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A framework for detecting financial statement fraud through multiple data sources

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Open access
Authors
Dillon, Darshan
Hadzic, Maja
Date
2009
Type
Conference Paper

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Citation
Dillon, Darshan and Hadzic, Maja. 2009. A framework for detecting financial statement fraud through multiple data sources, in Okyay Kaynak and Mukesh Mohania (ed), International Conference on Digital Ecosystems and Technology (DEST 2009), Jun 1 2009, pp. 692-696. Istanbul, Turkey: IEEE
Source Title
Proceedings of the international conference on digital ecosystems and technologies (DEST 2009)
Source Conference
International Conference on Digital Ecosystems and Technology (DEST 2009)
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Faculty
Curtin Business School
The Centre for Extended Enterprises and Business Intelligence (CEEBI)
School
Centre for Extended Enterprises and Business Intelligence
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Abstract

This project deals with how to detect fraud and non-compliance in financial statements in the present day in one of the biggest economies in the world, the U.S. Since it is mainly public companies that release detailed financial infor-mation, they are the focus. This project focuses on the top five market sectors where fraud is most common. It focuses on a variety of fraud types, but not on cases of deception that do not constitute fraud. A framework will be proposed which ac-counts for both structured data (the numbers in the balance sheet, income statement and cash flow statement) and unstruc-tured data (the footnotes in these financial statements). It uses ontology-driven data mining techniques to do so.