Prediction Financial Distress: The Pro-Technology Technique of Altman Z-Score Model

The Covid-۱۹ outbreak has had a severe effect on the world economy. The company's business operations and profitability are damaged during the covid ۱۹ outbreak. This deterioration is not only threatening the company’s survival position but also destroy the investor’s investment return. Therefore, it is vital to establish an effective early prediction technical method to foresee a corporate distress by a Pro-technical measurement to enhance the corporate sustainability. This study applies Altman Z-Score Model to as a Pro-Technology technique to the financial distress prediction of Malaysia’s Government Linked Plantation Companies (GLC-P) over a period of ۱۰ years starting from ۲۰۱۲ to ۲۰۲۱. The significant contribution of the study is that the Z-Score Model provides an advanced indication tool regarding the financial stability of the respective GLC-P companies. The findings indicate that Financial Distress Prediction was dependent via in-time application of leverage, liquidity, activity, and profitability to the Altman Z-Score Model. Profitability and leverage were found to be superior prediction tool to financial distress.

Keywords:

Investment , Pro-Technology , Altman Z-Score Model , Prediction Tool , sustainability