An application of GRA to analyze the credit risk in banking industry

This study proposes a new approach for analyzing the credit risks of banking industry based the modeling of grey relational analysis (GRA). In order to construct a financial distress warning system for banking industry, a GRA approach is developed and applied to the real data set with 111 samples. The results of the current model are compared to those of traditional ones. The results illustrate that in the prediction of financially distress as well as financially sound banks, the proposed GRA model demonstrates better prediction accuracy than the conventional ones. The results also imply that the financial data set one year before the crisis leads to the best accuracy. It is helpful for the establishment of early warning models of financial crisis. The current results show that the proposed GRA provides a novel approach in handling financial distress warning tasks.