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Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

This paper examines whether financial distress is associated with tax avoidance and whether the COVID-19 pandemic moderates such association.

The sample covers 38,958 firm-year observations from 32 countries during the period 2015–2020. Financial distress is measured using the ZSCORE by Altman (1968), while tax avoidance is based on the book-tax difference.

Financially distressed firms exhibit low tax avoidance pre- and during the pandemic periods. The authors find higher tax avoidance during the pandemic compared to the pre-pandemic period, but the pandemic enhances the negative relationship between financial distress and tax avoidance.

The study offers evidence on how financial distress drives firms to engage in more tax avoidance when firms globally encountered various levels of financial difficulty sparked by the economic challenges of the COVID-19 pandemic.

The findings provide insights to policymakers on the need to monitor and incentivise financially distressed firms, especially during economic challenges due to pandemic.

This study adds to the limited, albeit important, evidence on the joint effect of the COVID-19 pandemic and financial distress on tax avoidance.

This study investigated the visibility of carbon emissions allowances accounting in the financial reports of 32 clean development mechanism (CDM) projects in the UAE to uncover the obstacles to setting consistent standards for carbon emission accounting. As carbon emissions are monetized as credits, consistent accounting standards can aid decision-makers in the development of carbon emission mitigation strategies.

This study used a grounded theoretical framework for exploring the terms used in the policy documents of international accounting bodies regarding accounting standards and guidelines for carbon emission credits. Raw qualitative data were gathered, and an inductive approach was used by analyzing documents from various sources using the qualitative data text analysis software QDA Miner 6.

The findings showed that the financial statement reports of the corporations did not include disclosure of the carbon credit account. This omission was due to the lack of global standardization of carbon credit accounts and emission allowance recognition. This may hinder the production of a comprehensive report containing accurate and valuable financial information relevant to all stakeholders.

The study is among the first to use a grounded theoretical framework to investigate whether corporations are applying common standards and guidelines for carbon emissions accounting.

This study analyses to what extent politicians use public sector entities' financial statements along with the politicians' perceptions of the usefulness of such statements in the politicians' decision-making. The authors analyze financial statements' use and usefulness when the statements are prepared on a modified accrual basis and in the setting where there is the intention of full accrual accounting adoption. In addition, this study provides information about the use of the individual components of financial statements and investigates the reasons why the statements may not be used.

This study was conducted using a questionnaire. The authors surveyed politicians that are members of Croatian public sector bodies. To conduct this research, the politicians were contacted by telephone over the period from February to April 2022.

The findings of this study are of potential interest to researchers, regulators and policy makers. The findings show that most politicians use financial statements, but the politicians' perception of the statements' usefulness when the statements are prepared on a modified accrual accounting basis is greater than the politicians' actual use of the statements. The findings also show that in the process of making decisions, politicians use the selected financial statements that contain information of interest to the politicians; that the politicians tend to gravitate to the use of reports on revenue, expenses, receipts and expenditure prepared on modified accrual bases which are closer to budgetary reporting; that the politicians use the information that supports the politicians' sphere of responsibility as enforced by legislation.

This study provides insights into the use and usefulness of financial statements in public sector setting where modified accrual accounting is used to prepare the statements and reports. This study provides additional evidence on the significance of legal setting to the financial reporting in public sector.

An intractable effect of revenue and expense recognition based on tax regulation and accounting rules is unresolved and may be manageable only by reducing the value of deferred taxes. Therefore, in this study, the authors examined the relationship between the International Accounting Standard 12 (IAS 12) and deferred income taxes associated with tax and accounting rules.

The authors used a large sample of balanced data from 144 firms across 1992–2019. To mitigate the problem of superfluous results, the authors used the same number of firms and years for pre- and post-IAS 12 periods. The authors employed robust econometric estimations to establish the impact of IAS 12 on deferred tax.

The regression results show that deferred tax assets decreased significantly, whereas deferred tax liabilities increased significantly, in the post-IAS 12 period. These contrasting results imply that IAS 12 implementation has increased conservatism and prudence in financial reporting. However, the authors find that the increase in deferred tax assets post-IAS 12 is value destructive, suggesting that its implementation has unintended consequences. The results are robust to alternative measurements and econometric identification strategies.

While prior studies have explored topics such as deferred tax measurement and the impact of income and expense recognition, the authors specifically analyzed how IAS 12 affects deferred taxes and their effect on the market valuation. The authors find that certain accounting standards may not be relevant to the capital market.

The paper aims to provide empirical evidence of the impact of IFRS adoption on the value relevance of accounting information in the emerging market of Saudi Arabia.

The sample consists of 98 non-financial listed firms operating in Saudi Arabia from 2014 to 2019, representing the years before and after IFRS adoption. The authors apply basic and extended price models to examine the value relevance of select accounting figures.

The authors findings provide evidence that accounting information is, generally, value relevant to the Saudi Arabian capital market. However, mixed results exist for particular accounting variables. Both earnings and cash flows are value-relevant in the period before and after IFRS adoption; equity is only relevant in the post-adoption period. Furthermore, IFRS adoption also increases the explanatory power of earnings. An increase in the value relevance of earnings and equity hurts the value relevance of cash flows. The effects are moderated by leverage and dividend policy.

The authors contribute to the ongoing discussion of the economic effects of IFRS adoption in emerging markets. The empirical findings show that initial concerns about IFRS adoption, as reflected by the negative coefficient within the regression analysis, are mitigated once the usefulness of the individual accounting variables published in financial statements is investigated.

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

This study aims to fill the research gap regarding the usability of group reporting information in the central government. It answers the question of how the consolidated information should be formed to benefit the real needs of governmental information users.

The empirical research is based on a survey and interviews among key internal preparers and users in the central government sector in the case country, Finland.

Results show that the private sector approach regarding consolidation is not appropriately transferable to the central government sector. The key stakeholders identified several economic and financial reporting needs that exceed what formal Consolidated Financial Statement (CFS) can offer. Consolidation is needed but not according to the extensive full control approach, but rather following the budgetary approach consolidating units of the legal person of the government, and further using the partial control approach for consolidating by discretion essential special purpose SOEs.

Respondents and interviewees represented governmental internal organisations, free experts, auditors and financial managers from the group entities. Politicians and citizens were not directly represented.

Research gives applicable insights into central governments planning and developing group reporting for information needs in a favourable cost-benefit ratio. Findings benefit the development of EU's EPSAS (European Public Sector Accounting Standards) project which is still incomplete.

Research recommends governments to make a thorough analysis before deciding on a new financial reporting system. A critical analysis prevents governments to waste money and resources on a reporting system not fulfilling the real needs of information users.

The value of this research is that the private sector approach in consolidation was not taken as granted. This study investigated critically and empirically the real need for consolidated information serving steering and overseeing purposes of the government's group entities.

Small- and medium-sized enterprises (SMEs) often lack adequate accounting systems and may even fail because of accounting inefficiencies. Indeed, accounting can mitigate the course of a crisis and support a troubled SME’s turnaround. Its impact on reorganization success, however, has scarcely been researched so far. Therefore, this paper aims to examine the effects of several accounting parameters, namely, the quality of accounting systems, quality of early warning systems, formal planning, the standard of financial accounting and reorganization planning on the short- and long-term success of court-supervised reorganization.

The impact of accounting on reorganization success is investigated in a sample of all SME bankruptcy cases with ten or more employees (n = 117) in Upper Austria in 2012 including data for short-term survival (in 2016) and long-term survival (in 2019).

This study found evidence that the general quality of accounting systems, the quality of early warning systems and written reorganization plans positively influence the outcomes of the analyzed court-supervised reorganizations of SMEs. In particular, the existence of a reorganization plan significantly increases the short- and long-term reorganization success by ensuring the efficient and effective use of resources in the reorganization process.

This study should increase the awareness of SMEs’ owner managers, consultants, creditors and legislators for the importance of accounting in the context of reorganization. The fact that the effect of accounting on reorganization success is less pronounced in the long-term view indicates the necessity of increasing the strategic focus in SMEs’ accounting instruments.

This study provides new evidence on the impact of specific accounting parameters on the short- and long-term success of the court-supervised reorganization of SMEs. Furthermore, this study points out the high relevance of reorganization plans for SMEs.

The purpose of this study is to evaluate the current state of forensic accounting education in the Kingdom of Saudi Arabia (KSA), as well as to identify the desired aims and skills required to practice forensic accounting as a profession. It also seeks to understand the education and skills provided by KSA forensic accounting education programs, the job skills required by professional accountants and the skills required by professional accountants' employers.

The study is exploratory in nature. A convenience base sampling approach was used to select the academicians and practitioners working in KSA. Participants were requested to fill out an electronic questionnaire and rank each statement on a 5-point Likert score. The responses were converted and analyzed using the T-test, to evaluate the inter- and intra-group trends in the data.

The study included 58 responses from practitioners and 30 from academicians. Both groups mentioned that the classroom and the Internet were their primary source of forensic accounting information, especially in professional accounting qualifications. According to the participants, most of the institutions in KSA do not offer forensic accounting courses. Nonetheless, forensic accounting is critical for strengthening the credibility of financial reporting in courtrooms. The study finds subtle inter-group differences regarding the development of an ideal curriculum for forensic accounting, which translates to a bigger difference in curriculum development and practice skills. Both groups were optimistic about the future path of forensic accounting in KSA.

The study reports critical differences between the status of forensic accounting education and the skills required to practice forensic accountancy in KSA.