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Fraud detection wit...
Fraud detection with natural language processing
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- Boulieris, Petros (author)
- Athens University of Economics and Business, Athens, Greece
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- Pavlopoulos, John (author)
- Stockholms universitet,Institutionen för data- och systemvetenskap,University of Economics and Business, Athens, Greece
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- Xenos, Alexandros (author)
- Athens University of Economics and Business, Athens, Greece
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- Vassalos, Vasilis (author)
- Athens University of Economics and Business, Athens, Greece
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(creator_code:org_t)
- 2023
- 2023
- English.
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In: Machine Learning. - 0885-6125 .- 1573-0565.
- Related links:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Automated fraud detection can assist organisations to safeguard user accounts, a task that is very challenging due to the great sparsity of known fraud transactions. Many approaches in the literature focus on credit card fraud and ignore the growing field of online banking. However, there is a lack of publicly available data for both. The lack of publicly available data hinders the progress of the field and limits the investigation of potential solutions. With this work, we: (a) introduce FraudNLP, the first anonymised, publicly available dataset for online fraud detection, (b) benchmark machine and deep learning methods with multiple evaluation measures, (c) argue that online actions do follow rules similar to natural language and hence can be approached successfully by natural language processing methods.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- Fraud detection
- Natural language processing
- E-banking
- Feature engineering
- Varying class imbalance
Publication and Content Type
- ref (subject category)
- art (subject category)
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