Mining financial statement fraud: An analysis of some experimental issues

Maumita Bhattacharya; Jarrod West

doi:10.1109/ICIEA.2015.7334157

Mining financial statement fraud: An analysis of some experimental issues

Maumita Bhattacharya, Jarrod West

Research output: Book chapter/Published conference paper › Conference paper › peer-review

4 Citations (Scopus)

Abstract

Financial statement fraud detection is an important problem with a number of design aspects to consider. Issues such as (i) problem representation, (ii) feature selection, and (iii) choice of performance metrics all influence the perceived performance of detection algorithms. Efficient implementation of financial fraud detection methods relies on a clear understanding of these issues. In this paper we present an analysis of the three key experimental issues associated with financial statement fraud detection, critiquing the prevailing ideas and providing new understandings.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	461-466
Number of pages	6
ISBN (Electronic)	9781467373173
DOIs	https://doi.org/10.1109/ICIEA.2015.7334157
Publication status	Published - 2015
Event	IEEE Conference on Industrial Electronics and Applications - Crowne Plaza, Auckland, New Zealand Duration: 15 Jun 2015 → 17 Jun 2015 http://www.ieeeiciea.org/2015/

Conference

Conference	IEEE Conference on Industrial Electronics and Applications
Country/Territory	New Zealand
City	Auckland
Period	15/06/15 → 17/06/15
Internet address	http://www.ieeeiciea.org/2015/

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10.1109/ICIEA.2015.7334157

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title = "Mining financial statement fraud: An analysis of some experimental issues",

abstract = "Financial statement fraud detection is an important problem with a number of design aspects to consider. Issues such as (i) problem representation, (ii) feature selection, and (iii) choice of performance metrics all influence the perceived performance of detection algorithms. Efficient implementation of financial fraud detection methods relies on a clear understanding of these issues. In this paper we present an analysis of the three key experimental issues associated with financial statement fraud detection, critiquing the prevailing ideas and providing new understandings.",

author = "Maumita Bhattacharya and Jarrod West",

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year = "2015",

doi = "10.1109/ICIEA.2015.7334157",

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booktitle = "Proceedings of the 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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Bhattacharya, M & West, J 2015, Mining financial statement fraud: An analysis of some experimental issues. in Proceedings of the 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)., 7334157, IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 461-466, IEEE Conference on Industrial Electronics and Applications, Auckland, New Zealand, 15/06/15. https://doi.org/10.1109/ICIEA.2015.7334157

Mining financial statement fraud: An analysis of some experimental issues. / Bhattacharya, Maumita; West, Jarrod.
Proceedings of the 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA). United States: IEEE, Institute of Electrical and Electronics Engineers, 2015. p. 461-466 7334157.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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AB - Financial statement fraud detection is an important problem with a number of design aspects to consider. Issues such as (i) problem representation, (ii) feature selection, and (iii) choice of performance metrics all influence the perceived performance of detection algorithms. Efficient implementation of financial fraud detection methods relies on a clear understanding of these issues. In this paper we present an analysis of the three key experimental issues associated with financial statement fraud detection, critiquing the prevailing ideas and providing new understandings.

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M3 - Conference paper

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PB - IEEE, Institute of Electrical and Electronics Engineers

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Mining financial statement fraud: An analysis of some experimental issues

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