Bankruptcy prediction for credit risk using neural networks: A survey and new results

The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and p rofitability, This work presents two contributions. First we review the top ic of bankruptcy prediction, with emphasis on neural-network (NN) models, S econd, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton, we propose novel indic ators for the NN system. We show that the use of these indicators in additi on to traditional financial ratio indicators provides a significant improve ment in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).