Review of bankruptcy prediction using machine learning and deep learning techniques

Abstract Bankruptcy prediction has long been a significant issue in finance and management science, which attracts the attention of researchers and practitioners. With the great development of modern information technology, it has evolved into using machine learning or deep learning algorithms to do the prediction, from the initial analysis of financial statements. In this paper, we will review the machine learning or deep learning models used in bankruptcy prediction, including the classical machine learning models such as Multivariant Discriminant Analysis (MDA), Logistic Regression (LR), Ensemble method, Neural Networks (NN) and Support Vector Machines (SVM), and major deep learning methods such as Deep Belief Network (DBN) and Convolutional Neural Network (CNN). In each model, the specific process of experiment and characteristics will be summarized through analyzing some typical articles. Finally, possible innovative changes of bankruptcy prediction and its future trends will be discussed.