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Models to predict company failure



The failure of a number of big businesses in the last two decades has raised a lot of interest in trying to predict failure of businesses before they occur. As highlighted in the last article businesses don’t fail overnight. It has been observed that usually, company failure take years.
Company failure or insolvency results in the company’s affairs being wound up and its assets being sold in execution and the net proceeds, if any, being distributed amongst its stakeholders. The impact of company failures has far-reaching consequences for stakeholders, as has been observed in previous company failures.

Shareholders in a company stand to lose the most as the value of their investment deteriorates or disappears entirely. Creditors might receive partial or no repayment for their loans to the company. Other stakeholders such as employees lose their jobs, and the Government will lose its tax collections from both the company and employees earnings. To establish a company’s financial health is therefore very important for all stakeholders since this impacts on their survival as well.

Most of these stakeholders would use different sources of information to assess the financial health of the company. Some rely on published financial statements, or stockbroker reports or the daily financial newspapers to evaluate the performance of the company; whether it will operate for the foreseeable future or not. Some of the stakeholders incorporate the information in a financial failure prediction model to support their decision making process.

The challenge is that some of these predictive models are very sophisticated for the ordinary stakeholder to use. Notwithstanding these challenges, the early prediction of company financial distress or failure is essential to protect each stakeholder’s interests. A number of failure prediction models have been developed, based on various techniques. The most common models use financial ratio analysis to diagnose whether the company is likely to succeed or fail in future. Financial data constitutes the most significant element in monitoring the performance of a firm and in predicting the trend toward failure.
Financial figures can therefore be considered as an indicator in predicting the possibility of failure. However a number of analysts have found that the inclusion of non-financial variables to aid in the prediction of company failure is very important as it highlights certain issues that are not observable in financial information.

The early detection of a company’s financial distress is critical as it could potentially increase the likelihood of turning a company around to a positive financial health. The chances of returning the company to good financial health deteriorates over time if no action is taken in time to remedy the distress situation, hence the need for a company failure predictive model.

A number of models have been developed since the mid-sixties to predict company failure. These models use a number of financial variables based on audited financial results, using a number of statistical techniques which use either single financial variables or a number of financial variables simultaneously. These models have been able to predict company failure with reasonable accuracy. Each of the models has strengths and weaknesses as well as being limited in their applicability to certain industries.

A number of studies on financial ratios as a predictor of company failure have confirmed that ratios generally can be used to predict company failure successfully. However this does not apply to all ratios and their applicability vary over time and over industries. The commonly accepted financial indicators of impending failure include: low profitability related to assets and commitments, low equity returns, poor liquidity, high gearing and high variability of income. Some of the ratios are grouped below.

Debt-repaying ability of a company:
The following ratios would be used: inventory turnover in days (or average inventory days), debt to equity ratio, interest coverage ratio (times interest earned ratio) current ratio, acid test ratio (quick ratio) and accounts receivable turnover in days.
The above ratios would show whether a company is not able or able to meet its debt obligations.
Earning ability of the company:

The following ratios would be used to assess the earning capability of the company: earnings per share, return on equity, net profit margin and gross profit margin. Profitability is very important in determining the ability of a company to operate into the future.

Financial structure:
The ratios look at the way the business is being funded whether it’s through debt or equity or a combination of both. The debt to debt plus equity ratio is mostly used. This would indicate whether a company is highly geared or not. A company which is highly geared means that it’s being financed through a bigger proportion of debt and this could prove challenging when the company is not performing well because the company could easily fail to repay its debt and thereby be liquidated. The level of gearing ratio that is regarded as healthy depends on the type of industry.

Management efficiency:
The management efficiency ratios assess how effective the company is using the assets of the company in generating sales and profit. The following ratios are used: Inventory turnover (average inventory turnover), fixed assets turnover (turnover over fixed assets), equity turnover (turnover over equity) and accounts receivable turnover (turnover over accounts receivable)
The above ratios are measured against a certain benchmark and reviewed over a period of time to assess the financial status of the company.

In some failure predictive models, the ratios are combined into a single score, called a ‘Z score’, which when the score is low it usually indicates poor financial health. The ratios are in five categories, namely liquidity, profitability, leverage, solvency, and activity. The ratios used in calculating the Z score are: working capital/total assets, retained earnings/total assets, profit before interest and tax/total assets, market value of equity/book value of debt and sales/total assets
In the next article I will discuss the non-financial variables that can be used in predicting the failure of a company.

l Stewart Jakarasi is a business and financial strategist and a lecturer in business strategy, advanced performance management and entrepreneurship. For assistance in implementing some of the concepts discussed in these articles please contact him on the following contacts:, call on +266 58881062 or WhatsApp +266 62110062.

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