Bank failure prediction models usually combine financial attributes through binary
classification approaches. In this study we extend this standard framework in three main …

Unlike prior work in the area of bank failure prediction, this article focuses on
misclassifications: the individual banks that were predicted by a model to fail and yet have …

The Russian banking sector experienced considerable turmoil in the late 1990s, especially
around the Russian banking crisis in 1998. The question is what types of banks are …

This paper examines the problem of bank failure and proceeds to the development of bank
failure prediction models based on a multicriteria decision technique, namely UTilites …

While extensive research in data mining has been devoted to developing better
classification algorithms, relatively little research has been conducted to examine the effects …

In this paper we develop a novel bank failure prediction approach that uses the output of a
multiperiod logit model to assess banks' risk situations and then estimates a survival time …

The recent financial crisis shows that failure of some financial institutions can cause other
banks to fail and ultimately cause damage to the financial system worldwide. Eurozone …

This paper reiterates the importance of corporate governance in banks. Failure prediction
studies have mainly relied on using financial ratios as predictors. The most suitable financial …

The purpose of this paper is to present a neural network approach to predicting bank failures
and to compare it with existing prediction methods. The task of constructing a prediction …

Using discriminant analysis, we trace the US bank failures during the period from 2007 to
2010 to poor investment decisions and large exposure to systemic risk channels …