Factors influencing true and fair view when preparing financial statements under IFRS: evidence from the Czech Republic

Homola, David; Paseková, Marie

doi:10.24136/eq.2020.026

Cited by 4 publications

(3 citation statements)

References 24 publications

(2 reference statements)

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“…Svabova et al (2020) proceeded similarly, however, their model achieved up to 84% classification accuracy. Homola and Pasekova (2020), on the other hand, focused on accounting irregularities of Czech companies accounting under IFRS, while their frequency is not regular according to this analysis. Istrate et al (2015) add that the financial accounting quality in Romanian companies has increased after these companies have passed IFRS standards and started to be audited by CRA-s from the Big Four.…”

Section: Literature Reviewmentioning

confidence: 94%

Does the life cycle affect earnings management and bankruptcy?

et al. 2021

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Research background: Deteriorating economic conditions and a negative outlook increase the pressure on financial management and the need to show high financial performance. According to Positive Accounting Theory, the growing risk of bankruptcy is associated with the phenomenon of earnings management. Bankruptcy risk and the quality of reported profits, along with other aspects of financial performance, vary throughout the company's life cycle. Nevertheless, these factors or their interactions are investigated only to a very small extent. Purpose of the article: The aim of this study is to clarify the impact of corporate life cycle and bankruptcy on earnings management, in order to describe behaviour of companies at different stages of corporate life cycle. Methods: A hierarchical mixed model with a random time and industry effect was chosen as appropriate because it allows the investigation of multilevel data that is not independent. The sample covers the financial indicators of more than 33,000 Central European companies from 2015?2019. The non-sequential Dickinson model, company age, and three models of accrual earnings management were used as proxies for the company's life cycle and quality of reported profit. Findings & value added: Earnings management and bankruptcy risk have a U-shape, indicating that financially distressed firms reduce reported accounting profit at the Introduction, Decline and, to a lesser extent, at the Growth stage. Slovak and Czech companies manipulate profits to a similar extent, Hungarian companies increase accounting profit to a greatest extent than the surveyed countries by controlling bankruptcy ? life cycle effect; however, the variability of accounting manipulations across industries has not been demonstrated. These findings imply that start-ups and declining businesses provide crooked financial statements to obtain more favourable debt covenants, and estimating discretionary accruals using life-cycle subsamples can improve the predictive power of accrual earnings management models.

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Section: Literature Reviewmentioning

confidence: 94%

Does the life cycle affect earnings management and bankruptcy?

et al. 2021

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“…This fact is taken into account also by sophisticated detection techniques of opportunistic earnings management and fraudulent financial reporting. In this connection, an irreplaceable role is also played by the quality of accounting standards, whether of national or international character (Homola & Pasekova, 2020). Marinakis (2011) states that there are three main research approaches to this issue -conditional distribution models, discretionary accruals models, and specific accruals models.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The issue of earnings manipulation is a relatively frequently examined problem between academics and experts directly from practice (Homola & Pasekova, 2020;Pasekova et al, 2019). At present, there are various statistical methods or techniques of data collection that try to identify hidden, unusual or divergent patterns indicating financial fraud.…”

Section: Introductionmentioning

confidence: 99%

Detecting earnings manipulation and fraudulent financial reporting in Slovakia

Švábová

Kramárová

Chutka

et al. 2020

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Research background: Misleading financial reporting has a negative impact on all stakeholders since financial records are the primary source of information on financial stability, economic activity, and financial health of any company. The handling of them is primarily the responsibility of managers or owners and reasons for doing so may differ. Their common denominator is the artificial creation of information asymmetry to get different types of benefits. It is, therefore, logical that the issue of detecting opportunistic earnings management comes to the fore. Purpose of the article: The purpose of the study is to create a discriminant model of the detection of earnings manipulators in the conditions of the Slovak economy. Methods: We used the discriminant analysis to create a model to identify fraudulent companies, based on the real data on companies that were convicted from misleading financial reporting in connection with tax fraud in the years 2009–2018. The model is inspired by the Beneish model, which is one of the most applied fraud detection methods at all. Findings & Value added: In order to achieve more accurate detection results, we extended the original model by taking into account the values of indicators from three consecutive years, i.e. by taking into account the development of the potential tendency of companies to be involved in opportunistic earnings management. Our model correctly identified 86.4% of fraudulent companies and overall reaches 84.1% classification ability. Both models were applied on empirical data on 1,900 Slovak companies from the years 2016–2018, while their overlap was 32.7% for fraudulent companies and 38.4% for non-fraud companies. This is a very useful result, as the application of both models rein-forces the results obtained and the identical classification of the company into fraudulent indicates that the manipulation of earnings occurs with a high probability.

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Application of selected data mining techniques in unintentional accounting error detection

Papík

Papíková

2021

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Research background: Even though unintentional accounting errors leading to financial restatements look like less serious distortion of publicly available information, it has been shown that financial restatements impacts on financial markets are similar to intentional fraudulent activities. Unintentional accounting errors leading to financial restatements then affect value of company shares in the short run which negatively impacts all shareholders. Purpose of the article: The aim of this manuscript is to predict unintentional accounting errors leading to financial restatements based on information from financial statements of companies. The manuscript analysis if financial statements include sufficient information which would allow detection of unintentional accounting errors. Methods: Method of classification and regression trees (decision tree) and random forest have been used in this manuscript to fulfill the aim of this manuscript. Data sample has consisted of 400 items from financial statements of 80 selected international companies. The results of developed prediction models have been compared and explained based on their accuracy, sensitivity, specificity, precision and F1 score. Statistical relationship among variables has been tested by correlation analysis. Differences between the group of companies with and without unintentional accounting error have been tested by means of Kruskal-Wallis test. Differences among the models have been tested by Levene and T-tests. Findings & value added: The results of the analysis have provided evidence that it is possible to detect unintentional accounting errors with high levels of accuracy based on financial ratios (rather than the Beneish variables) and by application of random forest method (rather than classification and regression tree method).

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Factors influencing true and fair view when preparing financial statements under IFRS: evidence from the Czech Republic

Cited by 4 publications

References 24 publications

Does the life cycle affect earnings management and bankruptcy?

Does the life cycle affect earnings management and bankruptcy?

Detecting earnings manipulation and fraudulent financial reporting in Slovakia

Application of selected data mining techniques in unintentional accounting error detection

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