Digital financial inclusion in 2024: bibliometric analysis of prevailing and emerging trends
DOI:
https://doi.org/10.29105/vtga12.1-1279Keywords:
Digital financial inclusion, Bibliometric analysis, Scopus, LLM , NLPAbstract
This research aims to understand the predominant and emerging research areas in digital financial inclusion worldwide by 2024, as well as to identify the statistical tools most frequently used in the articles evaluated. This study is a bibliometric review of the literature published in the Scopus database, using Large Language Models (LLM) and Natural Language Processing (NLP) tools. The central research topics were: Digital Financial Inclusion (DFI) and Fintech, and how DFI influences socioeconomic development. The geographic focus of the sample reveals that low- and middle-income countries (Brazil, Russia, India, China, South Africa, Pakistan, Indonesia, Bangladesh and Argentina) are the ones studied this year. The most used statistical models are Probit, Generalized Method of Moments (GMM), and Dynamic Panel Models. DFI is a global concept that has generated growing interest in the last five years; however, no documented articles for our region were found in this sample. Therefore, if DFI promotes the development of a country, it would be advisable for such research to be conducted in depth in Mexico.
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