Excellence in Research and Innovation for Humanity
%0 Journal Article
%A Nermin Ozgulbas and  Ali Serhan Koyuncugil
%D 2012 
%J  International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 70, 2012
%T Risk Classification of SMEs by Early Warning Model Based on Data Mining
%U http://waset.org/publications/14725
%V 70
%X 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 7,853 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.

%P 2649 - 2660