@inbook{2d3fa4a740324aaf9fcb8da14f869cda,
title = "Detection and explanation of anomalies in real-time gross settlement systems by lossy data compression",
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",
author = "Ron Triepels and Hennie Daniels and R. Heijmans",
year = "2018",
language = "English",
isbn = "9783319933740",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer Verlag",
pages = "145--161",
editor = "Slimane Hammoudi and Michal Smialek and Olivier Camp and Joaquim Filipe",
booktitle = "Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017)",
address = "Germany",
}