Results 31 to 40 of about 34,803 (186)
IMPROVING CREDIT CARD FRAUD DETECTION USING TRANSFER LEARNING AND DATA RESAMPLING TECHNIQUES [PDF]
, 2023 This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or
Vinarta, Charmaine Eunice Mena
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Explainable Credit Card Fraud Detection with Image Conversion
Advances in Distributed Computing and Artificial Intelligence Journal, 2021 The increase in the volume and velocity of credit card transactions causes class imbalance and concept deviation problems in data sets where credit card fraud is detected. These problems make it very difficult for traditional approaches to produce robust
duygu sinanc +2 more
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[CREDIT CARD FRAUD DETECTION SYSTEM]
International Journal for Modern Trends in Science and Technology, 2020 It is essential that Visa organizations can distinguish false Mastercard exchanges so clients are not charged for things that they didn't buy. Such issues can be handled with Data Science and its significance, alongside Machine Learning, couldn't be more important.
Mittal, Pragya +3 more
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UHD Journal of Science and Technology, 2017 Due to the ascent and fast development of E-commerce, utilization of credit cards for online buys has significantly expanded, and it brought about a blast in the credit card fraud.
Ardalan Husin Awlla
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Bayesian Quickest Detection of Credit Card Fraud [PDF]
Bayesian Analysis, 2022 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Buonaguidi, Bruno +3 more
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The modus operandi of perpetrators for credit card fraud in the Vaal Region, South Africa
Cogent Social Sciences, 2021 Card payments in South Africa continue to be a predominant part of the National Payments System in an evolving payments ecosystem. Due to the growing volume of electronic payments, the monetary strain of credit card fraud is turning into a substantial ...
Witness Maluleke +3 more
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An Adversary Model of Fraudsters’ Behavior to Improve Oversampling in Credit Card Fraud Detection
IEEE Access, 2023 Imbalanced learning jeopardizes the accuracy of traditional classification models, particularly for what concerns the minority class, which is often the class of interest.
Daniele Lunghi +3 more
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Multiple perspectives HMM-based feature engineering for credit card fraud detection
, 2019 Machine learning and data mining techniques have been used extensively in order to detect credit card frauds. However, most studies consider credit card transactions as isolated events and not as a sequence of transactions.
Caelen, Olivier +6 more
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IEEE AccessCurrently, the continuous expansion of the credit card business and the increasingly fierce competition have made all kinds of fraud risks in the overall credit card business the biggest threat.
Zhichao Xie, Xuan Huang
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An Empirical Study of AML Approach for Credit Card Fraud Detection—Financial Transactions [PDF]
, 2020 Credit card fraud is one of the flip sides of the digital world, where transactions are made without the knowledge of the genuine user. Based on the study of various papers published between 1994 and 2018 on credit card fraud, the following objectives ...
Jain, Anurag, Singh, Ajeet
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