Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/14280
Author(s): | Trigueiros, D. Sam, C. |
Date: | 2016 |
Title: | A software application to streamline and enhance the detection of fraud in published financial statements of companies |
Volume: | 9 |
Number: | 1-2 |
Pages: | 95 - 106 |
ISSN: | 1942-2628 |
Keywords: | Fraud detection Financial knowledge discovery Predictive modelling of financial statements Type of information mining |
Abstract: | Considerable effort has been devoted to the development of software to support the detection of fraud in published financial statements of companies. Until the present date, however, the applied use of such research has been extremely limited due to the “black box” character of the existing solutions and the cumbersome input task they require. The application described in this paper solves both problems while significantly improving performance. It is based on Webmining and on the use of three Multilayer Perceptron where a modified learning method leads to the formation of meaningful internal representations. Such representations are then input to a features’ map where trajectories towards or away from fraud and other financial attributes are identified. The result is a Web-based, self-explanatory, financial statements’ fraud detection solution. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | CTI-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Files in This Item:
File | Description | Size | Format | |
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A software application to streamline and enhance the detection of fraud in published financial statements of companies.pdf | Versão Editora | 1,33 MB | Adobe PDF | View/Open |
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