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The digital revolution has significantly impacted financial transactions, leading to a notable increase in credit card usage. However, this convenience comes with a trade-off: a substantial rise in fraudulent activities. Traditional machine…

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

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

Credit card plays a very important rule in today's economy. It becomes an unavoidable part of household, business and global activities. Although using credit cards provides enormous benefits when used carefully and responsibly,significant…

密码学与安全 · 计算机科学 2016-11-22 SamanehSorournejad , Zahra Zojaji , Reza Ebrahimi Atani , Amir Hassan Monadjemi

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

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

For the highly imbalanced credit card fraud detection problem, most existing methods either use data augmentation methods or conventional machine learning models, while neural network-based anomaly detection approaches are lacking.…

机器学习 · 计算机科学 2022-06-30 Tungyu Wu , Youting Wang

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 fraud is a major issue nowadays, costing huge money and affecting trust in financial systems. Traditional fraud detection methods often fail to detect advanced and growing fraud techniques. This study focuses on using Graph…

密码学与安全 · 计算机科学 2025-04-01 Irin Sultana , Syed Mustavi Maheen , Naresh Kshetri , Md Nasim Fardous Zim

As the world is rapidly moving towards digitization and money transactions are becoming cashless, the use of credit cards has rapidly increased. The fraud activities associated with it have also been increasing which leads to a huge loss to…

人工智能 · 计算机科学 2021-08-24 Pooja Tiwari , Simran Mehta , Nishtha Sakhuja , Jitendra Kumar , Ashutosh Kumar Singh

Detection of a Fraud transaction on credit cards became one of the major problems for financial institutions, organizations and companies. As the global financial system is highly connected to non-cash transactions and online operations…

机器学习 · 计算机科学 2022-05-31 Dinara Rzayeva , Saber Malekzadeh

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 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 card fraud detection is a critical challenge in the financial sector, demanding sophisticated approaches to accurately identify fraudulent transactions. This research proposes an innovative methodology combining Neural Networks (NN)…

计算工程、金融与科学 · 计算机科学 2024-05-02 Mengran Zhu , Ye Zhang , Yulu Gong , Changxin Xu , Yafei Xiang

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…

Card payment fraud is a serious problem, and a roadblock for an optimally functioning digital economy, with cards (Debits and Credit) being the most popular digital payment method across the globe. Despite the occurrence of fraud could be…

密码学与安全 · 计算机科学 2020-12-01 Bemali Wickramanayake , Dakshi Kapugama Geeganage , Chun Ouyang , Yue Xu

This study proposes a credit card fraud detection method based on Heterogeneous Graph Neural Network (HGNN) to address fraud in complex transaction networks. Unlike traditional machine learning methods that rely solely on numerical features…

机器学习 · 计算机科学 2025-04-14 Qiuwu Sha , Tengda Tang , Xinyu Du , Jie Liu , Yixian Wang , Yuan Sheng

The detection of frauds in credit card transactions is a major topic in financial research, of profound economic implications. While this has hitherto been tackled through data analysis techniques, the resemblances between this and other…

社会与信息网络 · 计算机科学 2017-06-08 Massimiliano Zanin , Miguel Romance , Santiago Moral , Regino Criado

Credit card has become popular mode of payment for both online and offline purchase, which leads to increasing daily fraud transactions. An Efficient fraud detection methodology is therefore essential to maintain the reliability of the…

机器学习 · 计算机科学 2019-04-25 Xuetong Niu , Li Wang , Xulei Yang

Credit card fraud is a problem continuously faced by financial institutions and their customers, which is mitigated by fraud detection systems. However, these systems require the use of sensitive customer transaction data, which introduces…

密码学与安全 · 计算机科学 2022-11-15 David Nugent
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