This bibliometric review examines the research state of artificial intelligence (AI) and machine learning (ML) applications in the Banking, Financial Services, and Insurance (BFSI) sector. The study focuses on Scopus-indexed articles to identify key research clusters. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, 39,498 articles were screened, resulting in 1045 articles meeting the inclusion criteria. N-gram analysis identified 177 unique terms in the article titles and abstracts. Co-occurrence analysis revealed nine distinct clusters covering fintech, risk management, anti-money laundering, and actuarial science, among others. These clusters offer a comprehensive overview of the multifaceted research landscape. The identified clusters can guide future research and inform study design. Policymakers, researchers, and practitioners in the BFSI sector can benefit from the study’s findings, which identify research gaps and opportunities. This study contributes to the growing literature on bibliometrics, providing insights into AI and ML applications in the BFSI sector. The findings have practical implications, advancing our understanding of AI and ML’s role in benefiting academia and industry.

Research background: The realization of United Nations Sustainable Development Goals (SDGs) 8 hinges on the sustained growth of both the economy and the global employment outlook. In order to ensure progress in fostering inclusive and equitable growth and employment opportunities, it is essential to undertake a comprehensive analysis of the SDG findings across all relevant subtargets. Purpose of the article: This study provides an in-depth analysis of the research surrounding SDG 8 (Decent Work and Economic Growth), emphasizing its pivotal role in sustainable development. Methods: Utilizing the PRISMA framework and BERTopic method, it explores the intricate interconnections between SDG 8 and other goals, such as reducing inequalities (SDG 10), clean energy (SDG 7), climate action (SDG 13), poverty alleviation (SDG 1), and innovation and infrastructure (SDG 9). Findings & value added: The findings emphasize the importance of subtarget 8.1 (sustained per capita growth) and subtarget 8.5 (full employment and decent work for all). Additionally, the study underscores the need for policies supporting resource efficiency and sustainable consumption (subtarget 8.4), while green innovation and the digital economy are strongly linked to subtarget 8.2 (enhanced productivity through technological upgrading). Ensuring that economic growth is inclusive and equitable, as outlined in subtarget 8.3, is crucial for reducing inequalities. Policymakers must balance economic growth with environmental sustainability, promoting decent work conditions (subtarget 8.8) and adopting green technologies. These findings offer valuable insights for advancing SDG 8, ensuring that economic progress benefits all segments of society while safeguarding natural resources and fostering long-term prosperity.

Microfinance has gained significant attention as a social innovation, offering flexible and low-cost financial services to households who are otherwise excluded from formal financial services. Over the years, numerous research works have expanded the knowledge base of microfinance. Applying bibliometrics, we summarise findings from 1599 articles published between 1987 and 2022. Our performance analysis reveals insights into the research trend, including its geographical distribution, the theories under examination, and the most influential publications. More importantly, the knowledge foundation and thematic analysis categorize microfinance research into three broad themes, viz. impact of microfinance, management of microfinance and performance and efficiency of microfinance. Furthermore, we trace the evolution of various research topics and forecast future trends using periodical average publication years over time. This study, therefore, serves as a valuable reference in microfinance research both for new researchers and seasoned academics, as well as policymakers, providing insights into research trends, seminal works, and future directions.

Purpose: Post-independence, the rural credit market in India has undergone significant structural changes in order to enhance the availability and efficient use of credit. The purpose of this paper is to understand the challenges and changes in the Indian rural credit market in the post-independence period. Design/methodology/approach: Using data from the All India Debt and Investment Survey conducted by the National Sample Survey Organisation of the Government of India from 1971–1972 to 2012 and Reserve Bank of India in 1951–1952 and 1961–1962, the study focuses on three important aspect of rural credit market, i.e. the availability, sources and uses of credit. The analysis is based on both the national and state level data and uses the decadal growth rates to explain the changes in the rural credit market. Findings: Availability of credit, in terms of volume and number of households indebted, has increased substantially. However, the sharp rise in outstanding debt is a matter of concern. The share of credit from institutional agencies has seen a continuous decline post liberalisation. The non-institutional agencies, particularly the professional moneylenders, continue to be the most preferred sources of credit owing to their flexible nature of operation. Interesting, microfinance has emerged as a major source of credit particularly for the poor rural households. The rise in credit usage for non-income generating activities amongst poor households is another important concern. Originality/value: The study highlights some of the most important features and characteristics associated with the Indian rural credit market. An understanding of these issues would provide valuable insight for shaping the future policy responses.

Purpose: The Indian microfinance industry witnessed one of the fastest growths in the recent times. However, the striking feature of this growth is that the Microfinance Institutions (MFIs) are concentrated only in some specific regions of the country. There is a huge geographical skew in the distribution of the MFIs. In this paper, an attempt has been made to explain these geographical skew by using the macro variables of the states. The objective of the study is to identify the causes for this regional disparity in the growth of MFIs. Design/methodology/approach: We try to explain the level of penetration of microfinance in the states by using regression models. Findings: Our analysis suggests that state-level macro factors are significant in explaining the geographical skew. MFIs in India have concentrated in states which are richer, have good rural infrastructure, but lack in adequate banking facility, and have low human capital. Originality/value: The study provides an insight which would help in framing the necessary regulations to ensure that MFIs operate in all regions of the country.