Md. Azim1* and Md. Jamil Sharif2
1Department of Business Administration, World University of Bangladesh, Dhaka-1205, Bangladesh; and 2Department of Accounting & Information Systems, University of Dhaka, Dhaka, Bangladesh.
*Correspondence: azimbikrom@gmail.com (Md. Azim, M.Phil Student, Dept. of Accounting & Information Systems, University of Dhaka, Bangladesh).
Powered by Froala Editor
ABSTRACT
This study aims to identify whether or not the Z score is usable enough in doing prediction at the early stage of the financial distress of People’s Leasing and Financial Services (PLFS) and Bangladesh Industrial Finance Company (BIFC). To predict corporate failure, Multiple Discriminant Analysis is an effective solution. Z"-Score by Altman is a widely used model of multiple discriminant analysis. Using the data from 2011 to 2017 of PLFS and 2015-2017 of BIFC, this study applied the Altman Z"-Score Model as well as used SPSS software to analyze the descriptive statistics of the financial information and ratios of both company to know the level of financial distresses and attributes for reaching toward distress level. The analysis was presented in tables. The finding shows that Z"-Score by Altman is usable enough to predict the failure of the firm. The descriptive analysis shows that working capital, retained earnings, and income before interest and tax were negative which could be considered as the reasons for the distressed position. This study contributes by showing the usefulness of the Z score of Altman in emerging countries like Bangladesh. This is significant because early prediction can prevent liquidation which ultimately protects various stakeholders of an organization.
Keywords: Altman’s Z"-Score, Liquidation, Financial distress, Predicting corporate failure, and Leasing services.
Citation: Azim M. and Sharif MJ. (2020). Usability of Z score: a case study on people's leasing and financial services limited & Bangladesh industrial finance company limited, Int. J. Manag. Account. 2(3), 38-46. https://doi.org/10.34104/ijma.020.038046
Powered by Froala Editor
