Financial early warning system model and data mining application for risk detection
Expert Systems with Applications: An International Journal
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The aim of this study is to develop road maps for financial decision making. The study was conducted in Turkish Ministry of Health’s public hospitals that need urgent solutions for financial issues in Turkey. 800 hospitals were covered and financial and operational data of the year 2005 were used in the study. We used Chi-Square Automatic Interaction Detector (CHAID) Decision Tree Algorithm as a data mining method to discover hidden and useful pattern in a large amount of data and then determine the impact factors that provided steps for road maps. According to the results of the study, it was determined that financial performances of 1.75 % (14 hospitals) of the covered hospitals were high, whereas 98.25% (786 hospitals) of them displayed as low. Also covered hospitals were categorized in 7 different profiles in terms of level of financial performance by CHAID algorithm. According to these profiles, we developed 2 different financial road maps for the low performer hospitals to improve their financial performance.