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

RJMA (Ron Johannes Matheus Antonius) Triepels, Hennie Daniels, R Heijmans

Research output: Chapter/Conference proceedingChapterAcademic

2 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 languageEnglish
Title of host publicationLecture Notes in Business Information Processing
Place of PublicationCham
PublisherSpringer-Verlag
Pages145-161
Number of pages17
DOIs
Publication statusPublished - 2018

Fingerprint

Dive into the research topics of 'Detection and Explanation of Anomalous Payment Behaviour in Real-Time Gross Settlement Systems'. Together they form a unique fingerprint.

Cite this