The size of the training data set is a major determinant of classification accuracy.
Nevertheless, the collection of a large training data set for supervised classifiers can be a …

ABSTRACT The importance of Big Data and Artificial Intelligence in the fields of accounting
and auditing is beyond doubt. However, to date, the influence of these technologies on …

The article provides a comprehensive review regarding the theoretical approaches,
methodologies and empirical researches of corporate bankruptcy prediction, laying …

Financial distress prediction is a central issue in empirical finance that has drawn a lot of
research interests in the literature. This paper aims to predict the financial distress of French …

A great deal of research has been devoted to prediction of bankruptcy, to include application
of data mining. Neural networks, support vector machines, and other algorithms often fit data …

Corporate bankruptcies often have severe consequences on all stakeholders, from financial
stakeholders losing their investment to employees losing their jobs. Yet traditional …

Corporate bankruptcy prediction is very important for creditors and investors. Most literature
improves performance of prediction models by develo** and optimizing the quantitative …

Commercial activities have evolved during the past decade from a single-channel focus and
perspective on business opportunities to a multiple-channel approach, with mobile phones …

Ensemble techniques such as bagging or boosting, which are based on combinations of
classifiers, make it possible to design models that are often more accurate than those that …

Performance of bankruptcy prediction models (BPM), which partly depends on the
methodological approach used to develop it, has virtually stagnated over the years. The …