The week's pick
Reseach Article
A Fuzzy Logic based Model for Predicting Commercial Banks Financial Failure
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 79 - Number 11 |
| Year of Publication: 2013 |
| Authors: Ahmed A. Mohamed, Ahmed S. Salama |
10.5120/13785-1817
|
Ahmed A. Mohamed, Ahmed S. Salama . A Fuzzy Logic based Model for Predicting Commercial Banks Financial Failure. International Journal of Computer Applications. 79, 11 ( October 2013), 16-21. DOI=10.5120/13785-1817
Abstract
The financial failure of most commercial banks is hardly identified and detected. Machine learning techniques as Fuzzy logic (FL), Artificial Neural network (ANN), Case based reasoning (CBR) and Rule based system (RBS) are important techniques that are used in prediction and forecasting generally. This paper introduces a fuzzy logic based proposed model which can help the decision maker in commercial banks to make the right decision to determine level of financial failure in the bank. The proposed model employing financial ratios rules used in Egyptian commercial banks to measure the bank financial performance indicators i. e. capital adequacy, asset quality, liquidity, and earnings in order to determine their financial failure. The proposed model uses fuzzy logic in MATLAB to build financial ratios membership functions. In addition, the implementation of the proposed model used visual studio 2010 to build the graphical user interface for the user. The implemented system was tested on two of the Egyptian commercial banks i. e. CIB bank and CFEB bank. The mathematical equation of the defuzzification was applied to calculate financial failure in these two banks. After implementing and applying the proposed model, it was proved that the fuzzy logic technique is one of the most important machine learning techniques that can be used to detect financial failure in commercial banks and the proposed model proved that it is highly effective, scalable, and reliable in detecting the financial bank failure.
References
- Edward I. 1997 Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy, the Journal of Finance, Vol. 23, No. 4. pp. 589-609.
- Kolari, J. , Glennon, D. , Shin, H. and Caputo, M. 2000 Predicting Large U. S. Commercial Bank Failures, Economic and Policy Analysis Working Paper 2000-1, January.
- Laitinen, E. K. and Laitinen, T. 2000 "Bankruptcy prediction. Application of the Taylor's expansion in logistic regression", International Review of Financial Analysis. Vol. 9, p372-349.
- Molina, C. A. 2002 Predicting bank failures using a hazard model: the Venezuelan banking crisis. Emerging Market Review 3, 31-50.
- Mete M. , Ba?ak, N. , and Ramazan, C. 2005 Predicting Financial Failure of the Turkish Banks, University, Ankara, Turkey.
- Lanine, G, and Vander R. 2007 Failure prediction in the Russian bank sector, with logit and trait recognition models, Ghent University, Belgium, Ghent University, Belgium.
- Eygi B. 2008 Applied Mathematical Sciences, Vol. 2, no. 60, Marmara University, Art and Science Faculty, Department of Mathematics, Goztepe, Istanbul, Turkey, 2973 – 2982.
- Maisarh, F. , Yaseen, M. , and Omar, N. 2008 Predicting Financial Failure of Yemeni Banks, College of Business, Division of Finance and Banking, University Utara Malaysia.
- Mohammed, N. 2010 "Exploiting Machine Learning in Generating Future scenarios for the Tourism Industry in Egypt", Cairo University, Faculty of Computers and Information.
- Dostál, P. 2013 Forecasting of Time Series with Fuzzy Logic. Advances in Intelligent Systems and Computing , Volume 210, pp 155-161.
- Andrew G. , Belik, I. , and Rahimi1, S. 2010 "A Hybrid Expert System for IT Security Risk Assessment", Southern Illinois University, Carbondale, IL, USA.
Index Terms
Keywords