Results 81 to 90 of about 3,889 (172)

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   +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

Banks can’t fight online credit card fraud alone, and neither can you

, 2017
Online credit card fraud is on the rise in Australia, but pointing the finger at any one group won’t help. It’s an ecosystem problem: from the popularity of online shopping, to the insecure sites that process our transactions, and the banks themselves ...
Cross, Cassandra
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Robust Credit Card Fraud Detection Based on Efficient Kolmogorov-Arnold Network Models

IEEE Access
Credit card fraud detection remains a significant challenge in the financial industry, necessitating advanced models to identify fraudulent activities while minimizing false positives accurately.
Thi-Thu-Huong Le, Yeonjeong Hwang, Hyoeun Kang, Howon Kim   +3 more
doaj   +1 more source

Enhanced stacking classifiers system for credit card fraud detection

, 2022
Credit cards have been an option for payment method by many people nowadays. Despite that, without handling the usage of credit cards carefully, it may lead to undesirable incidents such as credit card fraud activities.
Ishak, Nur Amirah
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Credit Card Fraud Detection Predictive Modeling [PDF]

, 2020
Finance fraud is a growing problem with consequences in the financial industry and data mining has been successfully applied to huge volume of complex financial datasets to automate and analyze credit card frauds in online transactions.
Sharma, Nishant
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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 Fraud Detection Model Based on Machine Learning [PDF]

ITM Web of Conferences
Credit card fraud can be defined as a situation in which an individual uses another person's credit card for an unauthorized transaction and neither the cardholder nor the card issuer is aware of the action.
Jia Feiran
doaj   +1 more source

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   +1 more source

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
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