Currency, online shopping and more. [0003] But on the other hand, Internet finance also has many problems. First of all, Internet finance has not been connected to the credit information system of the People's Bank of China, nor does it have a credit information sharing mechanism, and does not have a bank-like risk control, compliance...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/951G06F16/2458G06K9/62G06Q40/04
CPCG06F16/951G06F16/2465G06Q40/04G06F18/2411
Inventor 王国强罗康洋张怡谢晓金施兴森李金姚兵李梦颖
Owner SHANGHAI UNIV OF ENG SCI
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