Results 91 to 100 of about 2,431 (186)

FinFD-GCN: Using Graph Convolutional Networks for Fraud Detection in Financial Data [PDF]

Journal of Artificial Intelligence and Data Mining
In recent years, new technologies have brought new innovations into the financial and commercial world, giving fraudsters many ways to commit fraud and cost companies big time.
Mohamad Mahdi Yadegar, Hossein Rahmani
doaj   +1 more source

Geo-location based credit card fraud detection

, 2018
The use of credit card is prevalent, and will continuously increase. Although EMV (Europay, MasterCard, and Visa) chips is one such alternative to prevent credit card fraud, experts predict that credit card fraud will continue to rise in numbers ...
Lee, Boon Peng
core  

Credit Card Fraud Detection Using Symbolic Aggregate Approximation

In the current digital age, credit card fraud is a cybercrime that costs billions of dollars every year through fraudulent transactions. This study aims to identify fraudulent credit card transactions using Symbolic Aggregate Approximation (SAX) and ...
Araya, Feven B., Zerea, Snit D., Ikuesan, Richard A., Woldemichael, Belsabel T.   +3 more
core   +1 more source

Uncertainty-aware credit card fraud detection using deep learning

, 2023
Uncertainty-aware credit card fraud detection using deep ...
M Habibpour (15427904), AR Tajally (15427910), M Mehdipour (7709255), H Asgharnezhad (13391376), S Nahavandi (13392411), Abbas Khosravi (13078944), H Gharoun (15427907), A Shamsi (13391379)   +7 more
core  

Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention

IEEE Access
Under the umbrella of artificial intelligence (AI), deep learning enables systems to cluster data and provide incredibly accurate results. This study explores deep learning for fraud detection, utilizing Graph Neural Networks (GNNs) and Autoencoders to ...
Fawaz Khaled Alarfaj, Shabnam Shahzadi
doaj   +1 more source

Hybrid Undersampling and Oversampling for Handling Imbalanced Credit Card Data

IEEE Access
Recent developments in the use of credit cards for a range of daily life activities have increased credit card fraud and caused huge financial losses for individuals and financial institutions. Most credit card frauds are conducted online through illegal
Maram Alamri, Mourad Ykhlef
doaj   +1 more source

A discrete choice approach to model credit card fraud

This paper analyses the demographic, socio-economics and banking specific determinants that influence the risk of fraud in a portfolio of credit cards. The data are from recent account archives for cards issued throughout Italy.
Paba, Antonello, Pulina, Manuela
core  

Credit Card Fraud Detection: An Improved Strategy for High Recall Using KNN, LDA, and Linear Regression. [PDF]

Sensors (Basel), 2023
Chung J, Lee K.
europepmc   +1 more source

Comparison of Classification Algorithms used in Credit Card Fraud Detection

, 2019
is one of the major ethical issues in the credit card industry. Various techniques are used to restrict these types of credit card frauds. Firstly, to detect the various types of credit card fraud, and, secondly, to review alternative techniques that ...
Kumar Shrivastava , Ankit, Kishore , Brij   +1 more
core  

Detecting Imbalanced Credit Card Fraud via Hybrid Graph Attention and Variational Autoencoder Ensembles

AppliedMath
Credit card fraud detection remains a major challenge due to severe class imbalance and the constantly evolving nature of fraudulent behaviors. To address these challenges, this paper proposes a hybrid framework that integrates a Variational Autoencoder (
Ibomoiye Domor Mienye, Ebenezer Esenogho, Cameron Modisane   +2 more
doaj   +1 more source