Financial Distress in Listed Manufacturing Entities in Kenya: Prediction and Rescue Strategies.

Abstract

A financially distressed company is one that is unable to honor its financial obligations or has failed to meet its financial contractual requirements to creditors or financial lenders. Financial prediction models can detect financial distress in listed manufacturing at the Nairobi Securities Exchange (NSE). There are 13 manufacturing companies listed on the NSE, however, there is no public information that identifies financially distressed manufacturing companies listed on the NSE from those that are not distressed. There are investors who do not know the status of these listed manufacturing companies, because analytical studies and scientific researches are almost still lacking on listed Kenyan manufacturing companies. The purpose of the study is to establish the applicability and use of the modified Altman Z-Score model in predicting financial distress on listed manufacturing companies and the ensuing results used to recommend rescue strategies. The sampling frame of the study was drawn from all manufacturing companies listed on the Nairobi Securities Exchange (NSE). The study adopted a descriptive research method, it is also quantitative in nature because it relied on published audited financial statements of the listed manufacturing entities for the financial years 2014 - 2018. Financial information extracted from the audited financial statements based on the 5 ratios of the Altman Z-Score model were used to predict financial distress of the 13 manufacturing companies. The variables used to compute the five ratios were: the working capital, total assets, total liabilities, retained earnings, borrowings, EBIT, the book value of equity and revenues. The results of the financial distress predictions of the manufacturing companies over the past 5 years helped classify entities into the following areas: stable, gray or distressed. Data analysis was carried out through the use of both the Microsoft Excel package (2018) version 16.2, and the Statistical Package for Social Science (SPSS), version 26. All research questions were analyzed separately while considering all analysis factors that were reinforced by descriptive analysis. From the findings of the research the following was observations were made: there is no existing legislation in Kenya that compels either listed manufacturing companies on the NSE, nor the regulator to the NSE to undertake prediction of financial distress. The Altman Z-score model is appropriate in predicting financial distress; and it is possible to predict financial distress in manufacturing companies listed on the NSE, and such timely prediction of financial distress can go a long way in putting in place timely rescue strategies. This study recommends the adoption of both the 1993 revised Altman Z-score model, and the enhanced Emerging Market Scoring (EMS) system model in the prediction of financial distress of manufacturing companies listed on the NSE. For manufacturing companies listed on the NSE, this study recommends a revision of the CMA Act to compel a public disclosure of their Z-Scores to investors in their published annual financial statements. Moreover, this research recommends that the CMA should add a prefix ‘FD’ (financial distress) before names of manufacturing companies listed on the NSE found to be in financial distress in order to distinguish them from non-financially distressed companies. Finally, this study recommends, that a department within the CMA be mandated and empowered to ensure that ‘FT’ status listed manufacturing companies comply with restructuring and reform activities. Such monitoring of restructuring and reform activities of listed manufacturing companies can be directed by adherence to the annual prediction of financial distress by the department in the CMA.