Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 39, Issue 6, Pages 6238-6253Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.12.021
Keywords
CHAID; Data mining; Early warning systems; Financial risk; Financial distress; SMEs
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Funding
- Scientific and Technological Research Council of Turkey (TUBITAK)
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One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an early warning system (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation. (C) 2011 Elsevier Ltd. All rights reserved.
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