A Statistical Prediction Of Likely Distress In Nigeria Banking Sector Using A Neural Network Approach

One of the most significant threats to the economy of a nation is the bankruptcy of its banks. This study evaluates the susceptibility of Nigerian banks to failure with a view to identifying ratios and financial data that are sensitive to solvency of the bank. Further, a predictive model is generated to guide all stakeholders in the industry. Thirty quoted banks that had published Annual Reports for the year preceding the consolidation i.e. year 2004 were selected. They were examined for distress using the Multilayer Perceptron Neural Network Analysis. The model was used to analyze further reforms by the Central Bank of Nigeria using published Annual Reports of twenty quoted banks for the year 2008 and 2011. The model can thus be used for future prediction of failure in the Nigerian banking system. {"references": ["Adefila, J.J. (2002) \"Assessing Financial Strenght to Determine \nBankruptcy Potential: A case study of Trade Bank Plc\" Nigerian Journal \nof Management Science Vol. 30 No. 2, pp. 24-35.", "Altman, E.I. (1968), \"Financial Ratios, Discriminant Analysis and the \nPrediction of Corporate Bankruptcy\" Journal of Finance, Vol. 23 p. 589 \n\u2013 609.", "Atiya, A.F., (2001) \"Bankruptcy Prediction for credit Risk using Neural \nNetworks: A Survey and New Results\" IEEE Transactions on Neural \nNetworks, Vol. 12 No. 4, pp. 929 \u2013 935.", "Beaver, William H. (1966) \"Financial Ratios as Predictions of Failure\" \nEmperical Research in Accounting. Selected Studies, Supplement to \nJournal of Accounting Research vol. 4, pp. 77-111.", "Boyacioglu, M.A., Kara Y and Baykan, O.K. (2009), \"Predicting bank \nfinancial failures using neural neworks, support vector machines and \nmultivariate statistical methods: A comparative anslysis in the sample of \nSavings Deposit Insurance Fund (SDIF) transferred banks in Turkey\" \nwww.citibank.co.in vol 36 issue 2 pp. 3355-3366. Acessed on May 31, \n2010.", "CBN, (2007) \"A case study of Distressed Banks in Nigeria\" Publication \nof Research and Statistics Department.", "Erdogan, B.E. (2008), \"Bankruptcy Prediction of Turkish Commercial \nBanks using Financial. Ratios\" Applied Mathematical Sciences Vol. 2 \nNo. 60, pp. 2973 \u2013 2982..", "Jimoh, A. (1993, \"The Role of Early warning Models in the \nIdentification of Problem Banks Evidence from Nigeria\". Nigeria \nFinancial Review. Vol. 6, No. 1, pp. 29-43.", "Konstandina, N.V. (2006) \"Probability of Bank Failure: The Russian \nCase\" Paper presented at Economics Education and Research \nConsortium: Russia and CIS. \n[10] Kosoko(2007) \"The Story of Banking Consolidation, Spring Bank as a \nCase Study'' Thisday Newspaper June 17, pp.14 \n[11] Lim, S.H. and Nam, K. (2006), \"Artificial Neural Network Modeling in \nForecasting Successful Implementation of ERP Systems\" International \nJournal of Computational Intelligence Research, vol. 2 No. 1, pp. 115 \u2013 \n119. \n[12] Odife, D. (2009), \"The rot started long ago\" Newswatch Magazine, Vol. \n50, No. 9, pp. 14-15. \n[13] Ohlson, J. (1980), \"Financial Ratios and the Probabilities Prediction of \nBankruptcy\" Journal of Accounting Research Vol. 18 pp. 109 \u2013 131. \n[14] Olaniyi, T.A. (2007), \"Predicting Potential of Failure in Nigerian \nBanking Sector: A Comparative Analysis of First Bank Plc and Trade \nBank Plc\". Journal of Management and Social Sciences, Babcock \nUniveristy. Vol. 6, No. 1, pp. 64-73. \n[15] Sogunro, A.B. (2008), \"Predicting Insurer Failures: An Artificial \nIntelligence Approach\". M.Sc. Thesis, University of Lagos. \n[16] Subramanian N., Yajnik, A., and Murthy, R.S.R. (2004), \"Artificial \nNeural Network as an Alternative to Multiple Regression Analysis in \nOptimizing Formulation Parameters of Cytarabine Liposomes\" \nAmerican Association of Pharmaceutical scientists.\nwww.aapspharm.scitech.org accessed 12/10/2010. . \n[17] Vallini, C., Ciampi, F.and Gordini, N., (2009) \"Using Artificial Neural \nNetwork Analysis for Small Enterprise Default Prediction Modelling: \nStatistical Evidence From Italian Firms\". Oxford Business and \nEconomics Conference Program. \n[18] Watanabe, K. (2010), \"Predicting Future Depositor's Rate of Return \nApplying Neural Network: A case study of Indonesian Islamic Bank\" \nInternational Journal of Economics and Finance Vol. 2 No. 3 pp. 1 - 9 \n[19] Zhang, G., Hu, M.Y., and Indro, D.C. (1999), \"Artificial Neural \nNetworks in Bankruptcy prediction: General Framework and Cross \u2013 \nValidation analysis\". European Journal of Operational Research. \nwww.sciencedirect.com accessed on 4/9/2010."]}