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Temporal Network Analytics for Fraud Detection in the Banking Sector

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ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium (TPDL 2020, ADBIS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1260))

Abstract

A new methodology in temporal networks is presented for the use of fraud detection systems in the banking sector. Standard approaches of fraudulence monitoring mainly have the focus on the individual client data. Our approach will concentrate on the hidden data produced by the network of the transaction database. The methodology is based on a cycle detection method with the help of which important patterns can be identified as shown by the test on real data. Our solution is integrated into a financial fraud system of a bank; the experimental results are demonstrated by a real-world case study.

The Authors gratefully acknowledge the European Commission for funding the InnoRenew CoE project (Grant Agreement 739574) under the Horizon2020 Widespread-Teaming program, and the Republic of Slovenia (Investment funding of the Republic of Slovenia and the European Union of the European Regional Development Fund).

L. Hajdu—Supported by the project ”Integrated program for training new generation of scientists in the elds of computer science”, no EFOP-3.6.3- VEKOP-16-2017-0002 (supported by the European Union and co-funded by the European Social Fund).

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Authors and Affiliations

  1. Innorenew CoE, Livade 6, 6310, Izola, Slovenia

    László Hajdu & Miklós Krész

  2. University of Primorska, 6000, Koper, Slovenia

    László Hajdu & Miklós Krész

  3. University of Szeged, Szeged, 6720, Hungary

    László Hajdu & Miklós Krész

Authors
  1. László Hajdu
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  2. Miklós Krész
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Corresponding author

Correspondence to László Hajdu .

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Editors and Affiliations

  1. ISAE-ENSMA, Poitiers, France

    Ladjel Bellatreche

  2. Slovak University of Technology, Bratislava, Slovakia

    Mária Bieliková

  3. Université Lumière Lyon 2, Lyon, France

    Omar Boussaïd

  4. University of Genova, Genova, Italy

    Barbara Catania

  5. Université Lumière Lyon 2, Lyon, France

    Jérôme Darmont

  6. Leibniz University of Hannover, Hannover, Niedersachsen, Germany

    Elena Demidova

  7. Université Claude Bernard Lyon 1, Lyon, France

    Fabien Duchateau

  8. The Open University, Milton Keynes, UK

    Mark Hall

  9. University of Ljubljana, Ljubljana, Slovenia

    Tanja Merčun

  10. National Research University Higher School of Economics, St. Petersburg, Russia

    Boris Novikov

  11. Ionian University, Corfu, Greece

    Christos Papatheodorou

  12. Goethe University Frankfurt, Frankfurt am Main, Hessen, Germany

    Thomas Risse

  13. Universitat Politècnica de Catalunya, Barcelona, Spain

    Oscar Romero

  14. AgroParisTech, Montpellier, France

    Lucile Sautot

  15. University of Lyon, Lyon, France

    Guilaine Talens

  16. Poznań University of Technology, Poznań, Poland

    Robert Wrembel

  17. University of Ljubljana, Ljubljana, Slovenia

    Maja Žumer

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Hajdu, L., Krész, M. (2020). Temporal Network Analytics for Fraud Detection in the Banking Sector. In: Bellatreche, L., et al. ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium. TPDL ADBIS 2020 2020. Communications in Computer and Information Science, vol 1260. Springer, Cham. https://doi.org/10.1007/978-3-030-55814-7_12

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  • DOI: https://doi.org/10.1007/978-3-030-55814-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-55813-0

  • Online ISBN: 978-3-030-55814-7

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