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Fraud Detection in Payments Transactions: Overview of Existing Approaches and Usage for Instant Payments
University of Rostock, Rostock, Germany; ITMO University, St. Petersburg, Russia.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics. University of Rostock, Rostock, Germany; ITMO University, St. Petersburg, Russia.ORCID iD: 0000-0002-7431-8412
ITMO University, St. Petersburg, Russia.
2019 (English)In: Complex Systems Informatics and Modeling Quarterly, E-ISSN 2255-9922, Vol. 20, p. 72-88Article in journal (Refereed) Published
Abstract [en]

Financial industries are undergoing a digital transformation of their products, services, overall business models. Part of this digitalization in banking aims at automating most of the manual work in payment handling and integrating the workflows of involved service providers. The focus of the work presented in this paper is on fraud discovery and steps to fully automate it. Fraud discovery in financial transactions has become an important priority for banks. Fraud is increasing significantly with the expansion of modern technology and global communication, which results in substantial damages for the banks. Instant payment (IP) transactions cause new challenges for fraud detection due to the requirement of short processing time. The paper investigates the possibility to use artificial intelligence in IP fraud detection. The main contributions of our work are (a) an analysis of problem relevance from business and literature perspective, (b) a proposal for technological support for using AI in fraud detection of instant payment transactions, and (c) a feasibility study of selected fraud detection approaches.

Place, publisher, year, edition, pages
Riga Technical University , 2019. Vol. 20, p. 72-88
Keywords [en]
Artificial Intelligence; Enterprise Modeling; Digital Transformation; Instant Payment
National Category
Information Systems
Identifiers
URN: urn:nbn:se:hj:diva-47495DOI: 10.7250/csimq.2019-20.04Local ID: POA;;1388203OAI: oai:DiVA.org:hj-47495DiVA, id: diva2:1388203
Available from: 2020-01-23 Created: 2020-01-23 Last updated: 2022-04-01Bibliographically approved

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Sandkuhl, Kurt

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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