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ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
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Financial Technology (Fintech): Current Research at The Cutting Edge
1 Maslinawati Mohamad*, 2 Salwa Zolkaflil, 3 Hairul Suhaimi Nahar
1 Faculty of Accountancy, Universiti Teknologi MARA, Selangor Campus, Puncak Alam Branch, Selan-
gor, Malaysia
2 Accounting Research Institute, Universiti Teknologi MARA, Malaysia
3 Accounting Department, College of Economics and Political Science, Sultan Qaboos University,
Muscat, Sultanate of Oman
* Corresponding Author
DOI: https://doi.org/10.51244/IJRSI.2025.1210000056
Received: 12 March 2025; Accepted: 19 March 2025; Published: 03 November 2025
ABSTRACT
Purpose – This study analyses the frontier of financial technology (FinTech) research repertoire by identifying
essential features to direct future research in the sector. This research used bibliometric and citation analysis.
Scopus yielded 1,011 data points linked to the article titled FinTech. Numerous programmes were used,
including Microsoft Excel to perform the frequency study, VOSviewer to visualise the data, and Harzing's
Publish or Perish to calculate and analyse citation metrics. The analysis results suggest that FinTech is a cross-
disciplinary research area where past literature concentrated mainly on business-related and environmental
science domains. The growing number of publications on FinTech demonstrates that the critical nature of
technology has affected the financial services sector, and there are undoubtedly some ramifications for the
economy. The data sources selected are from the Scopus database only. This study is the first bibliometric
examination of FinTech utilising a 38-year-old publication database.
Keywords: FinTech, Financial Technology, Bibliometric Analysis, Big Data, Cyber Security
INTRODUCTION
FinTech is a phrase that refers to technology that enables the improvement and automation of the use and supply
of financial services. Financial institutions, businesses, small company owners, and individuals often use it to
help them manage their financial operations, procedures, and even their daily lives more effectively. Most of the
time, FinTech uses specialised software and algorithms on computers. Arner et al. (2015) identified a pivotal
moment in the timetable for FinTech implementation. The introduction of Industry Evolution (IR) 4.0 has
changed life as the world moves towards automation and digitalisation. In line with IR 4.0, the financial
institutions have ventured into FinTech, which assists, supports, and manages their financial activities using
specialised applications and software. FinTech facilitates the public in performing business transactions from
anywhere (World Banks, 2018; Demirgüç-Kunt et al., 2018; Gai et al., 2018), which gives flexibility to all actors
(Anshari et al., 2019). To remain competitive in the market, the financial institutions have to support the
adaptation of FinTech to ensure their sustainability in the competitive market. The FinTech industry is a driving
force for sustainable economic growth with several effects on social, environmental, and ecological benefits that
can make financial business more sustainable, as it promotes green finance or sustainable finance (Chueca
Vergara and Ferruz Agudo, 2021; Nahar, Mohamad and Abd Rahman, 2022).
Hence, research on FinTech has been widely discussed by scholars, policymakers, and law enforcement agencies,
yet there are still areas to be explored. It is practically and academically imperative for academic literature to
look back at previous FinTech research, thereby providing the necessary reflections on what had been done so
far and what could be done to shape the trajectory of practical and empirical FinTech knowledge.
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Accordingly, this study explores the FinTech research repertoire by delineating critical research attributes under
the general theme of FinTech, which are arguably crucial in guiding the path of future FinTech research. Using
the commonly applied scientific analytical approach of bibliometric analysis, 1,011 FinTech-related papers pub-
lished in the Scopus database were identified and analysed. These papers were published between 1984 to 2022
in various Scopus indexed outlets. The following research questions (RQs) are addressed: RQ1: What is the
current state of FinTech publication? RQ2: What are the most productive contributors to FinTech research?
RQ3: Which are the most influential articles on FinTech? RQ4: What are the authorship patterns of the publi-
cation in FinTech? RQ5: Which themes of FinTech are most popular among researchers?
Previous researchers such as Li and Zu (2021) limit their work review to 1995 to 2021, using only the WoS
database. Nasir et al. (2021) only cover the analysis for 2010 to 2021, and Tepe et al. (2021) cover the analysis
period only for 2015 to 2021. Our literature review differs from those of other authors in several ways. First,
earlier reviews used a more limited data period than our study. We identify critical research properties for early
and/or matured researchers to plan their future research trajectory in the current research. Researchers will be
presented with readily available empirical and literature gaps based on the analyses conducted. Second, we iden-
tify the most important conceptual framework that underpins the present FinTech publications. It presents re-
search endeavour of bibliometric analysis on FinTech research using the established publication database over
38 years, leading to more data coverage.
The following is the order in which the paper is presented. The following section briefly describes FinTech and
then discusses the approach used to locate data from previous FinTech-related papers and the analytical
methodologies utilised. The functional analysis is given next, followed by the findings section. The last part ends
by discussing the ramifications of the results.
LITERATURE REVIEW
FinTech: An overview
FinTech, according to Leong and Sung (2018), may also be defined as "any creative concepts that enhance
financial service operations by providing technological solutions based on various business circumstances."
After the global financial crisis in 2008, advances in e-finance and mobile technologies for financial firms fueled
FinTech innovation. This development defined e-finance innovation, internet technology, social networking
services, artificial intelligence, and extensive analytic data. The word "FinTech" refers to information technology
applications in finance, financial innovation, and digital information (Zavolokina et al., 2020). All industries and
business sectors face difficulties as a result of digital transformation. The evolution of digital transformation has
also obviously spurred the creation of FinTech (financial technology) initiatives, which are often regarded as
some of the most significant breakthroughs in the financial sector. This puts pressure on many conventional
financial organisations, such as banks, to create more realistic business models (Gimpel et al., 2018). Insurance
services, crowdfunding, payment, lending, wealth management, and capital markets are the six FinTech business
models (Davis et al., 2017).
Figure 1: Technical Innovation in Financial Industries
The origins of technical innovation in the financial industry may be traced back to introducing checks as payment
(1945). Following that, the Bank of America issued the first credit card in 1958, and automatic teller machines
(ATMs) aided in processing financial transactions in 1967, followed by the release of a debit card as a transaction
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instrument. Internet banking was introduced in the 1990s, aided by the development of the Internet. FinTech, or
finance and technology combined, has been around for now. A more recent network that handles real-time
processes among banks was introduced in 2008 (Alt, Beck, and Smits, 2018). It is the only way to see how
FinTech compares with others in wealth and possessions. With so many new functions and tools available in the
technology industry, it is easier than ever to track account balances on the phone. There are many categories of
FinTech available in the market, namely financing, asset management, payment, insurance, loyalty programs,
risk management, exchanges, and regulatory technology (Haddad and Hornuf, 2019). However, financing is seen
as the most important segment, followed by payment, asset management, insurance, loyalty programs, risk
management, exchanges, and regulatory technology.
Benefits of FinTech
One small example of what FinTech has done is make financial matters easy and accessible to all people who
might not afford a broker or traditional banks (Laldin, 2018). There is no longer a need to go to a bank branch.
With FinTech, banking is done faster, easier for less money and with more security. Users can even open bank
accounts while on vacation or business trips. These are the many ways FinTech has changed the finance world.
Companies that sell financial products and services to consumers are noted spending habits based on spending
their money. Accurate records can give them a good insight into where people spend their money and may even
help them decide what products to offer in the future.
FinTech solutions have been around for a while, but the best ones improve as technology advances. FinTech
offers businesses and investors a better way to find out what is going on with their money. Users can now check
account balances at any time of the day. The possibilities are endless, from checking bank accounts and credit
cards to more complex financial products like prepaid cards or more traditional investments like stocks, trusts,
derivatives or bonds. FinTech can be a huge help for busy consumers who always want things done quickly and
conveniently.
FinTech is also less costly and less time-consuming than the traditional banking system. FinTech lending is more
efficient because it can reduce frictions in the application process, such as the mortgage origination process
(Fuster et al., 2019). The loan processing period has also been reduced by 20% faster without raising their risk
profile. Hence, FinTech can respond more elastically to changes in exogenous mortgage demand shocks
(Agarwal and Chua, 2020).
Identification is one of the most significant aspects that FinTech has created (Wang, 2021). It is so indispensable
today that it may be the next big thing in banking. With all of the money being opened, stolen, lost or spent in
irregular ways, identity theft has become common. FinTech introduces new technology for tracking money and
identification, which helps detect irregular transactions more easily and quickly. This way, users will learn what
occurred to their account without hassle or bother. It also keeps track of every transaction and movement in
users' bank accounts.
FinTech has many different styles, tools and styles that users can choose from depending on what they need.
There are some centralised ones where everything happens on the bank's servers, while some others are
decentralised where the data is saved on a blockchain or similar technology, while others still offer both options
to their users depending on their preferences (Naik et al., 2020). FinTech has gotten to a point where it is almost
impossible to find a bank that does not offer some FinTech tools to its customers. However, some people are
still hesitant about using them because they do not understand how they work or see the difference between what
they have now and what it used to be in the past.
Challenges in adopting FinTech
Whether it is a savings account, home loan, car finance, credit card or insurance quote, FinTech disrupts how
the business operates. As the world moves to digital and consumer demands change, FinTech is no longer an
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option. FinTech has become the norm. However, there are many challenges in adopting FinTech, and the benefits
outright the challenges. More people become aware of what it offers and are satisfied with the performance.
Many people still find technology confusing and fear giving up their traditional bank due to security concerns
(Broby, 2021). Some people do not know where to start when choosing a FinTech product. There are often
complaints about customer service. In some cases, people have reported being locked in or unable to get their
money out of the product. Unfamiliar with the product interface is one of the challenges in FinTech adoption
(Gomber et al., 2018). Since the FinTech sector will develop over time, there is a need to contribute new
knowledge in this vibrant area of technology innovation, process disruption, and services transformation to
enhance FinTech adoption.
Other challenges include cyber security and data protection concerns and not knowing how transactions will be
managed, stored, and paid into users' bank accounts. Some people are concerned about their protection if some-
thing goes wrong with the product. Nevertheless, some people find it far more expensive to deal with their banks
than with FinTech providers (Das, 2019). Sometimes there are hidden costs associated with FinTech products
that can catch people out. For example, a credit card charges a fee every time you use the card abroad. This
mentality is mainly due to the few assumptions of facing high fees associated with overdrafts and foreign trans-
actions compared with FinTech providers, who tend not to charge anything extra.
METHODS
Bibliometric Analysis
The scientific-analytical approach to bibliometric analysis employs suitable statistical techniques to examine
many published reading materials, including books, journals, and other works. The bibliometric approach based
on citation graph construction, which effectively refers to a network or graph representation of the citations
between documents, is widely used in library and information science. Its specific analytical tool of "Citation
Analysis" represents part of the bibliometric approach based on citation graph construction which effectively
refers to a network or graph representation of the citations between documents (Linnenluecke et al., 2020; Schaer,
2013). This phase allows for impact assessments of many aspects, such as the chosen research area, the group
of researchers, the published material, and selecting the most critical articles within a specific field of study
(Donthu et al., 2021; Ellegaard and Wallin, 2015).
This study extracted data from Scopus as of 6th September 2021. The search of the data is based on article titles
related to FinTech, such as "FinTech” OR "fin-tech" OR "financial technology" OR "financial technolo-
gies" OR "finance technology" OR "finance technologies" OR "e-finance" OR "electronics finance". From
the data search, we selected and analysed 1,011 article titles related to FinTech. Figure 1 shows the data search
and data selection process. The VOSViewer software is used to conduct bibliometric analysis to analyse the data.
In addition, Ms Excel is used to calculate the frequencies and design graphs and charts to support the results
retrieved from the bibliometric analysis. Besides that, Harzing’s Publish or Perish software calculates the citation
metrics and other frequencies.
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Figure 21. Flow diagram of the data search strategy.
RESULTS
Based on the data gathered from the Scopus database, this study will analyse the bibliometric attributes via
VOSViewer software, such as type of document, type of source, type of language, and subject area. We also
analysed the research trends such as the number of publications based on the year, the countries that contributed
to the publication, the most influential institution that contributed to the publication, the most productive authors,
1 Source: Modified from PRISMA (Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and
Meta-Analyses: The PRISMA Statement. PLoS Med 6 (7): e1000097. doi:10.1371/journal. pmed1000097)
Database: Scopus
Search Field: Article Title
Time Frame: All
Language: English
Source Type: Journal
Document Type: Article
TITLE ("fintech" OR "fin-tech" OR "financial
technology" OR "financial technologies" OR "fi-
nance technology" OR "finance technologies" OR
"e-finance" OR "electronics finance")
Keywords and
Search String
n = 1,011
Record Identified
and Screened
Fintech
S
c
r
ee
n
in
g
In
c
lu
d
e
d
T
o
p
ic
,
S
c
o
p
e
a
n
d
E
li
g
a
b
il
it
y
Topic
Scope and Cover-
age
Record Included for
Bibliometric Analy-
sis
n = 0 Record Removed
n = 1,011
6th September 2021 Date Extracted
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and the most active sources. In addition, we run the citation analysis to obtain the frequency of the citation on
publication and use the VOSViewer software to design the network visualisation map.
4.1 Document Profiles
We start our discussion on the finding with our RQ1 (RQ1: What is the current state of FinTech publication?).
From 780 data extracted from Scopus, we analysed the documents' profiles related to FinTech. Panel 1 of Table
1 shows the details of the type of document. Out of 780 documents, more than 70% (601 documents) are article,
12.31% (96 documents) are book chapter, and 7.44% (58 documents) comprises review, and 3.21% (25
documents) are editorial documents. The documents are further divided according to the type of source. Panel 2
shows the frequencies of the documents based on the type of source. There are 675 journals (86.54%), 61 (7.82%)
books, 42 book series (5.38%), and another 0.26% comprise trade journals.
Table 1. Document Profile
Panel 1. Document Type Panel 2. Source Type
Document
Type
Total Publica-
tion
Percent-
age
(N=780)
Article 601 77.05%
Book Chapter 96 12.31%
Review 58 7.44%
Editorial 25 3.21%
Source Type Total Publica-
tion
Percentage
(N=780)
Journal 675 86.54%
Book 61 7.82%
Book Series 42 5.38%
Trade Journal 2 0.26%
Panel 3. Subject Area
Subject Area Total
Publica-
tion
Percent-
age
(N=780)
Agricultural and Biologi-
cal Sciences
5 0.64%
Arts and Humanities 14 1.79%
Biochemistry, Genetics
and Molecular Biology
10 1.28%
Business, Management
and Accounting
397 50.90%
Chemical Engineering 4 0.51%
Chemistry 3 0.38%
Computer Science 201 25.77%
Decision Sciences 55 7.05%
Subject Area Total
Publica-
tion
Percent-
age
(N=780)
Environmental Science 40 5.13%
Health Professions 1 0.13%
Materials Science 10 1.28%
Mathematics 13 1.67%
Medicine 4 0.51%
Multidisciplinary 6 0.77%
Pharmacology, Toxicol-
ogy and Pharmaceutics
4 0.51%
Physics and Astronomy 5 0.64%
Psychology 14 1.79%
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Economics, Economet-
rics and Finance
323 41.41%
Energy 30 3.85%
Engineering 88 11.28%
Social Sciences 224 28.72%
Veterinary 1 0.13%
There are many subject areas where the research in relation to FinTech was conducted and published. Panel 3
shows the number of publications according to the subject areas. Among 780 documents that are related to
FinTech, there are 397 (50.90%) documents that were published in Business, Management, and Accounting, 323
(41.41%) publications in Economics, Econometrics and Finance, 224 (28.72%) publications in Social Sciences,
201 (25.77%) in Computer Science, 88 (11.28%) publications in Engineering and 55 (7.05%) publications in
Decision Sciences. The complete publication contains more than 780 documents.
4.2 Research Trends
In this study, we also observe the research trends about FinTech (RQ2: What are the most productive
contributors to FinTech research?). We run the citation metrics using Harzing’s Publish or Perish to analyse the
researcher's productivity (author). The researcher's productivity is measured based on citations, citations per year,
and the average citations per cited publication. We retrieved the data from 1984 to 2022 related to FinTech from
Scopus. It shows that the data consists of 38 years of publication. Despite this, it is very important to understand
that the number of citation years is 37, i.e., from 1984 to 2021
Table 6 shows the top 10 countries that contributed to the publications in FinTech. The United States of America
(USA) is ranked first (139:13.75%) among the 20 countries that contribute to the publications on FinTech. Next
is China (123:12.17%) and Indonesia (107:10.58%). The United Kingdom and India are ranked fourth and fifth
with total publications of 97 (9.59%) and 57 (5.64%), respectively.
Table II. Publications Profile
Panel 1. Top 10 Countries Contributed to the Publications
Country TP %
United States 115 14.74%
China 99 12.69%
United Kingdom 86 11.03%
Indonesia 59 7.56%
Australia 43 5.51%
Country TP %
India 42 5.38%
South Korea 42 5.38%
Germany 35 4.49%
Malaysia 31 3.97%
Italy 24 3.08%
Panel 2. Top 10 Most Active Source Titles
Source Title TP % Pub-
lisher
Cite
Score
SJR
2020
SNIP
2020
Sustainability Switzerland 16 2.05%
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Financial Innovation 13 1.67%
Economist United Kingdom 12 1.54%
International Journal of Advanced Science
And Technology
10 1.28%
Journal of Payments Strategy And Systems 10 1.28%
Finance Research Letters 8 1.03%
Journal of Open Innovation Technology
Market And Complexity
8 1.03%
Perspectives In Law Business And Innova-
tion
8 1.03%
Routledge Handbook of Financial Technol-
ogy And Law
8 1.03%
Studies In Computational Intelligence 8 1.03%
Notes: TP=total number of publications
Figure 2: Geographical distributions of publications
Table 7 indicates the results of the most influential institutions that have contributed to the publications in
FinTech for the past 38 years, i.e., from 1984 to 2022. This result is retrieved by limiting the counting of the
frequencies to a minimum of five institutions' publications. Bina Nusantara University and Universitas Indonesia
are the top influential institution with 22 (2.18%) and 15 (1.48%) publications, respectively, followed by UNSW
Sydney (13:1.29%), The University of Sydney (12:1.19%), and Amity University (10:0.99%).
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Table 7. Most influential institutions with minimum of five publications
Institution Total Publication Percentage (N=780)
United States 115 14.74%
China 99 12.69%
United Kingdom 86 11.03%
Indonesia 59 7.56%
Australia 43 5.51%
India 42 5.38%
South Korea 42 5.38%
Germany 35 4.49%
Malaysia 31 3.97%
Italy 24 3.08%
Notes: TP=total number of publications
The most productive authors are presented in Table 8. Rabbani, M.R. from Bahrain, became the most productive
author in FinTech with eight publications. Next is Reyes-Mercado, P. with 7 (0.79%) publications, followed by
Arner, D.W. from Hong Kong, with 6 (0.69%) publications on FinTech. Both Fernando, E. and Khan, S. also
are reported to contribute 6 ().59%) publications on FinTech.
Table 8. Most Productive Authors
Author Name
Total
Publication
Percentage
(N=1011)
Affiliation Country
Rabbani, M.R. 7 0.90% University of Bahrain, Sakhir Bahrain
Reyes-Mercado, P. 7 0.90% Universidad Anáhuac México Mexico
Arner, D.W. 6 0.77% The University of Hong Kong, Pokfulam Hong Kong
Martin, P.L. 6 0.77% unknown unknown
Khan, S. 5 0.64% University College of Bahrain Bahrain
Okoli, T.T. 5 0.64%
Schwienbacher, A. 5 0.64% SKEMA Business School, Lille France
Wonglimpiyarat, J. 5 0.64%
Wójcik, D. 5 0.64%
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Al-Dmour, A. 4 0.51%
Rabbani, M.R. 7 0.90% University of Bahrain, Sakhir Bahrain
Notes: TP=total number of publications
The most active source title is also further retrieved, and the results are presented in Table 9. The list is based on
a minimum of seven (7) total publications from the source. ACM International Conference Proceeding Series is
the most active source title that shows 18 (1.78%) publications on FinTech. Sustainability Switzerland has 15
publications on FinTech, contributing 1.48% of 1,011 documents, followed by the Economist United Kingdom
with 14 (1.38%) publications on FinTech.
Table 9. Most Active Source Title
Source Title
Total Pub-
lication
Per-
cent-
age
(N=10
11)
ACM International Conference Proceeding Series 18 1.78%
Sustainability Switzerland 15 1.48%
Economist United Kingdom 14 1.38%
Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial
Intelligence And Lecture Notes In Bioinformatics
13 1.29%
Lecture Notes In Networks And Systems 13 1.29%
E3s Web of Conferences 12 1.19%
Financial Innovation 11 1.09%
International Journal of Advanced Science And Technology 11 1.09%
Journal of Payments Strategy And Systems 10 0.99%
Advances In Intelligent Systems And Computing 9 0.89%
Routledge Handbook of Financial Technology And Law 9 0.89%
Impact of Financial Technology FinTech on Islamic Finance And Financial Stability 8 0.79%
Perspectives In Law Business And Innovation 8 0.79%
Routledge Handbook of FinTech 8 0.79%
Studies In Computational Intelligence 8 0.79%
Cutter Business Technology Journal 7 0.69%
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Industrial Management And Data Systems 7 0.69%
IOP Conference Series Materials Science And Engineering 7 0.69%
Journal of Advanced Research In Dynamical And Control Systems 7 0.69%
Journal of Open Innovation Technology Market And Complexity 7 0.69%
Palgrave Studies In Democracy Innovation And Entrepreneurship For Growth 7 0.69%
Notes: TP=total number of publications; TC=total citations
4.3 Citation Network Analysis
This section discusses our third RQ (RQ3: Which are the most influential articles on FinTech?). This study also
conducted the citation analysis using citation metrics via Harzing Publish or Perish software. On top of that, this
study also uses the bibliometric analysis to map the citation based on the publication by researcher/author, the
most cited publication, citation by countries, and co-authorship among the researchers/authors in publication of
articles on FinTech.
Table 10 shows the citation metrics of the 1,011 documents gathered from Scopus. There are 6,055 citations of
articles on FinTech from 1984 to 2021. In the previous section, it has to be indicated here that this study states
the publication year is 38, inclusive of the year 2022, for which one of the articles will be published in the year
2022. However, for the citation analysis, the number of years is 37, i.e., 1984 to 2021, as the citation is based on
the articles published in Scopus as of 2021. It is reported that the average citation per year is 163 citations. The
average citation per paper/article is six, and an average of 3 citations of the author.
Table 10. Citations Metrics
Metrics Data
Number of Papers 1011
Citations 6055
Citation Years 37
Cites/Year 163.65
Cites/Paper 5.99
Authors/Paper 2.58
h index 37
g index 60
Using bibliometric analysis, this study managed to map the most citation of the article/document based on
researcher/author. The network visualisation map is retrieved by setting the minimum citation number of an
article/document at 1. This excludes the article/document with zero (0) citations.
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Figure 4. Network visualisation map of the citation by documents
Minimum number of citations of a document = 1
Figure 4 shows the network visualisation map of the citation by articles/documents relating to FinTech. From
the map, it is obviously seen that the most cited articles/documents on FinTech are the articles/documents written
by Au, Y.A. that was published in the year 2008. This is based on the largest circle that appeared on the map.
The following article/document always being cited are the articles/documents written by Gomber, P., published
in 2018.
The citation map by article/documents based on researcher/author retrieved from Vosviewer is further proven
and explained by the frequencies using Ms Excel. The results of the most cited articles are based on the authors
shown in Table 11. The article by Au, Y.A., and Kauffman, R.J. (2008) is the most cited article/document with
243 citations, marking 19 citations per year. The second article/document that is always cited is the
article/document by Gomber et al. (2018), with 195 citations and an average citation per year is 65.
Table 11. Top 20 Highly cited articles
N
o
.
Authors Title
Y
ea
r
Ci
te
s
Cites
per
year
1 Y.A. Au, R.J. Kauffman
The economics of mobile payments: Understanding stake-
holder issues for an emerging financial technology appli-
cation
2
0
0
8
24
3
18.69
2
P. Gomber, R.J. Kauff-
man, C. Parker, B.W.
Weber
On the FinTech Revolution: Interpreting the Forces of In-
novation, Disruption, and Transformation in Financial Ser-
vices
2
0
1
8
19
5
65
3 I. Lee, Y.J. Shin
FinTech: Ecosystem, business models, investment deci-
sions, and challenges
2
0
1
8
18
9
63
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4
P. Gomber, J.-A. Koch,
M. Siering
Digital Finance and FinTech: current research and future
research directions
2
0
1
7
15
8
39.5
5 D. Gabor, S. Brooks
The digital revolution in financial inclusion: international
development in the FinTech era
2
0
1
7
13
4
33.5
6 M.E. Greiner, H. Wang
Building consumer-to-consumer trust in E-finance market-
places: An empirical analysis
2
0
1
0
10
7
9.73
7
G. Buchak, G. Matvos,
T. Piskorski, A. Seru
FinTech, regulatory arbitrage, and the rise of shadow
banks
2
0
1
8
10
6
35.33
8 K. Gai, M. Qiu, X. Sun A survey on FinTech
2
0
1
8
10
2
34
9 Q.K. Nguyen
Blockchain-A Financial Technology for Future Sustaina-
ble Development
2
0
1
6
99 19.8
1
0
P. Schueffel Taming the beast: A scientific definition of FinTech
2
0
1
6
96 19.2
1
1
C. Leong, B. Tan, X.
Xiao, F.T.C. Tan, Y.
Sun
Nurturing a FinTech ecosystem: The case of a youth mi-
croloan start-up in China
2
0
1
7
91 22.75
1
2
C. Haddad, L. Hornuf
The emergence of the global FinTech market: economic
and technological determinants
2
0
1
9
83 41.5
1
3
T. Puschmann FinTech
2
0
1
7
80 20
1
4
D.W. Arner, J. Barberis,
R.P. Buckley
FinTech, regTech, and the reconceptualisation of financial
regulation
2
0
78 19.5
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1
7
1
5
Y. Shim, D.-H. Shin
Analysing China's FinTech Industry from the Perspective
of Actor-Network Theory
2
0
1
6
76 15.2
1
6
I. Anagnostopoulos FinTech and regtech: Impact on regulators and banks
2
0
1
8
69 23
1
7
Y. Kim, J. Choi, Y.-J.
Park, J. Yeon
The adoption of mobile payment services for FinTech
2
0
1
6
67 13.4
1
8
A.V. Thakor FinTech and banking: What do we know?
2
0
2
0
62 62
1
9
M.A. Chen, Q. Wu, B.
Yang
How Valuable Is FinTech Innovation?
2
0
1
9
62 31
2
0
C.W. Cai
Disruption of financial intermediation by FinTech: a re-
view on crowdfunding and blockchain
2
0
1
8
61 20.33
Figure 5. Network visualisation map of the citation by countries
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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Note: Minimum number of documents of an author = 1; Minimum number of citations of an author = 1
Figure 5 shows the network visualisation map of the citation based on the author’s country. The most cited
articles/documents based on the author’s country appeared to be the enormous circle on the visual map. The
circles represent the United States of America (USA), China, and the United Kingdom (UK) are among the most
prominent circles, thus showing that the articles/documents from these three countries have been the most cited
in the publication. The visual map is further explained by referring to the results presented in Table 12. The USA
has the highest number of publications, i.e., 139 (13.75%) publications, next is China (123:12.17%), followed
by Indonesia (107:10.58%), United Kingdom (97:9.59%), and India (57:5.64%).
Table 12: Countries with Highest Publications
Country Total Publications
Percentage
(N=1011)
United States 139 13.75%
China 123 12.17%
Indonesia 107 10.58%
United Kingdom 97 9.59%
India 57 5.64%
Australia 52 5.14%
South Korea 45 4.45%
Germany 41 4.06%
Russian Federation 37 3.66%
Malaysia 31 3.07%
4.4 Authorship Analysis
To answer RQ4 (RQ4: What are the authorship patterns of the publication in FinTech?), Table 13 shows the
number of authors who collaborated on an article/document. 265 (26.21%) of 1,011 articles on FinTech were
written by one researcher/author. 261 (25.82%) articles/documents collaborated with two (2) authors. 223
(22.06%) articles/documents have three (3) authors, followed by 142 (14.05%) articles/documents with four (4)
authors. However, the authors' information is unavailable in 22 (2.18%) articles/documents and cannot be
obtained from Scopus.
Table 13. Number of Author(s) per document
Author Count Frequency Percentage (N=1011)
1 265 26.21
2 261 25.82
3 223 22.06
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4 142 14.05
5 50 4.95
6 25 2.47
7 12 1.19
8 5 0.49
9 2 0.20
10 3 0.30
11 1 0.10
0 22 2.18
Grand Total 1011 100.00
Figure 6. Network visualisation map of the co-authorship (country)
Note: Unit of analysis = Countries; Counting method: Full counting; Minimum number of documents of a
country = 1; Minimum number of citations of a country =1
Figure 6 shows the network visualisation map of the co-authorship retrieved from VOSViewer. The analysis
found nine (9) clusters with 189 links. It shows that most collaboration among authors was from the United
States of America (USA), the United Kingdom (UK), and Indonesia.
INTERNATIONAL JOURNAL OF RESEARCH AND SCIENTIFIC INNOVATION (IJRSI)
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Figure 7. Network visualisation map of the co-authorship (authors)
Note: Unit of analysis = Authors; Counting method: Fractional counting; Minimum number of documents of an
author = 1; Minimum number of citations of an author = 1
Figure 7 shows the network visualisation map of the co-authorship. This shows the collaboration between authors
in publications on FinTech. The authors in each cluster usually collaborate and cite each other publications.
There are 13 clusters shown in the network, which are presented in 13 different colours.
4.7 Keyword and co-occurrences analysis
To answer RQ5 (RQ5: Which themes of FinTech are most popular among researchers?), we utilised the
VOSViewer software and determined the frequent themes used in the publication related to FinTech. Based on
1,011 data obtained from Scopus, we examine the co-occurrence based on the authors’ keywords, the co-
occurrence of title and abstract fields, and the co-occurrence of title fields. The co-occurrence of the author
keywords network map is generated using the full counting. We set the minimum number of occurrences of a
keyword at 1
Figure 8. Network visualisation map of the co-occurrence of author keywords
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Based on the network visualisation map in Figure 8, the keyword most used by the author is FinTech. The biggest
red circle indicates the most keyword used in a publication related to FinTech. Table 14 also shows the top
keywords are FinTech (359:35.51%), FinTech (169:16.72%) and Financial Technology (107:10.58%). It is
important to know that the mapping (Figure 8) retrieved using VOSviewer to map the most keyword used by the
authors has grouped the three keywords i.e., FinTech, FinTech, and Financial Technology, as FinTech.
Table 14. Top Keywords
Keywords TP %
FinTech 359 35.51%
FinTech 169 16.72%
Financial Technology 107 10.58%
Finance 106 10.48%
Financial Service 60 5.93%
Blockchain 57 5.64%
Innovation 55 5.44%
Banking 53 5.24%
Financial Inclusion 45 4.45%
Artificial Intelligence 42 4.15%
Figure 9. VOSviewer visualisation of a term co-occurrence network based on title and abstract fields (Binary
Counting)
Figure 9 shows the visual of the co-occurrence network based on the title and abstract used in the
articles/documents. The co-occurrence is based on title, and abstract fields counted using binary counting. By
choosing the minimum number of occurrences of the term as 10, out of 113,823 terms, 4,806 meet the threshold.
Only 60% (by default) of the threshold are considered the most relevant terms, i.e. 2,884. The same colour that
presents the titles and abstract terms linked. This shows that the title and abstract keywords are grouped with the
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same colour, are closely related and co-occur together most of the time. There are four (6) clusters that appear
clearly on the visual map. The green cluster is about FinTech service, the yellow cluster is about techniques used
in FinTech, the red cluster is about the FinTech ecosystem, the light blue cluster is about digitalisation, the
orange cluster is big data, and the purple cluster is about the application of FinTech such as Islamic FinTech and
FinTech used in SMEs.
DISCUSSION AND CONCLUSION
The goal of the present article was to highlight a few research questions. We have addressed the following
research questions in this current article: RQ1: What is the current state of FinTech publication? RQ2: What are
the most productive contributors to FinTech research? RQ3: Which are the most influential articles on FinTech?
RQ4: What are the authorship patterns of the publication in FinTech? RQ5: Which themes of FinTech are most
popular among researchers?
According to our findings, FinTech research is convergent across multiple research areas. However, the most
prominent area focuses on business, management, and accounting. From 2016 to 2020, the number of
publications is increased. 2020 has the most publications, with 288 papers published in the Scopus database.
Rabbani, M.R. from Bahrain is the most well-known FinTech scholar, having published eight papers. Bina
Nusantara University in Indonesia is the most influential institution contributing to FinTech publications over
the last 38 years. However, if we rank countries, Indonesia comes in third place, trailing only the United States
of America (USA) and China.
The most popular topic is a mobile payment and financial service transformation. It is widely assumed that the
most popular topic of discussion in FinTech is related to the transformation of the banking industry. The
increased use of mobile devices increases the demand for financial technology applications developed during
COVID-19. The increment corresponds to FinTech 3.5, demonstrating a high reliance on smartphones daily.
The findings also show that the total number of citations increased significantly between 2016 and 2019.
FinTech has been of primary interest for decades. Our findings advance our understanding of the trend in
FinTech topic publication by analysing the trend for 38 years. Regardless of the obvious significance of this
work in revealing the edge of FinTech research, some limitations are unavoidable. Notably, the preceding
FinTech research repertory is limited to those solely indexed in the Scopus database, perhaps the most extensive
academic research collection. As a result, despite their potential importance, papers from sources other than
Scopus were excluded from the analysis. However, these constraints open exciting avenues and solutions for
future research on the same subject. It would be useful for future studies to include additional methodological
tools, such as multiple combination analyses and databases and bibliometric analysis. Future research may
extend this work by adding the coverage of the analysis by adding the systematic literature review of the analysis.
Researchers can further analyse the issues obstructing FinTech research and what more is to be done in this area.
ACKNOWLEDGEMENT
Financial support from the Accounting Research Institute through the Matching Research Grant Scheme (600-
RMC/ARI 5/3(016/2021) is acknowledged.
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