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Bankruptcy prediction using data mining techniques

This paper discusses the application and benefits of data mining techniques to construct prediction models in the field of corporate bankruptcy. It analyzes a dataset of 120 companies using different data mining techniques. Findings show that neural network is recommended as the best model to predict corporate bankruptcy. Findings also show that the proper use and selection of data mining techniques help to enhance the prediction accuracy of the models. Financial organizations can significantly benefit from using these prediction models as they allow them to anticipate the status of businesses in the future and make decisions accordingly.