Abnormal application detection method and device, computer device and storage medium

A detection method and abnormal technology, applied in the computer field, can solve problems such as changes in fraud methods and high labor costs, and achieve the effect of facilitating customer understanding and productization, and improving practicability

Pending Publication Date: 2019-06-07
ONE CONNECT SMART TECH CO LTD SHENZHEN
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Problems solved by technology

[0003] At present, the industry mainly uses supervised learning algorithms to detect fraudulent loan applications from users, but in most cases, the data

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  • Abnormal application detection method and device, computer device and storage medium
  • Abnormal application detection method and device, computer device and storage medium
  • Abnormal application detection method and device, computer device and storage medium

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[0055] In order to make the purpose, technical solutions, and advantages of this application clearer, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the application, and not used to limit the application.

[0056] The abnormal application detection method provided in this application is based on the Isolation Forest model and can be applied to figure 1 In the application environment shown, the terminal 102 where the application testing staff is located communicates with the server through the network, and the server 104 obtains the credit application data of the applicant provided by the application monitoring staff through the network. After the server receives the credit application data, First, obtain applicant information and the application feature set corresponding to the applicant information according to the ...

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Abstract

The invention relates to the field of artificial intelligence classification models, and specifically relates to an abnormal application detection method and device, a computer device and a storage medium. The method comprises the steps of obtaining credit application data of an applicant; obtaining applicant information and an application feature set corresponding to the applicant information according to the credit application data; inputting the application feature set into a preset isolated forest model, obtaining an application score corresponding to the application feature set, and constructing the preset isolated forest model based on an unmarked training feature set; and judging whether an application corresponding to the credit application data belongs to an abnormal application or not according to the application score. The credit application is scored by adopting the preset isolated forest model obtained by unsupervised learning, no label is needed for training, the practicability of the abnormal application scoring system is greatly improved, variable fraud and unseen fraud can be recognized, the abnormal degree of the abnormal application scoring system is output in ascoring mode, and the abnormal degree of the abnormal application scoring system is reflected, so that clients can understand and productize the abnormal application conveniently.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a method, device, computer equipment and storage medium for detecting abnormal applications. Background technique [0002] The online credit industry has developed rapidly in recent years, presenting a situation where a hundred schools of thought are contending and a hundred flowers are blooming. Along with the prosperous development of the industry, the black industry chain of fraud is constantly penetrating into this field, and various novel fraud modes emerge in endlessly. The healthy development of the Internet credit industry has cast a shadow. According to incomplete statistics, the annual loss due to fraud is 50 billion to 100 billion, and the risk of fraud has become the most important risk in the Internet credit industry. [0003] At present, the industry mainly uses supervised learning algorithms to detect fraudulent loan applications from users, but in mos...

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Application Information

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IPC IPC(8): G06Q40/02G06K9/62G06K9/66
CPCG06Q40/02G06V30/194G06F18/00
Inventor 马新俊
Owner ONE CONNECT SMART TECH CO LTD SHENZHEN
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