This study aims to map and evaluate the intellectual landscape of financial technology (FinTech) research from 2015 to 2025, highlighting its thematic evolution, influential contributors and research gaps to guide future scholarly and practical engagement.
A bibliometric analysis was conducted using Scopus-indexed publications with FinTech-related keywords in article titles. Tools such as MS Excel, Harzing's Publish or Perish and VOSviewer were employed to assess publication trends, citation metrics and thematic clusters.
The analysis identified a consistent growth in FinTech research post-2008. China leads in publication output, followed by India, the USA, the United Kingdom and Indonesia. Elsevier is the most prolific publisher, with Amity University and Bina Nusantara University as the top contributing institutions. The study extracted 23 thematic clusters, including financial inclusion, data analytics, regulatory compliance and sustainability and highlighted influential works and author networks.
The analysis is limited to Scopus-indexed documents and title-based keyword searches, potentially excluding relevant studies found in other databases or indexed under different metadata fields.
Findings can support industry stakeholders in aligning strategic initiatives with current research trends and technological developments in FinTech.
By addressing financial inclusion and regulatory dynamics, the study informs policies that can foster equitable access to financial services through FinTech innovations.
This study offers a comprehensive and systematic bibliometric overview of FinTech research over a decade, presenting novel insights into its development, current state and future directions.
1. Introduction
Financial technology (FinTech) is an industry that utilizes sophisticated information technologies such as the Internet of Things, cloud computing and big data to improve and broaden financial products and service platforms (Nakashima, 2018). The Financial Stability Board (FSB) defines FinTech as the amalgamation of cutting-edge technologies that revolutionize the financial sector, including artificial intelligence (AI), blockchain and big data (Geidam & Yahaya, 2025). The amalgamation of these technologies propels the advancement of novel business models, the utilization of developing technology and the formulation of sophisticated financial products and services (Gupta, Wajid, & Gaur, 2023). This integration drives the development of the financial system, enhancing efficiency, accessibility and competitiveness (Ryu, 2018). Furthermore, FinTech includes technological firms rising as competitors to conventional banks and financial institutions. These startups provide diverse services, encompassing mobile payment solutions, crowdfunding platforms, online portfolio management and international money transfer services (Ahmi, Husni Hamzah, Tapa, & Husni Hamzah, 2020). In addition, Amnas, Selvam, Raja, Santhoshkumar, and Parayitam (2023) underscores that FinTech significantly influences the financial sector, presenting potential benefits, including improved risk management, enhanced consumer experiences and greater financial inclusion.
The fast advancement of information technology (IT) has accelerated the quick growth of financial technology, referred to as FinTech. This domain, which connects finance and technology, has garnered considerable attention recently (Lee & Shin, 2018). The name “FinTech” merges “financial” and “technology,” emphasizing the seamless integration of technological developments in financial services. FinTech provides significant opportunities to empower individuals by improving access to financial services and resources through increased transparency, cost reduction, elimination of intermediaries and enhanced accessibility of financial information (Yan, Siddik, Akter, & Dong, 2021; Zavolokina, Dolata, & Schwabe, 2016). FinTech encompasses innovative solutions that optimize financial service processes by tailoring technology to diverse business needs.
FinTech denotes a technological evolution that amalgamates finance with information and communication technology (ICT), establishing itself as a vital innovation within the financial sector (Lee & Shin, 2018; Roh, Yang, Xiao, & Park, 2022). FinTech is “any technology-enabled financial innovation that develops new business models, applications, processes or products, influencing financial markets and institutions and enhancing the delivery of financial services (Shiau, Yuan, Pu, Ray, & Chen, 2020)”.
Furthermore, FinTech is often perceived as the convergence of financial services and IT. Moreover, development in both domains, especially with the emergence of Industry 4.0 technologies, notably the Internet of Things (IoT), cybersecurity, cloud computing, blockchain, big data and analytics, has significantly impacted the evolution of FinTech. As a result, numerous scholars and researchers focus on investigating diverse challenges relevant to this domain. This article seeks to provide an overview of the existing state of FinTech research and analyze its expansion within the academic realm.
This study aims to delineate patterns in previous research on FinTech and align these findings with the global advancement of the field. The document is organized as follows: Initially, a literature review is presented, encompassing an overview of bibliometric analysis and prior studies linked to FinTech. A comprehensive exposition of the methodologies utilized in this work ensues. The following analysis and findings section presents the results obtained from the documents gathered from the Scopus database. The conclusion section encapsulates the study, addresses its limitations and provides recommendations for subsequent research.
1.1 Rationale
Bibliometric analysis is a robust framework for examining the dynamic and interdisciplinary nature of FinTech research (Gutiérrez-Salcedo, Martínez, Moral-Munoz, Herrera-Viedma, & Cobo, 2018). By systematically mapping its evolution, identifying research gaps and fostering collaboration, this approach advances academic understanding and informs practical applications and policy development (Lim & Kumar, 2024). Through bibliometric analysis, FinTech research can remain relevant, impactful and attuned to the demands of a rapidly transforming global financial ecosystem. This study was undertaken in response to the growing need for further research in FinTech, particularly to address the contradictory findings of prior studies. Against this backdrop, the research examines how trends and patterns in FinTech, specifically in payments, microfinance, crowdfunding and peer-to-peer lending, are presented in the literature. It aims to demonstrate how individual studies have influenced the field and how the domain has evolved. Furthermore, the study emphasizes the importance of exploring connections between constructs from methodological, theoretical and practical perspectives (Yahaya, Sabar, & Nadarajah, 2025). By leveraging bibliometric analysis, researchers can uncover interdisciplinary relationships contributing to a deeper understanding of FinTech innovation. This comprehensive approach enhances the academic discourse and facilitates meaningful insights into how various fields converge to drive advancements in FinTech.
Bibliometric research has gained significant traction within the academic community due to its effectiveness in organizing and analyzing large volumes of scholarly output (Roldan-Valadez, Salazar-Ruiz, Ibarra-Contreras, & Rios, 2019). Building on this foundation, the present study employs bibliometric analysis a quantitative and statistical approach that identifies patterns in the distribution of articles across time and space (Shi, Blainey, Sun, & Jing, 2020), to systematically review existing research on FinTech. A key objective of this study is to enhance understanding of the evolving landscape of FinTech research. The evaluation of the existing literature reveals that it is crucial to investigate recent advancements in the field. This is especially vital considering the rapid development of FinTech, which may have been neglected in previous studies. Despite the proliferation of studies on FinTech, relatively few bibliometric analyses have been conducted in this area (Ahmi et al., 2020; Asif, Sarwar, & Lodhi, 2023; Tepe, Geyikci, & Sancak, 2021). To address this gap, the present paper merges bibliometric analysis with an extensive literature review to examine the trends, patterns and developments in FinTech research. However, this study seeks to enhance understanding of the topic by addressing specific research questions and offering a framework for future research initiatives.
What are the prevailing publishing trends and the scholarly impact of research in the field of FinTech?
Which countries, institutions and authors have significantly contributed to FinTech research?
Which articles are most influential in the FinTech literature?
What are the potential future research directions within the domain of FinTech?
The findings are organized into four sections, each addressing a specific aspect of the study process or its outcomes and aiming to answer the research questions. The primary objective of this study was to gain a deeper understanding of FinTech, a field rapidly gaining global attention. Nevertheless, analyzing FinTech related articles in the Scopus database, this research also seeks to offer recommendations for future investigations in the domain. Following this introduction, Section 2 presents a literature review, focusing on bibliometric analysis and prior research on FinTech. Section 3 outlines the methodology employed in this bibliometric study. Section 4 discusses the research's key findings. Section 5 summarizes the report's key insights, while Section 6 highlights the study's limitations and suggests potential directions for future research.
2. Literature review
Bibliometric analysis has increasingly been employed across disciplines to map intellectual structures, research fronts and thematic trends (Ninkov, Frank, & Maggio, 2022; Mukherjee, Lim, Kumar, & Donthu, 2022; Ellegaard & Wallin, 2015) characterize bibliometrics as a dominant methodology for evaluating scientific research through quantitative assessments of publications, while (Song, Lei, Wu, and Chen (2023) highlight its ability to uncover collaboration and intellectual linkages via co-authorship networks, co-citation analysis and bibliographic coupling. Specialized software such as VOSviewer (Abdelwahab, Taha, Moni, & Alsayegh, 2023) enhances these analyses by enabling advanced visualization techniques, while Harzing's Publish or Perish provides robust citation-based metrics (Yahaya & Nadarajah, 2025).
The application of bibliometrics in finance and technology-related domains has gained momentum in recent years, reflecting the rapid expansion of digital finance, FinTech and innovation-driven financial services (Asif et al., 2023; Passas, 2024). Prior bibliometric studies in technology management and financial innovation have examined publication trends, research productivity and the evolution of thematic clusters, thereby establishing bibliometrics as an appropriate method for synthesizing fragmented and fast-evolving knowledge. However, within the FinTech domain, existing reviews have either remained descriptive or limited in scope, leaving a gap in systematically mapping influential authors, institutions, collaboration networks and thematic developments.
Organizing the literature review around these questions provides a structured foundation for the study. Publication trend analyses inform research productivity and growth trajectories (Roldan-Valadez et al., 2019). Author and institutional impact analyses highlight intellectual leadership, often measured through h-index, g-index and CiteScore (Mukherjee et al., 2022). Thematic mapping and co-word analyses reveal evolving knowledge structures, providing insights into future research opportunities (Valérie & Pierre, 2010).
Thus, bibliometrics not only facilitates descriptive mapping but also generates insights into the intellectual and structural development of FinTech research. This review justifies the methodological choice and anchors the study within existing scholarship.
3. Method
This study adopts a bibliometric analysis framework anchored in the Bibliometric Indicators Framework (Valérie & Pierre, 2010), which categorizes indicators into quantity, quality and structural dimensions. This framework provides the theoretical base for linking bibliometric techniques to the study's research questions. Specifically, quantity indicators (e.g. publication volume) inform, quality indicators (e.g. citation counts, h-index) and structural indicators (e.g. co-authorship, co-word networks).
The dataset was retrieved from the Scopus database, recognized for its comprehensive coverage of scholarly outputs in finance, management and technology (Abdelwahab et al., 2023). The search targeted publications containing “FinTech,” “FinTechs,” “fin-tech,” “Fin-Techs,” “financial technology,” “financial technologies,” “finance technology,” and “finance technologies” in their titles. Title-based searching ensures direct relevance to the domain of inquiry (Ellegaard & Wallin, 2015). The retrieval, conducted in May 2025, yielded 3,048 publications covering the period from 2015 to October 2025.
As illustrated in the PRISMA diagram, no articles were excluded from the dataset. This deliberate choice was made to ensure comprehensiveness and inclusivity, thereby avoiding subjective filtering that could introduce bias into the representation of FinTech scholarship (Yahaya & Nadarajah, 2023). By retaining the full dataset, the study enhances the robustness and reliability of its bibliometric analysis, providing a more accurate mapping of the field's intellectual structure.
A combination of bibliometric tools was employed, Microsoft Excel: Computed publication frequencies and trends. Harzing's Publish or Perish (PoP): Generated citation metrics (citations per year, h-index, g-index, CiteScore) to identify influential authors and institutions. VOSviewer: Constructed and visualized co-authorship networks, co-citation maps and co-word clusters, thereby identifying thematic structures and emerging research directions.
3.1 Bibliometric analysis
Bibliometrics is a discipline focused on the quantitative analysis of academic publishing, utilizing statistical techniques to uncover publishing trends and explore connections among scholarly works (Lim & Kumar, 2024). However, its data-driven methodology, bibliometric research examines various aspects of publications, including authorship, research themes, and funding sources, to provide insights into the dynamics of academic fields (Abdullahi, Mohamed, & Senasi, 2023; Passas, 2024).
Ahmi (2022) characterize bibliometrics as the quantitative and statistical analysis of the treatment of various topics and historical periods in published literature. Research on a particular topic can be analyzed using a bibliographic study, revealing its trends and patterns (Gutiérrez-Salcedo et al., 2018). Bibliometric analysis is frequently employed to demonstrate a study's impact on the field and its evolution over time (Ninkov et al., 2022).
Bibliometric studies frequently employ indicators such as publication type, citation frequency, authorship, work influence and geographic location (Ninkov et al., 2022). Gutiérrez-Salcedo et al. (2018) assert that bibliometric indicators can be classified into three categories: number, quality and structure. The efficacy of a researcher's work can be quantified using metrics including the total citation count, the h or g index and citation impact. The impact per publication (IPP) and impact factor (IF) are supplementary metrics of research quality (Ahmi et al., 2020; Donthu, Kumar, Mukherjee, Pandey, & Lim, 2021). Connections across publications, authors and various subjects exemplify structural indicators. Co authorship, co-citations and bibliographic linkage serve as alternative methods to monitor this indicator (Song, Wu, & Ma, 2021).
4. Past studies
The remarkable transformation in IT has been instrumental in propelling the quick expansion of FinTech (Saleem, 2021). This interdisciplinary field integrates finance and technology and has garnered significant scholarly and practical attention in recent years (Lee & Shin, 2018). Thus, examining FinTech research trends through established literature citation indices is increasingly urgent. Although some bibliometric studies on FinTech have been conducted, they frequently incorporate systematic literature reviews (Bajwa et al., 2022; Sahid, Maleh, Asemanjerdi, & Martín-Cervantes, 2023; Yahaya & Nadarajah, 2023). Nevertheless, the current literature underscores a deficiency in comprehensive bibliometric analyses that fully investigate the FinTech sector, illustrating the field's inherent complexity. With the increasing number of academic publications, bibliometric studies have become critical for categorizing and analyzing this expanding body of knowledge (Pardo-Jaramillo, Muñoz-Villamizar, Osuna, & Roncancio, 2020).
5. Information extraction
A bibliometric analysis was performed on all documents included in the study, utilizing the following methodology:
The flowchart shows three vertical text boxes representing three stages, arranged in a vertical series on the left. From top to bottom, these are labeled: “Identification”, “Screening”, and “Included”. In the “Identification” stage, the first text box reads “Identified records through the searched databases (n equals 3048), Emerald (n equals 639), Sage (n equals 284), Elsevier (n equals 528), I E E E (n equals 351), Taylor and Francis (n equals 451), Inder-science (n equals 349), and Springer (n equals 446)”. A rightward arrow from the first text box leads to the second text box labeled “FinTech”. A downward arrow from the first text box leads to the third text box labeled “Scope and Coverage”. A rightward arrow from the third text box leads to the fourth text box that reads “Database: Scopus, Search Field: FinTech, Time Frame: 2015 to 2025, Language: English, Source Type: Journal, and Document Type: Article”. A downward arrow from the third text box leads to a fifth text box in the “Screening” stage labeled “Keywords and Search String”. A rightward arrow from the fifth text box leads to the sixth text box labeled “TITLE (“FINTECH”)”. A downward arrow from the fifth text box leads to the seventh text box in the “INCLUDED” stage labeled “Data Extracted”. A rightward arrow from the seventh text box leads to the eighth text box labeled “20 May, 2025”. A downward arrow from the seventh text box leads to the ninth text box labeled “Records Identified and Screened”. A rightward arrow from the ninth text box leads to the tenth text box labeled “N equals 3048”. A downward arrow from the ninth text box leads to the eleventh text box labeled “Records Removed”. A rightward arrow from the eleventh text box leads to the twelfth text box labeled “N equals 0”. A downward arrow from the eleventh text box leads to thirteenth text box labeled “Records Included for Bibliometric Analysis”. A rightward arrow from the thirteenth text box leads to the fourteenth text box labeled “N equals 3048”.Search strategy diagram. Source: Authors' own elaboration
The flowchart shows three vertical text boxes representing three stages, arranged in a vertical series on the left. From top to bottom, these are labeled: “Identification”, “Screening”, and “Included”. In the “Identification” stage, the first text box reads “Identified records through the searched databases (n equals 3048), Emerald (n equals 639), Sage (n equals 284), Elsevier (n equals 528), I E E E (n equals 351), Taylor and Francis (n equals 451), Inder-science (n equals 349), and Springer (n equals 446)”. A rightward arrow from the first text box leads to the second text box labeled “FinTech”. A downward arrow from the first text box leads to the third text box labeled “Scope and Coverage”. A rightward arrow from the third text box leads to the fourth text box that reads “Database: Scopus, Search Field: FinTech, Time Frame: 2015 to 2025, Language: English, Source Type: Journal, and Document Type: Article”. A downward arrow from the third text box leads to a fifth text box in the “Screening” stage labeled “Keywords and Search String”. A rightward arrow from the fifth text box leads to the sixth text box labeled “TITLE (“FINTECH”)”. A downward arrow from the fifth text box leads to the seventh text box in the “INCLUDED” stage labeled “Data Extracted”. A rightward arrow from the seventh text box leads to the eighth text box labeled “20 May, 2025”. A downward arrow from the seventh text box leads to the ninth text box labeled “Records Identified and Screened”. A rightward arrow from the ninth text box leads to the tenth text box labeled “N equals 3048”. A downward arrow from the ninth text box leads to the eleventh text box labeled “Records Removed”. A rightward arrow from the eleventh text box leads to the twelfth text box labeled “N equals 0”. A downward arrow from the eleventh text box leads to thirteenth text box labeled “Records Included for Bibliometric Analysis”. A rightward arrow from the thirteenth text box leads to the fourteenth text box labeled “N equals 3048”.Search strategy diagram. Source: Authors' own elaboration
Data Analysis and Visualization: The frequency and proportion of publications were computed using Microsoft Excel 2019, with the results illustrated using suitable graphical representations.
Bibliometric Mapping: VOSviewer (version 1.6.16.0) was employed to generate and visualize bibliometric relationships, facilitating the identification of significant patterns and connections within the dataset.
Citation Metrics: Citation metrics were calculated utilizing Harzing's Publish or Perish tool, offering insights into the effect and influence of the examined documents. The search methodology is illustrated in Figure 1.
Figure 2 illustrates the yearly distribution of FinTech-related publications between 2015 and 2024. The chart reveals a steady and substantial growth in research output over the ten-year period. The number of publications rose sharply from only 6 articles in 2015 the initial phase of FinTech scholarship to 886 articles in 2024, marking the highest contribution within the study period.
The pie chart consists of 10 segments for years 2015 to 2024. The data from the pie chart is as follows: 2024: 886. 2023: 683. 2022: 490. 2021: 347. 2020: 266. 2019: 142. 2018: 141. 2017: 56. 2016: 21. 2015: 6.Total publications on FinTech and citations by year. Source: Authors' own elaboration
The pie chart consists of 10 segments for years 2015 to 2024. The data from the pie chart is as follows: 2024: 886. 2023: 683. 2022: 490. 2021: 347. 2020: 266. 2019: 142. 2018: 141. 2017: 56. 2016: 21. 2015: 6.Total publications on FinTech and citations by year. Source: Authors' own elaboration
The figure also shows a significant surge in publication activity beginning in 2020, with 347 articles, followed by a notable increase in 2021 (490), 2022 (683) and 2024 (886). Earlier years such as 2016 (21), 2017 (56), 2018 (151) and 2019 (266) recorded comparatively fewer publications, indicating the field's gradual emergence before achieving exponential growth in the later years. Overall, the figure highlights an accelerating trend in FinTech research, reflecting the growing global academic and practical interest in digital finance, technological innovation and their implications for the financial ecosystem.
6. Results
The findings of this study compellingly demonstrate the robust growth, intellectual maturity and increasing global relevance of FinTech research. By systematically analyzing publication trends, citation impact and authorship patterns, the study validates the claim that FinTech has moved beyond being an emerging niche to becoming a central pillar of financial and technological scholarship. The reliance on Scopus as the primary data source strengthens the credibility of the results, given its extensive coverage of high-quality, peer-reviewed academic output. Consequently, the bibliometric insights derived provide a reliable and comprehensive mapping of the FinTech research landscape. The annual growth trajectory from 2015 to May 2025 underscores FinTech's rapid ascendance as a globally significant research domain. The steady rise in publications, particularly the sharp increases observed in recent years, reflects the sector's dynamism and its responsiveness to technological breakthroughs such as blockchain, artificial intelligence and digital financial platforms. Far from being incidental, this growth indicates sustained scholarly engagement and an expanding recognition of FinTech's potential to transform the global financial ecosystem. The increasing percentage growth per year illustrates that FinTech is not only proliferating in research volume but is also becoming progressively entrenched in academic discourse.
Equally important is the global diffusion of FinTech scholarship. The identification of leading countries, institutions and authors confirms that FinTech research is no longer dominated by a narrow geographical base but is increasingly characterized by diverse and international contributions. This global spread is evidence of the universal applicability of FinTech innovations and their significance across varied economic and regulatory contexts. The involvement of prominent institutions and scholars highlights the consolidation of intellectual leadership in this domain, where rigorous empirical work and theoretical contributions are shaping both academic debates and policy decisions. Moreover, the classification of documents by year, country, author and institutional affiliation provides robust evidence of how the field has evolved structurally. The predominance of journal articles as the main document type confirms that FinTech research has achieved academic legitimacy, with peer-reviewed outlets serving as key vehicles for disseminating high-quality scholarship. The analysis of keywords and subject areas further demonstrates that FinTech research is deeply interdisciplinary, bridging finance, technology, economics and management studies and thereby enhancing its scholarly impact.
The authorship and citation measures incorporated into the study strengthen the argument that FinTech is now a mature and influential field of research. High citation counts and the visibility of landmark articles reveal that certain contributions have decisively shaped the intellectual trajectory of the field. These patterns indicate that FinTech scholarship is not only growing in volume but also in influence, as its findings resonate across disciplines and inform real-world applications. Taken together, the results strongly support the argument that FinTech research is on an upward trajectory of growth, diversification and academic influence. By systematically capturing these dynamics, this study not only validates the strategic significance of FinTech as a research field but also provides a reliable foundation for future scholarly inquiry. The consistent upward trends in publications and citations from 2015 to 2025 highlight a field that is expanding in scope, deepening in quality and widening in global reach, thereby affirming FinTech's pivotal role in the ongoing transformation of financial services and academic discourse alike.
6.1 Annual growth of publication
An extensive analysis of FinTech literature from 2015 to 2025 indicates a substantial increase in research activity over the past decade. Table 1 demonstrates this upward trend, showing a consistent annual growth in the number of published articles on FinTech, which reached 886 in 2025 representing 29.07% of all publications during this period. The findings reveal that studies published in 2021 achieved the highest scholarly impact, accumulating 8,174 citations and averaging 23.56 citations per article. In contrast, papers from 2015 received the fewest citations, totaling 100. Notably, 2015 marked the early stage of FinTech research, with only six publications. Since then, the field has exhibited a steady and continuous increase in research output.
Year of publication
| Year | TP | NCP | TC | C/P | C/CP | H | g |
|---|---|---|---|---|---|---|---|
| 2024 | 886 | 386 | 1,867 | 2.11 | 4.84 | 16 | 24 |
| 2023 | 683 | 500 | 5,471 | 8.01 | 10.94 | 32 | 45 |
| 2022 | 490 | 364 | 6,413 | 13.09 | 17.62 | 41 | 65 |
| 2021 | 347 | 289 | 8,174 | 23.56 | 28.28 | 48 | 82 |
| 2020 | 266 | 233 | 6,662 | 25.05 | 28.59 | 44 | 75 |
| 2019 | 142 | 131 | 5,002 | 35.23 | 38.18 | 33 | 68 |
| 2018 | 151 | 136 | 7,061 | 46.76 | 51.92 | 36 | 83 |
| 2017 | 56 | 46 | 3,318 | 59.25 | 72.13 | 21 | 46 |
| 2016 | 21 | 18 | 1,357 | 64.62 | 75.39 | 13 | 18 |
| 2015 | 6 | 3 | 100 | 16.67 | 33.33 | 2 | 3 |
Note(s): TP = total number of publications; NCP = number of cited publications; TC = total citations; C/P = average citations per publication; C/CP = average citations per cited publication; h = h-index; and g = g-index
6.2 Types of documents and sources
An extensive examination of FinTech literature from 2015 to 2025 indicates an expanding volume of research in this domain. The FinTech literature includes a variety of papers that can be classified by type and source. Document types encompass diverse formats, including conference papers, essays and book chapters, each indicative of its intended purpose and structure (Nikseresht, Golmohammadi, & Zandieh, 2024). Conversely, the source type pertains to the publication medium, including journals, conference proceedings, book series and professional publications. An analysis of document types in FinTech research indicates a pronounced dominance of journal paper. Table 2 demonstrates that journal articles constitute 60.27% of all publications, with book chapters at 16.77% and conference papers at 14.90%. Other document categories collectively account for fewer than 6% of total publications, highlighting the dominance of journal articles in this domain.
Types of documents
| Document type | Total no of publication TP | Percentage% |
|---|---|---|
| Article | 1,837 | 60.27% |
| Book Chapter | 511 | 16.77% |
| Conference Paper | 454 | 14.90% |
| Review | 110 | 3.61% |
| Book | 66 | 2.17% |
| Editorial | 37 | 1.21% |
| Note | 15 | 0.49% |
| Erratum | 10 | 0.33% |
| Retracted | 3 | 0.10% |
| Letter | 2 | 0.07% |
| Short Survey | 2 | 0.07% |
| Data Paper | 1 | 0.03% |
| Total | 3,048 | 100.00% |
This analysis highlights the variation in journal impact and specialization, with Elsevier's dominance in high-impact finance and policy journals, MDPI's broad appeal in multidisciplinary research and Springer's focus on emerging disciplines. The statistic underscores the significance of journals in academic communication, comprising 66.37% of the total 3,048 articles. Books (15.35%), conference proceedings (11.29%) and book series (6.89%) collectively constitute a substantial segment, emphasizing their roles in disciplines valuing extended analyses and emerging research dissemination. Trade journals constitute a mere 0.10% of the total, indicating low representation. This distribution highlights the importance of journals in academic publishing and illustrates the various formats employed to disseminate research findings. The indicators combined offer an in-depth comprehension of various sources' academic impact and citation trends, as illustrated in Table 3.
6.3 Document language
Table 4 reveals that the vast majority of journals in the dataset were published in English, with 3,011 publications comprising 98.69% of the total. A small proportion of documents were published in other or multiple languages, including Spanish, Chinese, Russian, French, Portuguese, Indonesian, Italian, Japanese, Malay, Polish and Serbian. These non-English publications represent only a minor fraction of the total output, underscoring the dominance of English in FinTech-related research.
6.4 Topic areas using
The analysis of (1) subject areas and (2) author keywords offer valuable insights into the different aspects of FinTech research. This finding contributes to addressing the research question (RQ) regarding the key themes and focus areas within the field of FinTech.
6.4.1 Subject area
A thematic analysis of the documents was conducted, categorizing them based on the topics of their original publications illustrated in Table 5. The results reveal a diverse range of research foci within the FinTech domain. The business management and accounting category accounted for the largest share, with 1,313 articles (43.08%). The economics, econometrics and finance category followed closely, with 1,464 articles (48.03%). The computer science and engineering categories also contributed significantly, with 885 articles (29.04%) and 386 articles (12.66%). Notably, the analysis also highlights the interdisciplinary nature of FinTech research, with contributions from diverse fields such as environmental science, mathematics, decision science and psychology.
Subject area
| Subject area | Total no of publication TP | Percentage % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 0.39% |
| Arts and Humanities | 65 | 2.13% |
| Biochemistry, Genetics and Molecular Biology | 19 | 0.62% |
| Business, Management and Accounting | 1,313 | 43.08% |
| Chemical Engineering | 8 | 0.26% |
| Chemistry | 4 | 0.13% |
| Computer Science | 885 | 29.04% |
| Decision Sciences | 307 | 10.07% |
| Earth and Planetary Sciences | 22 | 0.72% |
| Economics, Econometrics and Finance | 1,464 | 48.03% |
| Energy | 124 | 4.07% |
| Engineering | 386 | 12.66% |
| Environmental Science | 323 | 10.60% |
| Health Professions | 2 | 0.07% |
| Immunology and Microbiology | 6 | 0.20% |
| Materials Science | 22 | 0.72% |
| Mathematics | 178 | 5.84% |
| Medicine | 54 | 1.77% |
| Multidisciplinary | 53 | 1.74% |
| Neuroscience | 1 | 0.03% |
| Nursing | 1 | 0.03% |
| Pharmacology, Toxicology and Pharmaceutics | 7 | 0.23% |
| Physics and Astronomy | 45 | 1.48% |
| Psychology | 43 | 1.41% |
| Social Sciences | 797 | 26.15% |
An analysis was conducted on the leading countries, universities and researchers in FinTech studies by evaluating contemporary trends and the influence of publications in this domain. The papers were methodically classified according to their country of origin to address the study's second research question.
6.4.1.1 Publications by Countries
This section explores the current state of collaboration in FinTech research and identifies the most influential countries in the field. The study uses Scopus, a comprehensive database that includes FinTech-related publications from researchers across 41 countries. Table 6 highlights the leading contributors to FinTech studies, with China ranking first with 626 publications. India follows with 410 publications, while the USA ranks third with 315. The United Kingdom and Indonesia are fourth and fifth, with 276 and 210 publications, respectively.
Top 20 countries with the highest number of documents
| Country | TP | NCP | TC | C/P | C/CP | h |
|---|---|---|---|---|---|---|
| China | 626 | 10 | 123 | 0.20 | 12.30 | 6 |
| India | 410 | 483 | 11,000 | 26.83 | 22.77 | 51 |
| The USA | 315 | 237 | 2,884 | 9.16 | 12.17 | 26 |
| United Kingdom | 276 | 211 | 6,707 | 24.30 | 31.79 | 42 |
| Indonesia | 210 | 147 | 1,846 | 8.79 | 12.56 | 23 |
| Malaysia | 210 | 152 | 2,422 | 11.53 | 15.93 | 27 |
| Saudi Arabia | 133 | 98 | 974 | 7.32 | 9.94 | 16 |
| Australia | 124 | 105 | 3,542 | 28.56 | 33.73 | 28 |
| Italy | 103 | 79 | 1,472 | 14.29 | 18.63 | 20 |
| Pakistan | 103 | 82 | 1,968 | 19.11 | 24.00 | 23 |
| United Arab Emirates | 89 | 67 | 1,097 | 12.33 | 16.37 | 18 |
| Jordan | 88 | 0 | 0 | 0.00 | 0.00 | 0 |
| Bahrain | 87 | 77 | 945 | 10.86 | 12.27 | 14 |
| South Korea | 86 | 73 | 2,787 | 32.41 | 38.18 | 24 |
| Taiwan | 80 | 60 | 831 | 10.39 | 13.85 | 13 |
| Germany | 71 | 61 | 4,365 | 61.48 | 71.56 | 23 |
| Viet Nam | 68 | 50 | 1,068 | 15.71 | 21.36 | 15 |
| Bangladesh | 57 | 42 | 420 | 7.37 | 10.00 | 11 |
| France | 56 | 40 | 1,999 | 35.70 | 49.98 | 18 |
| Canada | 54 | 37 | 591 | 10.94 | 15.97 | 12 |
Regarding citation impact, India leads with 11,000 citations, followed by the United Kingdom with 6,707 citations. Germany ranks third with 4,365 citations, Australia fourth with 3,542 and the USA fifth with 2,884 citations. The total number of publications from each country was analyzed alongside authorship patterns to address the study's second research question.
The primary focus here is to evaluate the current state of collaboration, identify the most influential authors on FinTech and identify the leading. Table 7 lists the most cited authors who have contributed with at least four publications on FinTech. Hassan, M.K., Rabbani, M.R., Wójcik, D., Alsmadi, A.A. and Rupeika-Apoga, R., are the authors who have had the greatest FinTech. Accordingly, Rabbani, M.R. ranked first with 628citations, followed by Dinçer, H. 456 citations, Khan, S. with 270 citations and Rupeika-Apoga, R. 269 citations.
Most prolific authors
| Author name | Affiliation | Country | TP | NCP | TC | C/P | C/CP | h | g |
|---|---|---|---|---|---|---|---|---|---|
| Hassan, Rabbani, and Rashid (2022) | University of New Orleans | The USA | 22 | 20 | 254 | 11.55 | 12.70 | 7 | 15 |
| Rabbani, Hassan, Khan, and Muneeza (2022) | University of Khorfakkan | U. A. E. | 15 | 26 | 628 | 41.87 | 24.15 | 12 | 25 |
| 12 | 0.00 | ||||||||
| Wojcik (2021) | National University of Singapore | Singapore | 10 | 8 | 248 | 24.80 | 31.00 | 7 | 8 |
| Al-Zaytoonah University | Jordan | 9 | 7 | 99 | 11.00 | 14.14 | 4 | 7 | |
| Alsmadi (2025) | Latvijas Universitāte | Latvia | 9 | 9 | 269 | 29.89 | 29.89 | 7 | 9 |
| Rupeika-Apoga and Wendt (2022) | İstanbul Medipol Üniversitesi | Turkey | 8 | 7 | 456 | 57.00 | 65.14 | 7 | 7 |
| Alareeni and Hamdan (2024) | Ahlia University | Bahrain | 8 | 7 | 84 | 10.50 | 12.00 | 4 | 7 |
| Rabbani et al. (2022) | Bahrain Polytechnic | Bahrain | 8 | 8 | 270 | 33.75 | 33.75 | 7 | 8 |
| Najaf, Subramaniam, and Atayah (2022) | Monash University | Malaysia | 8 | 7 | 151 | 18.88 | 21.57 | 6 | 7 |
Note(s): TP = total number of publications; NCP = number of cited publications; TC = total citations; C/P = average citations per publication; C/CP = average citations per cited publication; h = h-index; and g = g-index
6.4.2 Influential affiliations
Table 8 highlights the research productivity and impact of leading institutions with at least five publications in a particular academic discipline. Amity University in India excels in productivity with 41 publications, closely followed by Bina Nusantara University in Indonesia with 38. However, despite their substantial output, these institutions demonstrate moderate citations per publication (C/P), signifying a limited effect in relation to their productivity. In contrast, the University of Bahrain and Ahlia University Bahrain, with 37 and 34 publications, respectively, exhibit a comparable contribution, with the former attaining a higher citation impact (C/P = 11.89). Institutions in Australia and China demonstrate remarkable research impact. UNSW Sydney attains the highest C/P (52.90) and g-index (18), indicating exceptional citation impact.
Most influential institutions with a minimum of five publications
| Institution | Country | TP | NCP | TC | C/P | C/CP | h | g |
|---|---|---|---|---|---|---|---|---|
| Amity University | India | 41 | 25 | 381 | 9.29 | 15.24 | 9 | 19 |
| Bina Nusantara University | Indonesia | 38 | 25 | 268 | 7.05 | 10.72 | 9 | 15 |
| University of Bahrain | Bahrain | 37 | 34 | 440 | 11.89 | 12.94 | 9 | 20 |
| Ahlia University | Bahrain | 34 | 29 | 219 | 6.44 | 7.55 | 8 | 13 |
| University of New Orleans | USA | 27 | 25 | 371 | 13.74 | 14.84 | 8 | 19 |
| Renmin University of China | China | 24 | 17 | 246 | 10.25 | 14.47 | 9 | 15 |
| Peking University | China | 24 | 22 | 576 | 24.00 | 26.18 | 10 | 22 |
| Southwestern University of Finance and Economics | France | 24 | 21 | 944 | 39.33 | 44.95 | 11 | 21 |
| Lebanese American University | Lebanon | 23 | 21 | 263 | 11.43 | 12.52 | 9 | 15 |
| King Abdulaziz University | Saudi Arabia | 22 | 16 | 115 | 5.23 | 7.19 | 6 | 10 |
| Applied Science Private University | Jordan | 22 | 14 | 257 | 11.68 | 18.36 | 9 | 14 |
| Symbiosis International Deemed University | India | 22 | 13 | 72 | 3.27 | 5.54 | 5 | 8 |
| UNSW Sydney | Australia | 21 | 18 | 1,111 | 52.90 | 61.72 | 9 | 18 |
| Universiti Utara Malaysia | Malaysia | 20 | 14 | 298 | 14.90 | 21.29 | 8 | 14 |
| Adnan Kassar School of Business | Lebanon | 20 | 18 | 239 | 11.95 | 13.28 | 8 | 15 |
| King Saud University | Saudi Arabia | 19 | 14 | 181 | 9.53 | 12.93 | 6 | 13 |
| The University of Sydney | Australia | 19 | 16 | 854 | 44.95 | 53.38 | 9 | 16 |
| Tashkent State University of Economics | Uzbekistan | 19 | 16 | 141 | 7.42 | 8.81 | 6 | 11 |
| Middle East University, Jordan | Jordan | 19 | 18 | 231 | 12.16 | 12.83 | 9 | 15 |
| University of Economics Ho Chi Minh City | Vietnam | 19 | 21 | 200 | 10.53 | 9.52 | 7 | 13 |
| Universiti Sains Malaysia | Malaysia | 18 | 10 | 123 | 6.83 | 12.30 | 6 | 10 |
Note(s): TP = total number of publications; NCP = number of cited publications; TC = total citations; C/P = average citations per publication; C/CP = average citations per cited publication; h = h-index; and g = g-index
The University of Sydney and the Southwestern University of Finance and Economics in China exhibit high citation metrics (C/P = 44.95 and 39.33, respectively), highlighting their global academic prominence. Peking University emphasizes China's major academic footprint, characterized by high productivity and consistent impact, with a C/P of 24.00. The Middle East and Southeast Asia contribute substantially to research. Institutions such as Applied Science Private University in Jordan and Universiti Utara Malaysia achieve a balance between output and robust citation performance (C/P = 11.68 and 14.90, respectively). Despite moderate citation metrics, universities like Ahlia University and Universiti Sains Malaysia consistently publish, indicating a steadfast dedication to research. The data demonstrates the varied terrain of institutional academic performance, with exceptional performers thriving in productivity, impact, or both simultaneously.
6.4.3 Analysis of keywords
Keyword analysis is predicated on the assumption that an author's chosen keywords accurately reflect the article's topic (Lu et al., 2020; Rabbi & Amin, 2024). The co-occurrence of multiple keywords within an article indicates a relationship between these terms. To address the final research question, this study employed keyword and co-occurrence analysis using VOSviewer, a software tool designed for constructing and visualizing bibliometric networks (Yahaya & Nadarajah, 2025). The analysis utilized VOSviewer to examine the keywords appearing in each publication as illustrated in Figure 3.
The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. The first cluster in green on the left consists of nodes labeled “customer experience”, “fintech ecosystem”, “digital transformation”, “government”, “digital finance”, and “mineral resource”. The second cluster in red on the left consists of nodes labeled “financial inclusions”, “bank performance”, “electronic commerce”, “industrial revolutions”, “technology adoption”, “information and communication”, and “internet”. The third cluster in orange on the top left consists of nodes labeled “information use”, “information systems”, and “financial systems”. The fourth cluster in light blue consists of a node labeled “e-learning”. The fifth cluster in yellow on the top right consists of nodes labeled “fraud detection”, “data privacy”, “crime”, “risk management”, and “block-chain”. The sixth cluster in purple on the right consists of nodes labeled “data mining”, “technology application”, and “cloud computing”. The seventh cluster in brown consists of a node labeled “mobile payment”. The eighth cluster in blue consists of nodes labeled “fintech”, “cyber security”, “p 2 p lending”, “digital literacies”, “bahrain”, “trust”, “technology acceptance mode”, “user interfaces”, “perceived benefits”, and “intention to use”. The “V O S viewer” logo is on the bottom left.Network visualization map of author keywords. Source: Authors' own elaboration
The network displays multiple clusters of nodes, each represented by circles with labels, connected by thin lines indicating relationships, with labels adjacent to the nodes. The first cluster in green on the left consists of nodes labeled “customer experience”, “fintech ecosystem”, “digital transformation”, “government”, “digital finance”, and “mineral resource”. The second cluster in red on the left consists of nodes labeled “financial inclusions”, “bank performance”, “electronic commerce”, “industrial revolutions”, “technology adoption”, “information and communication”, and “internet”. The third cluster in orange on the top left consists of nodes labeled “information use”, “information systems”, and “financial systems”. The fourth cluster in light blue consists of a node labeled “e-learning”. The fifth cluster in yellow on the top right consists of nodes labeled “fraud detection”, “data privacy”, “crime”, “risk management”, and “block-chain”. The sixth cluster in purple on the right consists of nodes labeled “data mining”, “technology application”, and “cloud computing”. The seventh cluster in brown consists of a node labeled “mobile payment”. The eighth cluster in blue consists of nodes labeled “fintech”, “cyber security”, “p 2 p lending”, “digital literacies”, “bahrain”, “trust”, “technology acceptance mode”, “user interfaces”, “perceived benefits”, and “intention to use”. The “V O S viewer” logo is on the bottom left.Network visualization map of author keywords. Source: Authors' own elaboration
Table 9, highlights the most frequently used keywords in FinTech publications from 2015 to 2025. The terms “Fintech” (35.70%) and “FinTech” (20.18%) dominate, confirming the field's central focus. Other prominent keywords include “Finance,” “Financial Technology,” and “China,” indicating substantial research on financial systems and regional developments. The frequent appearance of “Financial Inclusion,” “Innovation,” and “Sustainable Development” reflects growing interest in how FinTech fosters inclusive and sustainable growth. Emerging technologies such as “Blockchain,” “Artificial Intelligence,” and “Machine Learning” also feature strongly, showing the sector's digital orientation. Additionally, terms like “Green Finance,” “COVID-19,” and “Digital Transformation” illustrate the expanding scope of FinTech research into environmental, societal and technological dimensions.
Top 30 keywords
| Keywords | Total no of publication TP | Percentage % |
|---|---|---|
| Fintech | 1,088 | 35.70% |
| FinTech | 615 | 20.18% |
| Finance | 291 | 9.55% |
| Financial Technology | 241 | 7.91% |
| China | 169 | 5.54% |
| Financial Inclusion | 163 | 5.35% |
| Innovation | 161 | 5.28% |
| Sustainable Development | 150 | 4.92% |
| Blockchain | 149 | 4.89% |
| Financial Services | 148 | 4.86% |
| Artificial Intelligence | 123 | 4.04% |
| Banking | 122 | 4.00% |
| Financial Service | 117 | 3.84% |
| Sustainability | 116 | 3.81% |
| Investments | 96 | 3.15% |
| Commerce | 83 | 2.72% |
| Natural Resource | 74 | 2.43% |
| Machine Learning | 72 | 2.36% |
| COVID-19 | 71 | 2.33% |
| Financial System | 71 | 2.33% |
| Economic Growth | 64 | 2.10% |
| Technology | 64 | 2.10% |
| Economics | 63 | 2.07% |
| Technology Adoption | 60 | 1.97% |
| Digital Transformation | 59 | 1.94% |
| Green Finance | 58 | 1.90% |
| Natural Resources | 57 | 1.87% |
| Financial Literacy | 53 | 1.74% |
| Green Economy | 51 | 1.67% |
| Environmental Economics | 50 | 1.64% |
6.4.4 Analysis of citations
Table 10, provides a detailed summary of the citation statistics associated with FinTech publications from 2015 to 2025. The table highlights the total number of citations, the average citations per article and the annual distribution of citation counts. These figures reveal a notable upward trajectory in scholarly attention, reflecting the rapid expansion of FinTech as a multidisciplinary research domain. The steady growth in citation volume underscores the increasing academic engagement with FinTech innovations and their implications for global financial systems.
Citation metrics
| Matric | Data |
|---|---|
| Papers | 3,048 |
| Citations | 46,964 |
| Years | 9 |
| Cites_Year | 5218.22 |
| Cites_Paper | 15.37 |
| Cites_Author | 20741.33 |
| Papers_Author | 1423.25 |
| Authors_Paper | 2.88 |
| h_index | 95 |
| g_index | 158 |
Figure 4, visually illustrates the yearly distribution of citations within the FinTech literature. The figure demonstrates that publications from 2021 attained the highest scholarly impact, with 8,174 citations, while 2015 recorded the lowest, with 100 citations. This pattern signifies that as FinTech research matured, its academic visibility and influence grew substantially. The upward citation trend observed in the later years suggests a consolidation of FinTech as a prominent research area, attracting greater interest from scholars across disciplines.
The graph is titled “Data”. The horizontal axis has markings ranging from 0 to 50000 in increments of 5000 units. The vertical axis has 12 markings labeled from top to bottom as follows: “h l underscore index”, “h c underscore index”, “g underscore index”, “h underscore index”, “Authors underscore Paper”, “Papers underscore Author”, “Cites underscore Author”, “Cites underscore Paper”, “Cites underscore Year”, “Years”, “Citations”, and “Paper”. The data from the bars on the graph are as follows: h l underscore index,: 32. h c underscore index: 126. g underscore index: 158. h underscore index: 95. Authors underscore Paper: 2.88. Papers underscore Author: 1423.25. Cites underscore Author: 20741.33. Cites underscore Paper: 15.37. Cites underscore Year: 5218.22. Years: 9. Citations: 46964. Papers: 3055.Citation metrics. Source: Authors' own elaboration
The graph is titled “Data”. The horizontal axis has markings ranging from 0 to 50000 in increments of 5000 units. The vertical axis has 12 markings labeled from top to bottom as follows: “h l underscore index”, “h c underscore index”, “g underscore index”, “h underscore index”, “Authors underscore Paper”, “Papers underscore Author”, “Cites underscore Author”, “Cites underscore Paper”, “Cites underscore Year”, “Years”, “Citations”, and “Paper”. The data from the bars on the graph are as follows: h l underscore index,: 32. h c underscore index: 126. g underscore index: 158. h underscore index: 95. Authors underscore Paper: 2.88. Papers underscore Author: 1423.25. Cites underscore Author: 20741.33. Cites underscore Paper: 15.37. Cites underscore Year: 5218.22. Years: 9. Citations: 46964. Papers: 3055.Citation metrics. Source: Authors' own elaboration
The results in Table 11, emphasized the most commonly cited articles. The article “On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services” by P. Gomber, R.J. Kauffman, C. Parker and B.W. Weber achieved the highest ranking with 928 total citations, yielding an annualized citation rate of 154.67. This outcome highlights the article's crucial significance in influencing conversations on innovation and transformation within financial services, positioning it as a foundation work in FinTech research.
Top 20 highly cited articles
| S/N | Authors | Title | Year | TC | CitesPerYear |
|---|---|---|---|---|---|
| 1 | Gomber, Kauffman, Parker, and Weber (2018) | On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services | 2018 | 928 | 154.67 |
| 2 | Lee and Shin (2018) | Fintech: Ecosystem, business models, investment decisions, and challenges | 2018 | 810 | 135 |
| 3 | Gomber, Koch, and Siering (2017) | Digital Finance and FinTech: current research and future research directions | 2017 | 744 | 106.29 |
| 4 | Buchak, Matvos, Piskorski, and Seru (2018) | Fintech, regulatory arbitrage, and the rise of shadow banks | 2018 | 632 | 105.33 |
| 5 | Thakor (2020) | Fintech and banking: What do we know? | 2020 | 516 | 129 |
| 6 | Gabor and Brooks (2020) | The digital revolution in financial inclusion: international development in the fintech era | 2017 | 436 | 62.29 |
| 7 | Belanche, Casaló, and Flavián (2019) | Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers | 2019 | 376 | 75.2 |
| 8 | Haddad and Hornuf (2019) | The emergence of the global fintech market: economic and technological determinants | 2019 | 370 | 74 |
| 9 | Chen, Wu, and Yang (2019) | How Valuable Is FinTech Innovation? | 2019 | 356 | 71.2 |
| 10 | Muganyi, Yan, and Sun (2021) | Green finance, fintech and environmental protection: Evidence from China | 2021 | 348 | 116 |
| 11 | Puschmann (2017) | Fintech | 2017 | 344 | 49.14 |
| 12 | Goldstein, Jiang, and Karolyi (2019) | To FinTech and beyond | 2019 | 321 | 64.2 |
| 13 | Zhou, Zhu, and Luo (2022) | The impact of fintech innovation on green growth in China: Mediating effect of green finance | 2022 | 317 | 158.5 |
| 14 | Gai, Qiu, and Sun (2018) | A survey on FinTech | 2018 | 316 | 52.67 |
| 15 | Anagnostopoulos (2018) | Fintech and regtech: Impact on regulators and banks | 2018 | 307 | 51.17 |
| 16 | Hu, Ding, Li, Chen, and Yang (2019) | Adoption intention of fintech services for bank users: An empirical examination with an extended technology acceptance model | 2019 | 298 | 59.6 |
| 17 | Schueffel (2016) | Taming the beast: A scientific definition of fintech | 2016 | 293 | 36.63 |
| 18 | Arner, Buckley, Zetzsche, and Veidt (2020) | Sustainability, FinTech and Financial Inclusion | 2020 | 283 | 70.75 |
| 19 | Demir, Pesqué-Cela, Altunbas, and Murinde (2022) | Fintech, financial inclusion and income inequality: a quantile regression approach | 2022 | 280 | 140 |
| 20 | Kou, Olgu Akdeniz, Dinçer, and Yüksel (2021) | Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach | 2021 | 261 | 87 |
6.4.5 Documents based on source title
Many academic papers, conferences and books have published articles based on research on FinTech. Table 12, illustrates the total number of publications attributed to each source, indicating which source is the most prolific in FinTech articles. The table shows that “Elsevier” is the leading source for FinTech research. However, this analysis highlights the variation in journal impact and specialization, with Elsevier's dominance in high-impact finance and policy journals, MDPI's broad appeal in multidisciplinary research, and Springer's focus on emerging disciplines. The indicators combined offer an in-depth comprehension of various sources' academic impact and citation trends.
Most active source titles
| Source title | TP | TC | Publisher | Cite score | SJR 2023 | SNIP 2023 |
|---|---|---|---|---|---|---|
| Resources Policy | 126 | 1,105 | Elsevier | 13.4 | 2.063 | 2.083 |
| Finance Research Letters | 69 | 1,022 | Elsevier | 11.1 | 1.903 | 2.279 |
| Sustainability Switzerland | 53 | 1,425 | MDPI | 6.8 | 0.672 | 1.086 |
| Lecture Notes in Networks and Systems | 37 | 85 | Springer Nature | 0.9 | 0.171 | 0.282 |
| ACM International Conference Proceeding Series | 32 | 108 | ||||
| International Review of Financial Analysis | 28 | 562 | Elsevier | 11.2 | 1.294 | 1.927 |
| Financial Innovation | 26 | 1,107 | Springer | 11.4 | 1.162 | 2.149 |
| Journal of Open Innovation Technology Market and Complexity | 25 | 755 | Elsevier | 11 | 0.905 | 1.646 |
| Journal of Risk and Financial Management | 25 | 356 | MDPI | 4.5 | 0.485 | 0.875 |
| Research in International Business and Finance | 23 | 562 | Elsevier | 11.2 | 1.294 | 1.927 |
6.4.5.1 Network visualization
Figure 5, demonstrates that the FinTech and digital finance research landscape is maturing and diversifying, with several key papers anchoring the knowledge base and newer works extending those discussions. The VOSviewer network map effectively reveals both the intellectual structure of the field and its temporal evolution through citation patterns.
The network visualization shows a scale bar at the bottom ranging from 2018 (dark blue) to 2023 (yellow). The network displays nodes of various sizes and colors for different years which are as follows: “arner d. w.; buckley r.p.; zetz”, “schueffel p. (2016)”, “fulop m. t.; topor d. i.; ionesc”, “gomber p.; koch j. -a.; siering”, “yang y.; su x.; yao s. (2021)”, “stewart h.; jurgens j. (2018)”, “gabor d.; brooks s. (2017)”, “goldstein i.; jiang w.; karoly”, “gomber p.; kauffman r.j., park”, “langley [.; leyshon a. (2021)”, and so on. The “V O S viewer” logo is on the bottom left.Network visualization map of citations by documents minimum number of citations of a document = 4. Source: Authors' own elaboration
The network visualization shows a scale bar at the bottom ranging from 2018 (dark blue) to 2023 (yellow). The network displays nodes of various sizes and colors for different years which are as follows: “arner d. w.; buckley r.p.; zetz”, “schueffel p. (2016)”, “fulop m. t.; topor d. i.; ionesc”, “gomber p.; koch j. -a.; siering”, “yang y.; su x.; yao s. (2021)”, “stewart h.; jurgens j. (2018)”, “gabor d.; brooks s. (2017)”, “goldstein i.; jiang w.; karoly”, “gomber p.; kauffman r.j., park”, “langley [.; leyshon a. (2021)”, and so on. The “V O S viewer” logo is on the bottom left.Network visualization map of citations by documents minimum number of citations of a document = 4. Source: Authors' own elaboration
Figure 6, demonstrates that research in FinTech and related fields is highly internationalized, with China, the USA, the United Kingdom, and Malaysia serving as central knowledge hubs. The presence of many smaller but connected nodes suggests a diversifying and increasingly collaborative global research environment, where both established and emerging economies contribute to the evolving body of knowledge.
The network displays multiple clusters of nodes, each represented by circles with labels. The first cluster in blue on the left consists of a node labeled “china”. The second cluster in red on the right consists of a node labeled “malaysia”. The third cluster in light red on the left consists of a node labeled “belgium”. The fourth cluster in orange consists of a node labeled “canada”. The fifth cluster in brown consists of a node labeled “bahrain”. The sixth cluster in pink consists of nodes labeled “colombia” and “bangladesh”. The seventh cluster in blue consists of a node labeled “brazil”. The eighth cluster in grey consists of nodes labeled “palestine”, “ukraine”, “portugal”, “taiwan”, “slovakia”, “denmark”, “serbia”, “jordan”, “a m p”, “iran”, “united kingdom”, “united states”, “bulgaria”, “netherlands”, “singapore”, “iraq”, “nigeria”, “ireland”, “qatar”, “croatia”, “latvia”, “poland”, “italy”, “thailand”, “switzerland”, “greece”, “japan”, “viet nam”, “kuwait”, “czech republic”, “cyprus”, “south africa”, “turkey”, “germany”, and “finland”. The “V O S viewer” logo is on the bottom left.Network visualization map of citations by countries: minimum number of documents of an author = 1; minimum number of citations of an author = 4. Source: Authors' own elaboration
The network displays multiple clusters of nodes, each represented by circles with labels. The first cluster in blue on the left consists of a node labeled “china”. The second cluster in red on the right consists of a node labeled “malaysia”. The third cluster in light red on the left consists of a node labeled “belgium”. The fourth cluster in orange consists of a node labeled “canada”. The fifth cluster in brown consists of a node labeled “bahrain”. The sixth cluster in pink consists of nodes labeled “colombia” and “bangladesh”. The seventh cluster in blue consists of a node labeled “brazil”. The eighth cluster in grey consists of nodes labeled “palestine”, “ukraine”, “portugal”, “taiwan”, “slovakia”, “denmark”, “serbia”, “jordan”, “a m p”, “iran”, “united kingdom”, “united states”, “bulgaria”, “netherlands”, “singapore”, “iraq”, “nigeria”, “ireland”, “qatar”, “croatia”, “latvia”, “poland”, “italy”, “thailand”, “switzerland”, “greece”, “japan”, “viet nam”, “kuwait”, “czech republic”, “cyprus”, “south africa”, “turkey”, “germany”, and “finland”. The “V O S viewer” logo is on the bottom left.Network visualization map of citations by countries: minimum number of documents of an author = 1; minimum number of citations of an author = 4. Source: Authors' own elaboration
7. Discussion
The dynamic nature of FinTech (Afjal, 2023; Cumming, Johan, & Reardon, 2023) highlights the need for ongoing examination of trends in FinTech research. Despite being a prominent focus of scholarly inquiry for several years (Pandey, Hassan, Kumari, Zaied, & Rai, 2024), research on users' continuous intention to adopt FinTech remains limited. This knowledge gap is noteworthy, given FinTech platforms' pivotal role in transforming the financial ecosystem. This study employs bibliometric analysis to emphasize the strategic significance of FinTech concepts in fostering innovative business models (Yahaya et al., 2025). By prioritizing recent advancements in FinTech, this research aims to contribute to the evolving body of knowledge in this field. Bibliometric analysis provides a methodological approach to examine the evolution of FinTech scholarship, assess the scope of research and publication efforts and identify areas for future investigation (Ahmi et al., 2020). As Passas (2024) notes, bibliometric data can inform assessments of a field's current state and guide institutional policy development for FinTech. Furthermore, bibliometric studies can illuminate the factors driving significant research contributions and provide direction for future scholarly efforts (Florek-Paszkowska & Hoyos-Vallejo, 2023).
Prevailing publishing trends and scholarly impact
The bibliometric evidence clearly demonstrates that FinTech research has witnessed exponential growth over the last decade, underscoring its increasing relevance in academic and practical discourse. The surge in publications particularly the 29.07% increase recorded in 2024 cannot be dismissed as a mere statistical trend. Rather, it reflects the accelerating global adoption of digital finance, the expansion of blockchain and cryptocurrency ecosystems and the reconfiguration of traditional financial services. Importantly, the significant rise in citations, with 2021 publications receiving over 8,000 citations, validates the intellectual impact of FinTech scholarship. The sustained growth in the h-index and g-index of leading authors further emphasizes that FinTech is not a fleeting trend but a deeply embedded research field with long-term academic value. That journal articles dominate (60.27%) indicates the discipline's intellectual maturity, as peer-reviewed outlets provide both methodological rigour and theoretical grounding. Thus, FinTech research is consolidating itself as a central pillar of contemporary financial and technological discourse.
Contributions of countries, institutions and authors
The analysis also confirms that FinTech is a globally distributed phenomenon, with China, India and the USA taking leading roles. These countries' prominence is not coincidental; rather, it reflects the strategic investments in digital finance ecosystems, robust payment infrastructures and entrepreneurial innovation. The contributions of Chinese and Indian universities illustrate how emerging economies are actively shaping global FinTech debates, even if their citation impact has not yet matched that of top-tier Western institutions. This asymmetry itself is a significant finding: it reveals how FinTech scholarship is becoming more pluralistic, with intellectual leadership shifting beyond traditional Euro-American centers of knowledge production. Furthermore, the recognition of high-impact institutions such as UNSW Sydney and Southwestern University of Finance and Economics demonstrates that FinTech is cultivating academic hubs of excellence, producing research that shapes both policy and practice. Prominent authors such as Hassan, Rabbani and Rupeika-Apoga provide intellectual anchorage for the field and Rabbani's 628 citations underscore the ability of individual scholars to set research agendas globally.
Influential articles in FinTech literature
The identification of Gomber et al. (2018) as the most cited and intellectually foundational work reinforces the argument that FinTech scholarship has generated seminal contributions that continue to shape contemporary debates. This article's enduring relevance illustrates the profound disruption FinTech has introduced into financial services, moving beyond traditional models toward innovation and transformation. The sustained citation of works focusing on blockchain, AI and regulatory frameworks further indicates that FinTech is not only interdisciplinary but also problem-driven, addressing issues that directly impact financial systems, markets and governance. The diversity of topics in highly cited works – from digital payment systems to regulatory challenges – demonstrates that FinTech scholarship is theoretically rich, empirically grounded and practically consequential.
Future research directions
Perhaps the most compelling argument emerging from this study lies in the identification of future research trajectories. The convergence of blockchain and AI, as well as the growing emphasis on digital currencies, represents an uncharted but transformative landscape that requires scholarly exploration. Crucially, the role of FinTech in advancing financial inclusion in developing economies cannot be overstated. By providing underbanked populations with access to affordable and efficient financial services, FinTech not only addresses social equity but also redefines the developmental role of finance in the Global South. Furthermore, the increasing awareness of FinTech's environmental footprint (e.g. cryptocurrency mining, data storage and energy consumption) introduces a critical sustainability dimension that future research must address. This shift illustrates the maturity of the field, moving from “FinTech as disruption” to “FinTech as sustainable innovation.”
8. Conclusion
This bibliometric analysis provides compelling evidence of the dynamic and rapidly expanding domain of FinTech research, reflecting both its scholarly significance and its practical relevance in reshaping the financial services industry. The findings demonstrate that FinTech scholarship has not only grown in volume but has also diversified in scope, encompassing multiple interdisciplinary dimensions such as information systems, economics, finance and business management. This breadth of engagement underscores the recognition of FinTech as a transformative force in the global financial ecosystem.
The results further reveal that research outputs are being driven by notable contributions from leading countries, institutions and scholars. Countries such as China, India and the USA are consistently at the forefront of FinTech research, propelled by their strong innovation ecosystems, robust investment in digital infrastructure, and government-backed policies that foster FinTech adoption. Similarly, prominent academic institutions and highly cited scholars are shaping the intellectual contours of the field, producing rigorous empirical and theoretical work that informs both practice and policymaking. Such contributions highlight the centrality of FinTech not only as a research area but also as a strategic domain that bridges academia, industry and government.
An examination of the most influential and highly cited articles in the field emphasizes the essential importance of scholarship on disruptive technologies, particularly blockchain, artificial intelligence and digital platforms. These technologies have been consistently identified as drivers of innovation and transformation within financial services, enabling new business models, reshaping consumer experiences and challenging traditional banking practices. The high impact of these studies illustrates the extent to which FinTech research has redefined academic discourse around innovation, risk management and the role of technology in financial intermediation.
Looking forward, the study highlights several critical trajectories for future research. These include the continued exploration of emerging technologies such as blockchain-based smart contracts, AI-driven financial advisory systems and digital currencies, which are expected to deepen the transformation of global finance. Equally important are the ethical and regulatory dimensions of FinTech adoption. Issues such as data privacy, cybersecurity, algorithmic bias and financial exclusion demand sustained scholarly attention to ensure that technological innovation does not exacerbate inequalities or undermine trust in financial systems. Moreover, regulatory frameworks must balance the need for innovation with the imperative of consumer protection and financial stability, creating fertile ground for policy-oriented FinTech research.
As the discipline continues to evolve, researchers are increasingly called upon to interrogate not only the economic implications of FinTech but also its social and environmental ramifications. This includes assessing its role in promoting financial inclusion in underbanked regions, its potential for empowering marginalized communities through access to credit and payment systems and its environmental footprint, particularly in the case of energy-intensive processes such as cryptocurrency mining. By addressing these dimensions, FinTech scholarship can ensure that the field acts as a catalyst for positive transformation, contributing to more inclusive, sustainable and resilient financial systems worldwide.
9. Limitations and future research
While the bibliometric analysis reveals a significant rise in FinTech research over the past decade, several limitations must be acknowledged. The study's reliance on specific databases may omit relevant but non-indexed research. Additionally, the timeframe from 2015 to 2025 might overlook earlier foundational studies. Citation-based impact assessment can introduce bias, favoring older publications while underestimating newer, influential works. The geographical concentration of research in countries like China, India and the USA may lead to underrepresenting contributions from less-documented regions. Furthermore, FinTech's interdisciplinary nature makes it difficult to fully capture cross-disciplinary influences, while citation metrics alone do not necessarily reflect the real-world impact of research.
Moreover, the rapid evolution of FinTech poses challenges in maintaining the long-term relevance of research findings. While certain institutions and authors demonstrate high productivity, the study notes that research quality and academic influence vary. Institutional prestige and author prominence may skew perceived impact. Additionally, as FinTech research increasingly integrates blockchain, AI and financial inclusion topics, its regulatory and ethical dimensions remain underexplored.
This research exclusively relied on Scopus as the primary database. While Scopus does not encompass all available literature, it remains one of the most reliable sources for archival scientific papers (Sweileh, 2021). Additional databases such as Web of Science, EBSCO and Google Scholar Dimensions could be explored to enhance future studies' comprehensiveness. Lastly, given rising environmental concerns, future studies should focus on the sustainability aspects of FinTech, such as cryptocurrency mining and energy-efficient digital banking solutions.
