Application of Neural Network in Prediction of Financial Viability
Roli Pradhan1, K.K. Pathak2, V.P. Singh3
1Roli Pradhan, Department of Management Studies, MANIT, Bhopal, (MP), India.
2Prof. K. K. Pathak, Scientist E ,AMPRI, Bhopal, (MP), India.
3Prof. V.P. Singh , Director Sagar Institute, Bhopal, (MP), India.
Manuscript received on April 25, 2011. | Revised Manuscript received on May 02, 2011. | Manuscript published on May 05, 2011. | PP: 41-45 | Volume-1 Issue-2, May 2011. | Retrieval Number: A037041211
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Bankruptcy prediction is very important for all the organization since it affects the economy and causes a rise in many social problems with incremental high costs. There are large number of techniques that have been developed to predict the bankruptcy of firms, which helps the decision makers such as investors and financial analysts to plan in accordance to the financial position of the firm regarding the terms of credit as well as the recovery of the lent amount. The Altman Model for prediction of financial bankruptcy has been considered in this work. The backpropagation neural networks been used to forecast the Z Score for the firms. The research work first estimates the internal parameters of the Z score for a firm from 2001-2008 to the train the BPNN and uses the estimates of the year 2009 and 2010 values for the validation process. Finally it dwells to draw predictions for the period 2011-2015 and emphasizes the growing role of BPNN application based Z Score computation of financial Bankruptcy.
Keywords: Bankruptcy prediction, financial ratio models, BPNN.