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Data Mining Used for Analyzing the Bankruptcy Risk of the Romanian SMEs
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Author(s): Laura Giurca Vasilescu (University of Craiova, Romania), Marian Siminica (University of Craiova, Romania), Cerasela Pirvu (University of Craiova, Romania), Costel Ionascu (University of Craiova, Romania)and Anca Mehedintu (University of Craiova, Romania)
Copyright: 2011
Pages: 28
Source title:
Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection
Source Author(s)/Editor(s): Ali Serhan Koyuncugil (Capital Markets Board of Turkey, Turkey, and Baskent University, Turkey)and Nermin Ozgulbas (Baskent University, Turkey)
DOI: 10.4018/978-1-61692-865-0.ch008
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Abstract
The small and medium enterprises (SMEs) represent the backbone of the economy, playing a major economic and social role in the process of developing a dynamic economy. But the recent evolutions in the financial markets, the international financial crisis, the increased competition on markets, the lack of financial resources and the insufficient adaptation of many firms to the requests of the European market are new threats which can determine the bankruptcies of the Romanian SMEs. In this context, starting from the necessity to design an early warning system, we will elaborate a new model for analysis of bankruptcy risk for the Romanian SMEs that combine two main categories of indicators: financial ratios and non-financial indicators. The authors‘ analysis is based on data mining techniques (CHAID) in order to identify the firms’ categories accordingly to the bankruptcy risk levels. Through the proposed analysis model they try to offer a real surveillance system for the Romanian SMEs which can allow an early signal regarding the bankruptcy risk.
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