Data mining technology has yielded fruitful results in the area of crime discovery and intelligent decision-making. Credit card is one of the most popular payment methods, providing great convenience and efficiency. However, due to the vulnerabilities of credit card transactions, criminals are able to commit fraud to infringe on the interests of the state and citizens. How to discover potential fraudsters while guaranteeing high efficiency becomes an extremely valuable problem to solve. In this work, we talk about the advantages and disadvantages of different models to detect credit card fraud. We first introduce the data preprocessing measures for handling imbalanced fraud detection dataset. Then we compare related models to implement fraudster recognition. We also propose a feature selection approach based on combined feature weights. Some future research interests are also envisioned.
Authors: Xiaoqian Liu (Jiangsu Police Institute), Chenfei Yu (Jiangsu Police Institute), Bin Xia (Nanjing University of Posts and Telecommunications), Haiyan Gu (Jiangsu Police Institute), Zhenli Wang (Jiangsu Police Institute),
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