Abstract
The scale of financial sector crime today makes the detection of anomalous financial flows into, out of and within, a nation one of the most important functions of modern government. The analysis necessary for detection of such criminal activity depends on the existence of a central IT infrastructure capable of maintaining historical transaction records and capable of enabling the application of advanced analysis techniques to large data volumes.
We describe a software tool developed to aid the rapid, error-free transformation of data held in aggregated transaction history databases into matrices for analysis by fraud detection experts. We also present some initial results of performance characterisation studies which will provide the basis for guidelines on how transformations can be tuned to make best use of underlying parallel database systems.
This is a preview of subscription content, log in via an institution.
Preview
Unable to display preview. Download preview PDF.
References
Italian Law. Legge 5/7/1991 n. 197
See for example the latest SQL standard (SQL-92) published by ANSI as ANSI X3.135-1992, “Database Language SQL” and by ISO as ISO/IEC 9075:1992, “Database Language SQL”
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Allen, P. et al. (1996). Interactive anomaly detection in large transaction history databases. In: Liddell, H., Colbrook, A., Hertzberger, B., Sloot, P. (eds) High-Performance Computing and Networking. HPCN-Europe 1996. Lecture Notes in Computer Science, vol 1067. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61142-8_540
Download citation
DOI: https://doi.org/10.1007/3-540-61142-8_540
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61142-4
Online ISBN: 978-3-540-49955-8
eBook Packages: Springer Book Archive