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Credit card fraud causes significant financial losses and frequently occurs as fraud attack, defined as short-term sequence of fraudulent transactions associated with high transaction rates and amounts, business areas historically tied to…

最优化与控制 · 数学 2025-03-27 Alexander Stotsky

Credit card fraud is an ongoing problem for almost all industries in the world, and it raises millions of dollars to the global economy each year. Therefore, there is a number of research either completed or proceeding in order to detect…

机器学习 · 计算机科学 2020-07-30 Yusuf Yazici

Credit cards play an exploding role in modern economies. Its popularity and ubiquity have created a fertile ground for fraud, assisted by the cross boarder reach and instantaneous confirmation. While transactions are growing, the fraud…

密码学与安全 · 计算机科学 2022-08-24 Gayan K. Kulatilleke

Credit card fraud has emerged as major problem in the electronic payment sector. In this survey, we study data-driven credit card fraud detection particularities and several machine learning methods to address each of its intricate…

机器学习 · 计算机科学 2020-10-14 Yvan Lucas , Johannes Jurgovsky

Credit card is one of the most extensive methods of instalment for both online and offline mode of payment for electronic transactions in recent times. credit cards invention has provided significant ease in electronic transactions.…

机器学习 · 计算机科学 2024-09-23 Sourav Verma , Joydip Dhar

Fraudulent activities on digital banking services are becoming more intricate by the day, challenging existing defenses. While older rule driven methods struggle to keep pace, even precision focused algorithms fall short when new scams are…

密码学与安全 · 计算机科学 2026-01-21 Karthikeyan V. R. , Premnath S. , Kavinraaj S. , J. Sangeetha

The automatic detection of frauds in banking transactions has been recently studied as a way to help the analysts finding fraudulent operations. Due to the availability of a human feedback, this task has been studied in the framework of…

机器学习 · 计算机科学 2020-04-24 Christelle Marfaing , Alexandre Garcia

Credit and debit cards, rather than actual money, have become the universal payment means. With these cards, it has become possible to buy expensive items easily without an additional complex authentication procedure being conducted.…

密码学与安全 · 计算机科学 2013-06-25 Chae Chang Lee , Ji Won yoon

With the increase of credit card usage, the volume of credit card misuse also has significantly increased. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to…

机器学习 · 计算机科学 2019-12-09 Niloofar Yousefi , Marie Alaghband , Ivan Garibay

The rise of digital payments has accelerated the need for intelligent and scalable systems to detect fraud. This research presents an end-to-end, feature-rich machine learning framework for detecting credit card transaction anomalies and…

With the proliferation of various online and mobile payment systems, credit card fraud has emerged as a significant threat to financial security. This study focuses on innovative applications of the latest Transformer models for more robust…

机器学习 · 计算机科学 2024-11-13 Chang Yu , Yongshun Xu , Jin Cao , Ye Zhang , Yinxin Jin , Mengran Zhu

Credit card frauds are at an ever-increasing rate and have become a major problem in the financial sector. Because of these frauds, card users are hesitant in making purchases and both the merchants and financial institutions bear heavy…

机器学习 · 计算机科学 2020-12-08 Thanh Thi Nguyen , Hammad Tahir , Mohamed Abdelrazek , Ali Babar

The credit cards' fraud transactions detection is the important problem in machine learning field. To detect the credit cards's fraud transactions help reduce the significant loss of the credit cards' holders and the banks. To detect the…

机器学习 · 统计学 2019-09-02 Loc Tran , Tuan Tran , Linh Tran , An Mai

In the age of digital finance, detecting fraudulent transactions and money laundering is critical for financial institutions. This paper presents a scalable and efficient solution using Big Data tools and machine learning models. We utilize…

分布式、并行与集群计算 · 计算机科学 2025-06-04 Chen Liu , Hengyu Tang , Zhixiao Yang , Ke Zhou , Sangwhan Cha

Electronic payment platforms are estimated to process billions oftransactions daily, with the cumulative value of these transactionspotentially reaching into the trillions. Even a minor error within thishigh-volume environment could…

密码学与安全 · 计算机科学 2025-07-04 Mao Luo , Zhi Wang , Yiwen Huang , Qingyun Zhang , Zhouxing Su , Zhipeng Lv , Wen Hu , Jianguo Li

Machine learning has opened up new tools for financial fraud detection. Using a sample of annotated transactions, a machine learning classification algorithm learns to detect frauds. With growing credit card transaction volumes and rising…

机器学习 · 计算机科学 2022-08-26 Gayan K. Kulatilleke

Automated fraud behaviors detection on electronic payment platforms is a tough problem. Fraud users often exploit the vulnerability of payment platforms and the carelessness of users to defraud money, steal passwords, do money laundering,…

密码学与安全 · 计算机科学 2019-09-06 Ruoyu Deng , Na Ruan

At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss. In this work, we propose xFraud, an explainable fraud transaction prediction framework which…

机器学习 · 计算机科学 2022-05-26 Susie Xi Rao , Shuai Zhang , Zhichao Han , Zitao Zhang , Wei Min , Zhiyao Chen , Yinan Shan , Yang Zhao , Ce Zhang

Breached data refers to the unauthorized access, theft, or exposure of confidential or sensitive information. Breaches typically occur when malicious actors or unauthorized users breach secure systems or networks, resulting in compromised…

数据库 · 计算机科学 2023-09-25 Mayank Gite

In recent years, financial fraud detection systems have become very efficient at detecting fraud, which is a major threat faced by e-commerce platforms. Such systems often include machine learning-based algorithms aimed at detecting and…

密码学与安全 · 计算机科学 2023-12-05 Chen Doytshman , Satoru Momiyama , Inderjeet Singh , Yuval Elovici , Asaf Shabtai
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