Subject type determination method and apparatus, computing device, and storage medium

By acquiring resource transaction information of the target entity and utilizing multi-scale permutation entropy and machine learning models, the problem of difficulty in identifying abnormal resource transactions in existing technologies has been solved, enabling timely identification and processing of abnormal transactions.

CN115205045BActive Publication Date: 2026-07-24TENPAY PAID TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
TENPAY PAID TECH
Filing Date
2022-08-09
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing technologies make it difficult to identify entities engaging in abnormal resource transactions in a timely and accurate manner, resulting in the inability to take appropriate countermeasures promptly.

Method used

By acquiring resource transaction information of the target entity within a target time period, and using a multi-scale permutation entropy model and a machine learning model, the characteristic values ​​of resource transfer in, transfer out, and retention are determined, thereby identifying the entity type.

Benefits of technology

It enables timely and accurate identification of abnormal resource transactions, allowing for prompt and appropriate countermeasures to prevent such transactions.

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Abstract

The disclosure provides a subject type determination method, characterized in that the method comprises: obtaining resource transaction information of a target subject in a target time period, the resource transaction information comprising resource transfer-in information, resource transfer-out information and resource retention information related to the target subject; determining, based on the resource transaction information, a resource transfer-in feature value corresponding to the resource transfer-in information, a resource transfer-out feature value corresponding to the resource transfer-out information, and a resource retention feature value corresponding to the resource retention information, wherein the resource transfer-in feature value, the resource transfer-out feature value, and the resource retention feature value respectively represent the degree of change in resource transaction represented by the corresponding resource transaction information of the target subject in the target time period; and determining the subject type of the target subject based on the resource transfer-in feature value, the resource transfer-out feature value, and the resource retention feature value.
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Citation Information

Patent Citations

  • Abnormal transaction object identification method, device and equipment

    CN109583890A

  • Risk identification method and device

    CN112446708A