  Bankruptcy prediction is very important for all the organization since it
affects the economy and rise many social problems with high costs. There are
large number of techniques have been developed to predict the bankruptcy, which
helps the decision makers such as investors and financial analysts. One of the
bankruptcy prediction models is the hybrid model using Fuzzy C-means clustering
and MARS, which uses static ratios taken from the bank financial statements for
prediction, which has its own theoretical advantages. The performance of
existing bankruptcy model can be improved by selecting the best features
dynamically depend on the nature of the firm. This dynamic selection can be
accomplished by Genetic Algorithm and it improves the performance of prediction
model.
