Journal ArticleDOI
The prognosis and surveillance of risks from commercial credit borrowers
TLDR
In this article, the main results of an empirical research project dealing with the prognosis and surveillance of corporate credit risks were reported, where quantitative (balance sheet analysis, current accounts data analysis) and qualitative (assessment of management) methods were applied.Abstract:
This paper reports the main results of an empirical research project dealing with the prognosis and surveillance of corporate credit risks. In the course of the research programme both quantitative (balance sheet analysis, current accounts data analysis) and qualitative (assessment of management) methods were applied. Each of the three parts of the project is independently usable However, the combined application of the three approaches avoids deficiencies of using only one of the components and improves the early detection of credit risks.read more
Citations
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Machine Learning: Neural and Statistical Classification
TL;DR: A survey of previous comparisons and theoretical work descriptions of methods dataset descriptions criteria for comparison and methodology (including validation) empirical results machine learning on machine learning can be found in this article, where the authors also discuss their own work.
Journal ArticleDOI
A survey of business failures with an emphasis on prediction methods and industrial applications
TL;DR: This paper provides a review of the literature and a framework for the presentation of prediction models, and relationships and research trends in the prediction of business failure are discussed.
Journal ArticleDOI
Modeling Credit Risk for SMEs: Evidence from the US Market
Edward I. Altman,Gabriele Sabato +1 more
TL;DR: In this article, the authors developed a distress prediction model specifically for the SME sector and analyzed its effectiveness compared to a generic corporate model, considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord.
Journal ArticleDOI
Modelling Credit Risk for SMEs: Evidence from the U.S. Market
Edward I. Altman,Gabriele Sabato +1 more
TL;DR: In this article, the authors developed a distress prediction model specifically for the SME sector and analyzed its effectiveness compared to a generic corporate model, considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord.
The value of non-financial information in small and medium-sized enterprise risk management
TL;DR: In this paper, the authors employed a sample consisting of over 5.8 million sets of accounts of unlisted firms, of which over 66,000 failed during the period 2000-2007.
References
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Journal ArticleDOI
On Estimation of a Probability Density Function and Mode
TL;DR: In this paper, the problem of the estimation of a probability density function and of determining the mode of the probability function is discussed. Only estimates which are consistent and asymptotically normal are constructed.
Journal ArticleDOI
Financial Ratios As Predictors Of Failure
TL;DR: In this article, the authors focus on the use of ratios as predictors of failure, defined as the inability of a firm to pay its financial obligations as they mature, and demonstrate that a firm is said to have failed when any of the following events have occurred.
Journal ArticleDOI
A nonparametric estimate of a multivariate density function
TL;DR: In this article, the problem of estimating a probability density function has only recently begun to receive attention in the literature, and an estimator is proposed and consistency is shown, but it is only recently that it has been considered in the context of nonparametric discrimination.
Book
Corporate financial distress : a complete guide to predicting, avoiding, and dealing with bankruptcy
TL;DR: The Z-score model has been used to classify and predict failure rates of business failures as discussed by the authors, and fine-tune failure classification models for non-industrial sectors, such as financial institutions.