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Bankruptcy Detection on Unbalanced Data with Various Machine Learning Models

Abstract: Machine learning has come a way long from past decades and the use of machine learning and machine learning models has been rapidly increasing in various fields. Today machine learning is playing a critical role in many streams especially finance. Bankruptcy is a technical term used to describe whether a company can run its operations in the future because of its losses or bad debts. The paper focuses on delivering a machine learning algorithmic approach to detect a company's state of bankruptcy based on the available data. The project implements a study on a dataset of companies in a specific period and By applying various machine learning algorithms like logistic regression, random forest, and artificial neural networks. Keywords: Machine learning, logistic regression, random forest, artificial neural networks