Impact of accounting standards on financial models evaluating the economic stability of enterprise

Abstract

Financial models for assessing the economic stability of an enterprise are typical by being created on empirical economic data. The test and verification samples on which they were designed contain the accounting information of selected businesses. This accounting information has been recorded, aggregated and consolidated in accordance with the accounting standards that an entity uses as a result of local legislation requirements or voluntarily. The purpose of bankruptcy models is, on the basis of accounting information, to designate an enterprise as financially sound or an enterprise that displays signs of bankruptcy. We can also use selected financial analysis indicators that can also mark the analyzed business as bankrupt or financially sound. In business practice, however, it is common for a financial indicator to show good value (for example ratios of profitability or activity), but another financial indicator shows negative values (for example ratios of debt, liquidity). In this case, the financial analyst has contradictory indications and cannot make a clear decision on the financial condition of the underlying undertaking. On the other hand, there is the benefit of one result, which provides bankruptcy models. Given that there are different accounting standards in different countries in the world, it can be assumed that even the bankruptcy model will show a different resulting valuation due to differences in input data from different accounting standards. Or is not it? Is it possible that the positive increase in the value of one ratio indicator contained in the bankruptcy model will offset the negative decline of another one? This case study works with accounting data of 13 enterprises, it compares the results of the financial bankruptcy model Z'score and IN05. The investigation revealed that although the models operate with different input values of the different accounting standards, the results did not show statistically significant differences.