Results 11 to 20 of about 139,322 (228)

A new fusion neural network model and credit card fraud identification. [PDF]

PLoS ONE
Credit card fraud identification is an important issue in risk prevention and control for banks and financial institutions. In order to establish an efficient credit card fraud identification model, this article studied the relevant factors that affect ...
Shan Jiang, Xiaofeng Liao, Yuming Feng, Zilin Gao, Babatunde Oluwaseun Onasanya   +4 more
doaj   +2 more sources

Enhancing Credit Card Fraud Detection: An Ensemble Machine Learning Approach

Big Data and Cognitive Computing
In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble ...
Abdul Rehman Khalid, Nsikak Owoh, Omair Uthmani, Moses Ashawa, Jude Osamor, John Adejoh   +5 more
doaj   +2 more sources

A Deep Learning Method of Credit Card Fraud Detection Based on Continuous-Coupled Neural Networks

Mathematics
With the widespread use of credit cards in online and offline transactions, credit card fraud has become a significant challenge in the financial sector. The rapid advancement of payment technologies has led to increasingly sophisticated fraud techniques,
Yanxi Wu, Liping Wang, Hongyu Li, Jizhao Liu   +3 more
doaj   +2 more sources

An Intelligent Approach to Credit Card Fraud Detection Using an Optimized Light Gradient Boosting Machine

IEEE Access, 2020
New advances in electronic commerce systems and communication technologies have made the credit card the potentially most popular method of payment for both regular and online purchases; thus, there is significantly increased fraud associated with such ...
Altyeb Altaher Taha, Sharaf Jameel Malebary   +1 more
doaj   +3 more sources

A novel method for detecting credit card fraud problems [PDF]

PLoS One
Credit card fraud is a significant problem that costs billions of dollars annually. Detecting fraudulent transactions is challenging due to the imbalance in class distribution, where the majority of transactions are legitimate.
Du H, Lv L, Wang H, Guo A.
europepmc   +2 more sources

A Neural Network Ensemble With Feature Engineering for Improved Credit Card Fraud Detection

IEEE Access, 2022
Recent advancements in electronic commerce and communication systems have significantly increased the use of credit cards for both online and regular transactions.
Ebenezer Esenogho, Ibomoiye Domor Mienye, Theo G. Swart, Kehinde Aruleba, George Obaido   +4 more
doaj   +3 more sources

A Hybrid Deep Learning Ensemble Model for Credit Card Fraud Detection

IEEE Access
The rising volume of online transactions has concurrently increased the incidence of credit card fraud, presenting severe challenges to financial institutions and consumers alike.
Emmanuel Ileberi, Yanxia Sun
doaj   +2 more sources

Deep Learning for Credit Card Fraud Detection: A Review of Algorithms, Challenges, and Solutions

IEEE Access
Deep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art methods used to analyse and detect complex patterns in ...
Ibomoiye Domor Mienye, Nobert Jere
doaj   +2 more sources

Credit Card Fraud Detection

International Journal of Advanced Research in Science, Communication and Technology, 2022
Now a days online transactions have become an important and necessary part of our lives. Credit card fraud detection is presently the most frequently occurring problem in the present world. This is due to the rise in both online transactions and ecommerce platforms.
null Prof. Radha Shirbhate, null Somnath Borude, null Vishal Hadke, null Sushama Walunjkar, null Shubham Bhujade   +4 more
  +9 more sources

HMOA-GNN: adaptive adversarial GraphSAGE with hierarchical hybrid sampling and metric-optimized graph construction for credit card fraud detection [PDF]

Scientific Reports
Accurate credit card fraud detection is vital for protecting financial systems and reducing economic losses. Graph neural networks (GNNs) have shown strong potential by capturing complex patterns in transaction networks.
Lina Ni, Xuqiang Li, Yuewei Zhou, Hang Qi, Xiaohui Man, Jinquan Zhang   +5 more
doaj   +2 more sources