On an ant colony-based approach for business fraud detection

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationEmerging Intelligent Computing Technology and Applications
Subtitle of host publication5th International Conference on Intelligent Computing, ICIC 2009, Proceedings
PublisherSpringer Verlag
Pages1104-1111
Volume5754 LNCS
ISBN (Print)3642040691, 9783642040696
Publication statusPublished - 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5754 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title5th International Conference on Intelligent Computing, ICIC 2009
PlaceKorea, Republic of
CityUlsan
Period16 - 19 September 2009

Abstract

Nowadays we witness an increasing number of business frauds. To protect investors' interest, a financial firm should possess an effective means to detect such frauds. In this regard, artificial neural networks (ANNs) are widely used for fraud detection. Traditional back-propagation-based algorithms used for training an ANN, however, exhibit the local optima problem, thus reducing the effectiveness of an ANN in detecting frauds. To alleviate the problem, this paper proposes an approach to training an ANN using an ant colony optimization technique, through which the local optima problem can be solved and the effectiveness of an ANN in fraud detection can be improved. Based on our approach, an associated prototype system is designed and implemented, and an exploratory study is performed. The results of the study are encouraging, showing the viability of our proposed approach. © 2009 Springer Berlin Heidelberg.

Research Area(s)

  • Ant colony optimization, Artificial neural network, Fraud detection

Citation Format(s)

On an ant colony-based approach for business fraud detection. / Liu, Ou; Ma, Jian; Poon, Pak-Lok; Zhang, Jun.

Emerging Intelligent Computing Technology and Applications: 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings. Vol. 5754 LNCS Springer Verlag, 2009. p. 1104-1111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5754 LNCS).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review