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Simulation of Bank Transaction Data

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Multi-Agent-Based Simulation XIX (MABS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11463))

Abstract

When working with data such as financial transactions or user activity logs, in domains with inherent privacy concerns, you will certainly run into problems with data protection and data availability. Among possible approaches to cope with these problems are data anonymization and data simulation. One of essential advantages in favor of data simulation is complete separation from subject identification.

In this paper, we present a multi-agent simulation framework applicable in financial domain for transaction data generation. We use the framework to create multiple simulation scenarios reproducing typical fraudulent behavioral patterns and we evaluate its applicability on the task of Anti Money Laundering (AML) by classification of fraudulent agents.

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Notes

  1. 1.

    https://chriswhong.com/open-data/foil_nyc_taxi/.

  2. 2.

    https://www.ffiec.gov/bsa_aml_infobase/pages_misc/red.htm.

  3. 3.

    https://github.com/projectmesa/mesa/.

  4. 4.

    https://www.ffiec.gov/bsa_aml_infobase/pages_misc/red.htm.

  5. 5.

    https://www.census.gov/topics/population/genealogy.html.

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Acknowledgement

This work was partially supported by CEAI Slovakia, Scientific Grant Agency of the Slovak Republic, grants No. VG 1/0646/15 and VG 1/0667/18 and Slovak Research and Development Agency under the contract No. APVV-15-0508.

Author information

Authors and Affiliations

  1. Faculty of Informatics and Information Technologies, Slovak University of Technology in Bratislava, Ilkovičova 2, 842 16, Bratislava, Slovakia

    Martin Mocko & Jakub Ševcech

Authors
  1. Martin Mocko
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  2. Jakub Ševcech
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Corresponding author

Correspondence to Jakub Ševcech .

Editor information

Editors and Affiliations

  1. Malmö University, Malmö, Sweden

    Paul Davidsson

  2. Stockholm University, Kista, Sweden

    Harko Verhagen

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Mocko, M., Ševcech, J. (2019). Simulation of Bank Transaction Data. In: Davidsson, P., Verhagen, H. (eds) Multi-Agent-Based Simulation XIX. MABS 2018. Lecture Notes in Computer Science(), vol 11463. Springer, Cham. https://doi.org/10.1007/978-3-030-22270-3_8

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  • DOI: https://doi.org/10.1007/978-3-030-22270-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22269-7

  • Online ISBN: 978-3-030-22270-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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