Online payment fraud: from anomaly detection to risk management
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Language: | English |
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Springer
2023
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Online Access: | https://link.springer.com/article/10.1186/s40854-023-00470-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/7852 |
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oai:localhost:PNK-78522023-04-12T09:29:11Z Online payment fraud: from anomaly detection to risk management Paolo, Vanini Sebastiano, Rossi Ermin, Zvizdic Online banking fraud individual’s online bank account CC BY Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account. Successfully preventing this requires the detection of as many fraudsters as possible, without producing too many false alarms. This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud. In addition, classical machine learning methods must be extended, minimizing expected financial losses. Finally, fraud can only be combated systematically and economically if the risks and costs in payment channels are known. 2023-04-12T09:29:11Z 2023-04-12T09:29:11Z 2023 Book https://link.springer.com/article/10.1186/s40854-023-00470-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/7852 en application/pdf Springer |
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Digital Phenikaa |
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Digital Phenikaa |
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English |
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Online banking fraud individual’s online bank account |
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Online banking fraud individual’s online bank account Paolo, Vanini Sebastiano, Rossi Ermin, Zvizdic Online payment fraud: from anomaly detection to risk management |
description |
CC BY |
format |
Book |
author |
Paolo, Vanini Sebastiano, Rossi Ermin, Zvizdic |
author_facet |
Paolo, Vanini Sebastiano, Rossi Ermin, Zvizdic |
author_sort |
Paolo, Vanini |
title |
Online payment fraud: from anomaly detection to risk management |
title_short |
Online payment fraud: from anomaly detection to risk management |
title_full |
Online payment fraud: from anomaly detection to risk management |
title_fullStr |
Online payment fraud: from anomaly detection to risk management |
title_full_unstemmed |
Online payment fraud: from anomaly detection to risk management |
title_sort |
online payment fraud: from anomaly detection to risk management |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1186/s40854-023-00470-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/7852 |
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