BenchCouncil Transactions on Benchmarks, Standards and
Evaluations, 2026
Review Article
REVIEW ARTICLE
Mapping the Intellectual Landscape of Blockchain in
the Banking Industry: A Hybrid Bibliometric and
Systematic Review (2015–2025)
Sadeq Abdullah Aladeeb
1,2,∗
and Fatima Zohra Sossi Alaoui
1
1
Laboratory of Economics, Finance, Management and Innovation, Faculty of Economics and Management, Ibn Tofail University, Kenitra, Morocco
and
2
Department of Accounting and Auditing, Faculty of Commerce and Economics, Sana’a University, Sana’a, Yemen
∗
Corresponding author. Email: sadeqabdullahhasan.al-adeeb@uit.ac.ma
Received on 8 August 2025; Accepted on 13 March 2026
Abstract
The advent of blockchain technology has introduced new alternatives to traditional banking systems, providing a decen-
tralized, secure, and transparent framework. However, its adoption is still complex and uneven for many reasons. This
study provides a comprehensive mapping of the intellectual trajectory, thematic structure, and development of blockchain
technology research in the banking sector. Using a hybrid literature review methodology that combines bibliometric anal-
ysis and systematic content review, the study analyzes 389 peer-reviewed publications retrieved from Scopus (2015–May
2025). VOSviewer was employed to conduct performance analysis and science mapping, including co-authorship, co-
citation, keyword co-occurrence, and bibliographic coupling analyses. In parallel, qualitative thematic analysis identied
six clusters: (1) blockchain in banking and nancial intermediation to enhance operational eciency, (2) decentralized
nance and cryptocurrencies, (3) integration of blockchain with other digital innovations, (4) trust-related dimensions,
(5) institutional and regulatory aspects, and (6) strategies for modernizing banking business models. The ndings reveal
a steady rise in research output, regional disparities in collaboration, and thematic evolution from early conceptualiza-
tion to recent signs of diversication of applied research. By integrating quantitative and qualitative insights, this study
highlights key research gaps, oers directions for future work, and provides guidance for academics, practitioners, and
policymakers on the transformative potential and challenges of blockchain in banking.
Key words: Blockchain Technology, Banking Sector, Bibliometric Analysis, Systematic Content Review, Financial
Technology, Decentralized Finance
1. Introduction
In recent years, the banking sector has undergone a signicant
transformation, driven by the rapid advancement of emerging
technologies, particularly blockchain. The widespread adoption of
smartphones and high-speed data transmission has not only dis-
rupted social interactions but also traditional business operations.
However, legacy banking systems have faced challenges in adapting
to these technological advancements due to factors such as struc-
tural rigidity, high operational costs, and inadequate transaction
processing speeds. For instance, cross-border remittances frequently
necessitate several days to complete, an ineciency that starkly con-
trasts with the near-instantaneous nature of digital communication
[1].
In this context, blockchain technology emerged in 2008 as the
technology underpinning Bitcoin, a peer-to-peer digital currency
eliminating the intermediary [2]. Its decentralized nature allows
for secure, anonymous, and cost-eective transactions. This has
led to the conclusion that it possesses considerable potential as an
o-balance sheet replacement for conventional banking systems [3].
The theory behind blockchain, however, goes back to the early
1990s when Stuart Haber and W. Scott Stornetta developed a cryp-
tographically secure method of time-stamping digital documents
[4]. Their subsequent introduction of Merkle trees enabled data
to be gathered into chained blocks, signicantly enhancing secu-
rity as well as eciency [5]. The modern blockchain, conceptualized
by Satoshi Nakamoto, is a form of Distributed Ledger Technology
(DLT) that utilizes consensus algorithms on distributed nodes to
record transactions [6, 7]. The design of the blockchain, which con-
sists of a series of blocks that are cryptographically linked, ensures
immutability and tamper-proong. Consequently, it establishes a
highly reliable digital record-keeping system [8]. The application
of blockchain technology has expanded beyond its initial imple-
mentation in the domain of cryptocurrency. It has been adopted
in various elds, including logistics, health, public administration,
supply chain management, and, notably, nancial services [9–14].
© The Author 2026. BenchCouncil Press on Behalf of International Open Benchmark Council.
1
S. A. Aladeeb et al.
In the banking sector, blockchain is increasingly seen as an inno-
vative way to transform the trustworthiness and reliability of data
management [15]. As digital technology continues to penetrate daily
life and concern about data security grows, blockchain’s signicance
will continue to rise. It may become as integral to daily life as the
internet [6]. Furthermore, the emergence of newer technologies, such
as blockchain, will transform the banking sector in the near future
[16]. For example, banks are expected to save $10 billion in cross-
border payment fees by 2030 by adopting blockchain technology
[17]. According to World Economic Forum projections, blockchain
technology will reach a signicant milestone by 2027, becoming in-
tegrated into various sectors of the global economy. A considerable
augmentation in the nancial sector, including the banking industry,
is projected to increase GDP by 10% [18].
Among the most prominent manifestations of this transformation
is the rise of decentralized nance (DeFi), which uses blockchain
technology to facilitate peer-to-peer nancial services without the
need for intermediaries such as conventional banks. This setup tran-
scends geographical locations and provides basic nancial services,
such as savings, loans, and investment products to poor communities
in emerging economies [19, 20].
As a revolutionary innovation, blockchain technology oers
numerous benets: enhanced security, privacy, operational trans-
parency, and increased eciency. This is all a result of its de-
centralized nature and the use of cryptographic algorithms, which
signicantly reduce the risk of cyberattacks and fraud while ensuring
traceability and data integrity [21–24]. Consequently, banks are in-
creasingly exploring blockchain technology for applications such as
cross-border payments, streamlined Know Your Customer (KYC)
processes, enhanced anti-money laundering (AML) measures, and
automated contract enforcement through smart contracts. These
innovations collectively contribute to lowering operational costs and
improving overall eciency [25, 26].
Despite the promise of blockchain technology, its adoption by
banks faces limiting factors. These factors include regulatory un-
certainty, technical complexity, and resistance to change at the
organizational level. A meticulous examination of the opportuni-
ties and limitations presented by this technology is imperative,
accompanied by a thorough assessment of awareness, readiness, and
acceptance levels among banks and customers [27–29].
The timing, evolution trajectory, and possible impact of
blockchain technology on banking have garnered considerable inter-
est among academics and practitioners. In recent years, academic
interest in the topic has increased markedly, resulting in a large and
diverse body of literature. No study, to the best of my knowledge,
has ever carried out a detailed systematic mapping of the intel-
lectual structure, theme development, and future research trends
of blockchain literature in the banking sector using a systematic
integration of bibliometric analysis and systematic content review
methods. Consequently, there is a need to identify and assess the
current state of the art and prevailing research trends in this domain.
To ll this gap, this study utilizes a hybrid methodology of lit-
erature review, combining the bibliometric analysis and systematic
content review to answer the following research questions:
RQ1: What are the prevailing research trends and patterns of
scholarly collaboration in the domain of blockchain technology in
the banking sector between 2015 and 2025?
RQ2: What are the core thematic clusters and intellectual
structures underpinning blockchain research in the banking sector?
RQ3: What key research gaps and future directions can be iden-
tied to advance the understanding and application of blockchain
technology in the banking sector?
Amidst the accelerating digitalization of banking and nancial
systems, blockchain technology is revolutionizing how banking ser-
vices are produced and disseminated. The primary aim of this
research is to synthesize the current academic literature on the
impact of blockchain on banking by identifying the key concepts,
emerging research trends, and prevailing themes. To this end, the
study adopts a mixed-method research approach combining quan-
titative bibliometric analysis with a qualitative systematic content
analysis to map the intellectual landscape of blockchain studies in
banking. The combination strengthens the validity and credibility of
the ndings, oering an overarching perspective on how blockchain
is reshaping the industry. Besides mapping the literature, the study
provides critical reections on academic and institutional responses
to the emergence of blockchain and indicates avenues for further re-
search in a bid to advance its revolutionary potential in the banking
sector.
By doing so, this study contributes to a deeper understanding of
the signicant development of the eld and guides future academic
and practical engagement with blockchain innovation in the banking
sector. The novelty of the study lies in its explicit framework of tri-
angulation and cross-validation that combines bibliometric science
mapping and qualitative thematic analysis, providing valuable and
actionable insights for academics, practitioners, and policymakers.
In addition, the study contributes to the development of transpar-
ent, safe, and eective banking and nancial systems by identifying
the advantages and obstacles related to the adoption of blockchain
technology systematically and the proposal of an organized agenda
for future research in this eld.
The present article is structured as follows. Subsequent to this
introduction, Section 2 delineates the hybrid review methodology,
meticulously expounding the bibliometric and systematic content
analysis approaches. In Section 3, the results of the performance
analysis and science mapping of 389 publications on blockchain in
banking are presented, and the six main thematic clusters identi-
ed are discussed. Section 4 identies the managerial and practical
implications of the ndings. Finally, Section 5 oers the main con-
clusions, which include a summary of the key ndings, a proposal
of directions for future research, and an acknowledgement of the
study’s limitations.
2. Research Methodology
To achieve the purposes of this study, we use a hybrid review
methodology that integrates bibliometric analysis and systematic
content analysis. The mixed-method approach combines quantita-
tive analysis with a substantial emphasis on qualitative analysis.
A hybrid review approach, as described by Paul and Criado [30],
is a method that facilitates a comprehensive examination of the lit-
erature by combining quantitative and qualitative approaches, with
the aim of organizing, analyzing, and interpreting data in a mean-
ingful way. The objective is to provide a comprehensive summary
of the scholarly literature on the adoption of blockchain technology
(BCT) in the banking industry and to oer an integrative review of
the main topics, major ndings, and research agendas for the future
in this domain.
Bibliometric analysis, which relies on the statistical evaluation of
academic production [31], is complemented in this study by content
analysis, a qualitative technique used for the systematic analysis of
textual information and disclosure structure of existing knowledge
within a given discipline [32]. The methodology stages and analytical
tools adopted to fulll the objectives of the study are outlined in
Figure 1.
2
Stage 1:Research
Planning
Stage 2: Data
Collection
Stage 3 : Bibliometrics
Analysis
Stage 4: Systematic
Content Review and
Thematic Analysis
Research Aims
Research Questions
Database Selection (Scopus)
Keyword Identification
Search Query Formation
Document Screening (Inclusion/Exclusion Criteria)
Final Dataset (389) Documents
Performance Analysis
Visualization (VOSviewer, Excel)
Bibliographic Coupling
Keyword Co-occurrence
Co-citation Analysis
Co-authorship Analysis
Selection of 70 Documents based on Bibliographic Coupling
Identification of Key Clusters
Cross-Validation with key Thematic Cluster
Manual Thematic Coding
Review and Analysis of the Dataset Content
Stage 5 : Outputs
Research Implications/ Future Research Directions
Thematic Clustering
Trends & Influential Entities
Finalize 6 Thematic Clusters
Figure 1. Research Design of the Hybrid Bibliometric–Systematic Literature Review (Developed by the Authors)
3
S. A. Aladeeb et al.
2.1. Data Collection
2.1.1. Database Selection
In this stage, data were collected from the Scopus database, a
widely recognized and reputable source for bibliometric research
[18, 33]. Although there are other databases, such as Web of
Science, IEEE Xplore, and Google Scholar, Scopus was selected be-
cause it oers the largest curated abstract and citation database
of peer-reviewed social science and business publications, index-
ing over 27,000 active titles from more than 7,000 international
publishers, with particularly strong coverage in Finance, Manage-
ment, Economics, and Information Systems disciplines[34, 35]. Prior
bibliometric methodology research indicates that Scopus retrieves
broader journal coverage and comparable citation structures to Web
of Science for management and interdisciplinary technology studies,
while oering superior metadata consistency for science mapping
analyses. Its extensive coverage also makes it convenient for re-
search in corporate nance, such as the adoption of blockchain in
the banking sector. A dened inclusion criterion was applied for the
selection of relevant keywords and the extraction of the dataset for
bibliometric analysis and systematic literature review.
2.1.2. Keyword Identication
To identify the appropriate keywords for retrieving the dataset of
our research, we have carried out a comprehensive review of the
previous literature on blockchain in the banking sector. The focus
was on determining the most frequent words used in the current
literature [18, 36, 37]. For this purpose, Google Scholar was used in
the search using the keyword phrase ”Blockchain Technology in the
Banking Sector,” and related studies were referenced to determine
common keywords. Besides, previous bibliometric and systematic
literature reviews were also examined to conrm that the selected
keywords were inclusive and specic.
Based on this literature review, we identied several frequently
used search terms, such as ”Blockchain in Bank,” ”Blockchain
Technology in Bank,” ”Blockchain in Finance,” and ”Blockchain
Technology in Finance.” Additionally, Boolean search strings such
as (blockchain AND banking) and (block-chain AND adoption
AND banking) were identied. Furthermore, consultation with two
academic experts in nance and block-chain conrmed that the key-
words ”Blockchain AND Banking” are frequently used to describe
studies where both blockchain and banking are major foci, rather
than merely contextually related.
Although this exploratory phase did identify a number of re-
lated terms, we purposely restricted the scope of the nal retrieval
query to just ”Blockchain AND Banking” to make sure that both
the blockchain and banking domains are the primary focus of our
analysis and that the studies retrieved are focused products of those
two areas of study. Moreover, the selection of these keywords is con-
gruent with our research objectives, particularly in developing an
intellectual structure and determining the main contributions to-
wards the understanding of the impact of blockchain technology on
banking.
2.1.3. Search Criteria and Data Extraction
The data collection process during the study was conducted system-
atically, following standard bibliometric study practices [38] and
PRISMA guidelines for transparent reporting [39]. On 12 May 2025,
a search was made using the Scopus database with the search term
”Blockchain AND Banking” and yielded 1,641 documents published
between 2015 and 12 May 2025. Although blockchain technol-
ogy emerged in 2008, until 2015, academic interest in adopting
blockchain technology in the banking sector was signicantly nonex-
istent. Therefore, the selected time frame (2015–2025) indicates the
evolution of scientic production in the eld.
Because of the novelty and rapid progress of the research eld,
formal inclusion criteria were applied to ensure the analytical rele-
vance and dataset quality. Only peer-reviewed articles, conference
papers, and review articles were chosen, restricting analysis to the
most relevant subject areas: Business, Management, and Account-
ing; Economics, Econometrics, and Finance; and Social Sciences.
Publications that focused primarily on technical or computational
aspects without a substantial connection to banking, economic, or -
nancial applications were excluded to maintain thematic consistency
with the study’s objectives. Additionally, only English-language doc-
uments were included to ensure conceptual consistency and facilitate
systematic review. The nal search string was as follows:
TITLE-ABS-KEY ( Blockchain AND Banking ) AND PUB-
YEAR > 2015 AND PUBYEAR < 2026 AND ( LIMIT-TO (
SUBJAREA , ”BUSI” ) OR LIMIT-TO ( SUBJAREA , ”ECON”
) OR LIMIT-TO ( SUBJAREA , ”SOCI” ) ) AND ( LIMIT-TO (
LANGUAGE , ”English” ) ) AND ( LIMIT-TO ( DOCTYPE , ”ar”
) OR LIMIT-TO ( DOCTYPE , ”cp” ) OR LIMIT-TO ( DOCTYPE
, ”re” ) )
This search strategy prioritizes thematic specicity over broad
recall, which is a typical approach used in bibliometric mapping
studies that strive for clearer concepts and greater analytical co-
herence. In addition, exploratory pilot studies utilizing broader
terminology (ntech, nancial services, distributed ledgers, etc.)
resulted in the retrieval of an excessive number of records (more
than double) that either only slightly or not substantially refer-
enced Blockchain and/or Banking. As a result, continued usage of
this focused search strategy was maintained to ensure precision and
maintain the analytical quality of the results of bibliometric and
thematic analyses of this research.
Following the removal of duplicates and non-relevant documents
using lters, the nal dataset of 389 documents was attained.
The records were saved in CSV (Comma-Separated Values) for-
mat for subsequent bibliometric analysis. To ensure replicability and
transparency, the dataset has been publicly released in a special
repository and is in line with the banking and nance literature’s
standard practices.
2.2. Data Renement and Analysis
The second stage of the systematic protocol involved rening re-
trieved data after the previous step to generate a dataset for
bibliometric mapping and thematic synthesis of the literature. It
is important to note that this stage did not change the content
or makeup of the dataset retrieved from earlier stages; rather, it
enhanced the reliability and interpretability of analyses of keyword-
based data, specically co-occurrence networks and clustering
themes from keywords.
Data preparation involved the systematic elimination of false
positives, the cleaning of metadata elds, and the normalization of
author-provided keywords. Keyword optimization was accomplished
by merging singular and plural forms, standardizing spelling dier-
ences, and consolidating synonymous terms into cohesive conceptual
labels. For instance, terms like ”cryptocurrency” and ”cryptocur-
rencies,” ”smart contracts” and ”smart contract,” as well as ”bank”
and ”banks,” were standardized into singular keyword inputs. Ad-
ditionally, terminology standardization was employed to harmonize
overlapping denitions typically found in the diverse blockchain lit-
erature. This process included incorporating equivalent phrases such
as ”distributed ledger,” ”distributed ledger technology,” ”ntech,”
”decentralized nance,” and ”DeFi,” along with ”banking sector”
4
and ”banking industry.” Terms that were irrelevant or contextu-
ally unsuitable (such as ”bibliometric analysis and COVID-19”)
were eliminated to uphold thematic consistency. After optimiza-
tion and normalization, two complementary analytical methods were
executed: - Descriptive bibliometric analysis, which evaluated pub-
lication trends, citation patterns, source productivity, and networks
of key contributors across various elds; - Systematic content anal-
ysis, which pinpointed key research themes, core theme groups, and
predominant scholarly discussions arising from the literature.
As a result, this renement process ensured the statistical relia-
bility of bibliometric network structures and the conceptual clarity
of thematic interpretations while not impacting article inclusion or
research coverage.
2.2.1. Bibliometric Analysis
Following the collection and preparation of the research dataset, a
scientometric analysis was conducted for the purpose of examin-
ing the structure and dynamics of the research eld. In this study,
VOSviewer [40], a specialized computer software program for con-
structing and visualizing large-scale bibliometric networks [41], was
employed. VOSviewer software was selected due to its proven capa-
bilities in the management of large networks, as well as its inbuilt
text-mining functionality, which enables the extraction and analysis
of valuable terms and concepts from the literature [42]. Additionally,
Microsoft Excel was used for statistical analysis and data visualiza-
tion, including examining publication trends by year, conducting
citation analysis, and determining keyword frequency.
Bibliometric analysis provides a comprehensive approach for
tracing the development of a research theme with established and
reproducible methods. These methods are largely recognized as
objective, accurate, and reproducible [43]. Two main bibliometric
approaches were applied in this study: performance analysis and
science mapping.
Performance analysis is a fundamental component of bibliometric
analysis, focused on the quantitative assessment of scientic produc-
tivity and impact. It provides a data-driven perspective of scholarly
output and the growth of a scientic discipline over time. This
technique encompasses the analysis of annual publication trends,
identication of highly cited publications, evaluation of leading sci-
entic journals, and assessment of the research contributions by
institutions, countries, and individual authors [44]. By examining
these indicators, performance analysis provides a comprehensive un-
derstanding of the intellectual evolution of the eld and uncovers its
most inuential contributors.
Science mapping, on the other hand, provides a graphic and
structural representation of the intellectual architecture of the eld
[45]. This technique involves advanced bibliometric techniques such
as co-authorship analysis, citation and co-citation analysis, keyword
co-occurrence, and bibliographic coupling. These analyses help to
uncover primary research areas, common keywords, and the the-
matic clusters that form the landscape of the eld [46]. In particular,
bibliographic coupling was used to study thematic clusters and cur-
rent fronts of research to identify emeging topics, research gaps,
and directions for future research. Certain previous bibliometric
research has utilized similar approaches to examine blockchain re-
search within the banking sector [18], [36], [37], conrming the
relevance and propriety of the methodology used herein.
2.2.2. Systematic Content Review
To comprehensively explore the emerging themes of block-chain
technology in banking, this study adopted a two-phase method-
ological design. Specically, it combined bibliometric analysis with
systematic content review. The mixed-method approach was used
to address the research questions RQ2 and RQ3. By integrating
quantitative and qualitative techniques, the study aimed to synthe-
size dominant research themes, assess how blockchain would impact
banking operations, and ascertain dominant scholarly trends. Sys-
tematic content analysis not only contributed to complementing
bibliometric ndings but also to enhancing the interpretative depth
of the results.
In the rst phase, bibliometric techniques were applied using
VOSviewer in order to visualize the intellectual structure of the
eld. Following the procedure outlined by [38], two science mapping
techniques were used. First, an analysis of keyword co-occurrence
was performed to identify words that frequently co-occur together
in the metadata of articles’ titles, abstracts, and keywords [47].
Consequently, the main research areas, key themes, and emerging
research topics were identied [45]. Second, bibliographic coupling
was employed to cluster articles that share common cited references,
thereby revealing thematically related research streams [48]. A min-
imum citation threshold of 30 citations per document was applied to
exclude publications with limited scholarly impact. This resulted in
the selection of 69 highly cited papers. Additionally, the 10 highly
cited papers were manually added to ensure conceptual compre-
hensiveness. After duplicate removal and further manual ltering,
the nal dataset of 70 peer-reviewed papers was established as the
foundation for the subsequent qualitative review.
In the second phase, a qualitative content analysis was per-
formed using Braun and Clarke’s framework [49] as follows. First,
each article in the nal dataset was examined and coded to extract
relevant information regarding research objectives, methodological
approaches, core themes, principal ndings, and identied research
gaps. Second, the coded content was grouped into preliminary the-
matic categories based on their conceptual similarities. Thereafter,
these thematic categories were manually rened to ensure concep-
tual relevance and logical coherence within the categorization. For
instance, thematic clusters that have similar central themes (e.g.,
blockchain and cryptocurrency, blockchain and DeFi) were con-
solidated into a common thematic cluster. Finally, the outcomes
derived from the qualitative analysis were cross-validated against
those generated through keyword co-occurrence analysis to enhance
the results of the study.
Methodological Novelty and Contribution
The novelty of the methodological approach of this study resides
in its explicit triangulation and cross-validation framework that
combines bibliometric maps of science with qualitative thematic
analysis. Previous studies in this eld either used descriptive bib-
liometric mapping or a qualitative synthesis, but these studies were
typically based on small samples and treated these methods sepa-
rately. In contrast, this research is designed in three stages: (i) to
identify macro-level thematic structure through quantitative biblio-
metric mapping; (ii) to use systematic qualitative content analysis to
capture in-depth conceptual patterns and research gaps; and (iii) to
cross-validate the results of quantitative and qualitative analysis to
determine both the statistical relationship and conceptual alignment
of those analyses.
The triangulation approach provides greater methodological
strength because it provides a more extensive and functionally re-
liable representation of the research landscape, helping to better
establish a framework for developing theories, as well as plan-
ning future investigations into the impact of blockchain on banking
studies.
5
S. A. Aladeeb et al.
Methodological Challenges and Mitigation
The rapid growth of the literature on blockchain applications
in banking presents several methodological challenges. These is-
sues arise from four dimensions of interrelated challenges: disci-
plinary fragmentation, terminological inconsistency, publication vol-
ume/size/overview, and methodological heterogeneity. Blockchain
research in banking spans broad disciplinary areas, including -
nance, computer science, information systems, law, and regulatory
research, making it dicult to align themes and integrate theo-
ries. Additionally, many overlapping terms exist, including ntech,
digital banking, cryptocurrencies, decentralized nance (DeFi), cen-
tral bank digital currency (CBDC), etc. These multiple terms
signicantly increase the potential for conceptual confusion and
misclassication.
In addition to these diculties caused by the rapid growth in
the number of publications, many dicult processes of literature
screening and synthesis occur when hundreds of literature arti-
cles are reviewed while attempting to keep the reviews analytically
sound. Moreover, the research literature reviewed exhibited con-
siderable methodological dierences, ranging from technical system
architectures and research analysis to policy-oriented and conceptual
frameworks, complicating the synthesis of cross-study data.
To alleviate these issues, the present research develops a triangu-
lated methodological approach that employs bibliometric mapping of
literature using computer analysis tools as well as systematic qual-
itative analysis and manual validation [50–52]. Triangulating the
methodology allows for increased coverage of the literature reviewed
while providing for increased assurance of analytical integrity and
credibility in addition to conceptual consistency.
In summary, this study’s integrated methodology enhances the
validity and reliability of its ndings by combining quantitative map-
ping, qualitative thematic interpretation, and cross-validation. This
integrative approach strengthens the robustness of the ndings and
enables a holistic understanding of blockchain’s role in banking.
It also provided a solid foundation for identifying future research
directions in this evolving eld.
3. Results and Discussion
3.1. General information and performance analysis
The bibliometric analysis revealed 389 documents, published in 269
sources between 2015 and May 2025, authored or co-authored by
1,077 scholars. The principal purpose of collecting this bibliographic
dataset is to provide an overall picture of the scientic literature
that addresses the application of blockchain in banking during this
period. This overview not only identies key publication patterns
but also brings an understanding of the evolution of the eld. Such
mapping is essential for understanding the development of the topic,
as it helps to identify publication patterns, collaborative networks,
and the most active research domains. Moreover, it underscores the
academic relevance of the dataset and provides a foundation for
further analysis.
Table 1 presents the descriptive statistics summarizing the
dataset. In addition, the results illustrate key aspects of research
productivity and collaboration, such as annual publication trends
(Table 2; Figure 2), top productive scientic journals publishing in
the eld (Table 3), top contributing authors (Table 4), and most
active institutions (Table 5),leading countries in publication output
(Table 6), and the highly cited documents (Table 7). These analy-
ses collectively provide a detailed account of the scientic landscape
and support the evaluation of scholarly performance in the eld.
Table 1. Main Information of the Dataset
Description Results
Retrieval Date 12 May 2025
Time-Span 2015–May 2025
Total Publications 389.00
Subject Area:
Business, Management, and Accounting
Economics, Econometrics, and Finance
Social Sciences
Document Type:
Article 274.00
Conference Paper 84.00
Review 31.00
Number of Cited Publications 313.00
Number of Non-Cited Publications 76.00
Total Citations 9354.00
Average Citations per Publication 24.05
Average Citations per Cited Publication 29.89
Average Years from Publication 3.10
Average Citations per Year per Document 4.63
Sources (Journals, Books, etc.) 269.00
Aliations 786.00
Countries 88.00
References 18437.00
Keywords Plus (ID) 1818.00
Author’s Keywords (DE) 1131.00
Authors 1077.00
Publications per Author 0.36
Authors per Publication 2.77
3.1.1. Publication Trends Over Time
Table 2 and Figure 2 illustrate the publication trends over a year
from 2016 to May 2025. The analysis comprises metrics such as
total publications (TP), cumulative publications (CTP), total ci-
tations (TC), and average citations per publication (TC/CTP and
TC/TCP). The data reveal three distinct phases in the evolution
of the research eld: (1) Early emergence and foundational impact
(2016–2018), (2) Expansion and thematic diversication (2019–
2021), and (3) Peak production with initial signs of saturation
(2022–2025).
The initial phase (2016–2018) reects the inception of academic
activity, with four articles published in 2016 being cited 1,249 times
(312.25 per article), indicating foundational signicance. The num-
ber of publications increased from eight in 2017 to 20 in 2018,
reecting growing interest in the potential of blockchain technology
in the banking sector.
In the second phase, between 2019 and 2021, production in-
creased sharply, from 30 in 2019 to 47 papers in 2020, though
decreasing slightly to 41 papers in 2021. Despite the growth be-
ing notable, average citations declined (TC/CTP fell from 8.85 in
2019 to 5.99 in 2021), most likely due to higher participation and
decline of the novelty. This is the stage that points towards the di-
versication of research themes and the decline in the productivity of
2021, possibly impacted by global disruptions such as the COVID-19
pandemic.
The third phase (2022–2025) represents the most productive pe-
riod in terms of publication volume, with annual outputs increasing
from 54 in 2022 to a peak of 78 in 2024. Publications during this
phase constitute over half of the total output, highlighting the area’s
rapid expansion and highest level of publication activity. Although
the TC/CTP ratio fell from 6.53 in 2022 to 1.17 in 2024, this decline
6
Figure 2. Total Publications (TP) over time (2016–2025). Note: The data for 2025 (33 publications) is incomplete, reecting the data cuto date of May
12, 2025, and therefore does not accurately represent a decline in annual output.
Table 2. Publication Trends Over Time
Year TP PTP CTP TCP TC TC/CTP TC/TCP
2016 4.00 1.00% 4.00 4.00 1249.00 312.25 312.25
2017 8.00 2.00% 12.00 8.00 850.00 70.83 106.25
2018 20.00 5.00% 32.00 19.00 1033.00 32.28 54.37
2019 30.00 12.00% 62.00 28.00 549.00
8.85
19.61
2020 47.00 12.00% 109.00 44.00 2321.00 21.29 52.75
2021 41.00 11.00% 150.00 38.00 899.00 5.99 23.66
2022 54.00 14.00% 204.00 52.00 1333.00 6.53 25.63
2023 74.00 19.00% 278.00 56.00 656.00 2.36 11.71
2024 78.00 20.00% 356.00 53.00 418.00 1.17 7.89
2025 33.00 8.00% 389.00 11.00 46.00 0.12 4.18
TP = Total Publications, PTP = Percentage of Total Publications, CTP = Cumulative Total Publications, TCP = Total Cited
Publications, TC = Total Citations.
is largely attributable to the recency eect, as newer articles have
not yet accumulated signicant citations.
The data for 2025 is partial and represents an artifact of the
data cuto. As of May 12, 2025, only 33 publications were indexed
at this time. So, the apparent decline in output for 2025 constitutes
a methodological artifact rather than a substantive downturn. While
this gure is expected to increase signicantly by the end of the year,
annual publication counts, rather than citation-based indicators, re-
ect a consistent rise in research activity. Moreover, the increasing
diversication of research themes, particularly applied studies inte-
grating blockchain with AI, IoT, and FinTech, is likely to inuence
future citation patterns.
Overall, while publication volumes have risen exponentially,
falling citation metrics indicate the need for yet more innovative and
theory-driven studies. Future studies need to undertake interdisci-
plinary, problem-based approaches to advance the practical uptake
of blockchain in banking contexts.
3.1.2. Leading Scientic Journals Publishing Blockchain
and Banking Research
The most impactful journals that publish research on block-chain
technology within the banking sector are detailed in Table 3, which
presents both productivity measures (Total number of publications)
and impact indicators (Total citations, Average citations per article,
Average publication year, and normalized citation metrics). These
combined measures enable the evaluation of not only the quantity
of output but also the intellectual impact of each journal within the
rapidly changing research environment.
An important observation in Table 3 is that, while Technologi-
cal Forecasting and Social Change and Sustainability (Switzerland)
are at the forefront journals in terms of volume, each journal’s schol-
arly impact varies signicantly. Technological Forecasting and Social
Change exhibits a notably superior citation prole (648 total cita-
tions; 92.57 citations per article), which underscores the journal’s
strong focus on technology adoption, innovation dissemination, and
socio-economic changes, subjects that closely relate to block-chain
research in the nancial sector. Its wide interdisciplinary reader-
ship and emphasis on theory-driven forecasting likely enhance its
visibility and citation across various elds. In comparison, although
Sustainability frequently covers block-chain topics, its more practi-
cal and policy-oriented focus, often aimed at specic sustainability
audiences, leads to lower average citation rates (18.86 per article),
indicating a more localized rather than broad academic inuence.
In contrast, Financial Innovation, despite having published only
ve articles, boasts the highest overall citations (922) and greatest
average impact per article (184.40). This remarkable achievement
illustrates that thematic relevance of a journal, rather than just
the volume of publications, drives academic inuence. The jour-
nal’s concentrated focus on nancial technologies, digital currencies,
and banking change positions it as a primary outlet for signicant
theoretical and empirical contributions, making its articles particu-
larly prominent and often cited across nance, economics, and policy
research communities.
7
S. A. Aladeeb et al.
Table 3. Leading Scientic Journals Publishing Blockchain in Banking Research
Rank Source Documents Citations Avg. Citations Avg. Year Avg. Norm. Citations
1 Technological Forecasting and Social Change 7.00 648.00 92.57 2022.29 4.04
2 Sustainability (Switzerland) 7.00 132.00 18.86 2021.57 0.98
3 International Journal of Scientic and Technology Research 6.00 57.00 9.50 2019.67 0.21
4 Financial Innovation 5.00 922.00 184.40 2020.40 1.99
5 Technology Analysis and Strategic Management 4.00 101.00 25.25 2022.75 3.55
6 Journal of Risk and Financial Management 4.00 72.00 18.00 2022.75 1.67
7 IEEE Transactions on Engineering Management 4.00 204.00 51.00 2022.00 6.44
8 Frontiers in Blockchain 4.00 93.00 23.25 2021.00 2.01
9 New Economic Windows 3.00 543.00 181.00 2016.00 0.58
10 Journal of Money Laundering Control 3.00 116.00 38.67 2020.00 2.00
11 Journal of Financial Stability 3.00 83.00 27.67 2020.33 0.99
12 Fintech 3.00 85.00 28.33 2023.00 1.15
A similar trend is evident in New Economic Windows, which
attained 543 citations with just three publications. Its early ex-
ploration of blockchain topics (with an average publication year of
2016) enabled its articles to gather citations over an extended pe-
riod, demonstrating the benets of early involvement in emerging
research areas. These foundational studies often serve as essential
reference points for subsequent scholarship.
On the other hand, journals like the International Journal of
Scientic and Technology Research, while comparatively produc-
tive (six publications), exhibit limited citation impact (averaging
9.5 citations per article). This variance likely stems from the jour-
nal’s broader technical audience and its less focused engagement
with nancial or banking communities, leading to reduced cita-
tion engagement within social science and nance-oriented research
networks.
Normalized citation metrics further enhance impact evaluation
by considering publication age. Journals such as IEEE Transac-
tions on Engineering Management (6.44) and Technology Analysis
and Strategic Management (3.55) show strong relative citation
performance given their more recent publication schedules. Their
heightened normalized impact emphasizes the increasing importance
of management- and gover-nance-related perspectives in blockchain
research, particularly at the crossroads of engineering innovation,
organizational strategy, and transformation in the nancial sector.
Overall, these trends suggest that scholarly inuence in the realm
of blockchain-banking research is more inuenced by journal the-
matic alignment, multidisciplinary engagement, early positioning in
specic topics, and theoretical focus rather than merely by pub-
lication frequency. Journals that contextualize blockchain within
wider discussions on nancial governance, innovation management,
regulatory adjustment, and socio-economic change achieve greater
citation visibility than journals that are technically oriented or
narrowly focused on sustainability. This uneven distribution of in-
uence indicates that the intellectual essence of the eld is anchored
in publications that connect nancial theory, policy analysis, and
studies of innovation rather than solely in technically driven or
sustainability-centric journals.
3.1.3. The 10 Most Inuential Authors
Table 4 shows the most prolic authors who have made the largest
academic contributions to blockchain research in the banking sector.
This evaluation considers their productivity, citation impact, nor-
malized inuence, and the strength of their collaborative networks.
These metrics not only identify the most visible researchers but also
show how intellectual leadership and collaboration patterns shape
the eld.
It can be seen that Devi, N. Chitra and Kumari, Anitha are the
most prolic with three papers each and the same citation count
of 105 and 35 average citations per paper. While both have the
same normalized citation score (2.14), only Devi has a sizable total
link strength (19), suggesting more robust collaboration networks.
This suggests that Devi’s inuence goes beyond citation metrics
to include a bridging function between various research teams, en-
couraging cross-pollination of ideas related to adoption, operational
eciency, and governance in blockchain.
In contrast, although Mbaidin, Hisham O. has the same number
of publications of Devi and Kumari, he has lower citations and aver-
age citation per document wit 43 and 14.33 respectively. Moreover,
the author is strongly linked (link strength: 23), suggesting broad
collaborative activity in the eld. This pattern highlights authors
whose main contributions are in interdisciplinary collaboration and
empirical research across multiple countries. This fosters method-
ological diversity but may not yet result in highly cited conceptual
breakthroughs.
A dierent type of intellectual leadership is seen in authors
like Ramzi El-Haddadeh, Nitham Hindi, Vishanth Weerakkody,
and especially Uthayasankar Sivarajah. They achieve notable cita-
tion eciency despite fewer publications. Each of them had two
high-impact papers with over than 100 citations, an average of 55
citations per article, and 2.54 normalized scores, indicating inuence
and visibility. However, Uthayasankar Sivarajah has the highest ci-
tation average (109.5) and a 5.03 normalized citation score, showing
exceptional scholarly impact with fewer papers. He particularly fo-
cuses on governance, data management, and digital transformation
strategies within nancial institutions. These authors help consoli-
date theory by presenting models that link blockchain adoption with
organizational readiness and regulatory issues.
Emerging researchers like Gan, Qingqiu, and Lau, Raymond
Yiu Keung, show strong normalized citation rates of 4.78 despite
their recent publication activity, with an average publication year
of 2024.5. Their rapid accumulation of citations highlights a grow-
ing second wave of leadership focused on algorithmic nance, data
analytics, and the convergence of emerging ntech. This trend in-
dicates a shift in the eld from foundational theoretical work to
application-oriented and interdisciplinary growth.
In summary, the author network structure illustrates a layered
knowledge ecosystem that balances established theorists, network
connectors, and rapidly advancing innovators. Leadership in this
eld is dened not just by the number of publications but also by
the ability to present impactful conceptual frameworks, provide scal-
able empirical evidence, and foster new research initiatives through
collaborative networks. This evolving prole of authorship shows the
maturation of blockchain and banking research into a more unied
yet methodologically diverse academic domain.
3.1.4. The Top 10 Most Productive Institutions
Table 5 presents the leading institutions that have contributed most
to blockchain research in banking in terms of productivity, impact,
8
Table 4. The Most Inuential Authors
Rank Author TP TC APY ACPP ANC TLS
1 Devi, N. Chitra 3.00 105.00 2022.33 35.00 2.14 19.00
2 Kumari, Anitha 3.00 105.00 2022.33 35.00 2.14 0.00
3 Mbaidin, Hisham O. 3.00 43.00 2023.67 14.33 1.91 23.00
4 Choo, Kim-Kwang Raymond 2.00 63.00 2022.00 31.50 2.14 3.00
5 El-Haddadeh, Ramzi 2.00 110.00 2022.00 55.00 2.54 27.00
6 Gan, Qingqiu 2.00 37.00 2024.50 18.50 4.78 8.00
7 Hindi, Nitham 2.00 110.00 2022.00 55.00 2.54 10.00
8 Lau, Raymond Yiu Keung 2.00 37.00 2024.50 18.50 4.78 3.00
9 Sivarajah, Uthayasankar 2.00 219.00 2022.00 109.50 5.03 13.00
10 Weerakkody, Vishanth 2.00 110.00 2022.00 55.00 2.54 10.00
TP = Total Publications; TC = Total Citations; APY = Average Publication Year; ACPP = Average Citations Per Publication; ANC =
Average Normalized Citations; TLS = Total Link Strength.
and other important indicators such as, citations, average publica-
tion year, average citations per document, and average normalized
citations.
Foremost among them is the Department of Management Studies
at the Indian Institute of Technology Delhi, with 3 papers that gar-
nered 110 citations, achieving an average of 36.67 citations per paper
and an average normalized citation score of 1.32. This reects a high
academic impact and research quality in the feild. Conversely, the
Adnan Kassar School of Business at the Lebanese American Univer-
sity, despite being equally prolic with 3 papers, has a lower average
citation (3.67) and normalized citation score (0.49), revealing a less
widespread scholarly impact.
In addition, certain institutions such as Al Qasimia University,
Mutah University, Abu Dhabi University, and independent institu-
tions such as the Financial and Taxation Consultant, Jordan, both
of which have 2 papers of low citation frequency (average number
of citations per paper of 6) but relatively high normalized citation
scores (1.12), showing greater engagement and increasing popularity
over the last few years (average year of publication: 2024), were also
taken into account.
Most prominently, Spiru Haret University of Romania, with only
2 publications, received 56 citations and the highest normalized cita-
tion score (3.23), indicating the inuence of its work in the discipline.
Similarly, Symbiosis Institute of Digital and Telecom Management
achieved a moderate impact with 21 citations from 2 publications.
In general, the results show geographically widespread and in-
stitutionally varied research eorts. Productivity is spread across
institutions, but citation impact is concentrated in a few, indicating
the distinction between quantity and quality of scholarly production.
3.1.5. The Most Productive and Inuential Countries
Table 6 illustrates the signicant geographical variation in research
contributions, citation impact, and other major indicators, such as
average publication year, average citations, average normalized cita-
tions, and total link strength of blockchain research in the banking
sector.
As shown in Table 6, India is the most prolic and productive
country with 94 documents, but it is lower ranked in citation impact
(average citations per paper with 17.33 ) and normalized citation
score (1.28). This indicates that while it leads in quantity, the overall
impact remains moderate.
In contrast, the United States, with 51 papers, has the highest
total citations (2,847) and a high average citation score (55.82), thus
indicating a high academic impact. Likewise, the United Kingdom,
with a lower productivity of 25 publications, achieves the top aver-
age citations (64.44) and normalized citation score (2.42), reecting
high-quality and highly recognized research output.
China also demonstrates a balanced prole with 24 papers and
an average citation of 47.79, showing a good compromise between
productivity and impact. The United Arab Emirates shows emerging
activity with 21 papers and a good normalized score (1.41), yet still
a moderate average citation per document (12.19).
Other countries, such as Germany, Italy, and Malaysia are
moderately impactful and productive. Jordan and Switzerland, in
contrast, while producing smaller volumes of output (12 and 10
papers, respectively), stand at competitive normalized citation av-
erages (1.15 and 0.82, respectively), indicating quite high-impact
research. Surprisingly, Spain and the Russian Federation have lower
normalized and average citation indicators, reecting limited impact
despite modest research production.
Overall, India produces the most research in quantity, but other
countries like the UK, the US, and China have a greater scientic
impact. These patterns show that there is a global contribution, but
the quality and visibility of research in the eld of blockchain in
banking are uneven.
3.1.6. The Top 10 Most Cited Documents
As we stated above, the dataset is retrieved from the Scopus
database, and as we know, the topic has been investigated in various
contexts by authors from Business, Management and Accounting,
Economics, Econometrics and Finance, and Social Sciences. The
analysis of the top 10 most cited documents in blockchain and
banking research identies the seminal works that have inuenced
academic investigation and applied applications in this multidisci-
plinary research area. These documents span various areas of study,
ranging from nancial innovation to accounting, regulatory studies,
and information systems. Citation counts indicate academic and
intellectual interest, while more complex metrics, such as average
citations per year and normalized citation score, provide a bet-
ter indication of the signicant documents and their comparative
inuence over time and across research elds [53].
In view of this, Table 7 presents the ten most highly cited docu-
ments in our research eld, according to the Scopus database. It is
noted that, nine of the ten most highly cited papers received more
than 200 citations, even though most of them were published less
than four years ago.
Leading the list is Guo and Liang [26] pioneering document enti-
tled ”Blockchain application and outlook in the banking industry,”
published in the Financial Innovation journal, with a total of 706
citations as the most cited document in nance. Its average annual
citation rate of 78.44 indicates a consistently high impact since its
publication, although its normalized citation score of 2.26 suggests
that, despite its high number of citations, its performance compared
to other publications in its eld is more moderate. Nonetheless,
9
S. A. Aladeeb et al.
Table 5. The Most Inuential Institutions
Rank Institution TP TC APY ACPP ANC
1 Adnan Kassar School of Business, Lebanese American University, Beirut,
Lebanon
3.00 11.00 2023.67 3.67 0.49
2 Dept. of Management Studies, Indian Institute of Technology Delhi, New
Delhi, India
3.00 110.00 2023.00 36.67 1.32
3 Al Qasimia University, United Arab Emirates 2.00 12.00 2024.00 6.00 1.12
4 Business Intelligence and Data Analytics Dept., Business School, Mutah Uni-
versity, Jordan
2.00 12.00 2024.00 6.00 1.12
5 Dept. of Economics, College of Economics and Management, Al Qasimia Uni-
versity, Sharjah, UAE
2.00 12.00 2024.00 6.00 1.12
6 Faculty of Economics, Kharazmi University, Tehran, Iran 2.00 13.00 2022.50 6.50 0.37
7 Faculty of IT, Abu Dhabi University, UAE 2.00 12.00 2024.00 6.00 1.12
8 Financial and Taxation Consultant, Jordan 2.00 12.00 2024.00 6.00 1.12
9 Spiru Haret University, Romania 2.00 56.00 2023.50 28.00 3.23
10 Symbiosis Institute of Digital and Telecom Mgmt., Symbiosis Intl. (Deemed
Univ.), Pune, India
2.00 21.00 2022.00 10.50 0.43
TP = Total Publications; TC = Total Citations; APY = Average Publication Year; ACPP = Average Citations Per Publication; ANC =
Average Normalized Citations.
Table 6. The Most Productive Countries
Rank Country TP TC APY ACPP ANC TLS
1 India 94.00 1629.00 2022.60 17.33 1.28 48.00
2 United States 51.00 2847.00 2021.35 55.82 1.62 31.00
3 United Kingdom 25.00 1611.00 2022.08 64.44 2.42 43.00
4 China 24.00 1147.00 2022.50 47.79 1.30 20.00
5 United Arab Emirates 21.00 256.00 2022.71 12.19 1.41 12.00
6 Italy 20.00 327.00 2021.70 16.35 0.90 16.00
7 Russian Federation 19.00 169.00 2019.58 8.89 0.29 0.00
8 Germany 18.00 740.00 2021.44 41.11 1.31 8.00
9 Malaysia 14.00 186.00 2022.36 13.29 0.97 19.00
10 Jordan 12.00 103.00 2023.75 8.58 1.15 18.00
11 Spain 11.00 145.00 2021.55 13.18 0.81 0.00
12 Indonesia 10.00 137.00 2022.30 13.70 0.33 2.00
13 Switzerland 10.00 280.00 2021.80 28.00 0.82 5.00
TP = Total Publications; TC = Total Citations; APY = Average Publication Year; ACPP = Average Citations Per Publication; ANC =
Average Normalized Citations; TLS = Total Link Strength.
the work is still inuential owing to its pioneering and general in-
troduction of the revolutionary nature of blockchain for banking,
specically as it pertains to operational eciency and transparency
and transactional security.
On the contrary, Thakor’s [54] article entitled ”Fintech and
banking: What do we know? ranks second in terms of total cita-
tions (601), but outperforms all other documents in terms of average
annual citations (120.20) and the number of normalized citations
(12.17). This suggests that the study has quickly become a leading
reference in its eld, although it has just 4 years since its publi-
cation. This suggests that the study is already a classic reference
in the area. The Journal of Financial Intermediation presents a
solid theoretical model on how ntech, including blockchain tech-
nology, is transforming long-established paradigms in banking. Its
very high normalized citation score also indicates high inuence and
cross-disciplinary adoption, especially in nance, economics, and
regulation studies in banking.
Its third most cited paper, authored by Dai and Vasarhelyi [55],
entitled ”Toward blockchain-based accounting and assurance,” pub-
lished in the Journal of Information Systems, has been cited 532
times. It has a high average of 66.5 yearly citations and a nor-
malized score of 5.01, attesting to its contributory quality as a
connecting publication between accounting theory and blockchain
technology. It oers research that informs discussion about the use
of blockchain to enable auditability and trust in nancial reports,
and is thus a reference work on the research of nancial assurance
with blockchain-based.
An equally signicant contribution is made by Peters and
Panayi [56], entitled ”Understanding modern banking ledgers us-
ing blockchain technologies,” cited 452 times. Its 50.22 times per
year citation rate indicates ongoing interest by researchers, while
its normalized citation of 1.45 indicates moderate impact in its
broader research eld. The signicance of this work lies in its spe-
cic contribution to addressing distributed ledger technology and
smart contracts, and oering insight into blockchain’s technology
foundation from a banking industry perspective.
Additionally, the International Journal of Information Manage-
ment published research by Schuetz and Venkatesh [57] on using
blockchain to drive nancial inclusion in India. The article was cited
297 times with an average annual citation rate of 59.4 and a normal-
ized citation rate of 6.01. This article is clearly very interdisciplinary
in applicability. Its focus on social and developmental implications
of blockchain makes it more relevant in policy development and
nancial inclusion policies, particularly in emerging economies.
With regard to infrastructure and security, although not
banking-focused, Minoli and Occhiogrosso’s [58] article entitled
”Blockchain Mechanisms for IoT Security,” has garnered 285 ci-
tations, an average annual citation of 40.71, and a normalized
10
Table 7. The Top 10 Most Cited Documents
Rank Authors Year Title Source Document Type TC ACPY NC
1 Ye Guo & Chen Liang 2016 Blockchain application and outlook
in the banking industry
Financial Innovation, 2(1) Original research article 706.00 78.44 2.26
2 Anjan V. Thakor 2020 Fintech and banking: What do we
know?
Journal of Financial Inter-
mediation, 41
Review article 601.00 120.20 12.17
3 Dai J.; Vasarhelyi M.A. 2017 Toward blockchain-based accounting
and assurance
Journal of Information Sys-
tems, 31(3)
Conceptual research article 532.00 66.50 5.01
4 Gareth W. Peters & Efstathios Panayi 2016 Understanding Modern Banking
Ledgers Through Blockchain Tech-
nologies: Future of Transaction
Processing and Smart Contracts on
the Internet of Money
New Economic Windows
(NEW), pp. 239–278
Book chapter 452.00 50.22 1.45
5 Schuetz S.; Venkatesh V. 2020 Blockchain, adoption, and nancial
inclusion in India: Research opportu-
nities
International Journal of In-
formation Management, 52
Original research article 297.00 59.40 6.01
6 Daniel Minoli & Benedict Occhiogrosso 2018 Blockchain mechanisms for IoT secu-
rity
Internet of Things (Nether-
lands), 1–2, 1–13
Original research article 285.00 40.71 5.52
7 Zetzsche D.A.; Arner D.W.; Buckley R.P. 2020 Decentralized Finance Journal of Financial Regula-
tion, 6(2), 172–203
Conceptual/policy article 264.00 52.80 5.35
8 Poonam Garg et al. 2021 Measuring the perceived benets of
implementing blockchain technology
in the banking sector
Technological Forecasting
and Social Change, 163
Empirical research article 218.00 54.50 9.94
9 Saurabh Ahluwalia et al. 2020 Blockchain technology and startup
nancing: A transaction cost eco-
nomics perspective
Technological Forecasting
and Social Change, 151
Empirical research article 212.00 42.40 4.29
10 Mohd Javaid et al. 2022 A review of Blockchain Technology
applications for nancial services
BenchCouncil Transactions
on Benchmarks, Standards
and Evaluations, 2(3)
Review article 207.00 69.00 8.39
TC = Total Citations; ACPY = Average Citations per Year; NC = Normalized Citations.
score of 5.52. Its interdisciplinary contribution comes in the form
of providing data transmission protocols that are secure, something
that would be essential to highly technologically advanced banking
systems that are based on Internet-of-Things (IoT) incorporation.
Furthermore, regulatory aspects of blockchain are analyzed in
the most highly-cited paper by Zetzsche, Arner, and Buckley [59],
entitled ”Decentralized Finance,” which has been cited 264 times.
The article has a yearly average of 52.8 citations and a normal-
ized citation of 5.35, and it illustrates increasing academic interest
in legal and compliance matters of decentralized nancial sys-
tems. Published in the Journal of Financial Regulation, it oers
a critical framework for the examination of blockchain’s legal and
systemic issues and thus is extremely useful to researchers as well as
policymakers.
Empirical understanding of blockchain adoption is presented
in their article ”Measuring the perceived benets of implementing
blockchain in the banking sector,” which has been cited 218 times,
by Garg et al. [60]. Interestingly, it has a high average citation rate
of 54.5 per year and a signicant normalized citation score of 9.94,
which indicates high use and strong cross-eld inuence. Using struc-
tural equation modeling, the authors assign a numeric value to the
benets of blockchain, such as trust, transparency, and eciency,
and make this study highly applicable to banking professionals.
Parallel to this is the work of Ahluwalia, Mahto, and Guerrero
[61] enhances the knowledge of blockchain technology within the
entrepreneurial nance context through their empirical article ti-
tled ”Blockchain and Startup Finance.” The paper has been cited
212 times at an average rate of 42.4 citations per annum, besides
a normalized citation count of 4.29. The article extends the use of
blockchain from traditional banking institutions to its impact on
startup and venture capital environments through the adoption of
transaction cost economics as a conceptual building block. Round-
ing out the list is the most recent contribution by Javaid et al. [62],
titled ”A Review of Blockchain Applications in Financial Services,”
which accumulated 207 citations within a brief period. With an an-
nual average of 69.0 citations and a normalized citation score of
8.39, the article’s direct impact and growing importance are evi-
dent. The article summarizes the various applications of blockchain
technology in nancial services, reecting the growing demand from
academics and industry experts for comprehensive reviews amid the
rapid development of the Fintech sector.
Taken together, the citation patterns observed suggest that the
inuence within the blockchain-banking literature is more linked to
the capacity to relate technological advancements to broader insti-
tutional, accounting, regulatory, and socio-economic issues than to
purely technological innovation. Works that receive a high num-
ber of citations bring together conceptual theorization (like ntech
transformation), incorporate insights from multiple disciplines (such
as accounting, law, and information systems), and present empiri-
cal evidence that tackles real-world banking issues, including trust,
nancial inclusion, compliance, and eciency. This highlights that
the most impactful articles in academia frame blockchain not merely
as a technical tool, but as a driver for signicant changes in bank-
ing ecosystems. As a result, the structure of citations indicates a
mature eld that is progressively focusing on governance frame-
works, adoption processes, regulatory legitimacy, and organizational
transformation instead of isolated demonstrations of technology.
3.2. Science Mapping
Science mapping examines the relationships among contributors in
a research eld. Particularly, it focuses on patterns of intellec-
tual interaction and structural connections between key scholarly
constituents, such as how sources, countries, institutions, au-
thors, references, keywords, and publications relate to each other
[46, 63, 64].
The present study uses a range of science mapping techniques,
including co-authorship analysis, co-citation analysis, co-occurrence
analysis, and bibliographic coupling analysis. These methods facili-
tate gaining in-depth knowledge about the evolution of the eld, the
collaborative patterns that characterize it, and the thematic struc-
ture that underpins it [46]. When paired with network visualization
software such as VOSviewer, these methods illustrate the bibliomet-
ric and intellectual structure of the research landscape [41, 45], as
outlined below.
11
S. A. Aladeeb et al.
pakistan
canada
bangladesh
ukraine
turkey
south africa
saudi arabia
romania
iran
australia
france
switzerland
poland
indonesia
spain
jordan
malaysia
germany
russian federation
italy
united states
india
VOSviewer
Figure 3. International Co-authorship Network of Countries in Blockchain and Banking Research. Node size represents publication volume, link
thickness indicates collaboration intensity, and colors denote distinct collaboration clusters.
3.2.1. Co-authorship of Countries
Co-authorship analysis is a bibliometric technique that is employed
to study patterns of collaboration among authors, institutions, and
countries based on joint publications [65, 66]. At the national level,
it reveals international research collaboration, mapping the global
dispersion of scientic production and the transnational network
structure [67, 68]. Particularly, the analysis reveals leading coun-
tries, maps geographical patterns of collaboration, and illustrates the
eect of international networks on knowledge production [69, 70].
To explore global collaboration in blockchain research in the
banking sector, we conducted a co-authorship analysis at the coun-
try level using VOSviewer. We included countries that had at least
ve documents and 30 citations. This led to 25 out of 88 countries
meeting the criteria, with 72 links and a total link strength (TLS)
of 105. As shown in Figure 3, the visualization displays six color-
coded clusters, where nodes represent countries and links indicate
the strength and frequency of co-authorships. Node size reects pub-
lication volume, while link thickness shows collaboration intensity,
and TLS quanties a country’s total collaborative strength.
The blue cluster, led by India, comprises the United Arab
Emirates, Jordan, and South Africa, indicating close cooperation
between South Asia and the Middle East. The central position and
large node size of India highlight its high research productivity and
its role as a regional leader in blockchain innovation. The partici-
pation of the United Arab Emirates and South Africa signies an
escalating level of interest in the nancial applications of blockchain
among digitally transforming economies.
The red cluster comprises the United States, China, Italy,
Romania, Saudi Arabia, Pakistan, and Canada, forming a wide in-
tercontinental network. The U.S. stands out for its high research
volume and multiple collaborative ties. This cluster spans North
America, Europe, the Middle East, and South Asia, indicating rich
interdisciplinary exchanges. China and Italy are major contribu-
tors to the technological and regulatory aspects of blockchain, while
Saudi Arabia and Pakistan can point to stronger academic connec-
tions with the West, possibly underpinned by digitization reforms
and plans like the Vision 2030 of Saudi Arabia.
The yellow cluster includes the Russian Federation, Germany,
Switzerland, and Turkey. Though geographically spread across Eu-
rope and Eurasia, these countries show strategic interest in digital
nance and decentralization. Germany and Switzerland lead in
ntech, while Russia and Turkey focus on modernizing nancial
systems, suggesting collaboration based on national strategies for
digital transformation.
Moreover, the purple cluster consists of the United Kingdom,
France, and Iran. The UK is the middle connection between the
Middle East and Western Europe, showing high intra-European co-
operation along with historical scholarly ties to the region. France
and the UK are high-output researchers, while Iran shows up as a
leading Middle Eastern producer of blockchain research. However,
the light blue cluster includes Poland, Spain, and Ukraine. The
nations, while not central, are reective of increasing Eastern and
Southern European engagement in blockchain research. Their inclu-
sion is reective of increased cross-border collaboration as well as a
willingness to adopt blockchain towards economic modernization.
12
Overall, the ndings of this analysis reveal a dispersed worldwide
and interconnected research landscape. Developed and emerging
economies are actively engaging with blockchain research in banking.
3.2.2. Co-citation of Authors
Co-citation analysis is a bibliometric technique that is applied to ex-
amine the intellectual landscape of a research area through analyzing
how frequently two documents, authors, or sources are cited together
in subsequent works [71]. A specic type of this analysis, Author
Co-citation Analysis (ACA), examines how frequently two authors
appear cited in tandem, therefore reecting the conceptual structure
underlying scholarly communication and conceptual evolution in an
area [72, 73]. An increased frequency of co-citation between two au-
thors implies a tight thematic correspondence or common inuence
on the shaping of specic streams of research [74].
In the current study, to better understand intellectual founda-
tions and underlying blockchain research in the banking context,
an author co-citation analysis was conducted using VOSviewer soft-
ware. We applied a minimum threshold of 25 citations per author,
resulting in the identication of 102 prominent authors out of a total
of 25,779 who met the predened criteria.
As shown in the network map in Figure 4, the authors were dis-
tributed to four distinct clusters, each represented by a dierent
color. This network included 4,921 co-citation links and a total link
strength of 56,680. The authors are shown as nodes within the clus-
ters, while the edges illustrate how they have been co-cited. The
sizes of the nodes indicate the extent of their co-citation. As a re-
sult, authors who are frequently co-cited appear as larger nodes.
This pattern reveals a strong trend in scholarly relationships and
co-citations, along with the overall growth in research for this eld.
The red color is the rst cluster in the network map. It is the
largest and most central cluster and consists of authors like Chen
Y., Chen S., Wang Y., Wang H., Liu J., Zhang Y., and Xu X.
These authors have made major contributions in applying blockchain
technology, digital technology, and information systems to banking
and nance. They are most frequently cited in academic literature,
i.e., they are the foundation of theoretical and empirical research on
blockchain technology in the eld. This cluster is also highly linked
to other clusters, which indicates the intellectual power of the cluster
over other elds.
In contrast, the second cluster, as can be shown by the blue color,
includes prominent authors Kumar S., Khan S., Arner D.W., Zet-
zsche D.A., Thakor A.V., Kauman R.J., and Hassan M.K. These
authors are mainly involved with nancial regulation, law, and
policy matters related to blockchain technology. Their co-citation
network indicates that they concentrate on the risk, governance,
and legal concerns of blockchain implementation in banks. The
uniqueness of the cluster indicates the interdisciplinary connection
of information systems, law, and nance.
The third cluster, shown in green color, consists of authors such
as Nakamoto S., Tapscott D., De Filippi P., Eyal I., Zhang Z., Has-
sani H., Janssen M., Potts J., and El-haddadeh R. They provide an
all-round perspective of the revolutionary role of blockchain tech-
nology in banks. They examine cryptocurrencies, decentralization,
governance, and innovation. Additionally, their co-citation suggests
blockchain research covers a wide range of themes, from technical
to legal, economic, and regulatory domains.
Finally, the fourth yellow color cluster comprises the following
authors: Dwivedi Y.K., Kshetri N., Gupta S., Gunasekaran A., and
Venkatesh V. This cluster also appears to be talking about infor-
mation systems, models of technology adoption, and regulatory
eects of blockchain technology. The cluster suggests that there
is a widening of the research landscape on the implementation of
blockchain technology in bank operations and business designs, with
a concentration on technology adoption and strategic management.
In summary, these ndings will be valuable to other researchers,
IT professionals, nancial service rms, practitioners, and banking
professionals looking to consult with the right experts in related
services.
3.2.3. Keyword Co-occurrence Analysis
Keyword co-occurrence analysis is a widely used bibliometric
method that is employed to map and identify the intellectual struc-
ture and thematic evolution of a research eld. It measures the
frequency with which co-occurring pairs of keywords appear in the
same papers, based on the assumption that higher co-occurrence in-
dicates a stronger conceptual relationship between the terms [47].
This technique enables researchers to identify the primary research
themes, evaluate the conceptual associations, and detect emerging
topics in the literature [45, 75].
In the present study, we conducted a keyword co-occurrence
analysis using VOSviewer software to gain a more profound un-
derstanding of the thematic context of blockchain technology in
the banking sector. This approach has been demonstrated to be
eective in identifying the leading research clusters and their con-
nections. This is based on the frequency of using keywords and how
they co-occur across publications’ titles, abstracts, and keywords.
For this study, a minimum of ve occurrences for an author-
keyword was applied as an inclusion criterion. This was used to
ensure an analytical focus on the most relevant and frequently oc-
curring terms. Of the 1,131 keywords examined, 52 satised this
initial criterion. In the second stage of our research protocol, we
manually rened the dataset of the selected keywords by merging
singular and plural terms, such as ”cryptocurrency” and ”cryp-
tocurrencies,” ”smart contract” and ”smart contracts,” and ”bank”
and ”banks.” We also consolidated and standardized synonyms, in-
cluding ”distributed ledger” and ”distributed ledger technology,”
”ntech” and ”nancial technology,” ”decentralized nance” and
”DeFi,” and ”banking industry” and ”banking sector.” Furthermore,
we eliminated keywords that were not related to our topic, such as
”bibliometric analysis and COVID-19.” Following the data rene-
ment, the 42 keywords were included in the nal analysis. Table
8 presents the most frequently occurring keywords and the data
needed to ascertain areas related to blockchain research in banking.
The 42 keywords yielded 289 links, with a total TLS of 799, and
were organized into six distinct thematic clusters.
Table 8. Top Keywords by Occurrence
Rank Keyword Occurrences TLS
1 blockchain 206.00 373.00
2 ntech 68.00 171.00
3 banking 49.00 125.00
4 blockchain technology 49.00 49.00
5 cryptocurrency 40.00 104.00
6 bitcoin 33.00 92.00
7 articial intelligence 19.00 54.00
8 nancial inclusion 16.00 39.00
9 smart contracts 16.00 30.00
10 nance 14.00 39.00
11 digital banking 13.00 27.00
12 nancial services 13.00 36.00
13 innovation 13.00 40.00
14 security 13.00 31.00
13
S. A. Aladeeb et al.
wang l.
weber i.
panayi e.
kauffman r.j.
auer r.
bouri e.
zetzsche d.a.
bellavitis c.
sharma r.
hassan m.k.
chen s.
arami m.
li h.
liu y.
huang x.
garg p.
liu j.
el-haddadeh r.
rabbani m.r.
hair j.f.
thakor a.v.
yarovaya l.
li z.
swan m.
sarkis j.
queiroz m.m.
beck r.
gunasekaran a.
corbet s.
kumar a.
li y.
weerakkody v.
tapscott a.
kshetri n.
arner d.w.
zhang h.
de filippi p.
guo y.
li j.
zheng z.
nakamoto s.
kumar s.
xu x.
chen y.
chen x.
venkatesh v.
gupta s.
wang y.
wang h.
VOSviewer
Figure 4. Author Co-citation Network in Blockchain and Banking Research. Node size corresponds to citation inuence, while links indicate co-citation
strength. Colors denote major intellectual clusters.
The network visualization produced (Figure 5) presents these
clusters with each node representing a keyword, the node size rep-
resenting frequency of occurrence, and lines (edges) representing
co-occurrence relationships. The thickness of the lines is indicative
of the strength of the relationship between terms, with thicker lines
denoting a stronger relationship. The closeness of the lines to each
other is also a helpful way to determine how related they are.
As shown in the network map, the keyword ”blockchain” is the
most central node in terms of frequency of occurrence and inter-
connectivity. This is indicative of its central position in scientic
discourse. Secondary keywords such as ”banking,” ”ntech,” ”cryp-
tocurrency,” and ”Bitcoin,” which are also highly frequent and
highly interconnected, emphasize blockchain’s central position in
discourse regarding digital change in the nance and banking sec-
tor. The visualization (Figure 5) breaks down six distinct thematic
clusters based on the following:
The initial cluster (blue) focuses on cryptocurrencies and de-
centralization, as evidenced by the terms ”blockchain,” ”Bitcoin,”
”cryptocurrencies,” ”decentralization,” ”Ethereum,” ”money,” and
”regulation.” The strong interconnection between these key-
words and ”blockchain” indicates the inherent relationship of
blockchain technology with digital currencies, particularly Bitcoin
and Ethereum, which have always been of academic interest and
a research topic in this eld. Furthermore, the cluster groups crit-
ical words that dene the world of cryptocurrency, since Bitcoin,
Ethereum, and cryptocurrencies in general have a very close link
with terms such as ”decentralization” and ”money.” It is clear that
the literature in this cluster provides a comprehensive overview of
the history and evolution of blockchain technology as applied to
decentralized digital currencies. In addition to this, it provides a
detailed discourse on the regulation of crypto assets, which is an in-
evitable consequence of the disruptive eect that these assets have
on traditional nancial institutions. This cluster reects a wide range
of studies on how blockchain technology can reshape the structure of
money and payment systems, indicating sustained academic interest
in decentralized money innovations.
Conversely, the second cluster (red) focuses on banking in-
novation and technology adoption. This cluster includes both
emerging technology keywords, such as machine learning, arti-
cial intelligence, big data, and the Internet of Things, as well
as banking applications, including technology adoption, cybersecu-
rity, sustainability, and digital banking. Together, these keywords
encapsulate the technological infrastructure necessary to integrate
blockchain technology into banking. Furthermore, this suggests that
researchers are progressively interested in examining the combina-
tion of blockchain with other emerging technologies to re-engineer
banking operations and service delivery. The emphasis on cyberse-
curity and sustainability indicates great concerns about the security
and sustainability of innovation within nancial institutions.
Similarly, the third cluster (in green) includes the keywords
”banking,” ”ntech,” ”nance,” ”nancial services,” ”nancial in-
clusion,” ”crowdfunding,” and ”peer-to-peer lending.” This indicates
an awareness of blockchain technology’s macro-level ramications
on the augmentation of access to and eciency of nancial sys-
tems. The prevalence of the term ”ntech” in this cluster captures
the essence of the transformation in nancial intermediation, high-
lighting the pivotal role of blockchain technology in reengineering
nancial services. Additionally, the intersection of ”ntech” and
14
”nancial inclusion” suggests a promising research area exploring
blockchain’s potential to address gaps in the banking sector.
Another notable cluster, marked in purple, focuses on trust-
related issues and includes terms such as ”trust,” ”transparency,”
”security,” ”privacy,” ”smart contracts,” and ”banking.” The preva-
lence of these keywords indicates a persistent academic interest in
the technological and ethical dimensions of blockchain technology.
Specically, the focus is on the potential impact of blockchain tech-
nology on trust, privacy, and security in banking and nancial
institutions. This thematic emphasis highlights blockchain tech-
nology’s central role in addressing data integrity and user trust
challenges, both of which are key to maximizing its value in banking
applications.
The fth cluster is represented by light blue and comprises key-
words such as ”digitization,” ”innovation,” ”digital transformation,”
”banking services,” and ”Islamic banking.” These terms pertain to
digital transformation and innovation in the banking sector. This
thematic cluster indicates research trends that investigate the im-
pact of blockchain technology on contemporary banking models with
the aim of diversication and modernization.
The yellow cluster is particularly signicant because it in-
cludes the keywords ”distributed ledger technology,” ”decentralized
nance,” ”nancial regulation,” ”central bank digital currency,”
”cryptocurrencies,” and ”RegTech.” These terms are poised to
dominate future discourse concerning regulation and decentralized
nance (DeFi). ”Regtech” signies the integration of regulatory con-
trol and compliance in blockchain-based banking. The cluster also
highlights the pivotal role of policy and governance mechanisms in
the adoption of blockchain technology in nancial markets.
The network visualization of keyword co-occurrence in (Figure
5) led to the identication of six major clusters, conrming the the-
matic structure of the eld. These clusters show the current research
frontiers and common terms used by scholars. For the nal synthesis
and interpretation of these thematic clusters, please see Section 3.3.
3.2.4. Bibliographic Coupling of Documents
Bibliographic coupling is a bibliometric technique that measures the
similarity between two documents based on their shared references.
The extent of the overlap between references is indicative of the
strength of the implied connection among the documents. This is
because it is assumed that they are discussing the same topics or
drawing on identical intellectual structures [48]. This technique is
particularly useful for identifying stable research streams and the
underlying intellectual structure of a research eld.
The present study used VOSviewer to perform bibliographic cou-
pling analysis and to visualize the intellectual structure of blockchain
literature in the banking sector. Two documents are considered to
be bibliographically coupled if they cite one or more of the common
references. To enhance interpretability and focus on inuential con-
tributions, a minimum of 30 citations per document and a minimum
cluster size of 10 documents were applied to be analytically signi-
cant. The application of this criterion resulted in the selection of 65
articles, which were subsequently organized into four clusters, each
distinguished by a distinct color as shown in Figure 6.
In the resulting network visualization, each node represents an
individual academic paper that has been used in the analysis. The
size of a node is directly proportional to the number of citations it
has received. The presence of larger nodes is indicative of a greater
level of scientic inuence. Lines linking nodes indicate bibliographic
coupling relationships, while the thickness of the lines signies the
number of common citations between the two documents. The thick-
ness of the line is indicative of the strength of the connection, with
thicker lines denoting closer intellectual or thematic relationships.
Moreover, the visualization map supports two important quantita-
tive indicators. It produced 603 bibliographic links among the 65
documents that have demonstrated exceptional scholarly impact, as
evidenced by their substantial citation counts. Additionally, the to-
tal link strength (TLS), calculated as the sum of all individual link
strengths, is 1,226, reecting high levels of connectivity and a com-
prehensive set of blockchain banking studies. The network map in
this case provides valuable insight into thematic connectivity among
highly cited articles. The clustering reects how closely related the
topics are and how references are linked between publications, which
in turn highlights the main themes across the eld.
Figure 6 demonstrates that Thakor’s (2020) work exhibits con-
siderable scholarly inuence, characterized by its substantial node
and cross-cluster edges, thereby establishing a signicant connec-
tion between the domains of mainstream banking and blockchain
literature. Dai (2017), Minoli (2018), and Schuetz (2020) have also
been revealed to be central and highly connected nodes, forming a
dense core within the red cluster. The signicant overlap between
these elds could potentially indicate an underlying contribution,
particularly to blockchain technology and nancial applications. In
contrast, Auer (2022), Rehman (2023), and Kumar (2018) have fo-
cused their attention on peripheral areas, suggesting the existence
of niches or novel research avenues that are less directly connected
to the central literature. The peripheral nodes in this case reect the
growing bifurcation of topics such as DeFi and cryptocurrency regu-
lation. As shown in Figure 6 6, the map visualization demonstrates
the following clusters:
Cluster 1 (Red) is dominated by inuential documents, includ-
ing Dai (2017), Peters (2016), Schuetz (2020), Alhuwalia (2020),
Hooper (2020), Shoaib (2020), and Cuccuru (2017). The cluster
forms the theoretical basis of the eld and focuses on blockchain
technology infrastructure, settlement processes, transparency, au-
ditability, and value creation within nancial systems. This cluster
constitutes a pivotal theoretical construct, establishing intricate
internal relationships and exhibiting notable coupling strength.
Cluster 2 (Green), to which Thakor (2020), Minoli (2028), Chen
(2017), Bayram (2022), Naimi-Sadigh (2022), Sangwan (2020), and
Kimani (2020) belong, is characterized by its high level of inter-
connectedness and its tendency to explore blockchain convergence
with FinTech innovation and nancial inclusiveness for transform-
ing banking services. This tendency is underpinned by a focus on
empirical rationales and case-study ndings.
Cluster 3 (Blue) consists of the following documents: Javaid
(2022), Khalil (2022), Menon (2024), Elbashbishy (2022), Choo
(2020), Rehma (2023), and Schlatt (2022). This cluster emphasizes
digital transformation, service innovation, and customer-focused
approaches to blockchain banking. The signicant number of con-
nections within this cluster indicates the presence of an emergent
yet cohesive scholarly conversation.
Cluster 4 (yellow) is led by Garg (2021), Osmani (2021), Kumar
(2018), Le Nguyen (2018), and Auer (2022). This cluster presents
a network that also focuses on blockchain adoption models, con-
sumer trust, and theories of innovation diusion. This cluster is
grounded in extant literature on the behavior and diusion of in-
novation, thereby establishing a relationship at both technical and
organizational levels.
The high interconnectivities among clusters emphasize the in-
terdisciplinary nature of blockchain research in banking, due to the
convergence of technology, economics, regulation, and behavioral
perspectives. The prevalence of strong coupling relationships and
numerous thematic avenues also suggests that, despite the fact that
the eld is still in its infancy, it has attained some level of maturity
with well-dened but interrelated subelds.
15
S. A. Aladeeb et al.
trust
p2p lending
ethereum
cybersecurity
banking services
technology adoption
regulation
money
islamic banking
financial regulation
decentralization
privacy
big data
banks
transparency
decentralized finance
iot
distributed ledger technology
digitalization
banking sector
security
innovation
financial services
digital banking
finance
smart contracts
financial inclusion
artificial intelligence
bitcoin
cryptocurrency
banking
fintech
blockchain
VOSviewer
Figure 5. Keyword Co-occurrence Network of Blockchain and Banking Research. Node size reects keyword frequency, link strength indicates
co-occurrence intensity, and clusters represent dominant thematic areas.
3.3. Content Analysis and Thematic Clustering
In order to address Research Question 2 (RQ2), this section presents
a qualitative thematic analysis of literature on blockchain tech-
nology in banking, which was systematically performed with the
aim of identifying the main themes and providing a comprehensive
understanding of the research landscape. Instead of repeating the
bibliometric analyses provided in Section 3.2, this section builds
on those quantitative ndings to provide contextual interpretation,
conceptual validation, and thematic coherence.
As outlined in the research methodology section, the initial
identication of the major themes was derived using two methods:
keyword co-occurrence and bibliographic coupling (as described in
Sections 3.2.3 and 3.2.4). Keyword co-occurrence and bibliographic
coupling highlight the closest relationships in terms of their relation-
ship, or co-occurrence with each other, based on the frequency with
which they were cited by authors and published in peer-reviewed
journals [48, 76].
The previously described bibliometric research methods are help-
ful for creating a high-level map of the research domain. However,
they do not provide a detailed explanation of the substantive con-
tent within the identied thematic clusters. To address this gap in
the literature, we conducted a qualitative content analysis to syn-
thesize, triangulate, and validate the mapped bibliometric thematic
clusters.
To achieve this qualitative synthesis, we employed Braun and
Clarke’s thematic analysis framework [49]. First, we identied a
dataset of 70 articles selected in previous sections of this paper. We
then reviewed the articles manually to determine if the thematic
clusters contained similar semantic meanings and if the cluster con-
tents were conceptually consistent. Finally, we examined whether
the thematic clusters contained relevant theories.
As illustrated in Table 9, this methodological approach yielded
six robust thematic clusters that collectively dene the intellec-
tual structure of blockchain research in the banking sector from
2015 to May 2025. These thematic clusters represent the analytical
framework through which to understand how blockchain inuences
nancial intermediation, business processes, compliance with reg-
ulation, innovation strategy, trust creation, and integration with
next-generation technology.
The following discussion focuses on the conceptual signicance
of these themes, providing a concentrated and analytical summary
of the key intellectual trends in the eld. This fullls the mandate
of the systematic content review phase.
3.3.1. Cluster 1: Blockchain Applications for
Transforming Banking Operations and Financial
Intermediation.
This cluster represents the most foundational and established body
of literature on blockchains in banking, focusing on their ability to
improve eciency, smooth transaction frictions, or transform core
banking systems. More conceptually, the literature in this stream is
concerned with the idea that the value of blockchains is not found
in isolated pilot projects but rather in their integration into back-
oce functions, interbank settlement mechanisms, and audit and
compliance processes.
Foundational studies, such as [55, 56], establish the theoretical
frameworks that describe how blockchain technology helps automate
16
elbashbishy (2022)
rjoub (2023)
gan (2024)
rehman (2023)
andrian (2018)
auer (2022)
khalil (2022)
saheb (2021)
schlatt (2022)
hooper (2020)
pal (2021)
naimi-sadigh (2022)
patel (2022)
cuccuru (2017)
sangwan (2020)
osmani (2021)
kumar (2018)
ahluwalia (2020)
garg (2021)
minoli (2018)
schuetz (2020)
dai (2017)
thakor (2020)
VOSviewer
Figure 6. Document–Bibliographic Coupling in Blockchain and Banking Research. Nodes represent documents, node size reects citation inuence, links
indicate bibliographic coupling strength, and colors represent major intellectual and thematic clusters.
Table 9. Identied Thematic Clusters in Blockchain Banking Research.
No. Cluster Thematic Main Themes Sample References
1 Blockchain Applications for Transform-
ing Banking Operations and Financial
Intermediation
Real-time accounting, automation, reconcili-
ation, operational eciency, startup nance,
and cost reduction.
[26], [55, 56],[61, 62],[77–80]
2 Decentralized Finance (DeFi) and Cryp-
tocurrencies Enabled by Blockchain
DeFi, ICOs, remittances, nancial decentral-
ization, ethics of crypto, speculative behav-
ior.
[81–87]
3 Blockchain as an Enabler of Digital and
Financial Technology Convergence
Integration with IoT, AI, ML, FinTech, KYC,
smart contracts, and digital ID; enhancing
automation and inclusion.
[46], [54], [58], [88–92]
4 Trust-Related Dimensions in Blockchain-
Based Banking
Trust, transparency, data privacy, organiza-
tional condence, strategic alignment, adop-
tion barriers.
[1], [60], [91], [93–96],
5 Regulatory, Legal, and Institutional
Frameworks for Blockchain Governance
Smart contracts and law, compliance, anti-
money laundering (AML), CBDCs, DeFi reg-
ulation, policy adaptation.
[59], [97–101]
6 Strategic Modernization of Banking
Business Model Enabled by Blockchain
Disruption, competitive strategy, sandboxes,
sustainable development.
[16], [37], [102]
banking ledgers, enhances settlement eciency and reconciliation
accuracy, and improves auditability. This technology also enables
continuous quality assurance and real-time accounting systems.
Building on this conceptual foundation, empirical evidence, notably
from the Sponta Banca initiative, shows that blockchain frame-
works signicantly reduce settlement timeframes, enhance data
traceability, and increase the reliability of interbank data exchange
[77].
A large body of literature on this cluster, such as works by
[26, 62, 80, 103, 104], consistently emphasizes the advantages of
blockchain technology. Compared to traditional systems, blockchain
technology enhances operational eciency in terms of cost savings,
risk mitigation, transaction security, transparency, and privacy.
Also, this technology helps minimize information asymmetry and
startup capital costs [61]. These benets extend beyond payments to
credit information systems, international settlements, and broader
nancial data networks. This reinforces the idea that blockchain
technology is fundamental rather than limited in application.
Furthermore, this cluster emphasizes the strategic and organiza-
tional factors that facilitate successful blockchain implementation.
17
S. A. Aladeeb et al.
Research using technology adoption models [79] and innovation ca-
pability frameworks [105] identies critical factors that mediate the
operational eectiveness of blockchain technology, including trust,
management commitment, and resource readiness. Furthermore,
studies focusing on emerging markets [78, 106] indicate that banks’
ability to achieve eciency improvements is signicantly aected by
institutional maturity and technological infrastructure.
Overall, these ndings underscore the importance of blockchain
technology as a key tool capable of reducing operational costs,
automating complex verication tasks, and promoting resilient -
nancial systems with low response times. However, the studies also
point to ongoing challenges, particularly with regard to scalability
and institutional readiness, which continue to aect the speed and
scope of practical implementation.
3.3.2. Cluster 2: Decentralized Finance (DeFi) and
Cryptocurrencies Enabled by Blockchain
This thematic cluster focuses on an increasingly signicant body
of research that examines blockchain technology as the core infras-
tructure for decentralized nance (DeFi) and cryptocurrency-driven
nancial systems. Theoretically, research presents blockchain as a
tool that eliminates intermediaries in conventional nancial oper-
ations by allowing direct peer-to-peer value exchange, automating
processes thr-ough smart contracts, and fostering transparent nan-
cial frameworks that function independently of central authorities.
The core idea that emerges from this stream is that decentralized -
nance not only improves current banking processes but also radically
challenges traditional models of nancial intermediation.
Groundbreaking research indicates that decentralized nance of-
fers an alternative nancial structure capable of replicating essential
banking activities or services, such as lending, borrowing, and as-
set trading, through decentralized protocols that are governed by
code rather than traditional institutions [81]. This viewpoint is fur-
ther reinforced by theoretical contributions that depict blockchain
as a “trust protocol,” highlighting its function in enabling trans-
parency, immutability, and the automated execution of nancial
transactions [86]. Collectively, this body of literature lays the the-
oretical groundwork for comprehending how decentralized systems
challenge conventional banking frameworks.
Furthermore, empirical and analytical studies within this the-
matic cluster reveal a more nuanced and diverse landscape. While
blockchain-based money transfer systems and tokenized nancial in-
struments show the potential to reduce costs and increase eciency,
evidence suggests that adoption of cryptocurrencies is often driven
by speculative behavior rather than dissatisfaction with traditional
banking services [85, 87]. Furthermore, research highlights persis-
tent concerns about market volatility, governance ambiguity, and
regulatory uncertainty, which continue to shape the risk prole of
decentralized nance (DeFi) systems [82–84].
In addition to technical and economic factors, this research high-
lights the ethical, behavioral, and institutional consequences of
DeFi. Studies focusing on accountability, nancial inclusion, and
ethical responsibilities caution that the decentralization of nan-
cial authority introduces new challenges associated with consumer
protection, systemic risk, and regulatory supervision [82, 83, 107].
These ndings imply that the transformative capacity of DeFi is
closely connected to governance and public policy factors.
In summary, these studies arm that decentralized nance
(DeFi) and cryptocurrencies signify a groundbreaking extension
of blockchain technology with the potential to transform nan-
cial intermediation. However, the research notes that the long-term
viability of DeFi and its integration into mainstream banking sys-
tems depends on establishing regulatory frameworks, governance
structures, and empirical evaluations of systemic risks.
3.3.3. Cluster 3: Blockchain as an Enabler of Digital and
Financial Technology Convergence
This thematic cluster includes studies that look at blockchain as
a fundamental infrastructure that supports and enhances the func-
tionality of other emerging digital and nancial technologies, such
as articial intelligence (AI), machine learning (ML), the Internet of
Things (IoT), FinTech platforms, smart contract applications, and
digital identity systems. Conceptually, the literature in this stream
portrays blockchain not as an isolated solution but as a coordina-
tion and trust layer that improves interoperability, automation, and
data integrity across complex digital ecosystems.
Key contributions within this cluster highlight the potential of
blockchain to reshape nancial value chains by facilitating decentral-
ized data exchange, automated decision-making, and secure identity
management [54]. In addition to nancial services, this stream also
highlights the role of blockchain technology in securing Internet of
Things (IoT) systems by preventing data manipulation and enabling
decentralized control, particularly in environments that require high
levels of reliability and trust [58]. These studies portray blockchain
as a complementary technology that enhances the reliability and
transparency of data-driven nancial services while paving the way
for innovative digital intermediation. In this context, blockchain
technology enables the secure integration of diverse technologies that
typically operate in isolated locations.
Empirical studies further indicate that the convergence of
blockchain with AI, big data analytics, cloud computing, and mobile
banking technologies can lead to signicant performance enhance-
ments in the delivery of nancial services, especially in lending, risk
assessment, and customer onboarding processes [89, 90, 92, 107]. Ev-
idence from banking applications points out that such technological
convergence improves predictive accuracy, operational scalability,
and nancial inclusion, particularly for small and medium-sized
enterprises and underrepresented populations.
A notable subtheme within this cluster focuses on digital iden-
tity management and automated compliance processes. Research on
blockchain-based self-sovereign identity and smart contract–enabled
Know Your Customer (KYC) processes shows signicant advances
in privacy protection, cost-eectiveness, and regulatory compliance
[91]. Similarly, research on block-chain-enabled access control mech-
anisms highlights its potential to improve data management and
security across interconnected digital platforms [88]. These applica-
tions demonstrate blockchain’s potential to address long-standing
ineciencies in identity verication and data governance within
nancial institutions.
In summary, this cluster emphasizes the importance of
blockchain as a key driver of technological convergence in digital
nance. However, the literature also indicates ongoing challenges
related to the system’s compatibility, organizational coordination,
and institutional compatibility. However, the literature also empha-
sizes ongoing challenges concerning system interoperability, regu-
latory harmonization, and compatibility. These limitations imply
that the advantages of blockchain integration hinge on supportive
institutional frameworks and the maturity of related technologies.
3.3.4. Cluster 4: Trust-Related Dimensions in
Blockchain-Based Banking
This cluster synthesizes literature examining the impact of trust
on the use of blockchain technology in banking. Cryptographic
18
verication and decentralized consensus have often led to charac-
terizing blockchain as a ”trustless” technology; however, existing
studies continually highlight the importance of trust between orga-
nizations, user condence, and the legitimacy of institutions when
implementing blockchain within the nancial sector. From a concep-
tual framework, research within this stream illustrates that whilst
blockchain does not remove trust, it re-establishes it, moving it from
centralized intermediaries to the technology itself, to governance
structures, and to the institutions.
Empirical research indicates that, for both users and banks, per-
ceived usefulness, transparency, and security are strong motivators
for the adoption of blockchain technology, while technical capabil-
ity is not as signicant [1, 60, 93]. These results indicate that both
types of trust (in technology and in the institution) interact with
each other rather than exist separately.
A second theme in this cluster discusses blockchain’s eects on
increasing transparency and providing customers with greater data
integrity and privacy. The research has indicated that the imple-
mentation of blockchain-based architectures can decrease the level
of information asymmetry between lenders and borrowers, provide
an increased level of auditing capabilities, and create greater levels
of condence in nancial transactions through various regulatory
processes, including lending [95, 96]. However, the literature points
out that certain organizational barriers to establishing trust exist
within nancial industries, such as resistance to changing current
ways of distributing credit and the lack of standardization, and the
uncertainty regarding accountability, i.e., which party or parties are
ultimately responsible in any given transaction [94].
Another prominent sub-theme is connected to digital identity
and the privacy-preserving elements of the associated trust mech-
anism. Research examining digital identity management through
blockchain and the application of KYC frameworks has illustrated
that decentralized identity models will augment user control over
their personal data and enable compliance with regulatory KYC re-
quirements, while also assisting banks and regulators in forming a
greater degree of institutional trust [91]. Furthermore, current re-
search has demonstrated that the manner in which a digital identity
is constructed has a direct impact on the level of trust between
banks, regulatory authorities, and their customers.
In summary, the literature supporting this stream clearly es-
tablishes trust as a multi-dimensional construct that acts as an
intermediary factor in the adoption of blockchain technology in the
nancial industry. While blockchain technologies provide a structure
to increase transparency and security, the literature conrms that
accepting blockchain technology into an organization must reach the
appropriate balance between the institution’s expectations regard-
ing the reliability of the technology, the organizational readiness to
use the technology, the availability of clear laws and regulations re-
lated to the use of the technology, and the overall level of acceptance
by society at large.
3.3.5. Cluster 5: Regulatory, Legal, and Institutional
Frameworks for Blockchain Governance
This thematic cluster synthesizes research on the impact of regula-
tions, laws, and institutional frameworks on the use and adoption
of blockchain technology in nancial institutions. In theory, and
according to the literature in this stream, blockchain technology
contributes to greater transparency, process automation, and in-
creased eciency. However, institutions are unable to fully leverage
this potential due to the uncertainty surrounding the regulation of
this technology and because the current limited regulatory and legal
structures are unable to keep pace with the transformation brought
about by blockchain technology.
This theme focuses primarily on how enforcement and gover-
nance issues related to blockchain applications and the use of smart
contracts are evolving. Many researchers point to numerous areas
where the mechanisms for creating automatically enforced records
conict, as well as many unresolved issues related to accountability,
jurisdiction, and the enforceability of programming-based agree-
ments [97]. These challenges illustrate the diculty of applying
standard regulatory structures to decentralized nancial systems.
Other important areas in this thematic cluster are compliance
and risks that may threaten the integrity of the nancial system and
the systemic risks of blockchain technology. The use of blockchain
technology for pseudonyms in nancial transactions poses a poten-
tial dilemma for nancial regulators [73] [99, 74]. The ease of creating
anonymous accounts gives users easier access to money laundering
[98]. At the same time, technologies enabled by blockchain, such
as automated reporting, automated audit trails, and early warning
systems, enhance transparency and regulatory eectiveness [100].
Additionally, studies indicate that regulatory approaches are
necessary to support blockchain technology innovations. Regula-
tory sandboxes serve as tools for managing the relationship between
innovation and risk through controlled testing, contributing to op-
portunities for learning, public policy development, and institutional
adaptation [26]. Researchers are also exploring ways to integrate
regulation into decentralized nance (DeFi) applications, emphasiz-
ing the need to incorporate governance and compliance mechanisms
into system design as a means of mitigating the risks associated with
decentralization [59].
Finally, studies on central bank digital currencies (CBDCs) show
how the introduction of blockchain technology has prompted pub-
lic authorities to develop hybrid governance models. Evidence from
digital currency projects shows central banks’ eorts to combine
technological advances with centralized oversight to achieve nancial
stability objectives and ensure the eective transmission of monetary
policy [101].
In conclusion, this research corpus reinforces the three essential
ingredients for the long-term success of blockchain technology in
the banking sector: regulatory clarity, institutional exibility, and
adaptive governance. In all three areas, the literature shows that
sustainable governance of blockchain technology requires a balance
between providing an environment conducive to innovation, ensuring
legal certainty for consumers, and maintaining systemic nancial
stability.
3.3.6. Cluster 6. Strategic Modernization of Banking
Business Model Enabled by Blockchain
This thematic cluster focuses on the role of blockchain as a mecha-
nism for modernizing conventional business models in the banking
industry, specically as a type of strategic transformation. While
much research refers to blockchain for its greater operational e-
ciency, the literature in this stream points out that blockchain’s
inuence will create long-term economic and social governance sys-
tems by creating new biases toward competition and allowing for
entirely new nancial service architectures.
The literature in this cluster collectively conceptualizes
blockchain technology as disruptive rather than complementary to
existing systems and processes. This body of literature recognizes
that blockchain platforms disrupt the traditional centralized struc-
ture of the banking industry by enabling the delivery of new services
to customers and allowing peer-to-peer interactions to create value
without going through a bank or intermediary. Consequently, banks
are under increased pressure to reevaluate their strategic positioning,
organizational structure, and competitive response to their evolving
roles in the digital nancial service environment [16, 37].
19
S. A. Aladeeb et al.
In addition, this cluster of research has further explored how
business model innovation driven by blockchain technology can
support nancial inclusion and global sustainable development.
Studies have identied ways in which blockchain can provide
expanded access to nancial services, decrease transaction costs, and
improve transparency in areas such as payments, savings, credit,
and insurance, particularly inunderserved areas and regions [102].
However, the literature of this cluster has also emphasized that,
for these potential strategic benets to be realized, a supporting
institutional framework is necessary.
In general, this cluster validates the assertion that blockchain is a
strategic enabler of banking modernization, encompassing more than
incremental process improvements. That said, the ndings also indi-
cate that the eect of blockchain on banking ultimately depends on
how well nancial institutions use and integrate the new technology
into their organizational strategies and adapt to achieve organiza-
tional compliance and advance organizational goals in a changing
economy and broader social structure.
4. Research Implications
4.1. Theoretical Implications
This review enhances blockchain adoption theory by broadening pri-
marily individual-level acceptance models (e.g., TAM, UTAUT) and
organization-centered readiness viewpoints (e.g., TOE, RBV) into
a multi-tiered, ecosystem-based comprehension of blockchain dis-
semination in tightly regulated nancial contexts. The bibliometric
clustering demonstrates that blockchain adoption in the banking sec-
tor is inuenced not only by technological preparedness or perceived
value but also by the interplay of regulatory legitimacy, institutional
trust, cross-organizational interoperability, and strategic resource
management throughout nancial networks. This observation re-
nes traditional technology adoption models by highlighting that
disruptive nancial technologies face diusion constraints imposed
by governance frameworks and regulatory compliance demands, re-
sulting in adoption pathways that are fundamentally dierent from
those seen in cons-umer-oriented digital technologies.
Additionally, the thematic evolution indicates a theoretical shift
within the literature from initial techno-optimistic narratives to an-
alytical perspectives that focus on institutional, risk-oriented, and
governance issues. This progression marks a shift from exploratory
research on technology diusion to integrated frameworks that re-
gard blockchain as a facilitator of organizational transformation
rather than simply a discrete operational tool. Therefore, this review
presents a cohesive conceptual framework that incorporates tech-
nological, organizational, regulatory, and ecosystem dynamics into
a comprehensive explanatory model for blockchain-driven nancial
innovation.
By synthesizing bibliometric ndings with qualitative thematic
analysis, this study presents an established, multi-level framework
that describes the process by which the banking sector adopts
blockchain technology as a broader ecosystemic and governance-
driven process rather than a technology-driven phenomenon.
4.2. Managerial Implications
In addition to outlining technological advantages, the current nd-
ings suggest a strategic rethinking of blockchain as a tool for
organizational transformation rather than a mere digital upgrade.
By synthesizing insights from bibliometric and thematic clusters,
this research shows that the success of adoption is more dependent
on banks’ capacity to implement coordinated process reengineering,
cross-unit integration, and alignment of institutional governance
than on technical installation.
The thematic clusters that highlight operational eciency, cost
savings, and process automation imply that blockchain should be
viewed not just as a technological asset but also as a driver of op-
erational reorganization. Therefore, banking managers are urged to
re-evaluate current workows and identify areas where distributed
ledger technologies can optimize accounting processes, enhance rec-
onciliation accuracy, and decrease overhead expenses through smart
contract automation [55, 62].
Moreover, the ndings stress the growing importance of security,
transparency, and trust in modern banking practices. With increas-
ing cyber threats and regulatory compliance demands, blockchain-
based systems provide solutions for ensuring data integrity, tracing
audit trails, and automating contract enforcement. These fea-
tures are particularly pertinent to Know Your Customer (KYC)
and Anti-Money Laundering (AML) compliance frameworks, where
blockchain applications can support regulatory adherence while
simultaneously enhancing institutional credibility [98, 103].
Similarly, the rise of decentralized nance (DeFi) and token-
based ecosystems indicates a fundamental shift in banking busi-
ness models. As a result, managers must look beyond incremen-
tal enhancements to investigate new service architectures, such
as peer-to-peer intermediation platforms, blockchain-enabled pay-
ment systems, and digital asset tokenization. This shift requires
innovation-driven leadership cultures, investment in blockchain-
related expertise, and strategic alliances with ntech developers to
maintain a competitive advantage.
Lastly, the noted decrease in citation impact alongside increasing
publication volumes highlights the need for more practically oriented
blockchain initiatives. Banking leaders must connect blockchain
adoption to clearly dened institutional objectives, quantiable
performance metrics, and stepwise implementation strategies to en-
sure that investments yield tangible benets rather than remaining
symbolic or experimental.
In summary, these managerial implications illustrate that the
adoption of blockchain is primarily a challenge of leadership, gover-
nance, and change management, rather than solely a decision related
to technological procurement.
4.3. Practical Implications
From a practical viewpoint, this review indicates that blockchain
technology generates its most signicant benets when it is inte-
grated within regulatory and transactional frameworks rather than
operated as a standalone pilot initiative. The most pronounced em-
pirical focus in the literature pertains to cross-border settlements
and interbank transaction clearing, where ineciencies are still com-
mon. Incorporating blockchain into these areas has the ability to
speed up settlement times, lower operational expenses, and reduce
the risks of fraud [26, 56, 60].
Concurrently, blockchain provides capabilities for automating
regulatory processes and managing identities. Smart contracts and
decentralized identity systems can improve compliance precision and
operational transparency, yielding considerable cost savings in ful-
lling KYC, AML, and nancial reporting requirements [80, 98].
Therefore, regulatory bodies and nancial institutions are urged
to consider RegTech-driven blockchain solutions not merely as
additional controls but as comprehensive compliance frameworks.
The literature also highlights the inclusive potential of
blockchain, especially via DeFi-enabled micronance platforms,
crowdfunding opportunities, and mobile-focused peer lending
initiatives[59, 85, 108]. Such models create avenues for underserved
communities to obtain nancial services without reliance on tra-
ditional intermediaries. Implementation eorts should, therefore,
prioritize areas with high rates of nancial exclusion, particularly
20
in emerging and developing economies. For technology developers
and consulting agencies, the insights point to key areas for develop-
ment that include secure audit platforms, green nance traceability
systems, decentralized asset management frameworks, and interop-
erable payment solutions. Collaborative design partnerships with
nancial institutions are essential to ensure that technological mod-
els closely correspond with sector-specic regulatory and operational
needs.
Ultimately, the eective implementation of blockchain in the
banking sector necessitates not only experimental adoption but
also ongoing institutional coordination that encompasses regula-
tory dialogue, workforce education, governance adaptation, and
strategic oversight. Thus, the full potential of blockchain is real-
ized when technical advancements are aligned with organizational
preparedness and policy coherence.
5. Conclusion and Future Research
5.1. Conclusion
This research comprehensively examined the evolving intellectual
landscape and thematic development of blockchain studies within
the banking industry from 2015 to 2025 using a hybrid approach
that combines bibliometric analysis with qualitative systematic syn-
thesis. The analysis of 389 peer-reviewed articles highlighted distinct
developmental stages—from initial conceptual exploration to the-
matic broadening and into the current phase of applied governance
and integration studies.
An analysis of geographic contributions revealed disparities, with
the majority coming from India, the United States, and the United
Kingdom, while newer research centers in China, the United Arab
Emirates, and various parts of Europe are progressively inuencing
the empirical direction of the eld. At the levels of institutions and
authorship, research networks show both fragmentation and cross-
regional collaboration, indicating that global integration in research
is inconsistent.
Six key thematic clusters delineate the structure of disciplinary
knowledge: nancial intermediation and operational eciency, de-
centralized nance (DeFi) and cryptocurrencies, convergence of
blockchain technology, infrastructures for trust and transparency,
regulatory and governance frameworks, and modernization strate-
gies in banking. Together, these aspects characterize blockchain
as not just a standalone technological x but as an integrated
transformation platform that concurrently impacts organizational
frameworks, regulatory systems, and nancial ecosystems.
Although the volume of publications is on the rise, the literature
remains empirically scattered. Studies focusing on large-scale indus-
try adoption are limited, the interactions between blockchain and
complementary technologies (such as AI and IoT) are insuciently
theorized, and long-term evaluations of nancial stability and sys-
temic risk are scarce. Governance research, especially in areas of
regulatory enforcement and international coordination, is also still
underexplored.
In addition to mapping thematic growth, this review oers an
integrative theoretical framework based on our synthesis of the
six thematic clusters. This framework improves our understanding
of blockchain adoption by presenting it as an innovation pro-
cess inuenced by regulatory legitimacy, organizational governance,
and ecosystem interoperability, rather than merely a technical
event. This integrative view distinguishes the current review from
previous bibliometric analyses because it clearly articulates the
causal relationships connecting our validated knowledge structure
to the broader agenda of organizational transformation, regulatory
alignment, and strategic value creation in nance.
As a result, this study provides a cohesive theoretical groundwork
for future empirical research and oers practical insights for banking
professionals and policymakers as they navigate the implementation
of blockchain technologies in regulatory environments undergoing
transition.
5.2. Future Research Directions
To improve our understanding of this research area, more research
should be conducted on the six thematic clusters discussed earlier.
Since research on blockchain technology in the banking sector is in
its infancy, identifying and dening possible areas for future research
is crucial. These research directions are derived from existing liter-
ature and reect the gaps, constraints, and prospects identied by
previous researchers.
Existing studies have identied that blockchain has the potential
to transform operational processes in the banking sector for greater
eectiveness, nancial inclusion, and decentralized nance (DeFi),
as well as to completely modernize business models [55, 81, 86].
However, serious issues remain regarding regulatory ambiguity [59],
interoperability [26], adoption of trust [93], and integration into
future-proof technologies [90]. Thus, future research must bridge
these gaps through empirical, interdisciplinary, and cross-regional
studies.
Table 10 shows directions reecting both conceptual and practi-
cal priorities. These directions provide a research map for charting
blockchain scholarship and positioning policymakers, nancial insti-
tutions, and technology providers toward the development of secure,
ethical, and scalable distributed ledger technology applications.
5.3. Limitations of the Study
Despite providing an overall bibliometric and thematic analysis, this
study has some limitations that should be acknowledged. First, the
dataset was derived exclusively from the Scopus database. Although
Scopus provides the widest coverage of peer-reviewed journals re-
lated to nance, management, and information systems research,
the exclusion of other databases (such as Web of Science, IEEE
Xplore, and Google Scholar) may have resulted in the omission
of some relevant publications, particularly conference proceedings
and technically oriented studies. Nevertheless, this review focuses
primarily on the social, economic, managerial, and organizational
aspects of blockchain technology in the banking sector, rather than
on the development of engineering or cryptographic systems, which
are typically covered in technical databases.
Furthermore, the study examined 389 peer-reviewed articles from
2015 to May 2025. Due to Scopus’s dynamic nature, the database
used for the study might not include the newest publications at
the cuto time of the nal submission, which could slightly aect
the bibliometric results. The study only used VOSviewer to map
and visualize bibliometric networks. Although VOSviewer is a pop-
ular tool, other tools, such as Gephi or CiteSpace, could have been
used to provide additional bibliometric measures, including network
centrality, modularity, and mediation scores.
Furthermore, this research did not propose a conceptual model
for how banks adopt blockchain technology. Therefore, subsequent
studies can build on this research to develop a more extensive model
that encapsulates the multidimensionality of blockchain applica-
tions. Despite its limitations, the research provides a preliminary
examination of the intellectual structure and thematic history of
blockchain research in the banking sector.
21
S. A. Aladeeb et al.
Ethical Statement
No ethical approval was required for this study, as it did not involve
human or animal subjects.
Funding
This research received no specic grant from any funding agency in
the public, commercial, or not-for-prot sectors.
Declaration of competing interests
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to in-
uence the work reported in this article. Moreover, they assert that
no conicts of interest exist.
Declaration of generative AI and AI-assisted
technologies in the writing process
During the preparation of this manuscript, the author(s) used
language editing tools/services, including DeepL and Grammarly,
to improve grammatical accuracy and readability. The author(s)
subsequently reviewed and edited the contents thoroughly for accu-
racy and integrity after utilizing these tools/services and are fully
responsible for the nal version of the manuscript.
Data Availability Statement
The bibliometric dataset supporting the ndings of this study, in-
cluding the Scopus CSV le used for VOSviewer analyses, is publicly
available on Zenodo at:
https://doi.org/10.5281/zenodo.17992285
Credit authorship contribution statement
[Sadeq Abdullah Aladeeb]: Conceptualization, Software, Methodol-
ogy, Data curation, Formal analysis, Investigation, Visualization,
Writing – original draft & Editing. [Fatima Zohra Sossi Alaoui]:
Supervision, Validation, review & editing.
22
Table 10. Blockchain Themes and Future Research Directions in Banking.
No.Cluster Theme Future Research Directions References
1 Blockchain Applica-
tions for Transform-
ing Banking Opera-
tions and Financial
Intermediation
• Carry out comparative empirical research assessing the eects of smart contracts on transac-
tion settlement durations and operational costs in various banks.
• Create process-mapping models to quantify the reduction of reconciliation steps in interbank
clearing attributable to blockchain (utilizing Business Process Model and Notation “BPMN”
and time–motion analysis).
• Perform cross-country econometric evaluations to determine how blockchain-based remittance
solutions impact transfer expenses and delivery times in developing compared to developed
nations.
• Employ UTAUT2 or TOE frameworks to pinpoint the factors inuencing blockchain adoption
in retail versus corporate banking sectors.
• Employ UTAUT2 or TOE frameworks to pinpoint the factors inuencing blockchain adoption
in retail versus corporate banking sectors.
• Conduct case studies in low-income nations to uncover obstacles to scalability, interoperability,
and institutional integration.
[56],[61, 62], [77],[79],
[103],[105]
2 Decentralized Fi-
nance (DeFi) and
Cryptocurren-
cies Enabled by
Blockchain
• Model contagion and systemic risks within DeFi ecosystems through network analytics and
simulation methodologies (e.g., agent-based modeling).
• Conduct studies on regulatory impacts, comparing the eectiveness of various legal frameworks
in mitigating fraud and protecting consumers in DeFi lending platforms.
• Conduct studies on regulatory impacts, comparing the eectiveness of various legal frameworks
in mitigating fraud and protecting consumers in DeFi lending platforms
• Evaluate the inuence of DeFi credit markets on the liquidity, protability, and risk parameters
of commercial banks.
• Carry out behavioral studies to examine how cultural dierences shape motivations for adopt-
ing cryptocurrencies (speculation versus utility).
[81–83],[85–87]
3 Blockchain as an En-
abler of Digital and
Financial Technology
Convergence
• Design and evaluate blockchain–IoT prototypes for real-time Know Your Customer (KYC) /
Anti-Money Laundering (AML) monitoring within banking data streams.
• Assess the eectiveness of AI-enhanced smart contracts in dynamic access control through
penetration testing and cybersecurity evaluations.
• Create machine-learning models using blockchain transaction data to forecast credit risk or
fraud patterns, and validate using actual banking datasets.
• Develop and assess (Self-Sovereign Identity) SSI-based identity frameworks in partnership with
banks to gauge improvements in onboarding eciency and KYC compliance.
[58], [88],[90],[91]
4 Trust-Related
Dimensions in
Blockchain-Based
Banking
• mixed-methods surveys and interviews to evaluate the impact of human trust and organiza-
tional culture on blockchain adoption within banks.
• Establish a standardization readiness index to evaluate how system compatibility, legacy sys-
tems, and regulations impede blockchain integration.
• Design blockchain-based credit scoring prototypes and assess their eectiveness in diminishing
information asymmetry in SME lending.
• Implement longitudinal studies to track how increased transparency through blockchain inu-
ences customer trust over time.
[60],[93], [95],[96]
5 Regulatory, Legal,
and Institutional
Frameworks for
Blockchain Gover-
nance
• Propose and evaluate blockchain-enabled AML/CFT (Countering the Financing of Terrorism)
monitoring systems and measure their detection accuracy compared to traditional systems.
• Examine the ecacy of regulatory sandboxes by monitoring innovation outputs (patents,
pilots, startups) preceding and following sandbox involvement.
• Develop automated reporting and cryptographic proof systems for embedded supervision mod-
els in DeFi.
• Analyze real-world CBDC pilot projects (e.g., e-CNY) to gauge privacy risks, transaction
speeds, and impacts on monetary policy using macro-nancial models.
[26],[59],[97],[98],[101]
6 Strategic Moderniza-
tion of Banking Busi-
ness Model Enabled
by Blockchain
• Employ scenario analysis to illustrate how blockchain inuences competition between neobanks
and traditional banks.
• Perform studies on the eects of nancial inclusion by evaluating blockchain-based micro-
nance initiatives in rural or underserved areas.
• Chart out policy, infrastructure, and institutional elements that contribute to successful
blockchain-driven transformation using the PESTEL (Political, Economic, Social, Techno-
logical, Environmental, and Legal) framework and multi-country case research.
[16],[37],[102]
23
S. A. Aladeeb et al.
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