Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks
We combine multilayer perceptrons and self-organizing maps for bankruptcy prediction. We calculate the probability of distress up to three years before bankruptcy occurs. We develop a tool to assess bank risk in the short, medium and long term. Our model outperforms traditional models of bankruptcy prediction. Distressed banks are concentrated in real estate loans and have more provisions.
neural networks multilayer perceptron self-organizing maps bankruptcy prediction financial crisis