A brief review of recent research trends on applications of computational and statistical techniques in financial and business intelligence

Bhattacharya, Sukanto and Kumar, Kuldeep 2010, A brief review of recent research trends on applications of computational and statistical techniques in financial and business intelligence, in BIDW 2010 : Proceedings from the Business Intelligence and Data Warehousing conference, Global Science and Technology Forum, [Singapore], pp. 30-37.

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Title A brief review of recent research trends on applications of computational and statistical techniques in financial and business intelligence
Author(s) Bhattacharya, Sukanto
Kumar, Kuldeep
Conference name Business Intelligence and Data Warehousing conference (1st : 2010 : Singapore)
Conference location Singapore
Conference dates 12-13 Jul. 2010
Title of proceedings BIDW 2010 : Proceedings from the Business Intelligence and Data Warehousing conference
Editor(s) Kumar, Kuldeep
Publication date 2010
Conference series Business Intelligence and Data Warehousing conference
Start page 30
End page 37
Total pages 8
Publisher Global Science and Technology Forum
Place of publication [Singapore]
Summary Artificial neural networks and statistical techniques like decision trees, discriminant analysis, logistic regression and survival analysis play a crucial role in Business Intelligence. These predictive analytical tools exploit patterns found in historical data to make predictions about future events. In this paper we have shown some recent developments of a few of these techniques in financial and business intelligence applications like fraud detection, bankruptcy prediction and credit rating scoring.
Language eng
Field of Research 010499 Statistics not elsewhere classified
159999 Commerce, Management, Tourism and Services not elsewhere classified
Socio Economic Objective 970115 Expanding Knowledge in Commerce, Management, Tourism and Services
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2010, GSTF
Persistent URL http://hdl.handle.net/10536/DRO/DU:30034959

Document type: Conference Paper
Collection: Deakin Graduate School of Business
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