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1Dr. Roli Pradhan is an Assistant Professor in MANIT, Bhopal. She can be reached at pradhanroli@gmail.com
2Dr. K.K. Pathak is a professor in the Civil Engineering Department, Nitttr, Bhopal. He can be reached on kkpathak1@rediffmail.com
3Professor V.P. Singh is a Director in Sagar Institute, Bhopal. He can be reached on singhvp@gmail.com
Bankruptcy prediction is very important for all the organisations in the financial sector, as it affects the economy and leads to rise in many social problems with added incremental costs. There are large number of techniques that have been developed to predict the bankruptcy, which help the decision makers, such as investors and financial analysts. One of the bankruptcy prediction models is back-propagation neural network (BPNN). The paper first surveys the existing literature for various techniques that have been developed to assess credit risks, including the credit scoring models and quantitative models pioneered by Beaver and Altman, which focuses on the borrower’s inability to meet credit obligation. Thereafter, this paper, using the tailored BPNN, endeavours to predict the financial ratios expressing the position of a firm to regulate the bankruptcy and assess the credit risks. It first estimates the financial ratio for a firm from 2001 to 2008 to the train the BPNN and uses the estimates of the year 2009 and 2010 values in the validation process. Finally, it dwells to draw predictions for the period 2011-2015 and emphasises the growing role of BPNN application-based prediction models for banking sector with a case study of Oriental Bank of Commerce. We conclude with practical suggestions on how best to integrate models and research into credit lending decisions.
Credit lending, Back propagation neural network, Credit lending, Ratio analysis
JEL CLASSIFICATION: G 17
Altman, E. (1968). ‘Financial ratios, discriminant analysis and the prediction of corporate bankruptcy’, The Journal of Finance, Vol. 13, no. 4, pp. 589-609.
Beaver, W. (1966). Financial ratios as predictors of failure. Journal of Accounting Research. 4 (1), 71-111.
Beaver, W. (1967). Financial Ratios as Predictors of Failure, Empirical Research in Accounting: Selected Studies, Supplement, Journal of Accounting Research 5, 71-127.
Beaver, W.H., Mcnichols, M.F. and Rhie, J.W. (2005). ‘Have financial statements become less informative? Evidence from the ability of financial ratios to predict bankruptcy’, Review of Accounting Studies, no 10, pp. 93-122.
Bharath, S.T. and Shumway, T. (2008). ‘Forecasting default with the Merton distance to default model’, The Review of Economic Times, Vol. 21, Issue 3, pp. 1339-1369.
Campbell et. al (2008). “In search of Distressrisk, Journal of finance, 636, 2899-2939.
Crosbie, Peter J. and Jeffrey R. Bohn, (2001). Modeling Default Risk, KMV, LLC, San Francisco.
Hillegeist, S., Keating, E., Cram, D. and Lundstedt, K. (2004). ‘Assessing the probability of bankruptcy’, Review of Accounting Studies, Vol no. 9, pp. 5-34.
Merton, R.C. (1974). “On the pricing of corporate debt: the risk structure of interest rates’, Journal of Finance, Vol. 29, No. 2, pp. 449-470.
Ohlson, J.A. (1980). ‘Financial ratios and the probabilistic prediction of bankruptcy’, Journal of Accounting Research, Vol. 18, no. 1, pp. 109-131.
Shumway, T. (2001). ‘Forecasting bankruptcy more accurately: a simple hazard model’, Journal of Business, Vol. 74, no.1, pp.101-124.
Zmijewski, M.E. (1984). ‘Methodological issues related to the estimation of financial distress prediction models’, Journal of Accounting Research, Vol. 22, supplement, pp. 59-82.
