Despite the number of studies on bankruptcy prediction using financial ratios, very little is known about how external audit information can contribute to anticipating financial distress. A handful of papers have shown that a combination of ratios and audit data is significant for predictive...

In the era of Basel II a powerful tool for bankruptcy prognosis isvital for banks. The tool must be precise but also easily adaptable tothe bank's objections regarding the relation of false acceptances (TypeI error) and false rejections (Type II error). We explore the suitabil-ity of Smooth...

Die Prognose der Insolvenzgefährdung von Unternehmen anhand statistischer Methodik war und ist eine bedeutende Aufgabe empirischer Forschung. Eine Möglichkeit der Beurteilung der finanziellen bzw. wirtschaftlichen Verfassung von Unternehmen stellt die sog. externe Bilanzanalyse anhand...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

Predicting default probabilities is important for firms and banks to operate successfully and to estimate their specific risks. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ratios. Here we propose the so called Support Vector Machine (SVM) to...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

Graphical data representation is an important tool for model selection in bankruptcy analysis since the problem is highly non-linear and its numerical representation is much less transparent. In classical rating models a convenient representation of ratings in a closed form is possible reducing...

In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...

We develop a model of neural networks to study the bankruptcy of U.S. banks. We provide a new model to predict bank defaults some time before the bankruptcy occurs, taking into account the specific features of the current financial crisis. Based on data from the Federal Deposit Insurance...

Bankruptcy filings are as high today as ever, calling into question the efficacy of existing bankruptcy prediction models. This paper tries to provide an alternative for bankruptcy prediction by integrated Multi Layered Perceptron with Imperialist Competitive Algorithm (MLP-ICA) and Kohonen self...