Financial technology is a powerful tool in financial infrastructure, used to strengthen and smooth the delivery of financial services into the broader space. Financial technology involves software, applications, and other technologies designed to improve and automate traditional forms of financial services for businesses established in different areas. The authors aimed to explore the impact of financial technology on the digital literacy rate in India, by utilizing the poverty score as a moderating variable. The panel data analysis (PDA) has been employed in the current study. Data from 29 states and two union territories (UTs) of India were considered for three financial years, i.e., 2017–2018 to 2019–2020. The study’s findings reveal that Kisan Credit Cards (KCCs), both in terms of numbers and amount, are positively associated with the literacy rate. However, ATMs are negatively significant in association with literacy rate. Furthermore, the study’s empirical results show that KCCs and ATMs positively impact literacy when interacting with poverty scores. The study’s findings bring noteworthy implications for the government and other officials to understand the situation at the ground level of Indian states and UTs while forming new rules and policies for society’s betterment, particularly in finance and digital literacy. Additionally, the findings imply that ordinary people living in urban and rural areas of India should take advantage of financial technology and get motivated towards digital literacy.

The present study examines the impact of the Net Stable Funding Ratio (NSFR) on the performance of Indian commercial banks from 2010 to 2021. The study further investigates how the relationship between liquidity and performance varies under the influence of bank-specific factors such as ownership structure (Promoter vs. Institutional investors). Bank performance is evaluated using a two-fold approach—Profitability measures (NIMs and ROA) and NPA levels of banks. Using the Dynamic panel data regression technique, we find that the relationship between NSFR and NIMs is negative, implying that bank NIMs tend to decline as banks comply with NSFR regulation. Furthermore, the study demonstrates that the inverse relationship between NSFR and bank NIMs becomes more profound when promoters’ stakes are high. Finally, the results highlight that for banks with higher institutional holdings, NPA levels witness an upward trend as the NSFR ratio increases. From a policy perspective, study results will help policymakers understand how changes in liquidity levels impact the wider banking sector and guide them on the overall direction in which to progress with the reforms.

Purpose: The authors have attempted to reveal the impact that transparency and disclosure (T&D) and financial distress (FD) have on the valuation of banks working in India. T&D involves disclosing the firm's operational and financial performance and corporate governance practices. FD is a position in which a company or individual is not in a condition to fulfill their promise of paying their obligations on time.Design/methodology/approach: In this study, the authors have used panel data analysis (PDA) and secondary data of 34 banks working in the Indian banking sector for four financial years, i.e. 2016 to 2019.Findings: This study has established that FD and T&D have a positive and significant impact on the valuation of firms. The authors also find evidence that T&D significantly impacts the value of firms under the influence of FD.Practical implications: The present study implies that it will help firms realize how significantly the transparency level and disclosure policies impact their value in the market. Firms can understand how badly distressing situations can impact the company's whole image. This learning will encourage them to start managing their money and debts efficiently.Originality/value: The authors study has considered T&D as an independent variable and FD as a moderating variable to find the interacting impact of T&D and FD on the valuation of banks working in India. No such study has come to the authors' knowledge that has established such a relationship of variables in the study.

The present study primarily examines the impact of financial distress (FD) on the dividend policy of 33 banks working in the Indian economy from 2010 to 2019. In addition, we further explore the association between financial distress and dividend policy under the influence of shareholder activism (SHA). Using the static panel data regression technique, it is revealed that financial distress is non-linearly associated with the dividend policy of banks in an inverted U-shape. In the initial phase of a distressing situation, banks tend to have a liberal dividend policy. However, after reaching the pressure point, the banks start to squeeze dividend distribution to the stakeholders. Furthermore, the significant impact of shareholder activism has been found in the association between financial distress and the dividend payout policy of banks. From the policy perspective, the study will provide the policymakers with a clear all-round perspective of distressing situations, as the current research involves exploring the impact of distress on the dividend policy that will help the experts in basically understanding the adverse effect of financial distress and the repercussions, respectively, on the earning of the shareholders.

Purpose: Distressed companies create panic among investors. The overall effect comes on the economy and leads to a degraded image and value of all the companies operating in a country. These distressing situations are harmful to the efficient development of a country in process of development. Financial distress (FD) is when a company or individual cannot promise to pay their obligations on time. Therefore, to analyze the threatening impacts of FD, the current study aims to reveal the impact of FD on the debt ratio (proxy of capital structure) of firms working in India. Design/methodology/approach: Panel data analysis (PDA) has been used in the current study to analyze the data and generate novel results. The authors have considered the secondary data of firms present in the S&P BSE 100 index for ten financial years, i.e. 2010 to 2019. Findings: This study has established that FD has no significant impact on the firm's capital structure. In addition, it has also been proved that asset size, learner's index, market capitalization and operating profit margin (OPM) have no interacting impact on the association between FD and the capital mix of firms. Originality/value: As per the authors’ observation, no such study has been conducted till now that involves finding out the moderating impact of four different but significant factors of the business environment (assets size, learner's index, market capitalization and OPM) on the association between FD and capital structure of companies operating in a such an extensive and diverse economy.