Predicting Financial Distress in Enterprises by Applying Multilevel Ensemble Technique

The exponential growth in technology and economy over the years has delivered data driven statistical learning and Data mining progressively. It has been broadly identified that the determinant factor of financial distress in enterprises is poor management, and company's performance reliably reflects the corporate management. The best an enterprise can deliver is to predict its financial status to survive any future financial crisis. During the study it has been identified that management, investing and financing are three most important sections of a company to predict the financial crisis. In this research paper, a multilevel ensemble model has been proposed to predict the financial distress in various companies. This multi level ensemble approach incorporates six different machine learning models: SVM, ANN, DT, RF, RRF, and LR are combined to predict financial distress.