Results 81 to 90 of about 2,431 (186)

Quantum Autoencoder for Enhanced Fraud Detection in Imbalanced Credit Card Dataset

IEEE Access
Credit card fraud detection is crucial for financial security which entails identifying unauthorized transactions that can result in significant financial losses.
Chansreynich Huot, Sovanmonynuth Heng, Tae-Kyung Kim, Youngsun Han   +3 more
doaj   +1 more source

“Feeling out of place”: A mixed methods investigation of the impostor phenomenon among BIPOC and LGBTQ STEM college students

Analyses of Social Issues and Public Policy, Volume 26, Issue 2, August 2026.
Abstract This mixed‐methods study examines the experience of the impostor phenomenon in a racially/ethnically and sexually diverse sample of undergraduates in majors related to science, technology, engineering, and math (STEM). Guided by an intersectionality framework, we examined whether experiences of the impostor phenomenon differ at the ...
Richard Chang, Diana R. Beltran, Gloria Wong‐Padoongpatt, Rachael D. Robnett   +3 more
wiley   +1 more source

A Hybrid Deep Learning Approach with Generative Adversarial Network for Credit Card Fraud Detection

Technologies
Credit card fraud detection is a critical challenge in the financial industry, with substantial economic implications. Conventional machine learning (ML) techniques often fail to adapt to evolving fraud patterns and underperform with imbalanced datasets.
Ibomoiye Domor Mienye, Theo G. Swart
doaj   +1 more source

Credit Card Fraud Detection using TabNet

, 2023
The adopting of cashless payment methods, such as credit card payments and online transactions, has significantly enhanced the payment experience and added convenience to our daily lives.
Lim, Kian Ming, Lim, Jit Yan, Meng, Chew Chee, Lee, Chin Poo   +3 more
core   +1 more source

Literature Review of Credit Card Fraud Detection with Machine Learning [PDF]

, 2023
This thesis presents a comprehensive examination of the field of credit card fraud detection, aiming to offer a thorough understanding of its evolution and nuances.
Rodríguez Vaquero, Patricia
core  

Credit card fraud detection by adaptive neural data mining

, 1999
The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is ...
Brause, Rüdiger W., Hepp, Hans-Michael, Langsdorf, Timm Sebastian   +2 more
core  

Credit Card Transactions Fraud Detection, and Machine Learning: Modelling Time with LSTM Recurrent Neural Networks

, 2007
>Magister Scientiae - MScIn recent years, topics such as fraud detection and fraud prevention have received a lot of attention on the research front, in particular from plastic card issuers.
Wiese, Benard Jacobus
core  

Credit Card Fraud Using Adversarial Attacks

, 2022
Banks lose billions to fraudulent activities every year, affecting their revenue and customers. The most common type of financial fraud is Credit Card Fraud. The key challenge in designing a model for credit card fraud detection is its maintenance. It is
Lakshmi Babu Saheer (16661823), Mahdi Maktab Dar Oghaz (16664745), Hafya Ullah (16666995), Aysha Thahsin Zahir Ismail (16666998)   +3 more
core   +1 more source

Credit Card Fraud Detection by Nearest Neighbor Algorithms [PDF]

, 2023
As the usage of internet banking and online purchases have increased dramatically in today’s world, the risk of fraudulent activities and the number of fraud cases are increasing day by day.
Maghsood, Ramin
core  

Adaptive Model for Credit Card Fraud Detection

, 2020
While the flow of banking transactions is increasing, the risk of credit card fraud is becoming greater particularly with the technological revolution that we know, fraudulent are improve and always find new methods to deal with the preventive measures ...
Benabbou, Faouzia, Sael, Naoual, Sadgali, Imane   +2 more
core