Template-Type: ReDIF-Article 1.0 Author-Name: Rakhi Peswani Author-X-Name-First: Rakhi Author-X-Name-Last: Peswani Author-Name: Priyanka Vijay Author-X-Name-First: Priyanka Author-X-Name-Last: Vijay Title: Minimising exposure to cyber frauds in digital finance: perspectives from technology threat avoidance theory Abstract: Leveraging technological advancements related to digitisation for financial transactions is convenient, yet it is not free of challenges. Cyber frauds, particularly related to the infringement of financial data and deceitfulness related to monetary means have become largely prevalent. This study aims to revisit the technology threat avoidance theory (TTAT) by incorporating the elements of attitude and perceived financial loss, taken as essential components. This is done in the context of cyber frauds that befall in the online payment domain. Based on the constructs, an initial model was developed to show the relationships. Regression and correlation analysis were used to validate the model after the constructs went through exploratory factor analysis. Based on the data collected from 118 online payment platform users, the findings exhibit that while the perceived threat and attitude were not found to have a significant impact on avoidance motivation, perceived financial loss depicted contrasting results. This shows that attitudes towards fraud and perceived threats were not capable of motivating online payment users to avoid fraud. Journal: American J. of Finance and Accounting Pages: 76-98 Issue: 1 Volume: 9 Year: 2026 Keywords: TTAT; technology threat avoidance theory; digital finance; online transactions; attitude; perceived financial loss; fraud avoidance. File-URL: http://www.inderscience.com/link.php?id=151476 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:amerfa:v:9:y:2026:i:1:p:76-98 Template-Type: ReDIF-Article 1.0 Author-Name: Surmai Sharma Author-X-Name-First: Surmai Author-X-Name-Last: Sharma Author-Name: Roopali Sharma Author-X-Name-First: Roopali Author-X-Name-Last: Sharma Author-Name: Diksha Sinha Author-X-Name-First: Diksha Author-X-Name-Last: Sinha Title: Green bonds: driving sustainable investment in India Abstract: Tackling climate change demands unprecedented global collaboration. The World Bank Group supports developing nations in fostering sustainable solutions, particularly in finance. In India, sustainable finance - investment integrating environmental, social, and governance (ESG) factors - has emerged as essential. Green bonds, a popular fixed-income instrument, play a pivotal role in funding climate-related projects. This paper examines India's green bond market by analysing its growth relative to global trends, conducting a sector-wise review, and projecting future developments in the Indian financial landscape. Descriptive research, based on secondary data, utilises statistical tools like frequency and trend analysis to achieve its objectives. The study highlights the growing significance of green bonds in aligning India's financial sector with sustainability goals. It concludes with actionable recommendations, emphasising that green bonds have the potential to transform India's financial and fiscal frameworks, making them instrumental in driving sustainable economic growth. Journal: American J. of Finance and Accounting Pages: 35-47 Issue: 1 Volume: 9 Year: 2026 Keywords: green bonds; sustainability; Indian financial market; sustainable investment; climate change. File-URL: http://www.inderscience.com/link.php?id=151477 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:amerfa:v:9:y:2026:i:1:p:35-47 Template-Type: ReDIF-Article 1.0 Author-Name: Jasleen Kaur Author-X-Name-First: Jasleen Author-X-Name-Last: Kaur Author-Name: Amarjit Gill Author-X-Name-First: Amarjit Author-X-Name-Last: Gill Author-Name: Jatinderkumar R. Saini Author-X-Name-First: Jatinderkumar R. Author-X-Name-Last: Saini Title: An integrated bibliometric and content analysis of financial natural language processing: advancements and challenges Abstract: Financial natural language processing (NLP) is increasingly essential for analysing unstructured financial text to support improved decision-making. While prior studies identified key applications, but lacked a comprehensive analysis of influential works, trends and guiding theories, a gap this study addresses. Using bibliometric and content analysis, this research examines 684 Financial NLP articles from WoS (1999-2025) to map publication trends, influential authors, collaborations, and themes. An in-depth analysis of 105 high-impact studies is conducted to identify dominant methodologies, applications, and theories. The findings reveal a significant rise in Financial NLP research after 2020, with an annual growth rate of 4.32%, highlighting major applications such as sentiment analysis, risk assessment, fraud detection, and algorithmic trading. While deep learning models remain dominant, emerging frontiers include explainable artificial intelligence, large language models, and real-time financial analytics. This study provides insights for academics, policymakers, and practitioners, laying a foundation for future research. Journal: American J. of Finance and Accounting Pages: 48-75 Issue: 1 Volume: 9 Year: 2026 Keywords: finance; NLC; natural language processing; sentiment analysis; machine learning; financial forecasting; bibliometric analysis; stock market. File-URL: http://www.inderscience.com/link.php?id=151478 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:amerfa:v:9:y:2026:i:1:p:48-75 Template-Type: ReDIF-Article 1.0 Author-Name: Mustafa Faza Author-X-Name-First: Mustafa Author-X-Name-Last: Faza Author-Name: Nemer Badwan Author-X-Name-First: Nemer Author-X-Name-Last: Badwan Title: The mediating role of accounting information systems between big data and financial performance: empirical evidence from a developing market Abstract: This paper investigates the mediating role of the rate of quality of accounting information systems. An overview of earlier research in this area was carried out by the researchers. By consulting relevant books, journals, theses, and accounting standards, the researcher employed the deductive method to examine and evaluate earlier big data research projects. When performing the fieldwork and evaluating the statistical hypotheses pertaining to the investigation of the connection between big data technology use and businesses' financial performance, the researcher used an inductive approach. The results demonstrate a statistically significant relationship between the advancement of accounting information systems and the improvement of financial performance in big data technology. Big data analytics positively affects the rate of return on assets. The evidence supporting the existence of a statistically significant relationship between big data technology use and improved financial performance reflects this relationship. This study contributes to the body of literature by showing how the use of big data changes the procedures for preparing the final accounts and fairly presents them, especially the financial position, which in turn increases investor confidence. Journal: American J. of Finance and Accounting Pages: 1-34 Issue: 1 Volume: 9 Year: 2026 Keywords: accounting information systems; big data technology; financial performance; return on assets; return on equity; developing market. File-URL: http://www.inderscience.com/link.php?id=151479 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:amerfa:v:9:y:2026:i:1:p:1-34