Integrated learning anti-fraud test method and system

A technology that integrates learning and testing methods, applied in business, instrument, character and pattern recognition, etc., can solve problems such as limiting the efficiency and stability of business development, and achieve the effect of good generalization performance

Inactive Publication Date: 2018-05-15
杭州恩牛网络技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

At present, the corresponding risk review work still requires manual access to va

Method used

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  • Integrated learning anti-fraud test method and system
  • Integrated learning anti-fraud test method and system

Examples

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Embodiment 1

[0023] Such as figure 1 As shown, the embodiment of the present invention provides a learning anti-fraud test method, and the method includes the following steps:

[0024] S101 extracts a training sample set, and extracts a feature view of user information in the training sample set.

[0025] Specifically, the feature views extracted in this step include one or a combination of one or more of the user credit card data feature view, the credit report feature view, the operator data feature view, and the application list submodel feature view.

[0026] The user credit card data feature view refers to the user information card related data, including data feature views such as credit card opening data and transaction data.

[0027] The credit report feature view refers to credit data similar to the personal credit report issued by the People's Bank of China Credit Information Center, including data feature views such as user personal information, credit transactions, personal provident fu...

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PUM

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Abstract

The invention discloses an integrated learning anti-fraud test method, and aims at overcoming deficiencies of risk control and anti-fraud technologies in the industry of internet finance in the priorart, and providing an application integrated learning technology to carry out risk control test on users and transaction behaviors. The method comprises the following steps of: extracting a training sample set and extracting features of user information in the training sample set; training a base classifier, and training a feature view by adoption of a multi-term classification algorithm so as toobtain a base classifier set; processing the base classifier set by utilizing an integrated learning method so as to obtain an integrated classification model; and classifying test samples by using the integrated classification model so as to obtain a test result, and carrying out integration by using another machine learning algorithm so as to obtain a final result. The invention furthermore discloses an integrated learning anti-fraud test system on the basis of the method. According to the method and system, fraud users in internet transactions can be effectively tested, and relatively goodgeneralization and higher stability are provided at the same time.

Description

Technical field [0001] The invention relates to the technical field of credit investigation and anti-fraud, in particular to an anti-fraud method and system. Background technique [0002] With the development of the Internet financial industry, the use of Internet channels to conduct financial service transactions has become more and more popular. It is particularly important for both parties to Internet transactions to correctly assess transaction risks and prevent financial fraud. [0003] For the credit review and anti-fraud test of Internet financial users, it is necessary to review all kinds of credit and evaluation materials of users to evaluate transaction risks and ensure the interests of the financial platform. At present, the corresponding risk review work also requires manual access to varying degrees, which limits the efficiency and stability of business development. Summary of the invention [0004] The present invention aims to overcome the above-mentioned shortcomin...

Claims

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Application Information

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IPC IPC(8): G06Q30/00G06K9/62
CPCG06Q30/0185G06F18/2411G06F18/214
Inventor 李海峰
Owner 杭州恩牛网络技术有限公司
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