BenchCouncil Transactions on Benchmarks, Standards and

Evaluations, 2026

DOI: https://doi.org/10.66834/xqpw3878

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

Laboratory of Economics, Finance, Management and Innovation, Faculty of Economics and Management, Ibn Tofail University, Kenitra, Moro cco

and

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 identied

six clusters: (1) blockchain in banking and nancial intermediation to enhance operational eciency, (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 diversication of applied research. By integrating quantitative and qualitative insights, this study

highlights key research gaps, oers 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 signicant

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 ineciency 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-eective 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, signicantly enhancing secu-

rity as well as eciency [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-proong. 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].

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 signicance

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 signicant 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 oers

numerous benets: enhanced security, privacy, operational trans-

parency, and increased eciency. This is all a result of its de-

centralized nature and the use of cryptographic algorithms, which

signicantly 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 eciency [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 intel lectual

structures underpinning blockchain research in the banking sector?

RQ3: What key research gaps and future directions can be iden-

tied 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, oering an overarching perspective on how blockchain

is reshaping the industry. Besides mapping the literature, the study

provides critical reections 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 signicant 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 eective 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 identies the managerial and practical

implications of the ndings. Finally, Section 5 oers 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 oer 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 fulll the objectives of the study are outlined in

Figure 1.

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)

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 oers 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 oering 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 dened 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 Identication

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 conrm that the selected

keywords were inclusive and specic.

Based on this literature review, we identied 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 identied. Furthermore, consultation with two

academic experts in nance and block-chain conrmed 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 signicantly nonex-

istent. Therefore, the selected time frame (2015–2025) indicates the

evolution of scientic 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 specicity 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 Renement and Analysis

The second stage of the systematic protocol involved rening 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, specically 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 dier-

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 denitions 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”

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 renement 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 scientic produc-

tivity and impact. It provides a data-driven perspective of scholarly

output and the growth of a scientic discipline over time. This

technique encompasses the analysis of annual publication trends,

identication of highly cited publications, evaluation of leading sci-

entic 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 inuential 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], conrming 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. Specically, 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 identied [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 identied research

gaps. Second, the coded content was grouped into preliminary the-

matic categories based on their conceptual similarities. Thereafter,

these thematic categories were manually rened 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.

S. A. Aladeeb et al.

Methodological Chal lenges 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 dicult 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

signicantly increase the potential for conceptual confusion and

misclassication.

In addition to these diculties caused by the rapid growth in

the number of publications, many dicult 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 dierences, 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 scientic literature

that addresses the application of blockchain in banking during this

period. This overview not only identies 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 scientic 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 scientic 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

Aliations 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 diversication (2019–

2021), and (3) Peak production with initial signs of saturation

(2022–2025).

The initial phase (2016–2018) reects the inception of academic

activity, with four articles published in 2016 being cited 1,249 times

(312.25 per article), indicating foundational signicance. The num-

ber of publications increased from eight in 2017 to 20 in 2018,

reecting 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-

versication 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

Figure 2. Total Publications (TP) over time (2016–2025). Note: The data for 2025 (33 publications) is incomplete, reecting 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 eect, as newer articles have

not yet accumulated signicant 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 signicantly 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

diversication of research themes, particularly applied studies inte-

grating blockchain with AI, IoT, and FinTech, is likely to inuence

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 Scientic 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 signicantly. Technological Forecasting and Social

Change exhibits a notably superior citation prole (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 specic sustainability

audiences, leads to lower average citation rates (18.86 per article),

indicating a more localized rather than broad academic inuence.

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 inuence. The jour-

nal’s concentrated focus on nancial technologies, digital currencies,

and banking change positions it as a primary outlet for signicant

theoretical and empirical contributions, making its articles particu-

larly prominent and often cited across nance, economics, and policy

research communities.

S. A. Aladeeb et al.

Table 3. Leading Scientic 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 Scientic 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 benets 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

Scientic 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 inuence in the realm

of blockchain-banking research is more inuenced by journal the-

matic alignment, multidisciplinary engagement, early positioning in

specic 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 Inuential Authors

Table 4 shows the most prolic authors who have made the largest

academic contributions to blockchain research in the banking sector.

This evaluation considers their productivity, citation impact, nor-

malized inuence, 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 prolic 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 inuence goes beyond citation metrics

to include a bridging function between various research teams, en-

couraging cross-pollination of ideas related to adoption, operational

eciency, 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 dierent 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 eciency 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 inuence

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 dened 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 prole of authorship shows the

maturation of blockchain and banking research into a more unied

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,

Table 4. The Most Inuential 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 reects 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 prolic 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 inuence 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 eorts. 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 Inuential Countries

Table 6 illustrates the signicant 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 prolic 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), reecting

high-quality and highly recognized research output.

China also demonstrates a balanced prole 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, reecting 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 scientic

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 identies the seminal works that have inuenced

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 signicant documents and their comparative

inuence 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,

S. A. Aladeeb et al.

Table 5. The Most Inuential 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 inuential owing to its pioneering and general in-

troduction of the revolutionary nature of blockchain for banking,

specically as it pertains to operational eciency 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 inuence 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 oers 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 signicant 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 signicance of this work lies in its spe-

cic contribution to addressing distributed ledger technology and

smart contracts, and oering 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

Table 7. The Top 10 Most Cited Documents

Rank Authors Year Title Source Document Type TC ACPY NC

1 Ye Guo & Chen Liang 2016 Blo ckchain application and outlo ok

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 Blo ckchain, 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 benets 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 Blo ckchain 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 Blo ckchain 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 p er 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 oers

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 benets 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 signicant normalized citation score of 9.94,

which indicates high use and strong cross-eld inuence. Using struc-

tural equation modeling, the authors assign a numeric value to the

benets of blockchain, such as trust, transparency, and eciency,

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, reecting 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

inuence 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 eciency. This highlights that

the most impactful articles in academia frame blockchain not merely

as a technical tool, but as a driver for signicant 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.

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 scientic production and the transnational network

structure [67, 68]. Particularly, the analysis reveals leading coun-

tries, maps geographical patterns of collaboration, and illustrates the

eect 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 reects pub-

lication volume, while link thickness shows collaboration intensity,

and TLS quanties 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 signies 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 reective of increasing Eastern and

Southern European engagement in blockchain research. Their inclu-

sion is reective of increased cross-border collaboration as well as a

willingness to adopt blockchain towards economic modernization.

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 specic type of this analysis, Author

Co-citation Analysis (ACA), examines how frequently two authors

appear cited in tandem, therefore reecting 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 inuence

on the shaping of specic 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 identication of 102 prominent authors out of a total

of 25,779 who met the predened criteria.

As shown in the network map in Figure 4, the authors were dis-

tributed to four distinct clusters, each represented by a dierent

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., Kauman 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

eects 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

eective 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 satised this

initial criterion. In the second stage of our research protocol, we

manually rened 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 rene-

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 articial 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

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 inuence, 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 scientic

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 dene 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 eect that these assets have

on traditional nancial institutions. This cluster reects 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 ramications

on the augmentation of access to and eciency 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

”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.

Specically, 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 diversication and modernization.

The yellow cluster is particularly signicant 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” signies 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 identication of six major clusters, conrming 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 inuential 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 scientic inuence. Lines linking nodes indicate bibliographic

coupling relationships, while the thickness of the lines signies 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, reecting 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 reects 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 inuence, characterized by its substantial node

and cross-cluster edges, thereby establishing a signicant 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 signicant 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 reect 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 inuential 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 signicant 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 diusion. This cluster is

grounded in extant literature on the behavior and diusion 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-dened but interrelated subelds.

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 reects 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

identication 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 identied 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 identied 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 dene 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 inuences

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 signicance

of these themes, providing a concentrated and analytical summary

of the key intellectual trends in the eld. This fullls 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 eciency, 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-

oce 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

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 reects citation inuence, links

indicate bibliographic coupling strength, and colors represent major intellectual and thematic clusters.

Table 9. Identied 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 eciency, 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 condence, 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 eciency 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 signicantly 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 eciency 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 benets 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.

S. A. Aladeeb et al.

Research using technology adoption models [79] and innovation ca-

pability frameworks [105] identies critical factors that mediate the

operational eectiveness of blockchain technology, including trust,

management commitment, and resource readiness. Furthermore,

studies focusing on emerging markets [78, 106] indicate that banks’

ability to achieve eciency improvements is signicantly aected 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 verication 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 aect 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 signicant 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 eciency,

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 prole 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 arm 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 articial 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 signicant 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 signicant advances

in privacy protection, cost-eectiveness, 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

ineciencies in identity verication 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

verication 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 condence, 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 signicant [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 eects 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 condence 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 conrms 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 eciency. 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

conict, as well as many unresolved issues related to accountability,

jurisdiction, and the enforceability of programming-based agree-

ments [97]. These challenges illustrate the diculty 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 eectiveness [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’ eorts to combine

technological advances with centralized oversight to achieve nancial

stability objectives and ensure the eective 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, specically 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

inuence 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].

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 identied 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 benets 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 eect 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 inuenced 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 diusion constraints imposed

by governance frameworks and regulatory compliance demands, re-

sulting in adoption pathways that are fundamentally dierent 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 diusion 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 eciency, 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 workows 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 dened institutional objectives, quantiable

performance metrics, and stepwise implementation strategies to en-

sure that investments yield tangible benets 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 signicant benets 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 ineciencies 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 micronance 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 eorts should, therefore,

prioritize areas with high rates of nancial exclusion, particularly

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-specic regulatory and operational

needs.

Ultimately, the eective 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 inuencing

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 eciency, 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 insuciently

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 oers 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 inuenced 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 oers 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 dening possible areas for future research

is crucial. These research directions are derived from existing liter-

ature and reect the gaps, constraints, and prospects identied by

previous researchers.

Existing studies have identied that blockchain has the potential

to transform operational processes in the banking sector for greater

eectiveness, 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 reecting 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 aect

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.

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 specic grant from any funding agency in

the public, commercial, or not-for-prot 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 conicts 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.

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 eects 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 inuencing blo ckchain adoption

in retail versus corporate banking sectors.

• Employ UTAUT2 or TOE frameworks to pinpoint the factors inuencing blo ckchain 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

• Mo del 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 eectiveness of various legal frameworks

in mitigating fraud and protecting consumers in DeFi lending platforms.

• Conduct studies on regulatory impacts, comparing the eectiveness of various legal frameworks

in mitigating fraud and protecting consumers in DeFi lending platforms

• Evaluate the inuence of DeFi credit markets on the liquidity, protability, and risk parameters

of commercial banks.

• Carry out behavioral studies to examine how cultural dierences shape motivations for adopt-

ing crypto currencies (sp eculation versus utility).

[81–83],[85–87]

3 Blockchain as an En-

abler of Digital and

Financial Technology

Convergence

• Design and evaluate blo ckchain–IoT prototypes for real-time Know Your Customer (KYC) /

Anti-Money Laundering (AML) monitoring within banking data streams.

• Assess the eectiveness 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 eciency and KYC compliance.

[58], [88],[90],[91]

4 Trust-Related

Dimensions in

Blockchain-Based

Banking

• mixed-metho ds 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 eectiveness in diminishing

information asymmetry in SME lending.

• Implement longitudinal studies to track how increased transparency through blo ckchain inu-

ences customer trust over time.

[60],[93], [95],[96]

5 Regulatory, Legal,

and Institutional

Frameworks for

Blockchain Gover-

nance

• Prop ose and evaluate blockchain-enabled AML/CFT (Countering the Financing of Terrorism)

monitoring systems and measure their detection accuracy compared to traditional systems.

• Examine the ecacy of regulatory sandboxes by monitoring innovation outputs (patents,

pilots, startups) preceding and following sandbox involvement.

• Develop automated rep orting 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 inuences competition between neobanks

and traditional banks.

• Perform studies on the eects of nancial inclusion by evaluating blockchain-based micro-

nance initiatives in rural or underserved areas.

• Chart out p olicy, 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]

S. A. Aladeeb et al.

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