A Credit Card Fraud Detection Method Based on Imbalanced Flow Data Classification

A detection method and credit card technology, applied in data processing applications, finance, instruments, etc., can solve the problems of not being able to adapt to the new data flow environment of credit card flow data in time

Active Publication Date: 2022-03-29
ZHEJIANG GONGSHANG UNIVERSITY
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, if the categories of credit card flow data samples are reversed at a certain moment, the block-based integrated classification credit card fraud detection method often cannot adapt to the new data flow environment of credit card flow data in time.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] The present invention proposes a credit card fraud detection method based on classification of unbalanced flow data. The method does not need to keep small samples of credit card flow data at any past time, and can effectively classify and predict credit card dynamic flow data with unbalanced category distribution to detect to credit card fraud transaction data. First, the method only needs to learn one block of credit card flow data at each moment, and does not need to access past samples of credit card flow data blocks. Second, the method consistently emphasizes misclassified samples of credit card flow data during the update process. Again, this method can cope with concept drift of multiple types of credit card flow data simultaneously. At the same time, the method can quickly adapt to the new credit card flow data environment when the size category labels are swapped. Finally, the method uses a performance-based ensemble pruning technique to timely remove poorly ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a credit card fraud detection method based on unbalanced flow data classification. The credit card flow data classification model of the present invention includes a bag-based credit card flow data oversampling mechanism, a credit card flow data multi-type concept drift processing mechanism, a credit card flow data basic classifier weighting mechanism, a credit card flow data integration pruning mechanism, and classification prediction mechanism. The invention does not need to keep small samples of credit card flow data at any past time, and can effectively classify and predict credit card dynamic flow data with unbalanced category distribution, so as to detect credit card fraud transaction data.

Description

technical field [0001] The invention relates to a credit card fraud detection method based on unbalanced flow data classification. Background technique [0002] While the widespread use of credit cards brings great convenience to businesses and users, it also faces a large number of credit card frauds. my country's financial institutions lose billions of yuan due to credit card frauds every year. Credit card fraud is a financial risk faced by the country and society, especially the banking industry, in the current era of big data finance. How to realize credit card flow data fraud detection is an important technical and social problem that financial institutions need to solve, and has great financial value and social significance. . [0003] In the context of offline credit card swiping or online shopping applications, a massive, real-time, and dynamic data form is generated, which is called credit card flow data. The dynamic change of credit card flow data is called conce...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06Q40/02G06K9/62
CPCG06Q40/03G06F18/2433
Inventor 任思琪韩嵩
Owner ZHEJIANG GONGSHANG UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products