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Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.

Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.

Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.

Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.

Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).

We develop and test an innovative approach to teaching financial statement analysis (FSA) and assessing student learning outcomes based on making complex stock investment decisions compared to professional analysts. We train students to apply FSA and emphasize interdisciplinary factors and high integrative complexity. Our innovative FSA teaching approach, which we apply in an MBA financial reporting course, involves the instructor lecturing on FSA as a tool for integrative and complex decision making, students researching and applying FSA to public companies, and presenting the rationale for individual and group stock investment decisions. The instructor gives high-quality and timely feedback on the students’ application of FSA with a focus on investment judgments involving critical thinking, problem-solving, and teamwork skills. Our detailed efficacy analysis shows that our FSA teaching approach is effective. Students who perceive a public company to have credible management, effective competitive strategy, and an acceptable level of financial flexibility make comparable individual and group stock investment decisions as professional analysts.

This review shows the systematic and bibliometric review of 361 papers on the impact of corporate social responsibility on firm performance from 2013 to 2023. The aim of this review is to research the development trends of women’s financial inclusion and women’s financial literacy during this period. The outcomes show that the issue of women’s financial literacy and women’s financial inclusion is particularly highlighted by scholars since 2019, especially for 2021 and 2022. This review focusses on two aspects of analysis: publish performance and content. In terms of published performance analysis, the publication information of papers is analysed to understand the publication trends and author’s research trends in this decade, and bibliometric maps are generated using VOS-viewer software. The bibliometric map shows that India and the USA are in the middle of the map which shows that the authors from these two nations have strong correlations with other authors. For the content analysis, we used VOS-viewer software to analyse the content of the title and abstract, the outcomes reveal three main streams about financial literacy and financial inclusion for women, especially in rural regions in developing economics and the suggestions for policymakers and government. This review attempts to cover the systematic and bibliometric analysis by presenting findings through analysis of selected papers, which highlights some possible gaps and opportunities in the literature along with a scope of directions for future research.

Purpose: FinTech is exploding all over the world. FinTech companies play a critical role in growing the banking industry. This chapter reviews existing literature on FinTech in banking, particularly its publication trend, journal productivity and impact, affiliated organisations and related themes.

Need for the Study: FinTech is reshaping the banking sector as banks move towards digitisation. FinTech has eliminated the need for paper, reduced the requirement for physical presence, and destroyed the necessity for cash. Several researchers have studied the features and benefits of FinTech technologies in the banking field. So, there is a need to analyse the available literature to identify the scope of further research in this field.

Methodology: For a comprehensive review, Bibliometric and content analysis of 77 open access green articles collected through the structured database of ‘Dimensions’ is done. These articles are published in the UGC Journal List Group II.

Findings: It is revealed that the execution of FinTech is continuously increasing in the banking sector, which has resulted in automation in various banking activities. The study revolves around technology and Banking, Financial Inclusion and Growth, and the Impact of the Financial Crisis on Banking and Peer-to-Peer (P2P) lending.

Practical Implications: The conclusions of this study can help academia and industry improve their understanding of FinTech in Banking, specifically its publication trend, geographical distribution, and creation of coherent themes. Careful analysis of collected articles will help to explore the scope of further research.

Risk reporting in financial reports has a positive impact on the company and its stakeholders. The purpose of this research is to present a literature review using the bibliometric method with the title we used is Risk Reporting, and the keywords are risk disclosure, risk reporting, stakeholders, and stakeholder theory. Data processing in this chapter uses Publish or Perish (PoP) software and Vos Viewers. This study uses the Google Scholar database. The researcher scanned the journal by using Scimagojr.com to view the journal quartile. Before the search was revised, there were 230 papers from 1991 to 2021 (30 years). Researchers will see the development of risk reporting from several sides, such as the country of origin of the researcher, the type of industry that reports risk, the research methods that have been used so far, and the analysis used for reporting risk.

This study investigates the efficiency of value relevance and faithful representation when stock market price derivates from its firm value to the investigated IT companies listed in FTSE Taiwan 50. The empirical investigation reveals one financial indicators: Return on equity (ROE) has explanatory ability among seven financial indicators, earnings per share (EPS), book value (BV), dividend yield (Div.), price–earnings ratio (P/E), ROE, return on assets (ROA), and return on operating asset (ROOA) to both sampled companies, United Microelectronics Corporation, UMC, (2303) and Taiwan Semiconductor Manufacturing Company Limited, TSMC, (2330). Furthermore, the empirical results indicate that the higher order moments, skewness and kurtosis, of price deviation do not provide a reliable prediction or explanatory power for stock price trends.

This chapter examines the impact of macroeconomic factors on the financial performance of Chinese companies. Using multiple regression analysis, the study finds that gross domestic product (GDP) growth rate, inflation rate, interest rate, exchange rate, and government expenditure are significant predictors of the financial performance of Chinese companies. The results show that GDP growth rate, leverage, size, liquidity, profitability, and growth in sales all have significant positive impacts on financial performance, while growth in assets has a negative impact. The study provides insights into the impact of macroeconomic factors on the financial performance of Chinese companies. Policymakers and investors should take these findings into account when making decisions about economic policies and investments, and companies operating in China should be aware of the potential impact of these factors on their financial performance and look for ways to manage them effectively. The chapter also includes a model specification test and a robustness test to validate the accuracy of the results. The findings have important guiding significance for policy makers and investors in making economic policies and investment decisions. However, the study has limitations such as the use of horizontal panel data and the limited data sources used.

The financial sector’s growing interest in leveraging artificial intelligence (AI) for forecasting has been noted in recent years. In this chapter, we delve into the application of AI in financial forecasting within Indonesia’s stock market. Our primary focus is to assess how AI’s prediction potential can impact investors and financial regulators in this context. Our review spans existing literature on AI and financial forecasting, recent developments in the Indonesian stock market, and ethical and regulatory concerns that surround AI in finance. Our analysis indicates that AI can enhance forecast accuracy in Indonesia’s stock exchange; however, we must also consider limitations and challenges.

The chapter explores the challenges in the financial education of the new generation under the influence of digital transformation, building awareness, and compliance with the new model of society. The rapid development of technology significantly influences our daily lives, thus making us look at the progress of various processes differently, thus facilitating the social and professional performance of subjects. The need for a comprehensive, fast, and logical personality is growing in a society that can analyse a set of different interconnections, draw logical conclusions, and assess risks. The impact of technology is particularly felt in educating future financiers, as accounting, financial analysis, and financial management decision-making have long been unthinkable without the skills to use various computer programmes, big data processing, and visualisation of financial information using the latest information technology tools. The survey was organised to collect data from student questionnaires. The questionnaire analysis allows for assessing students’ digital competences, advantages and drawbacks of the digitalisation process, and university challenges in the digital transformation process as well as detecting the areas that require additional attention to make digital transformation effective. Digital transformation significantly changes the ecosystem, and the level of students’ abilities and skills is also a variable. Therefore, it is important to identify the readiness of the participants in the higher education system for new challenges and to use the limited resources as efficiently as possible to prepare the financial specialists necessary for the development of society.