Review Article

The bankruptcy prediction approach: An empirical study of comparison between the emerging market score model and bankruptcy prediction indicators approach in the Johannesburg Stock Exchange

Ronel J. Cassim, Matthys J. Swanepoel
Journal of Economic and Financial Sciences | Vol 14, No 1 | a539 | DOI: | © Ronel J. Cassim, Matthys J. Swanepoel | This work is licensed under CC Attribution 4.0
Submitted: 26 November 2019 | Published: 29 January 2021

About the author(s)

Ronel J. Cassim, Department of Accountancy, Faculty of Management Sciences, Vaal University of Technology, Vanderbijlpark, South Africa
Matthys J. Swanepoel, Department of Accountancy, Faculty of Economic and Management Sciences, North-West University, Vanderbijlpark, South Africa


Orientation: The effective and timely bankruptcy prediction is crucial to the survival of companies. In order to attain a desired result an effective bankruptcy prediction tool needs to be applied within a South African context.

Research purpose: The aim of this study was to determine whether bankruptcy could have been predicted within the 5 years prior to failure for the study period between 2016 and 2018.

Motivation for the study: Most of the bankruptcy prediction studies in South Africa are industry- or sector-based, not many studies are found to be generic, easy to use and apply, and thus one model is applied for different industries or sectors.

Research approach/design and method: From the population, the total sample consists of five companies within four different sectors, such as industrial, construction, retail, and personal and household sectors. Financial indicators (financial ratios) were obtained for both the BPIA and EMS from the INET (a South African supplier of quality financial data) McGregor BFA database, a JSE portal. A mixed-method research approach was applied by making use of a qualitative and quantitative methodology.

Main findings: The findings revealed that the BPIA is an effective and reliable analytical tool to predict or detect the bankruptcy of South African companies.

Practical/managerial implications: Based on the finding of the study companies within diverse industries should apply the BPIA regularly and take remedial action significantly to improve their financial well-being.

Contribution/value add: The study has identified the BPIA has a better prediction accuracy than the renowned EMS model in South African context.


Bankruptcy prediction indicator approach; Bankruptcy; Company failure; Emerging Market Score model approach; Financial distress; South African context


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Crossref Citations

1. Application of artificial neural networks in predicting financial distress in the JSE financial services and manufacturing companies
Fikile Dube, Ntokozo Nzimande, Paul-Francois Muzindutsi
Journal of Sustainable Finance & Investment  vol: 13  issue: 1  first page: 723  year: 2023  
doi: 10.1080/20430795.2021.2017257