Fraud detection with natural language processing

Boulieris, Petros (author): Athens University of Economics and Business, Athens, Greece

Pavlopoulos, John (author): Stockholms universitet,Institutionen för data- och systemvetenskap,University of Economics and Business, Athens, Greece

Xenos, Alexandros (author): Athens University of Economics and Business, Athens, Greece

Vassalos, Vasilis (author): Athens University of Economics and Business, Athens, Greece

(creator_code:org_t)

Related links:: https://doi.org/10.1...; show more...; https://urn.kb.se/re...; https://doi.org/10.1...; show less...

Abstract Subject headings

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.

By the author/editor: Boulieris, Petro ...; Pavlopoulos, Joh ...; Xenos, Alexandro ...; Vassalos, Vasili ...

About the subject

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.