Banka finansal başarısızlıklarının sinirsel bulanık ağ yöntemi ile öngörüsü

Bu çalışmanın amacı, özellikle 2000-2001 kriz yıllarında, çeşitli sebeplerle mali bünyeleri bozulup Tasarruf Mevduatı Sigorta Fonu’na devredilen bankaların, bu finansal başarısızlıklarının öngörüsünü sinirsel bulanık ağ yöntemi ile gerçekleştirmektir. Sinirsel bulanık ağ yöntemi istatistiksel yöntemlerin varsayımlarından kaynaklanan sorunları yaşamamakta ve yapay sinir ağ modellerinde olduğu gibi, verilerin içindeki ilişkiyi öğrenebilmektedir. Aynı zamanda model yapay sinir ağlarında olduğu gibi kara kutu içinde kalmamakta, modelin karar alma süreci yorumlanabilmektedir. Sinirsel bulanık ağ modeli özelliklerinden dolayı önemli bir alternatif olarak karşımıza çıkmaktadır. Bu çalışmada sinirsel bulanık ağ modelinden yüksek öngörü başarısı elde edilmesinin yanında, öncü göstergelerin karar alma sürecine olan katkısıda yorumlanabilmiştir.

Predicting bank bankruptcies with neuro fuzzy method

The 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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