Please use this identifier to cite or link to this item:
Title: Maltese company failures and their recent financial history : an analysis
Authors: Abela, Renè Kriss
Keywords: Bankruptcy -- Malta -- Mathematical models
Bankruptcy -- Forecasting -- Mathematical models
Business failures -- Malta
Issue Date: 2020
Citation: Abela, R.K. (2020). Maltese company failures and their recent financial history: an analysis (Master's dissertation).
Abstract: Purpose : The purpose of this study is threefold. First, to identify financial and non-financial factors that can predict insolvency. Second, to compare and contrast these factors with the factors identified in the literature. Third, to analyse whether the factors identified are in line with how users of the financial statements assess the risk of an entity in the Maltese scenario. Design : A mixed methodology approach is applied. Data gathered from financial statements of both failed and non-failed companies is statistically analysed through 2 logistic regressions that can predict corporate insolvency within 1 and 2 years before failure. The qualitative aspect of the study comprises of 10 interviews with auditors, company representatives and the Malta Association for Credit Management. The findings are then compared to the factors found significant in the models. Findings : Model 1 that predicts corporate failure from one year prior has 11 signifcant variables. These include 5 financial variables : Total Assets/Total Liabilities, Positive Profit and Net Assets, Dividend Paid/Total Assets, Cash/Total Assets and Trade Receivables/Current Assets, 3 internal non-financial variables : Going Concern Paragraph, Audit Opinion and Owner Managed, 2 industry variables; Accommodation and Food and Wholesale and Retail, and 1 macroeconomic variable; Inflation Model 2 that predicts corporate failure from 2 years prior has 4 significant variables which include 3 variables from Model 1; Owner Managed, Going Concern and Positive Profit and Net Assets and another financial variable which is the Current Ratio. Model 1 and 2 have a classification accuracy of 93.3% and 90.6% respectively. From the interviews conducted it was noticed that cashflow is perceived as the most important financial factor. Company representatives believe that clients failing to honour their payments is the major risk that can lead to insolvency. The interview with MACM also provides reasons why Malta has a high daily outstanding sales ratio when compare to the EU average. Conclusions : Company failure prediction models can be used as a tool to assist users of financial statements to get a quick indication of the risk of insolvency of a company. However, it is important to complement the model with other factors, some of which are mentioned by the interviewees. Value : A failure prediction model study dates back to 2011, which, given a dynamic market may not be suitable anymore. Also, this is the first study of this kind that incorporates non-financial information including also industry variables and macroeconomic variables.
Description: M.ACCTY.
Appears in Collections:Dissertations - FacEma - 2020
Dissertations - FacEMAAcc - 2020

Files in This Item:
File Description SizeFormat 
  Restricted Access
19.58 MBAdobe PDFView/Open Request a copy

Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.