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Credit Card Fraud Detection Using Machine Learning Techniques [PDF]
, 2022 This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily.
Elhusseny, Nermin Samy +2 more
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Credit Card Fraud Detection System
International Journal for Research in Applied Science and Engineering Technology, 2022 Abstract: In today’s world everything is online which also increases the chances of fraud. There are approximately 36.4 percent fraud related to commercial cards which include credit card, debit card, etc. In 2022 there are 64 million people who uses credit card to initiate the transaction, therefore they are also prone to the card fraud.
Aakash ., Akash Kuma, Ravi Pratap Singh
openaire +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 +4 more
doaj +1 more source
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
core +1 more source
Credit Card Fraud Detection Using Perceptron Training Algorithm and Prevention Using One Time Password. [PDF]
, 2015 In today’s world with evolving technologies and a new mode of shopping through online website, use of credit card has increased day by day. Since the credit card is more prone to fraud than debit card prevention of fraud is an important aspect.
, Prof. Gajanan Bherde, Ashwin Telang, Mehul Bhuva, Harsh Gajra, Ajit Patel
core +2 more sources
IEEE Access, 2021 The advance in technologies such as e-commerce and financial technology (FinTech) applications have sparked an increase in the number of online card transactions that occur on a daily basis.
Emmanuel Ileberi +2 more
doaj +1 more source
Credit Card Fraud: A New Perspective On Tackling An Intransigent Problem [PDF]
, 2011 This article offers a new perspective on battling credit card fraud. It departs from a focus on post factum liability, which characterizes most legal scholarship and federal legislation on credit card fraud and applies corrective mechanisms only after ...
Mana, Jafar +2 more
core +1 more source
International Journal of Finance &Economics, EarlyView.ABSTRACT Big data and financial innovations are vital to enhancing the performance of banking institutions. However, limited evidence exists on the effects of big data applications and financial innovation on bank performance. This study addresses this gap by constructing a theoretical framework linking big data applications and financial innovations ...
Mandella Osei‐Assibey Bonsu +1 more
wiley +1 more source
Neural data mining for credit card fraud detection [PDF]
, 2010 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. +2 more
core
Journal of Organizational Behavior, EarlyView.ABSTRACT In the course of a workday, employees attend to various tasks whose challenge might be equal to, higher than, or lower than employees' present level of capabilities. Moreover, employees encounter these tasks sequentially throughout the day with different levels of prior motivation. Investigating carryover effects in motivation from one task to
Sherry (Qiang) Fu +4 more
wiley +1 more source