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International Conference on Enterprise Information Systems

ICEIS 2017: Enterprise Information Systems pp 145–161Cite as

Detection and Explanation of Anomalous Payment Behavior in Real-Time Gross Settlement Systems

Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 321)

Abstract

In this paper, we discuss how to apply an autoencoder to detect anomalies in payment data derived from an Real-Time Gross Settlement system. Moreover, we introduce a drill-down procedure to measure the extent to which the inflow or outflow of a particular bank explains an anomaly. Experimental results on real-world payment data show that our method can detect the liquidity problems of a bank when it was subject to a bank run with reasonable accuracy.

Keywords

  • Anomaly detection
  • Autoencoders
  • Payment behavior
  • Real-Time Gross Settlement systems

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Fig. 1.
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Notes

  1. 1.

    Many FMIs settle their positions in an RTGS system.

  2. 2.

    A feature of many RTGS systems is that banks may initiate payments on behalf of other banks. This is known as tiering, see e.g. [1]. Payments settled between indirect participants in the settlement system via the same direct participant are recorded as internal payments of the direct participant.

  3. 3.

    For a more detailed description of TARGET2, see [15, 16].

  4. 4.

    The extent to which banks actively participated in the settlement system was based on the number of payments that they initiated each month.

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Acknowledgements

We would like to thank Ron Berndsen and Richard Heuver for their helpful suggestions and feedback.

Author information

Authors and Affiliations

  1. Tilburg University, Warandelaan 2, Tilburg, The Netherlands

    Ron Triepels & Hennie Daniels

  2. De Nederlandsche Bank, Westeinde 1, Amsterdam, The Netherlands

    Ron Triepels & Ronald Heijmans

  3. Erasmus University, Burg. Oudlaan 50, Rotterdam, The Netherlands

    Hennie Daniels

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  1. Ron Triepels
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Correspondence to Ron Triepels .

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Editors and Affiliations

  1. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. MODESTE/ESEO, Angers, France

    Olivier Camp

  4. INSTICC, Polytechnic Institute of Setúbal, Setúbal, Poland

    Joaquim Filipe

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Triepels, R., Daniels, H., Heijmans, R. (2018). Detection and Explanation of Anomalous Payment Behavior in Real-Time Gross Settlement Systems. In: Hammoudi, S., Śmiałek, M., Camp, O., Filipe, J. (eds) Enterprise Information Systems. ICEIS 2017. Lecture Notes in Business Information Processing, vol 321. Springer, Cham. https://doi.org/10.1007/978-3-319-93375-7_8

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