Accounting can be regulated using either a principle-based or rule-based approach; however, profit determined for taxes purposes is invariably subject to rigorous regulation, permitting minimal flexibility. Entities are strongly motivated to utilize same or highly similar tax figures for financial accounting and tax purposes, as it reduces costs and effort. Nevertheless, this form of tax-book conformity frequently results in decreased financial reporting quality, as proven by prior studies. In numerous jurisdictions, governments are developing simplified accounting systems that utilize figures established by accounting regulations, as this facilitates accurate tax calculations and enables entities to optimize efforts and expenses in preparing financial statements. However, these systems result in lower-quality financial statements, which consequently reduce transparency and makes decision-making. more complicated and less accurate. This study examines a specific example from Hungary where a simplified accounting system was introduced in conformity with tax regulations; nonetheless, the principle of true and fair view was replaced by standardization and uniformity. The research investigates if this tradeoff is acceptable as organizations utilizing this legislation (qualifying entities) are those whose scale suggests that such simplification will not significantly compromise public interest. The study reveals that in Hungary, smaller entities typically do not make significant changes to determine their taxable earnings. The introduction of this system is justifiable given the regulations available for smaller organizations. 

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

Several studies have explored green economy and the needs for improvement on the standard of living among low-income families or households in many developing countries including Bangladesh. Similarly, there is an emphasis on economic growth and vision 2030 is regarded stressed. Nonetheless, there is less attention in exploring green economy in propelling sustainable financial inclusion among low-income families and households in Bangladesh in order to attain vision 2030 and overall economic growth.  The primary objective is to explore green economy in fostering sustainable financial inclusion among low-income families and households in Bangladesh in enhancing economic growth and vision 2030 in Bangladesh. Content Analysis (CA) and systematic literature review (SLR) as an integral part of qualitative research. Secondary data were gathered through different sources such as: Web of Science (WOS), related journals, published references, research papers, library sources and reports. The results indicated that poverty is a prime challenge impeding sustainable financial inclusion among low-income families and households in Bangladesh. The study has further established the potential of green economy in improving well-beings and social fairness in fostering sustainable and inclusive finance among families or households with low-income in the country. The paper also highlighted the necessity of implementing policy relating to vision 2030 by enhancing sustainable and inclusive finance among low-income households in particular and overall economic growth in the country in general. In conclusion, it has been reiterated that green economy has been a mechanism for achieving sustainable development in general and poverty eradication among low-income households in Bangladesh. It is therefore suggested that the government and economic policymakers should provide enabling environment for improving green economy among low-income households in achieving Vision 2030 and overall economic growth in the country.