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Detection and explanation of anomalous payment behavior in real-time gross settlement systems

Triepels,Ron
; 
Daniels,Hennie
; 
Heijmans,Ronald
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.
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Date
2018
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Publisher
Springer Verlag
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Tilburg University Research Output Collection
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Keywords
anomaly detection, autoencoders, payment behavior, real-time gross settlement systems
Citation
Triepels, R, Daniels, H & Heijmans, R 2018, Detection and explanation of anomalous payment behavior in real-time gross settlement systems. in S Hammoudi, M Smialek, O Camp & J Filipe (eds), Enterprise Information Systems : 19th International Conference, ICEIS 2017. Lecture Notes in Business Information Processing, vol. 321, Springer Verlag, Cham, pp. 145-161. https://doi.org/10.1007/978-3-319-93375-7_8
URI
https://hdl.handle.net/20.500.14602/22543
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