Predicting Bank Bankruptcies with Neuro Fuzzy Method
AbstractThe aim of this study is to actualize the prediction of bankruptcies of the banks whose financial structures have gone bad with various reasons and transferred to Savings Deposit Insurance Fund especially in 2000-2001 crisis years, with neuro fuzzy. Neuro fuzzy does not have the problems which are sourced from the hypothesis of statistical methods and as in artificial neural network, it can learn the relationship of the data. At the same time the model does not stay in a black box like artificial neural network, the process of predicting of the model can be commented. Because of these features neuro fuzzy appears as an alternative. In this study, besides getting high prediction success from neuro fuzzy, the addition of the forerunner indicators on the decision making process can also be commented
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Bibliographic InfoArticle provided by Banking Regulation and Supervision Agency in its journal Journal of Banking and Financial Markets.
Volume (Year): 3 (2009)
Issue (Month): 1 ()
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Bank Failure Prediction; Neuro-fuzzy; Early Warning Systems; Discriminant Analysis;
Find related papers by JEL classification:
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies
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- Akkoç, Soner, 2012. "An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish cred," European Journal of Operational Research, Elsevier, vol. 222(1), pages 168-178.
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