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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 <jats:italic>FraudNLP<\/jats:italic>, 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.<\/jats:p>","DOI":"10.1007\/s10994-023-06354-5","type":"journal-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T18:03:06Z","timestamp":1689789786000},"page":"5087-5108","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Fraud detection with natural language processing"],"prefix":"10.1007","volume":"113","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8531-103X","authenticated-orcid":false,"given":"Petros","family":"Boulieris","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Pavlopoulos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandros","family":"Xenos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vasilis","family":"Vassalos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,7,19]]},"reference":[{"key":"6354_CR1","doi-asserted-by":"crossref","unstructured":"Achituve, I., Kraus, S., & Goldberger, J. 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