An Intelligent Agent System for Bankruptcy Analysis and Prediction
Keywords:
Bankrupt Analysis, Logistic Regression, Random Forest, Ensemble Methods, Machine LearningAbstract
The term Bankruptcy can be interpreted as a legal proceeding in which any person or organization is unable to repay the loans. Bankruptcy is one of the crucial problems for both organizations and banks. Throughout the world, academic literature and professional researchers have discussed the possibility of business insolvency. Successful prediction at the initial stage of bankruptcy may help the banks reduce their financial losses and assist them to make correct decisions. We used a bankruptcy data set from Polish companies, where synthetic characteristics were utilized to depict higher-order statistics. This study focuses on the analysis of bankruptcy using different Machine learning algorithms. Among them, Random Forest has shown the highest accuracy. This model helps us to detect whether any person or organization will go bankrupt or not.
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