Predicting smes' survival using multivariate model

The purpose of this study is primarily to implement the Altman Z-score model to predict bankruptcy and to measure the financial performance of SMEs in Malaysia. In addition, this study aims to introduce the Z-score model to this industry as a beneficial diagnostic tool for possible causes standing behind the deterioration of financial performance. The methodology that has been used in this study is based on Z-score model developed by Altman. The related studies have proved that Z-score has more than 80 percent accuracy and verified as a robust tool. It is useful in assessing the business performance and predicting the potential distress of firms. The approach determined in this study is to examine the financial statements of the SMEs by calculating the Z-score for the past ten years and comparing it with the current year's score as an effort to measure the overall financial performance as well as the likelihood of bankruptcy of the SMEs. It is concluded that SMEs in Malaysia are financially unsound and unhealthy throughout the study period. The study proves that Z-score is a useful tool that can be used by other authorities or banks in measuring these SMEs performance to complement the existing financial analysis techniques available. The study also found that the ratios used in the Z-score model can be regarded as valuable in providing some indicators of SMEs condition. In other words, the study concluded that the Z score ratio is the most highly recommended tool for predicting failures of SMEs. This information is also valuable for shareholders as well as the banks in their decision making process. Finally, to understand better their past and present performance in the industry, SMEs should work on improving the ratios that are dragging their scores down. As a recommendation for future research, it is suggested that more effort should be put in collecting larger sample data sets. It is also recommended that the coefficient values of each ratio in this Z-score model to be updated based on the inputs from larger samples to represent the SMEs population, thus giving some true value for better prediction of SMEs distress condition.