Predicting fraud in mobile money transfer using case-based reasoning

Conference paper


Adedoyin, A., Kapetanakis, S., Samakovitis, G. and Petridis, M. 2017. Predicting fraud in mobile money transfer using case-based reasoning. SGAI 2017: International Conference on Innovative Techniques and Applications of Artificial Intelligence. Cambridge, United Kingdom 12 - 14 Dec 2017 Springer. https://doi.org/10.1007/978-3-319-71078-5_28
TypeConference paper
TitlePredicting fraud in mobile money transfer using case-based reasoning
AuthorsAdedoyin, A., Kapetanakis, S., Samakovitis, G. and Petridis, M.
Abstract

This paper proposes an improved CBR approach for the identification of money transfer fraud in Mobile Money Transfer (MMT) environments. Standard CBR capability is augmented by machine learning techniques to assign parameter weights in the sample dataset and automate k-value random selection in k-NN classification to improve CBR performance. The CBR system observes users’ transaction behaviour within the MMT service and tries to detect abnormal patterns in the transaction flows. To capture user behaviour effectively, the CBR system classifies the log information into five contexts and then combines them into a single dimension, instead of using the conventional approach where the transaction amount, time dimensions or features dimension are used individually. The applicability of the proposed augmented CBR system is evaluated using simulation data. From the results, both dimensions show good performance with the context of information weighted CBR system outperforming the individual features approach.

Research GroupArtificial Intelligence group
LanguageEnglish
ConferenceSGAI 2017: International Conference on Innovative Techniques and Applications of Artificial Intelligence
Proceedings TitleArtificial Intelligence XXXIV. SGAI 2017
ISSN0302-9743
ISBN
Hardcover9783319710778
Electronic9783319710785
PublisherSpringer
Publication dates
Online21 Nov 2017
PrintDec 2017
Publication process dates
Deposited06 Mar 2018
Accepted31 Aug 2017
Output statusPublished
Accepted author manuscript
Copyright Statement

This is a Author Accepted Manuscript version of an paper published in Artificial Intelligence XXXIV. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-71078-5_28

Additional information

Published as: Adedoyin A., Kapetanakis S., Samakovitis G., Petridis M. (2017) Predicting Fraud in Mobile Money Transfer Using Case-Based Reasoning. In: Bramer M., Petridis M. (eds) Artificial Intelligence XXXIV. SGAI 2017. Lecture Notes in Computer Science, vol 10630. Springer, Cham

Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-71078-5_28
Book titleArtificial Intelligence XXXIV: 37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings
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