Data Mining Approach for Financial Situation Analysis
Project no. 21759 · Status: Kapanmış · 2020
Summary
<p>Estimating the financial failure of a company is very important in terms of determining the financial risks that may occur in the future and determining the measures that can be taken. In undetected cases, companies may face undesirable consequences and go bankrupt. Although different methods and techniques have been used for many different models in the studies carried out so far for the prediction of financial failure, the lack of a perfect forecasting model continues the need for studies in this field to continue.</p><p>In this study, a model was determined for the prediction of financial failure, and the financial situation of the companies was estimated by using data mining classification techniques. The data of the study was obtained from the financial statement data of 179 companies operating in the manufacturing industry between 2013 and 2018, obtained from the KAP. In the study, the financial status of the companies was labeled separately according to Altman Z-Score and Springate S-Score values, and two different data sets were created. The results were evaluated by applying K-Nearest Neighbors, Naive Bayes, Decision Tree and Support Vector Machine methods to each data group. When the results were evaluated, it was determined that the model had high classification success rates.</p>