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 objectives of this study are to predict bankruptcy risk among SMEs in the hospitality industry for a three-year horizon period and investigate factors that significant determining bankruptcy. contribution is essential as businesses dominated by SME operators. However, failure rate relatively high almost 50 percent establishments do not survive beyond five years operation. Stepwise logistic ...

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...

Bankruptcy prediction is a key part in corporate credit risk management. Traditional bankruptcy prediction models employ financial ratios or market prices to predict bankruptcy or financial distress prior to its occurrence. We investigate the predictive accuracy of corporate efficiency measures along with standard financial ratios in predicting corporate distress in Chinese companies. Data Enve...