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

Ron Triepels; Hennie Daniels; Ronald Heijmans

doi:10.1007/978-3-319-93375-7_8

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

Ron Triepels, Hennie Daniels, Ronald Heijmans

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

6 Citations (Scopus)

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.

Original language	English
Title of host publication	Enterprise Information Systems
Subtitle of host publication	19th International Conference, ICEIS 2017
Editors	S. Hammoudi, M. Smialek, O. Camp, J. Filipe
Place of Publication	Cham
Publisher	Springer Verlag
Pages	145-161
DOIs	https://doi.org/10.1007/978-3-319-93375-7_8
Publication status	Published - 2018

Publication series

Name	Lecture Notes in Business Information Processing
Volume	321

Keywords

anomaly detection
autoencoders
payment behavior
real-time gross settlement systems

Access to Document

10.1007/978-3-319-93375-7_8

Cite this

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 (pp. 145-161). (Lecture Notes in Business Information Processing; Vol. 321). Springer Verlag. https://doi.org/10.1007/978-3-319-93375-7_8

Triepels, Ron ; Daniels, Hennie ; Heijmans, Ronald. / Detection and explanation of anomalous payment behavior in real-time gross settlement systems. Enterprise Information Systems: 19th International Conference, ICEIS 2017. editor / S. Hammoudi ; M. Smialek ; O. Camp ; J. Filipe. Cham : Springer Verlag, 2018. pp. 145-161 (Lecture Notes in Business Information Processing).

@inproceedings{832057ce2dd3486a9ab30f52e9ace625,

title = "Detection and explanation of anomalous payment behavior in real-time gross settlement systems",

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 Ronald Heijmans",

year = "2018",

doi = "10.1007/978-3-319-93375-7_8",

language = "English",

series = "Lecture Notes in Business Information Processing",

publisher = "Springer Verlag",

pages = "145--161",

editor = "S. Hammoudi and M. Smialek and O. Camp and J. Filipe",

booktitle = "Enterprise Information Systems",

address = "Germany",

}

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

Detection and explanation of anomalous payment behavior in real-time gross settlement systems. / Triepels, Ron; Daniels, Hennie; Heijmans, Ronald.
Enterprise Information Systems: 19th International Conference, ICEIS 2017. ed. / S. Hammoudi; M. Smialek; O. Camp; J. Filipe. Cham: Springer Verlag, 2018. p. 145-161 (Lecture Notes in Business Information Processing; Vol. 321).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Detection and explanation of anomalous payment behavior in real-time gross settlement systems

AU - Triepels, Ron

AU - Daniels, Hennie

AU - Heijmans, Ronald

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - anomaly detection

KW - autoencoders

KW - payment behavior

KW - real-time gross settlement systems

U2 - 10.1007/978-3-319-93375-7_8

DO - 10.1007/978-3-319-93375-7_8

M3 - Conference contribution

T3 - Lecture Notes in Business Information Processing

SP - 145

EP - 161

BT - Enterprise Information Systems

A2 - Hammoudi, S.

A2 - Smialek, M.

A2 - Camp, O.

A2 - Filipe, J.

PB - Springer Verlag

CY - Cham

ER -

Triepels R, Daniels H, Heijmans R. Detection and explanation of anomalous payment behavior in real-time gross settlement systems. In Hammoudi S, Smialek M, Camp O, Filipe J, editors, Enterprise Information Systems: 19th International Conference, ICEIS 2017. Cham: Springer Verlag. 2018. p. 145-161. (Lecture Notes in Business Information Processing). doi: 10.1007/978-3-319-93375-7_8

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

Abstract

Publication series

Keywords

Access to Document

Fingerprint

Cite this