The problems of bankruptcy prediction and fraud detection have been extensively considered in the financial literature. The objective of this work is twofold. Firstly, we investigate the efficiency of multi-instance learning in bankruptcy prediction. For this reason, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 150 ...

The problems associated with the application of bankruptcy prediction models are a wide range. A review literature shows lack uniform definition bankruptcy. existing diversity in definitions complicates comparability different studies, hence why it is considered appropriate to take specific that based on into account when applying them practice. selection companies various studies has also been...

This paper examines the performance of the Morningstar Solvency Score, Morningstar's new accounting-ratio based metric for predicting bankruptcy, in comparison to the Altman Z-Score and Distance to Default models. Specifically we tested the following: 1. The ordinal ability of each model to distinguish companies most likely to file for bankruptcy from those least likely to file for bankruptcy a...