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

  • Ron TriepelsEmail author
  • Hennie Daniels
  • Ronald Heijmans
Conference paper
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 

Notes

Acknowledgements

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

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Ron Triepels
    • 1
    • 2
    Email author
  • Hennie Daniels
    • 1
    • 3
  • Ronald Heijmans
    • 2
  1. 1.Tilburg UniversityTilburgThe Netherlands
  2. 2.De Nederlandsche BankAmsterdamThe Netherlands
  3. 3.Erasmus UniversityRotterdamThe Netherlands

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