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,

Morocco and

Department of Accounting and Auditing, Faculty of Commerce and Economics, Sana’a University, Sana’a, Yemen

∗

Corresponding author. Email: sadeqab dullahhasan.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 identiﬁed

six clusters: (1) blockchain in banking and ﬁnancial intermediation to enhance operational eﬃciency, (2) decentralized

ﬁnance 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 ﬁndings reveal

a steady rise in research output, regional disparities in collaboration, and thematic evolution from early conceptualiza-

tion to recent signs of diversiﬁcation of applied research. By integrating quantitative and qualitative insights, this study

highlights key research gaps, oﬀers 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 signiﬁcant

transformation, driven by the rapid advancement of emerging

technologies, particularly blockchain. The widespread adoption

of smartphones and high-speed data transmission has not only

disrupted social interactions but also traditional business oper-

ations. However, legacy banking systems have faced challenges

in adapting to these technological advancements due to factors

such as structural rigidity, high operational costs, and inade-

quate transaction processing speeds. For instance, cross-border

remittances frequently necessitate several days to complete, an

ineﬃciency that starkly contrasts 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 cur-

rency eliminating the intermediary [2]. Its decentralized nature

allows for secure, anonymous, and cost-eﬀective transactions.

This has led to the conclusion that it possesses considerable

potential as an oﬀ-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 de-

veloped a cryptographically secure method of time-stamping

digital documents [4]. Their subsequent introduction of Merkle

trees enabled data to b e gathered into chained blocks, signiﬁ-

cantly enhancing security as well as eﬃciency [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 consists of a series of blocks

that are cryptographically linked, ensures immutability and

tamper-prooﬁng. Consequently, it establishes a highly reliable

digital record-keeping system [8]. The application of blockchain

technology has expanded beyond its initial implementation in

the domain of cryptocurrency. It has been adopted in various

S. A. Aladeeb et al.

ﬁelds, including logistics, health, public administration, supply

chain management, and, notably, ﬁnancial services [9–14].

In the banking sector, blockchain is increasingly seen as an

innovative way to transform the trustworthiness and reliabil-

ity of data management [15]. As digital technology continues

to p enetrate daily life and concern about data security grows,

blockchain’s signiﬁcance will continue to rise. It may become as

integral to daily life as the internet [6]. Furthermore, the emer-

gence 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 signiﬁcant milestone by 2027, becoming integrated into

various sectors of the global economy. A considerable augmen-

tation in the ﬁnancial sector, including the banking industry,

is projected to increase GDP by 10% [18].

Among the most prominent manifestations of this trans-

formation is the rise of decentralized ﬁnance (DeFi), which

uses blo ckchain technology to facilitate peer-to-peer ﬁnancial

services without the need for intermediaries such as conven-

tional banks. This setup transcends geographical locations and

provides basic ﬁnancial services, such as savings, loans, and in-

vestment products to poor communities in emerging economies

[19, 20].

As a revolutionary innovation, blockchain technology of-

fers numerous b eneﬁts: enhanced security, privacy, operational

transparency, and increased eﬃciency. This is all a result of its

decentralized nature and the use of cryptographic algorithms,

which signiﬁcantly reduce the risk of cyberattacks and fraud

while ensuring traceability and data integrity [21–24]. Conse-

quently, banks are increasingly exploring blockchain technology

for applications such as cross-border payments, streamlined

Know Your Customer (KYC) pro cesses, enhanced anti-money

laundering (AML) measures, and automated contract enforce-

ment through smart contracts. These innovations collectively

contribute to lowering operational costs and improving overall

eﬃciency [25, 26].

Despite the promise of blockchain technology, its adoption

by banks faces limiting factors. These factors include reg-

ulatory uncertainty, technical complexity, and resistance to

change at the organizational level. A meticulous examination

of the opportunities and limitations presented by this technol-

ogy 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

interest among academics and practitioners. In recent years,

academic interest in the topic has increased markedly, result-

ing in a large and diverse bo dy of literature. No study, to the

best of my knowledge, has ever carried out a detailed systematic

mapping of the intellectual 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 ﬁll this gap, this study utilizes a hybrid metho dology

of literature review, combining the bibliometric analysis and

systematic content review to answer the following research

questions:

RQ1: What are the prevailing research trends and pat-

terns of scholarly collaboration in the domain of blockchain

technology in the banking sector between 2015 and 2025?

RQ2: What are the core thematic clusters and intellectual

structures underpinning blockchain research in the banking

sector?

RQ3: What key research gaps and future directions can

be identiﬁed to advance the understanding and application of

blockchain technology in the banking sector?

Amidst the accelerating digitalization of banking and ﬁ-

nancial systems, blockchain technology is revolutionizing how

banking services are pro duced and disseminated. The primary

aim of this research is to synthesize the current academic liter-

ature 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 quantitative 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 ﬁndings, oﬀering

an overarching perspective on how blockchain is reshaping the

industry. Besides mapping the literature, the study provides

critical reﬂections on academic and institutional responses to

the emergence of blockchain and indicates avenues for further

research in a bid to advance its revolutionary potential in the

banking sector.

By doing so, this study contributes to a deeper understand-

ing of the signiﬁcant development of the ﬁeld 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 triangulation and cross-validation that combines

bibliometric science mapping and qualitative thematic analysis,

providing valuable and actionable insights for academics, prac-

titioners, and policymakers. In addition, the study contributes

to the development of transparent, safe, and eﬀective bank-

ing and ﬁnancial systems by identifying the advantages and

obstacles related to the adoption of blockchain technology sys-

tematically and the proposal of an organized agenda for future

research in this ﬁeld.

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 re-

sults of the performance analysis and science mapping of 389

publications on blockchain in banking are presented, and the six

main thematic clusters identiﬁed are discussed. Section 4 iden-

tiﬁes the managerial and practical implications of the ﬁndings.

Finally, Section 5 oﬀers the main conclusions, which include a

summary of the key ﬁndings, 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 system-

atic content analysis. The mixed-method approach combines

quantitative analysis with a substantial emphasis on qualitative

analysis.

A hybrid review approach, as describ ed by Paul and Criado

[30], is a method that facilitates a comprehensive examina-

tion of the literature by combining quantitative and qualitative

approaches, with the aim of organizing, analyzing, and inter-

preting data in a meaningful way. The ob jective is to provide a

comprehensive summary of the scholarly literature on the adop-

tion of blockchain technology (BCT) in the banking industry

and to oﬀer an integrative review of the main topics, ma jor

ﬁndings, and research agendas for the future in this domain.

Bibliometric analysis, which relies on the statistical eval-

uation 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 struc-

ture of existing knowledge within a given discipline [32]. The

methodology stages and analytical tools adopted to fulﬁll the

objectives of the study are outlined in Figure 1.

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 re-

search [18, 33]. Although there are other databases, such as

Web of Science, IEEE Xplore, and Google Scholar, Scopus was

selected because it oﬀers the largest curated abstract and ci-

tation database of peer-reviewed social science and business

publications, indexing over 27,000 active titles from more than

7,000 international publishers, with particularly strong cov-

erage in Finance, Management, Economics, and Information

Systems disciplines[34, 35]. Prior bibliometric methodology re-

search indicates that Scopus retrieves broader journal coverage

and comparable citation structures to Web of Science for man-

agement and interdisciplinary technology studies, while oﬀering

superior metadata consistency for science mapping analyses.

Its extensive coverage also makes it convenient for research in

corporate ﬁnance, such as the adoption of blockchain in the

banking sector. A deﬁned 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 Identiﬁcation

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 exam-

ined to conﬁrm that the selected keywords were inclusive and

speciﬁc.

Based on this literature review, we identiﬁed several fre-

quently 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 identiﬁed. Further-

more, consultation with two academic experts in ﬁnance and

block-chain conﬁrmed that the keywords ”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

related terms, we purposely restricted the scope of the ﬁnal re-

trieval 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 congruent with our research objectives,

particularly in developing an intellectual structure and deter-

mining the main contributions towards the understanding of

the impact of blo ckchain technology on banking.

2.1.3. Search Criteria and Data Extraction

The data collection process during the study was conducted

systematically, following standard bibliometric study practices

[38] and PRISMA guidelines for transparent rep orting [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 technology emerged in 2008, until 2015,

academic interest in adopting blockchain technology in the

banking sector was signiﬁcantly nonexistent. Therefore, the

selected time frame (2015–2025) indicates the evolution of

scientiﬁc production in the ﬁeld.

Because of the novelty and rapid progress of the research

ﬁeld, formal inclusion criteria were applied to ensure the

analytical relevance and dataset quality. Only peer-reviewed

articles, conference papers, and review articles were chosen,

restricting analysis to the most relevant subject areas: Busi-

ness, Management, and Accounting; Economics, Econometrics,

and Finance; and Social Sciences. Publications that focused

primarily on technical or computational aspects without a

substantial connection to banking, economic, or ﬁnancial ap-

plications 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 ﬁnal 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 speciﬁcity over

broad recall, which is a typical approach used in bibliometric

mapping studies that strive for clearer concepts and greater

analytical coherence. In addition, exploratory pilot studies

utilizing broader terminology (ﬁntech, ﬁnancial services, dis-

tributed ledgers, etc.) resulted in the retrieval of an excessive

number of records (more than double) that either only slightly

or not substantially referenced 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 doc-

uments using ﬁlters, the ﬁnal dataset of 389 documents was

attained. The records were saved in CSV (Comma-Separated

Values) format 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 ﬁnance literature’s standard practices.

2.2. Data Reﬁnement and Analysis

The second stage of the systematic protocol involved reﬁning

retrieved data after the previous step to generate a dataset for

bibliometric mapping and thematic synthesis of the literature.

S. A. Aladeeb et al.

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)

It is important to note that this stage did not change the con-

tent or makeup of the dataset retrieved from earlier stages;

rather, it enhanced the reliability and interpretability of analy-

ses of keyword-based data, speciﬁcally co-occurrence networks

and clustering themes from keywords.

Data preparation involved the systematic elimination of

false positives, the cleaning of metadata ﬁelds, and the nor-

malization of author-provided keywords. Keyword optimization

was accomplished by merging singular and plural forms, stan-

dardizing spelling diﬀerences, and consolidating synonymous

terms into cohesive conceptual labels. For instance, terms like

”cryptocurrency” and ”cryptocurrencies,” ”smart contracts”

and ”smart contract,” as well as ”bank” and ”banks,” were

standardized into singular keyword inputs. Additionally, termi-

nology standardization was employed to harmonize overlapping

deﬁnitions typically found in the diverse blockchain literature.

This process included incorporating equivalent phrases such as

”distributed ledger,” ”distributed ledger technology,” ”ﬁntech,”

”decentralized ﬁnance,” and ”DeFi,” along with ”banking sec-

tor” and ”banking industry.” Terms that were irrelevant or

contextually unsuitable (such as ”bibliometric analysis and

COVID-19”) were eliminated to uphold thematic consistency.

After optimization and normalization, two complementary an-

alytical methods were executed: - Descriptive bibliometric

analysis, which evaluated publication trends, citation patterns,

source productivity, and networks of key contributors across

various ﬁelds; - Systematic content analysis, which pinpointed

key research themes, core theme groups, and predominant

scholarly discussions arising from the literature.

As a result, this reﬁnement process ensured the statistical

reliability 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 exam-

ining the structure and dynamics of the research ﬁeld. In this

study, VOSviewer [40], a specialized computer software pro-

gram for constructing and visualizing large-scale bibliometric

networks [41], was employed. VOSviewer software was selected

due to its proven capabilities in the management of large net-

works, as well as its inbuilt text-mining functionality, which

enables the extraction and analysis of valuable terms and con-

cepts from the literature [42]. Additionally, Microsoft Excel

was used for statistical analysis and data visualization, includ-

ing 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 metho ds. These methods are largely recog-

nized 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 bib-

liometric analysis, focused on the quantitative assessment of

scientiﬁc productivity and impact. It provides a data-driven

perspective of scholarly output and the growth of a scientiﬁc

discipline over time. This technique encompasses the analysis of

annual publication trends, identiﬁcation of highly cited publi-

cations, evaluation of leading scientiﬁc journals, and assessment

of the research contributions by institutions, countries, and

individual authors [44]. By examining these indicators, per-

formance analysis provides a comprehensive understanding of

the intellectual evolution of the ﬁeld and uncovers its most

inﬂuential contributors.

Science mapping, on the other hand, provides a graphic and

structural representation of the intellectual architecture of the

ﬁeld [45]. This technique involves advanced bibliometric tech-

niques 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 thematic clusters that form the landscape of

the ﬁeld [46]. In particular, bibliographic coupling was used to

study thematic clusters and current fronts of research to iden-

tify emeging topics, research gaps, and directions for future

research. Certain previous bibliometric research has utilized

similar approaches to examine blockchain research within the

banking sector [18], [36], [37], conﬁrming 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. Speciﬁcally, 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 synthesize dominant research themes, assess

how blockchain would impact banking operations, and ascertain

dominant scholarly trends. Systematic content analysis not only

contributed to complementing bibliometric ﬁndings but also to

enhancing the interpretative depth of the results.

In the ﬁrst phase, bibliometric techniques were applied us-

ing VOSviewer in order to visualize the intellectual structure

of the ﬁeld. 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 identiﬁed

[45]. Second, bibliographic coupling was employed to cluster

articles that share common cited references, thereby revealing

thematically related research streams [48]. A minimum citation

threshold of 30 citations per do cument 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

comprehensiveness. After duplicate removal and further man-

ual ﬁltering, the ﬁnal 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 ﬁnal dataset was examined and co ded

to extract relevant information regarding research objectives,

methodological approaches, core themes, principal ﬁndings,

and identiﬁed research gaps. Second, the coded content was

grouped into preliminary thematic categories based on their

conceptual similarities. Thereafter, these thematic categories

were manually reﬁned to ensure conceptual relevance and logi-

cal coherence within the categorization. For instance, thematic

clusters that have similar central themes (e.g., blockchain and

cryptocurrency, blockchain and DeFi) were consolidated into a

common thematic cluster. Finally, the outcomes derived from

S. A. Aladeeb et al.

the qualitative analysis were cross-validated against those gen-

erated through keyword co-o ccurrence analysis to enhance the

results of the study.

Methodological Novelty and Contribution

The novelty of the metho dological approach of this study

resides in its explicit triangulation and cross-validation frame-

work that combines bibliometric maps of science with qualita-

tive thematic analysis. Previous studies in this ﬁeld either used

descriptive bibliometric mapping or a qualitative synthesis, but

these studies were typically based on small samples and treated

these methods separately. In contrast, this research is designed

in three stages: (i) to identify macro-level thematic structure

through quantitative bibliometric mapping; (ii) to use system-

atic qualitative content analysis to capture in-depth conceptual

patterns and research gaps; and (iii) to cross-validate the re-

sults 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 function-

ally reliable representation of the research landscape, helping

to better establish a framework for developing theories, as well

as planning future investigations into the impact of blockchain

on banking studies.

Methodological Challenges and Mitigation

The rapid growth of the literature on blo ckchain applications

in banking presents several methodological challenges. These

issues arise from four dimensions of interrelated challenges: dis-

ciplinary fragmentation, terminological inconsistency, publica-

tion volume/size/overview, and methodological heterogeneity.

Blockchain research in banking spans broad disciplinary areas,

including ﬁnance, computer science, information systems, law,

and regulatory research, making it diﬃcult to align themes and

integrate theories. Additionally, many overlapping terms exist,

including ﬁntech, digital banking, cryptocurrencies, decentral-

ized ﬁnance (DeFi), central bank digital currency (CBDC), etc.

These multiple terms signiﬁcantly increase the potential for

conceptual confusion and misclassiﬁcation.

In addition to these diﬃculties caused by the rapid growth

in the number of publications, many diﬃcult processes of liter-

ature screening and synthesis occur when hundreds of literature

articles are reviewed while attempting to keep the reviews an-

alytically sound. Moreover, the research literature reviewed

exhibited considerable methodological diﬀerences, 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 tri-

angulated methodological approach that employs bibliometric

mapping of literature using computer analysis tools as well as

systematic qualitative 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 ﬁndings by combining quan-

titative mapping, qualitative thematic interpretation, and

cross-validation. This integrative approach strengthens the ro-

bustness of the ﬁndings 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 ﬁeld.

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

scientiﬁc literature that addresses the application of blockchain

in banking during this period. This overview not only identiﬁes

key publication patterns but also brings an understanding of

the evolution of the ﬁeld. Such mapping is essential for under-

standing the development of the topic, as it helps to identify

publication patterns, collaborative networks, and the most ac-

tive 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 pub-

lication trends (Table 2; Figure 2), top productive scientiﬁc

journals publishing in the ﬁeld (Table 3), top contributing

authors (Table 4), and most active institutions (Table 5),lead-

ing countries in publication output (Table 6), and the highly

cited documents (Table 7). These analyses collectively provide

a detailed account of the scientiﬁc landscape and support the

evaluation of scholarly performance in the ﬁeld.

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

Aﬃliations 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

Figure 2. Total Publications (TP) over time (2016–2025). Note: The data for 2025 (33 publications) is incomplete, reﬂecting the data cutoﬀ 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.

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 met-

rics such as total publications (TP), cumulative publications

(CTP), total citations (TC), and average citations per publica-

tion (TC/CTP and TC/TCP). The data reveal three distinct

phases in the evolution of the research ﬁeld: (1) Early emer-

gence and foundational impact (2016–2018), (2) Expansion and

thematic diversiﬁcation (2019–2021), and (3) Peak production

with initial signs of saturation (2022–2025).

The initial phase (2016–2018) reﬂects the inception of aca-

demic activity, with four articles published in 2016 being cited

1,249 times (312.25 per article), indicating foundational signiﬁ-

cance. The number of publications increased from eight in 2017

to 20 in 2018, reﬂecting growing interest in the potential of

blockchain technology in the banking sector.

In the second phase, b etween 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 diversiﬁcation of research themes and the decline in the pro-

ductivity of 2021, possibly impacted by global disruptions such

as the COVID-19 pandemic.

The third phase (2022–2025) represents the most productive

period in terms of publication volume, with annual outputs

increasing from 54 in 2022 to a peak of 78 in 2024. Publica-

tions during this phase constitute over half of the total output,

highlighting the area’s rapid expansion and highest level of pub-

lication activity. Although the TC/CTP ratio fell from 6.53

in 2022 to 1.17 in 2024, this decline is largely attributable to

the recency eﬀect, as newer articles have not yet accumulated

signiﬁcant citations.

The data for 2025 is partial and represents an artifact of the

data cutoﬀ. As of May 12, 2025, only 33 publications were in-

dexed at this time. So, the apparent decline in output for 2025

constitutes a methodological artifact rather than a substantive

downturn. While this ﬁgure is expected to increase signiﬁcantly

by the end of the year, annual publication counts, rather than

citation-based indicators, reﬂect a consistent rise in research

activity. Moreover, the increasing diversiﬁcation of research

themes, particularly applied studies integrating blockchain with

AI, IoT, and FinTech, is likely to inﬂuence 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

interdisciplinary, problem-based approaches to advance the

practical uptake of blockchain in banking contexts.

S. A. Aladeeb et al.

Table 3. Leading Scientiﬁc Journals Publishing Blockchain in Banking Research

Rank Source Documents Citations Avg. Citations Avg. Year Avg. Norm. Citations

1 Technological Forecasting and So cial 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 Scientiﬁc 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

3.1.2. Leading Scientiﬁc 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 evalua-

tion 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 Tech-

nological Forecasting and Social Change and Sustainability

(Switzerland) are at the forefront journals in terms of volume,

each journal’s scholarly impact varies signiﬁcantly. Technolog-

ical Forecasting and Social Change exhibits a notably superior

citation proﬁle (648 total citations; 92.57 citations per arti-

cle), which underscores the journal’s strong focus on technol-

ogy adoption, innovation dissemination, and socio-economic

changes, sub jects that closely relate to blo ck-chain research

in the ﬁnancial sector. Its wide interdisciplinary readership

and emphasis on theory-driven forecasting likely enhance its

visibility and citation across various ﬁelds. In comparison, al-

though Sustainability frequently covers block-chain topics, its

more practical and policy-oriented focus, often aimed at spe-

ciﬁc sustainability audiences, leads to lower average citation

rates (18.86 per article), indicating a more localized rather than

broad academic inﬂuence.

In contrast, Financial Innovation, despite having published

only ﬁve articles, boasts the highest overall citations (922)

and greatest average impact per article (184.40). This re-

markable achievement illustrates that thematic relevance of a

journal, rather than just the volume of publications, drives aca-

demic inﬂuence. The journal’s concentrated focus on ﬁnancial

technologies, digital currencies, and banking change p ositions

it as a primary outlet for signiﬁcant theoretical and empir-

ical contributions, making its articles particularly prominent

and often cited across ﬁnance, economics, and policy research

communities.

A similar trend is evident in New Economic Windows, which

attained 543 citations with just three publications. Its early

exploration of blockchain topics (with an average publication

year of 2016) enabled its articles to gather citations over an ex-

tended period, demonstrating the b eneﬁts of early involvement

in emerging research areas. These foundational studies often

serve as essential reference p oints for subsequent scholarship.

On the other hand, journals like the International Jour-

nal of Scientiﬁc and Technology Research, while comparatively

productive (six publications), exhibit limited citation impact

(averaging 9.5 citations per article). This variance likely stems

from the journal’s broader technical audience and its less

focused engagement with ﬁnancial or banking communities,

leading to reduced citation engagement within social science

and ﬁnance-oriented research networks.

Normalized citation metrics further enhance impact evalu-

ation by considering publication age. Journals such as IEEE

Transactions on Engineering Management (6.44) and Technol-

ogy Analysis and Strategic Management (3.55) show strong

relative citation performance given their more recent publica-

tion 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 ﬁnancial sector.

Overall, these trends suggest that scholarly inﬂuence in

the realm of blockchain-banking research is more inﬂuenced

by journal thematic alignment, multidisciplinary engagement,

early positioning in sp eciﬁc topics, and theoretical focus rather

than merely by publication frequency. Journals that contex-

tualize blockchain within wider discussions on ﬁnancial gov-

ernance, 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 inﬂuence indicates

that the intellectual essence of the ﬁeld is anchored in pub-

lications that connect ﬁnancial theory, policy analysis, and

studies of innovation rather than solely in technically driven

or sustainability-centric journals.

3.1.3. The 10 Most Inﬂuential Authors

Table 4 shows the most proliﬁc authors who have made the

largest academic contributions to blockchain research in the

banking sector. This evaluation considers their productivity,

citation impact, normalized inﬂuence, 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 ﬁeld.

It can be seen that Devi, N. Chitra and Kumari, Anitha are

the most proliﬁc 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 col-

laboration networks. This suggests that Devi’s inﬂuence goes

beyond citation metrics to include a bridging function b etween

various research teams, encouraging cross-pollination of ideas

related to adoption, op erational eﬃciency, and governance in

blockchain.

Table 4. The Most Inﬂuential 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.

In contrast, although Mbaidin, Hisham O. has the same

number of publications of Devi and Kumari, he has lower ci-

tations and average citation per document wit 43 and 14.33

respectively. Moreover, the author is strongly linked (link

strength: 23), suggesting broad collaborative activity in the

ﬁeld. This pattern highlights authors whose main contribu-

tions are in interdisciplinary collaboration and empirical re-

search across multiple countries. This fosters methodological

diversity but may not yet result in highly cited conceptual

breakthroughs.

A diﬀerent type of intellectual leadership is seen in authors

like Ramzi El-Haddadeh, Nitham Hindi, Vishanth Weerakkody,

and especially Uthayasankar Sivarajah. They achieve notable

citation eﬃciency despite fewer publications. Each of them had

two high-impact papers with over than 100 citations, an average

of 55 citations p er article, and 2.54 normalized scores, indicat-

ing inﬂuence and visibility. However, Uthayasankar Sivarajah

has the highest citation average (109.5) and a 5.03 normal-

ized citation score, showing exceptional scholarly impact with

fewer papers. He particularly focuses on governance, data man-

agement, and digital transformation strategies within ﬁnancial

institutions. These authors help consolidate theory by present-

ing models that link blockchain adoption with organizational

readiness and regulatory issues.

Emerging researchers like Gan, Qingqiu, and Lau, Ray-

mond 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 cita-

tions highlights a growing second wave of leadership focused

on algorithmic ﬁnance, data analytics, and the convergence

of emerging ﬁntech. This trend indicates a shift in the ﬁeld

from foundational theoretical work to application-oriented and

interdisciplinary growth.

In summary, the author network structure illustrates a

layered knowledge ecosystem that balances established theo-

rists, network connectors, and rapidly advancing innovators.

Leadership in this ﬁeld is deﬁned not just by the number of pub-

lications but also by the ability to present impactful conceptual

frameworks, provide scalable empirical evidence, and foster new

research initiatives through collaborative networks. This evolv-

ing proﬁle of authorship shows the maturation of blockchain

and banking research into a more uniﬁed yet metho dologically

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 productiv-

ity, impact, and other important indicators such as, citations,

average publication 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 pa-

pers that garnered 110 citations, achieving an average of 36.67

citations per paper and an average normalized citation score of

1.32. This reﬂects a high academic impact and research quality

in the feild. Conversely, the Adnan Kassar School of Business at

the Lebanese American University, despite being equally pro-

liﬁc 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 Univer-

sity, Mutah University, Abu Dhabi University, and independent

institutions such as the Financial and Taxation Consultant,

Jordan, b oth 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 p opularity 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 nor-

malized citation score (3.23), indicating the inﬂuence 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

institutionally varied research eﬀorts. 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 Inﬂuential Countries

Table 6 illustrates the signiﬁcant geographical variation in

research contributions, citation impact, and other ma jor indi-

cators, such as average publication year, average citations, av-

erage normalized citations, and total link strength of blockchain

research in the banking sector.

As shown in Table 6, India is the most proliﬁc and pro-

ductive 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.

S. A. Aladeeb et al.

Table 5. The Most Inﬂuential 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

University, Jordan

2.00 12.00 2024.00 6.00 1.12

5 Dept. of Economics, College of Economics and Management, Al Qasimia

University, 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.

In contrast, the United States, with 51 papers, has the high-

est 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 average citations (64.44) and normalized cita-

tion score (2.42), reﬂecting high-quality and highly recognized

research output.

China also demonstrates a balanced proﬁle with 24 papers

and an average citation of 47.79, showing a good compromise

between pro ductivity and impact. The United Arab Emirates

shows emerging activity with 21 pap ers 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 pro ductive. Jordan and Switzerland,

in contrast, while producing smaller volumes of output (12 and

10 pap ers, respectively), stand at competitive normalized ci-

tation averages (1.15 and 0.82, respectively), indicating quite

high-impact research. Surprisingly, Spain and the Russian Fed-

eration have lower normalized and average citation indicators,

reﬂecting 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

scientiﬁc impact. These patterns show that there is a global

contribution, but the quality and visibility of research in the

ﬁeld 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 docu-

ments in blockchain and banking research identiﬁes the seminal

works that have inﬂuenced academic investigation and applied

applications in this multidisciplinary research area. These doc-

uments span various areas of study, ranging from ﬁnancial

innovation to accounting, regulatory studies, and information

systems. Citation counts indicate academic and intellectual in-

terest, while more complex metrics, such as average citations

per year and normalized citation score, provide a better in-

dication of the signiﬁcant documents and their comparative

inﬂuence over time and across research ﬁelds [53].

In view of this, Table 7 presents the ten most highly

cited documents in our research ﬁeld, 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

entitled ”Blockchain application and outlo ok in the banking in-

dustry,” published in the Financial Innovation journal, with a

total of 706 citations as the most cited document in ﬁnance. Its

average annual citation rate of 78.44 indicates a consistently

high impact since its publication, although its normalized ci-

tation score of 2.26 suggests that, despite its high number of

citations, its performance compared to other publications in

its ﬁeld is more moderate. Nonetheless, the work is still in-

ﬂuential owing to its pioneering and general introduction of

the revolutionary nature of blockchain for banking, speciﬁcally

as it pertains to operational eﬃciency 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 citations (601), but outperforms all other do cuments

in terms of average annual citations (120.20) and the num-

ber of normalized citations (12.17). This suggests that the

study has quickly become a leading reference in its ﬁeld, al-

though it has just 4 years since its publication. This suggests

that the study is already a classic reference in the area. The

Journal of Financial Intermediation presents a solid theoreti-

cal model on how ﬁntech, including blockchain technology, is

transforming long-established paradigms in banking. Its very

high normalized citation score also indicates high inﬂuence and

cross-disciplinary adoption, especially in ﬁnance, economics,

and regulation studies in banking.

Its third most cited paper, authored by Dai and Vasarhelyi

[55], entitled ”Toward blockchain-based accounting and assur-

ance,” published in the Journal of Information Systems, has

been cited 532 times. It has a high average of 66.5 yearly

citations and a normalized score of 5.01, attesting to its

contributory quality as a connecting publication between ac-

counting theory and blo ckchain technology. It oﬀers research

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.

Table 7. The Top 10 Most Cited Documents

Rank Authors Year Title Source Document Type TC ACPY NC

1 Ye Guo & Chen Liang 2016 Blockchain application and out-

look 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 account-

ing and assurance

Journal of Information

Systems, 31(3)

Conceptual research arti-

cle

532.00 66.50 5.01

4 Gareth W. Peters & Efstathios Panayi 2016 Understanding Modern Ba nking

Ledgers Through Blockchain

Technologies: Future of Trans-

action Processing and Smart

Contracts on the Internet of

Money

New Economic Windows

(NEW), pp. 239–278

Book chapter 452.00 50.22 1.45

5 Schuetz S.; Venkatesh V. 2020 Blockchain, adoption, and ﬁnan-

cial inclusion in India: Research

opportunities

International Journal of

Information Management,

Original research article 297.00 59.40 6.01

6 Daniel Minoli & Benedict Occhiogrosso 2018 Blockchain mechanisms for IoT se-

curity

Internet of Things

(Netherlands), 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 Regu-

lation, 6(2), 172–203

Conceptual/policy article 264.00 52.80 5.35

8 Poonam Garg et al. 2021 Measuring the perceived beneﬁts

of implementing blockchain tech-

nology in the banking sector

Technological Forecasting

and Social Change, 163

Empirical research article 218.00 54.50 9.94

9 Saurabh Ahluwalia et al. 2020 Blockchain technology and startup

ﬁnancing: A transaction cost eco-

nomics perspective

Technological Forecasting

and Social Change, 151

Empirical research article 212.00 42.40 4.29

10 Mohd Javaid et al. 2022 A review of Blockchain Technol-

ogy applications for ﬁnancial ser-

vices

BenchCouncil Transac-

tions on Benchmarks,

Standards and Evalua-

tions, 2(3)

Review article 207.00 69.00 8.39

TC = Total Citations; ACPY = Average Citations p er Year; NC = Normalized Citations.

that informs discussion about the use of blockchain to en-

able auditability and trust in ﬁnancial reports, and is thus

a reference work on the research of ﬁnancial assurance with

blockchain-based.

An equally signiﬁcant contribution is made by Peters and

Panayi [56], entitled ”Understanding modern banking ledgers

using 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 im-

pact in its broader research ﬁeld. The signiﬁcance of this

work lies in its speciﬁc contribution to addressing distributed

ledger technology and smart contracts, and oﬀering insight into

blockchain’s technology foundation from a banking industry

perspective.

Additionally, the International Journal of Information Man-

agement published research by Schuetz and Venkatesh [57] on

using blockchain to drive ﬁnancial inclusion in India. The ar-

ticle was cited 297 times with an average annual citation rate

of 59.4 and a normalized 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 ﬁnancial 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

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 ad-

vanced 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 Buck-

ley [59], entitled ”Decentralized Finance,” which has been cited

264 times. The article has a yearly average of 52.8 citations and

a normalized citation of 5.35, and it illustrates increasing aca-

demic interest in legal and compliance matters of decentralized

S. A. Aladeeb et al.

ﬁnancial systems. Published in the Journal of Financial Reg-

ulation, it oﬀers 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 beneﬁts of implement-

ing blockchain in the banking sector,” which has been cited 218

times, by Garg et al. [60]. Interestingly, it has a high aver-

age citation rate of 54.5 per year and a signiﬁcant normalized

citation score of 9.94, which indicates high use and strong cross-

ﬁeld inﬂuence. Using structural equation modeling, the authors

assign a numeric value to the beneﬁts of blockchain, such as

trust, transparency, and eﬃciency, and make this study highly

applicable to banking professionals.

Parallel to this is the work of Ahluwalia, Mahto, and Guer-

rero [61] enhances the knowledge of blockchain technology

within the entrepreneurial ﬁnance context through their empiri-

cal article titled ”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 envi-

ronments through the adoption of transaction cost economics

as a conceptual building block. Rounding out the list is the

most recent contribution by Javaid et al. [62], titled ”A Review

of Blockchain Applications in Financial Services,” which ac-

cumulated 207 citations within a brief period. With an annual

average of 69.0 citations and a normalized citation score of 8.39,

the article’s direct impact and growing importance are evident.

The article summarizes the various applications of blockchain

technology in ﬁnancial services, reﬂecting 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 inﬂuence within the blockchain-banking literature is more

linked to the capacity to relate technological advancements

to broader institutional, accounting, regulatory, and so cio-

economic issues than to purely technological innovation. Works

that receive a high number of citations bring together con-

ceptual theorization (like ﬁntech transformation), incorporate

insights from multiple disciplines (such as accounting, law, and

information systems), and present empirical evidence that tack-

les real-world banking issues, including trust, ﬁnancial inclu-

sion, compliance, and eﬃciency. This highlights that the most

impactful articles in academia frame blockchain not merely as

a technical tool, but as a driver for signiﬁcant changes in bank-

ing ecosystems. As a result, the structure of citations indicates

a mature ﬁeld that is progressively fo cusing on governance

frameworks, adoption pro cesses, regulatory legitimacy, and or-

ganizational transformation instead of isolated demonstrations

of technology.

3.2. Science Mapping

Science mapping examines the relationships among contribu-

tors in a research ﬁeld. Particularly, it focuses on patterns of

intellectual interaction and structural connections between key

scholarly constituents, such as how sources, countries, institu-

tions, authors, references, keywords, and publications relate to

each other [46, 63, 64].

The present study uses a range of science mapping tech-

niques, including co-authorship analysis, co-citation analysis,

co-occurrence analysis, and bibliographic coupling analysis.

These methods facilitate gaining in-depth knowledge about

the evolution of the ﬁeld, the collaborative patterns that

characterize it, and the thematic structure that underpins it

[46]. When paired with network visualization software such as

VOSviewer, these methods illustrate the bibliometric and intel-

lectual structure of the research landscape [41, 45], as outlined

below.

3.2.1. Co-authorship of Countries

Co-authorship analysis is a bibliometric technique that is em-

ployed to study patterns of collaboration among authors, in-

stitutions, and countries based on joint publications [65, 66].

At the national level, it reveals international research collab-

oration, mapping the global dispersion of scientiﬁc production

and the transnational network structure [67, 68]. Particularly,

the analysis reveals leading countries, maps geographical pat-

terns of collaboration, and illustrates the eﬀect 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

country level using VOSviewer. We included countries that had

at least ﬁve 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 visual-

ization displays six color-coded clusters, where nodes represent

countries and links indicate the strength and frequency of co-

authorships. Node size reﬂects publication volume, while link

thickness shows collaboration intensity, and TLS quantiﬁes a

country’s total collaborative strength.

The blue cluster, led by India, comprises the United Arab

Emirates, Jordan, and South Africa, indicating close cooper-

ation 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 in-

novation. The participation of the United Arab Emirates and

South Africa signiﬁes an escalating level of interest in the ﬁ-

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 intercontinental 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 contributors to the technological and regula-

tory aspects of blockchain, while Saudi Arabia and Pakistan can

point to stronger academic connections with the West, possibly

underpinned by digitization reforms and plans like the Vision

2030 of Saudi Arabia.

The yellow cluster includes the Russian Federation, Ger-

many, Switzerland, and Turkey. Though geographically spread

across Europe and Eurasia, these countries show strategic in-

terest in digital ﬁnance and decentralization. Germany and

Switzerland lead in ﬁntech, while Russia and Turkey focus on

modernizing ﬁnancial systems, suggesting collaboration based

on national strategies for digital transformation.

Moreover, the purple cluster consists of the United King-

dom, France, and Iran. The UK is the middle connection

between the Middle East and Western Europ e, showing high

intra-European cooperation 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,

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 Blo ckchain and Banking Research. Node size represents publication volume, link

thickness indicates collaboration intensity, and colors denote distinct collaboration clusters.

are reﬂective of increasing Eastern and Southern European en-

gagement in blockchain research. Their inclusion is reﬂective of

increased cross-border collaboration as well as a willingness to

adopt blockchain towards economic modernization.

Overall, the ﬁndings 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 examine the intellectual landscape of a research area through

analyzing how frequently two documents, authors, or sources

are cited together in subsequent works [71]. A speciﬁc type

of this analysis, Author Co-citation Analysis (ACA), examines

how frequently two authors appear cited in tandem, therefore

reﬂecting the conceptual structure underlying scholarly com-

munication and conceptual evolution in an area [72, 73]. An

increased frequency of co-citation between two authors implies

a tight thematic correspondence or common inﬂuence on the

shaping of speciﬁc streams of research [74].

In the current study, to better understand intellectual foun-

dations and underlying blockchain research in the banking

context, an author co-citation analysis was conducted using

VOSviewer software. We applied a minimum threshold of 25

citations per author, resulting in the identiﬁcation of 102 promi-

nent authors out of a total of 25,779 who met the predeﬁned

criteria.

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

distributed to four distinct clusters, each represented by a dif-

ferent 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 clusters, while the edges illustrate how they have

been co-cited. The sizes of the nodes indicate the extent of their

co-citation. As a result, 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 ﬁeld.

The red color is the ﬁrst 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 ma jor contributions in applying

blockchain technology, digital technology, and information sys-

tems to banking and ﬁnance. They are most frequently cited

in academic literature, i.e., they are the foundation of theo-

retical and empirical research on blockchain technology in the

ﬁeld. This cluster is also highly linked to other clusters, which

indicates the intellectual power of the cluster over other ﬁelds.

In contrast, the second cluster, as can b e shown by the blue

color, includes prominent authors Kumar S., Khan S., Arner

D.W., Zetzsche D.A., Thakor A.V., Kauﬀman R.J., and Hassan

M.K. These authors are mainly involved with ﬁnancial regula-

tion, 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 imple-

mentation in banks. The uniqueness of the cluster indicates

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 inﬂuence, while links indicate co-citation

strength. Colors denote major intel lectual clusters.

the interdisciplinary connection of information systems, law,

and ﬁnance.

The third cluster, shown in green color, consists of au-

thors such as Nakamoto S., Tapscott D., De Filippi P., Eyal I.,

Zhang Z., Hassani H., Janssen M., Potts J., and El-haddadeh

R. They provide an all-round perspective of the revolution-

ary role of blockchain technology in banks. They examine

cryptocurrencies, decentralization, governance, and innovation.

Additionally, their co-citation suggests blockchain research cov-

ers a wide range of themes, from technical to legal, economic,

and regulatory domains.

Finally, the fourth yellow color cluster comprises the follow-

ing authors: Dwivedi Y.K., Kshetri N., Gupta S., Gunasekaran

A., and Venkatesh V. This cluster also appears to be talking

about information systems, models of technology adoption, and

regulatory eﬀects of blockchain technology. The cluster suggests

that there is a widening of the research landscape on the im-

plementation of blockchain technology in bank operations and

business designs, with a concentration on technology adoption

and strategic management.

In summary, these ﬁndings will be valuable to other re-

searchers, IT professionals, ﬁnancial service ﬁrms, practition-

ers, 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 intellec-

tual structure and thematic evolution of a research ﬁeld. It

measures the frequency with which co-occurring pairs of key-

words appear in the same papers, based on the assumption that

higher co-occurrence indicates a stronger conceptual relation-

ship between the terms [47]. This technique enables researchers

to identify the primary research themes, evaluate the concep-

tual 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

understanding of the thematic context of blockchain technology

in the banking sector. This approach has been demonstrated to

be eﬀective in identifying the leading research clusters and their

connections. 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 ﬁve occurrences for an author-

keyword was applied as an inclusion criterion. This was used

to ensure an analytical focus on the most relevant and fre-

quently occurring terms. Of the 1,131 keywords examined,

52 satisﬁed this initial criterion. In the second stage of our

research protocol, we manually reﬁned the dataset of the se-

lected keywords by merging singular and plural terms, such

as ”cryptocurrency” and ”cryptocurrencies,” ”smart contract”

and ”smart contracts,” and ”bank” and ”banks.” We also con-

solidated and standardized synonyms, including ”distributed

ledger” and ”distributed ledger technology,” ”ﬁntech” and ”ﬁ-

nancial technology,” ”decentralized ﬁnance” 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

reﬁnement, the 42 keywords were included in the ﬁnal analy-

sis. 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 ﬁntech 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 artiﬁcial intelligence 19.00 54.00

8 ﬁnancial inclusion 16.00 39.00

9 smart contracts 16.00 30.00

10 ﬁnance 14.00 39.00

11 digital banking 13.00 27.00

12 ﬁnancial services 13.00 36.00

13 innovation 13.00 40.00

14 security 13.00 31.00

The network visualization produced (Figure 5) presents

these clusters with each node representing a keyword, the node

size representing frequency of occurrence, and lines (edges) rep-

resenting 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 close-

ness 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 occur-

rence and interconnectivity. This is indicative of its central

position in scientiﬁc discourse. Secondary keywords such as

”banking,” ”ﬁntech,” ”cryptocurrency,” and ”Bitcoin,” which

are also highly frequent and highly interconnected, empha-

size blockchain’s central p osition in discourse regarding digital

change in the ﬁnance and banking sector. The visualization

(Figure 5) breaks down six distinct thematic clusters based on

the following:

The initial cluster (blue) focuses on cryptocurrencies and

decentralization, as evidenced by the terms ”blockchain,”

”Bitcoin,” ”cryptocurrencies,” ”decentralization,” ”Ethereum,”

”money,” and ”regulation.” The strong interconnection be-

tween these keywords and ”blockchain” indicates the inherent

relationship of blo ckchain technology with digital currencies,

particularly Bitcoin and Ethereum, which have always b een of

academic interest and a research topic in this ﬁeld. Further-

more, the cluster groups critical words that deﬁne the world of

cryptocurrency, since Bitcoin, Ethereum, and cryptocurrencies

in general have a very close link with terms such as ”decen-

tralization” and ”money.” It is clear that the literature in this

cluster provides a comprehensive overview of the history and

evolution of blo ckchain technology as applied to decentralized

digital currencies. In addition to this, it provides a detailed dis-

course on the regulation of crypto assets, which is an inevitable

consequence of the disruptive eﬀect that these assets have on

traditional ﬁnancial institutions. This cluster reﬂects 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 b oth

emerging technology keywords, such as machine learning, arti-

ﬁcial intelligence, big data, and the Internet of Things, as well

as banking applications, including technology adoption, cyber-

security, 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 combination of blockchain with other emerg-

ing technologies to re-engineer banking op erations and service

delivery. The emphasis on cybersecurity and sustainability in-

dicates great concerns about the security and sustainability of

innovation within ﬁnancial institutions.

Similarly, the third cluster (in green) includes the keywords

”banking,” ”ﬁntech,” ”ﬁnance,” ”ﬁnancial services,” ”ﬁnancial

inclusion,” ”crowdfunding,” and ”peer-to-peer lending.” This

indicates an awareness of blockchain technology’s macro-level

ramiﬁcations on the augmentation of access to and eﬃciency

of ﬁnancial systems. The prevalence of the term ”ﬁntech” in

this cluster captures the essence of the transformation in ﬁnan-

cial intermediation, highlighting the pivotal role of blo ckchain

technology in reengineering ﬁnancial services. Additionally,

the intersection of ”ﬁntech” and ”ﬁnancial inclusion” suggests

a promising research area exploring blockchain’s p otential to

address gaps in the banking sector.

Another notable cluster, marked in purple, focuses on

trust-related issues and includes terms such as ”trust,” ”trans-

parency,” ”security,” ”privacy,” ”smart contracts,” and ”bank-

ing.” The prevalence of these keywords indicates a persistent

academic interest in the technological and ethical dimensions

of blockchain technology. Speciﬁcally, the focus is on the po-

tential impact of blockchain technology on trust, privacy, and

security in banking and ﬁnancial institutions. This thematic

emphasis highlights blockchain technology’s central role in ad-

dressing data integrity and user trust challenges, both of which

are key to maximizing its value in banking applications.

The ﬁfth cluster is represented by light blue and comprises

keywords such as ”digitization,” ”innovation,” ”digital trans-

formation,” ”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 impact of blockchain technology on con-

temporary banking models with the aim of diversiﬁcation and

modernization.

The yellow cluster is particularly signiﬁcant because it

includes the keywords ”distributed ledger technology,” ”decen-

tralized ﬁnance,” ”ﬁnancial regulation,” ”central bank digital

currency,” ”cryptocurrencies,” and ”RegTech.” These terms are

poised to dominate future discourse concerning regulation and

decentralized ﬁnance (DeFi). ”Regtech” signiﬁes the integra-

tion of regulatory control and compliance in blockchain-based

banking. The cluster also highlights the pivotal role of pol-

icy and governance mechanisms in the adoption of blockchain

technology in ﬁnancial markets.

The network visualization of keyword co-occurrence in (Fig-

ure 5) led to the identiﬁcation of six major clusters, conﬁrming

the thematic structure of the ﬁeld. These clusters show the cur-

rent research frontiers and common terms used by scholars. For

the ﬁnal synthesis and interpretation of these thematic clusters,

please see Section 3.3.

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 reﬂects keyword frequency, link strength indicates

co-occurrence intensity, and clusters represent dominant thematic areas.

3.2.4. Bibliographic Coupling of Documents

Bibliographic coupling is a bibliometric technique that mea-

sures 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 iden-

tifying stable research streams and the underlying intellectual

structure of a research ﬁeld.

The present study used VOSviewer to perform bibliographic

coupling 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 inﬂuential contributions, a minimum of 30 citations

per document and a minimum cluster size of 10 documents were

applied to be analytically signiﬁcant. 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 no de represents

an individual academic paper that has been used in the analysis.

The size of a node is directly proportional to the number of cita-

tions it has received. The presence of larger no des is indicative

of a greater level of scientiﬁc inﬂuence. Lines linking nodes indi-

cate bibliographic coupling relationships, while the thickness of

the lines signiﬁes the number of common citations between the

two documents. The thickness of the line is indicative of the

strength of the connection, with thicker lines denoting closer

intellectual or thematic relationships. Moreover, the visualiza-

tion map supports two important quantitative 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 total link

strength (TLS), calculated as the sum of all individual link

strengths, is 1,226, reﬂecting high levels of connectivity and a

comprehensive set of blockchain banking studies. The network

map in this case provides valuable insight into thematic connec-

tivity among highly cited articles. The clustering reﬂects how

closely related the topics are and how references are linked b e-

tween publications, which in turn highlights the main themes

across the ﬁeld.

Figure 6 demonstrates that Thakor’s (2020) work exhibits

considerable scholarly inﬂuence, characterized by its substan-

tial node and cross-cluster edges, thereby establishing a signiﬁ-

cant connection 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 signiﬁcant overlap b etween these ﬁelds could potentially

indicate an underlying contribution, particularly to blockchain

technology and ﬁnancial applications. In contrast, Auer (2022),

Rehman (2023), and Kumar (2018) have focused their atten-

tion 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 reﬂect

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 reﬂects citation inﬂuence, links

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

the growing bifurcation of topics such as DeFi and cryptocur-

rency regulation. As shown in Figure 6 6, the map visualization

demonstrates the following clusters:

Cluster 1 (Red) is dominated by inﬂuential documents, in-

cluding Dai (2017), Peters (2016), Schuetz (2020), Alhuwalia

(2020), Ho oper (2020), Shoaib (2020), and Cuccuru (2017).

The cluster forms the theoretical basis of the ﬁeld and fo-

cuses on blockchain technology infrastructure, settlement pro-

cesses, transparency, auditability, and value creation within

ﬁnancial systems. This cluster constitutes a pivotal theoreti-

cal 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), Sang-

wan (2020), and Kimani (2020) belong, is characterized by

its high level of interconnectedness and its tendency to ex-

plore blockchain convergence with FinTech innovation and

ﬁnancial inclusiveness for transforming banking services. This

tendency is underpinned by a focus on empirical rationales and

case-study ﬁndings.

Cluster 3 (Blue) consists of the following documents: Javaid

(2022), Khalil (2022), Menon (2024), Elbashbishy (2022),

Choo (2020), Rehma (2023), and Schlatt (2022). This clus-

ter emphasizes digital transformation, service innovation, and

customer-focused approaches to blockchain banking. The sig-

niﬁcant number of connections 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, consumer trust, and theories of innovation diﬀusion.

This cluster is grounded in extant literature on the behavior

and diﬀusion of innovation, thereby establishing a relationship

at both technical and organizational levels.

The high interconnectivities among clusters emphasize the

interdisciplinary nature of blockchain research in banking, due

to the convergence of technology, economics, regulation, and

behavioral perspectives. The prevalence of strong coupling re-

lationships and numerous thematic avenues also suggests that,

despite the fact that the ﬁeld is still in its infancy, it has at-

tained some level of maturity with well-deﬁned but interrelated

subﬁelds.

3.3. Content Analysis and Thematic Clustering

In order to address Research Question 2 (RQ2), this sec-

tion presents a qualitative thematic analysis of literature on

blockchain technology in banking, which was systematically

performed with the aim of identifying the main themes and

providing a comprehensive understanding of the research land-

scape. Instead of repeating the bibliometric analyses provided

in Section 3.2, this section builds on those quantitative ﬁndings

to provide contextual interpretation, conceptual validation, and

thematic coherence.

As outlined in the research methodology section, the ini-

tial identiﬁcation of the ma jor 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 relationship, or co-occurrence with each other,

S. A. Aladeeb et al.

based on the frequency with which they were cited by authors

and published in p eer-reviewed journals [48, 76].

The previously described bibliometric research metho ds are

helpful for creating a high-level map of the research domain.

However, they do not provide a detailed explanation of the

substantive content within the identiﬁed thematic clusters. To

address this gap in the literature, we conducted a qualitative

content analysis to synthesize, 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 iden-

tiﬁed 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 contents 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 deﬁne the

intellectual structure of blockchain research in the banking sec-

tor from 2015 to May 2025. These thematic clusters represent

the analytical framework through which to understand how

blockchain inﬂuences ﬁnancial intermediation, business pro-

cesses, compliance with regulation, innovation strategy, trust

creation, and integration with next-generation technology.

The following discussion focuses on the conceptual signiﬁ-

cance of these themes, providing a concentrated and analytical

summary of the key intellectual trends in the ﬁeld. This fulﬁlls

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 eﬃciency, smooth transaction frictions, or

transform core banking systems. More conceptually, the lit-

erature 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-oﬃce functions, interbank

settlement mechanisms, and audit and compliance processes.

Foundational studies, such as [55, 56], establish the theoret-

ical frameworks that describe how blockchain technology helps

automate banking ledgers, enhances settlement eﬃciency and

reconciliation accuracy, and improves auditability. This tech-

nology 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 frameworks signiﬁcantly reduce settle-

ment 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 eﬃciency in terms

of cost savings, risk mitigation, transaction security, trans-

parency, and privacy. Also, this technology helps minimize

information asymmetry and startup capital costs [61]. These

beneﬁts extend beyond payments to credit information sys-

tems, international settlements, and broader ﬁnancial data

networks. This reinforces the idea that blockchain technology

is fundamental rather than limited in application.

Furthermore, this cluster emphasizes the strategic and or-

ganizational factors that facilitate successful blockchain imple-

mentation. Research using technology adoption models [79] and

innovation capability frameworks [105] identiﬁes critical factors

that mediate the operational eﬀectiveness of blockchain tech-

nology, including trust, management commitment, and resource

readiness. Furthermore, studies focusing on emerging markets

[78, 106] indicate that banks’ ability to achieve eﬃciency im-

provements is signiﬁcantly aﬀected by institutional maturity

and technological infrastructure.

Overall, these ﬁndings underscore the importance of

blockchain technology as a key tool capable of reducing op-

erational costs, automating complex veriﬁcation tasks, and

promoting resilient ﬁnancial systems with low response times.

However, the studies also point to ongoing challenges, partic-

ularly with regard to scalability and institutional readiness,

which continue to aﬀect 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 signiﬁcant

body of research that examines blockchain technology as

the core infrastructure for decentralized ﬁnance (DeFi) and

cryptocurrency-driven ﬁnancial systems. Theoretically, re-

search presents blockchain as a tool that eliminates interme-

diaries in conventional ﬁnancial operations by allowing direct

peer-to-peer value exchange, automating processes thr-ough

smart contracts, and fostering transparent ﬁnancial frameworks

that function independently of central authorities. The core

idea that emerges from this stream is that decentralized ﬁnance

not only improves current banking processes but also radically

challenges traditional models of ﬁnancial intermediation.

Groundbreaking research indicates that decentralized ﬁ-

nance oﬀers an alternative ﬁnancial structure capable of repli-

cating essential banking activities or services, such as lending,

borrowing, and asset trading, through decentralized protocols

that are governed by code rather than traditional institu-

tions [81]. This viewpoint is further reinforced by theoretical

contributions that depict blockchain as a “trust protocol,” high-

lighting its function in enabling transparency, immutability,

and the automated execution of ﬁnancial transactions [86].

Collectively, this body of literature lays the theoretical ground-

work for comprehending how decentralized systems challenge

conventional banking frameworks.

Furthermore, empirical and analytical studies within this

thematic cluster reveal a more nuanced and diverse landscape.

While blockchain-based money transfer systems and tokenized

ﬁnancial instruments show the potential to reduce costs and

increase eﬃciency, evidence suggests that adoption of cryp-

tocurrencies is often driven by speculative behavior rather than

dissatisfaction with traditional banking services [85, 87]. Fur-

thermore, research highlights persistent concerns about market

volatility, governance ambiguity, and regulatory uncertainty,

which continue to shape the risk proﬁle of decentralized ﬁnance

(DeFi) systems [82–84].

In addition to technical and economic factors, this research

highlights the ethical, behavioral, and institutional conse-

quences of DeFi. Studies focusing on accountability, ﬁnancial

inclusion, and ethical responsibilities caution that the decen-

tralization of ﬁnancial authority introduces new challenges

associated with consumer protection, systemic risk, and reg-

ulatory supervision [82, 83, 107]. These ﬁndings imply that

Table 9. Identiﬁed Thematic Clusters in Blockchain Banking Research.

No. Cluster Thematic Main Themes Sample References

1 Blockchain Applications for Trans-

forming Banking Operations and Fi-

nancial Intermediation

Real-time accounting, automation, rec-

onciliation, operational eﬃciency, startup

ﬁnance, and cost reduction.

[26], [55, 56],[61, 62],[77–80]

2 Decentralized Finance (DeFi)

and Cryptocurrencies Enabled by

Blockchain

DeFi, ICOs, remittances, ﬁnancial decen-

tralization, ethics of crypto, speculative

behavior.

[81–87]

3 Blockchain as an Enabler of Digi-

tal and Financial Technology Conver-

gence

Integration with IoT, AI, ML, FinTech,

KYC, smart contracts, and digital ID; en-

hancing automation and inclusion.

[46], [54], [58], [88–92]

4 Trust-Related Dimensions in

Blockchain-Based Banking

Trust, transparency, data privacy, orga-

nizational conﬁdence, strategic alignment,

adoption barriers.

[1], [60], [91], [93–96],

5 Regulatory, Legal, and Institutional

Frameworks for Blockchain Gover-

nance

Smart contracts and law, compliance,

anti-money laundering (AML), CBDCs,

DeFi regulation, policy adaptation.

[59], [97–101]

6 Strategic Modernization of Bank-

ing Business Model Enabled by

Blockchain

Disruption, competitive strategy, sand-

boxes, sustainable development.

[16], [37], [102]

the transformative capacity of DeFi is closely connected to

governance and public policy factors.

In summary, these studies aﬃrm that decentralized ﬁnance

(DeFi) and cryptocurrencies signify a groundbreaking exten-

sion of blo ckchain technology with the p otential to transform

ﬁnancial intermediation. However, the research notes that the

long-term viability of DeFi and its integration into mainstream

banking systems dep ends on establishing regulatory frame-

works, 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 functionality of other emerging digital and ﬁnancial tech-

nologies, such as artiﬁcial intelligence (AI), machine learning

(ML), the Internet of Things (IoT), FinTech platforms, smart

contract applications, and digital identity systems. Conceptu-

ally, the literature in this stream portrays blockchain not as an

isolated solution but as a coordination and trust layer that im-

proves interoperability, automation, and data integrity across

complex digital ecosystems.

Key contributions within this cluster highlight the potential

of blockchain to reshape ﬁnancial value chains by facilitat-

ing decentralized data exchange, automated decision-making,

and secure identity management [54]. In addition to ﬁnan-

cial services, this stream also highlights the role of blockchain

technology in securing Internet of Things (IoT) systems by

preventing data manipulation and enabling decentralized con-

trol, 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 ﬁnancial 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 signiﬁcant per-

formance enhancements in the delivery of ﬁnancial services,

especially in lending, risk assessment, and customer onboarding

processes [89, 90, 92, 107]. Evidence from banking applica-

tions points out that such technological convergence improves

predictive accuracy, operational scalability, and ﬁnancial inclu-

sion, particularly for small and medium-sized enterprises and

underrepresented populations.

A notable subtheme within this cluster focuses on digital

identity management and automated compliance processes. Re-

search on blockchain-based self-sovereign identity and smart

contract–enabled Know Your Customer (KYC) processes shows

signiﬁcant advances in privacy protection, cost-eﬀectiveness,

and regulatory compliance [91]. Similarly, research on block-

chain-enabled access control mechanisms highlights its poten-

tial to improve data management and security across intercon-

nected digital platforms [88]. These applications demonstrate

blockchain’s potential to address long-standing ineﬃciencies

in identity veriﬁcation and data governance within ﬁnancial

institutions.

In summary, this cluster emphasizes the importance of

blockchain as a key driver of technological convergence in dig-

ital ﬁnance. However, the literature also indicates ongoing

challenges related to the system’s compatibility, organizational

coordination, and institutional compatibility. However, the lit-

erature also emphasizes ongoing challenges concerning system

interoperability, regulatory harmonization, and compatibility.

These limitations imply that the advantages of blockchain in-

tegration 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. Crypto-

graphic veriﬁcation and decentralized consensus have often led

to characterizing blockchain as a ”trustless” technology; how-

ever, existing studies continually highlight the importance of

trust between organizations, user conﬁdence, and the legiti-

macy of institutions when implementing blockchain within the

ﬁnancial sector. From a conceptual framework, research within

this stream illustrates that whilst blockchain does not remove

S. A. Aladeeb et al.

trust, it re-establishes it, moving it from centralized intermedi-

aries to the technology itself, to governance structures, and to

the institutions.

Empirical research indicates that, for both users and banks,

perceived usefulness, transparency, and security are strong

motivators for the adoption of blockchain technology, while

technical capability is not as signiﬁcant [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 ef-

fects on increasing transparency and providing customers with

greater data integrity and privacy. The research has indicated

that the implementation of blockchain-based architectures can

decrease the level of information asymmetry b etween lenders

and borrowers, provide an increased level of auditing capa-

bilities, and create greater levels of conﬁdence in ﬁnancial

transactions through various regulatory processes, including

lending [95, 96]. However, the literature points out that certain

organizational barriers to establishing trust exist within ﬁnan-

cial industries, such as resistance to changing current ways of

distributing credit and the lack of standardization, and the un-

certainty regarding accountability, i.e., which party or parties

are ultimately responsible in any given transaction [94].

Another prominent sub-theme is connected to digital iden-

tity and the privacy-preserving elements of the associated trust

mechanism. 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 requirements, while also assisting banks and

regulators in forming a greater degree of institutional trust [91].

Furthermore, current research has demonstrated that the man-

ner 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 ﬁnancial industry. While blockchain technologies provide

a structure to increase transparency and security, the liter-

ature conﬁrms that accepting blockchain technology into an

organization must reach the appropriate balance between the

institution’s expectations regarding the reliability of the tech-

nology, the organizational readiness to use the technology, the

availability of clear laws and regulations related 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

regulations, laws, and institutional frameworks on the use

and adoption of blockchain technology in ﬁnancial institu-

tions. In theory, and according to the literature in this stream,

blockchain technology contributes to greater transparency, pro-

cess automation, and increased eﬃciency. 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 gov-

ernance issues related to blockchain applications and the use

of smart contracts are evolving. Many researchers point to nu-

merous areas where the mechanisms for creating automatically

enforced records conﬂict, as well as many unresolved issues

related to accountability, jurisdiction, and the enforceability

of programming-based agreements [97]. These challenges illus-

trate the diﬃculty of applying standard regulatory structures

to decentralized ﬁnancial systems.

Other important areas in this thematic cluster are compli-

ance and risks that may threaten the integrity of the ﬁnancial

system and the systemic risks of blockchain technology. The

use of blockchain technology for pseudonyms in ﬁnancial trans-

actions poses a potential dilemma for ﬁnancial regulators [73]

[99, 74]. The ease of creating anonymous accounts gives users

easier access to money laundering [98]. At the same time, tech-

nologies enabled by blockchain, such as automated reporting,

automated audit trails, and early warning systems, enhance

transparency and regulatory eﬀectiveness [100].

Additionally, studies indicate that regulatory approaches

are necessary to support blockchain technology innovations.

Regulatory sandboxes serve as to ols for managing the relation-

ship between innovation and risk through controlled testing,

contributing to opportunities for learning, public policy devel-

opment, and institutional adaptation [26]. Researchers are also

exploring ways to integrate regulation into decentralized ﬁnance

(DeFi) applications, emphasizing the need to incorporate gov-

ernance and compliance mechanisms into system design as a

means of mitigating the risks associated with decentralization

[59].

Finally, studies on central bank digital currencies (CB-

DCs) show how the introduction of blo ckchain technology has

prompted public authorities to develop hybrid governance mod-

els. Evidence from digital currency pro jects shows central

banks’ eﬀorts to combine technological advances with cen-

tralized oversight to achieve ﬁnancial stability objectives and

ensure the eﬀective 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, institu-

tional ﬂexibility, and adaptive governance. In all three areas,

the literature shows that sustainable governance of blockchain

technology requires a balance between providing an environ-

ment conducive to innovation, ensuring legal certainty for

consumers, and maintaining systemic ﬁnancial stability.

3.3.6. Cluster 6. Strategic Modernization of Banking

Business Model Enabled by Blockchain

This thematic cluster fo cuses on the role of blockchain as a

mechanism for modernizing conventional business models in

the banking industry, speciﬁcally as a type of strategic trans-

formation. While much research refers to blo ckchain for its

greater operational eﬃciency, the literature in this stream

points out that blo ckchain’s inﬂuence will create long-term

economic and social governance systems by creating new bi-

ases toward competition and allowing for entirely new ﬁnancial

service architectures.

The literature in this cluster collectively conceptualizes

blockchain technology as disruptive rather than complemen-

tary to existing systems and processes. This body of literature

recognizes that blockchain platforms disrupt the traditional

centralized structure 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 in-

termediary. Consequently, banks are under increased pressure

to reevaluate their strategic positioning, organizational struc-

ture, and competitive response to their evolving roles in the

digital ﬁnancial service environment [16, 37].

In addition, this cluster of research has further explored how

business model innovation driven by blockchain technology can

support ﬁnancial inclusion and global sustainable development.

Studies have identiﬁed ways in which blockchain can pro-

vide expanded access to ﬁnancial 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 beneﬁts 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, en-

compassing more than incremental process improvements. That

said, the ﬁndings also indicate that the eﬀect of blockchain on

banking ultimately depends on how well ﬁnancial institutions

use and integrate the new technology into their organiza-

tional strategies and adapt to achieve organizational compli-

ance 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 broaden-

ing primarily individual-level acceptance models (e.g., TAM,

UTAUT) and organization-centered readiness viewpoints (e.g.,

TOE, RBV) into a multi-tiered, ecosystem-based comprehen-

sion of blockchain dissemination in tightly regulated ﬁnan-

cial contexts. The bibliometric clustering demonstrates that

blockchain adoption in the banking sector is inﬂuenced not only

by technological preparedness or perceived value but also by

the interplay of regulatory legitimacy, institutional trust, cross-

organizational interoperability, and strategic resource manage-

ment throughout ﬁnancial networks. This observation reﬁnes

traditional technology adoption models by highlighting that

disruptive ﬁnancial technologies face diﬀusion constraints im-

posed by governance frameworks and regulatory compliance

demands, resulting in adoption pathways that are fundamen-

tally diﬀerent from those seen in cons-umer-oriented digital

technologies.

Additionally, the thematic evolution indicates a theoreti-

cal shift within the literature from initial techno-optimistic

narratives to analytical perspectives that focus on institu-

tional, risk-oriented, and governance issues. This progression

marks a shift from exploratory research on technology diﬀusion

to integrated frameworks that regard blo ckchain as a facil-

itator of organizational transformation rather than simply a

discrete operational tool. Therefore, this review presents a co-

hesive conceptual framework that incorporates technological,

organizational, regulatory, and ecosystem dynamics into a com-

prehensive explanatory model for blockchain-driven ﬁnancial

innovation.

By synthesizing bibliometric ﬁndings with qualitative the-

matic 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

ﬁndings suggest a strategic rethinking of blockchain as a tool

for organizational transformation rather than a mere digital up-

grade. 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 eﬃciency,

cost savings, and process automation imply that blockchain

should be viewed not just as a technological asset but also

as a driver of operational reorganization. Therefore, banking

managers are urged to re-evaluate current workﬂows and iden-

tify areas where distributed ledger technologies can optimize

accounting processes, enhance reconciliation accuracy, and de-

crease overhead expenses through smart contract automation

[55, 62].

Moreover, the ﬁndings stress the growing importance of se-

curity, transparency, and trust in modern banking practices.

With increasing cyber threats and regulatory compliance de-

mands, blockchain-based systems provide solutions for ensuring

data integrity, tracing audit trails, and automating contract en-

forcement. These features 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 ﬁnance (DeFi) and token-

based ecosystems indicates a fundamental shift in banking

business models. As a result, managers must look beyond incre-

mental enhancements to investigate new service architectures,

such as peer-to-peer intermediation platforms, blo ckchain-

enabled payment systems, and digital asset tokenization. This

shift requires innovation-driven leadership cultures, investment

in blockchain-related expertise, and strategic alliances with

ﬁntech developers to maintain a competitive advantage.

Lastly, the noted decrease in citation impact alongside in-

creasing publication volumes highlights the need for more prac-

tically oriented blockchain initiatives. Banking leaders must

connect blockchain adoption to clearly deﬁned institutional ob-

jectives, quantiﬁable performance metrics, and stepwise imple-

mentation strategies to ensure that investments yield tangible

beneﬁts rather than remaining symbolic or experimental.

In summary, these managerial implications illustrate that

the adoption of blockchain is primarily a challenge of leader-

ship, governance, 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 signiﬁcant beneﬁts

when it is integrated within regulatory and transactional frame-

works rather than operated as a standalone pilot initiative.

The most pronounced empirical focus in the literature p er-

tains to cross-border settlements and interbank transaction

clearing, where ineﬃciencies are still common. Incorporating

blockchain into these areas has the ability to speed up settle-

ment times, lower operational expenses, and reduce the risks of

fraud [26, 56, 60].

S. A. Aladeeb et al.

Concurrently, blockchain provides capabilities for automat-

ing regulatory processes and managing identities. Smart con-

tracts and decentralized identity systems can improve com-

pliance precision and operational transparency, yielding con-

siderable cost savings in fulﬁlling KYC, AML, and ﬁnancial

reporting requirements [80, 98]. Therefore, regulatory bodies

and ﬁnancial 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 microﬁnance platforms,

crowdfunding opportunities, and mobile-focused peer lending

initiatives[59, 85, 108]. Such models create avenues for under-

served communities to obtain ﬁnancial services without reliance

on traditional intermediaries. Implementation eﬀorts should,

therefore, prioritize areas with high rates of ﬁnancial exclusion,

particularly in emerging and developing economies. For tech-

nology developers and consulting agencies, the insights point

to key areas for development that include secure audit plat-

forms, green ﬁnance traceability systems, decentralized asset

management frameworks, and interoperable payment solutions.

Collaborative design partnerships with ﬁnancial institutions are

essential to ensure that technological models closely correspond

with sector-speciﬁc regulatory and operational needs.

Ultimately, the eﬀective implementation of blockchain in

the banking sector necessitates not only experimental adoption

but also ongoing institutional coordination that encompasses

regulatory dialogue, workforce education, governance adap-

tation, and strategic oversight. Thus, the full potential of

blockchain is realized 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 intellec-

tual 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 synthesis. The analysis of 389 peer-reviewed articles

highlighted distinct developmental stages—from initial concep-

tual exploration to thematic 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 progres-

sively inﬂuencing the empirical direction of the ﬁeld. 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 dis-

ciplinary knowledge: ﬁnancial intermediation and operational

eﬃciency, decentralized ﬁnance (DeFi) and cryptocurrencies,

convergence of blockchain technology, infrastructures for trust

and transparency, regulatory and governance frameworks, and

modernization strategies in banking. Together, these aspects

characterize blo ckchain as not just a standalone technological

ﬁx but as an integrated transformation platform that concur-

rently impacts organizational frameworks, regulatory systems,

and ﬁnancial ecosystems.

Although the volume of publications is on the rise, the

literature remains empirically scattered. Studies focusing on

large-scale industry adoption are limited, the interactions be-

tween blockchain and complementary technologies (such as AI

and IoT) are insuﬃciently theorized, and long-term evaluations

of ﬁnancial stability and systemic 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 oﬀers

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 process inﬂuenced by regulatory legitimacy, orga-

nizational governance, and ecosystem interoperability, rather

than merely a technical event. This integrative view distin-

guishes the current review from previous bibliometric analyses

because it clearly articulates the causal relationships connect-

ing our validated knowledge structure to the broader agenda

of organizational transformation, regulatory alignment, and

strategic value creation in ﬁnance.

As a result, this study provides a cohesive theoretical

groundwork for future empirical research and oﬀers practi-

cal 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 deﬁning

possible areas for future research is crucial. These research di-

rections are derived from existing literature and reﬂect the gaps,

constraints, and prospects identiﬁed by previous researchers.

Existing studies have identiﬁed that blockchain has the po-

tential to transform operational processes in the banking sector

for greater eﬀectiveness, ﬁnancial inclusion, and decentralized

ﬁnance (DeFi), as well as to completely modernize business

models [55, 81, 86]. However, serious issues remain regard-

ing 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 reﬂecting both conceptual and

practical priorities. These directions provide a research map

for charting blockchain scholarship and positioning policymak-

ers, ﬁnancial institutions, 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 related to ﬁnance, management, and in-

formation 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 publi-

cations, 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 pub-

lications at the cutoﬀ time of the ﬁnal submission, which could

slightly aﬀect the bibliometric results. The study only used

VOSviewer to map and visualize bibliometric networks. Al-

though VOSviewer is a popular tool, other tools, such as Gephi

or CiteSpace, could have been used to provide additional biblio-

metric 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 applications. Despite its limitations, the research

provides a preliminary examination of the intellectual struc-

ture and thematic history of blockchain research in the banking

sector.

Ethical Statement

No ethical approval was required for this study, as it did not

involve human or animal subjects.

Funding

This research received no speciﬁc grant from any funding

agency in the public, commercial, or not-for-proﬁt sectors.

Declaration of competing interests

The authors declare that they have no known competing ﬁnan-

cial interests or personal relationships that could have appeared

to inﬂuence the work reported in this article. Moreover, they

assert that no conﬂicts 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 accuracy and integrity after utilizing these

tools/services and are fully resp onsible for the ﬁnal version of

the manuscript.

Data Availability Statement

The bibliometric dataset supporting the ﬁndings of this study,

including the Scopus CSV ﬁle 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,

Methodology, Data curation, Formal analysis, Investigation,

Visualization, Writing – original draft & Editing. [Fatima Zohra

Sossi Alaoui]: Supervision, Validation, review & editing.

S. A. Aladeeb et al.

Table 10. Blockchain Themes and Future Research Directions in Banking.

No.Cluster Theme Future Research Directions References

1 Blockchain Ap-

plications for

Transforming

Banking Opera-

tions and Financial

Intermediation

• Carry out comparative empirical research assessing the eﬀects of smart contracts on

transaction settlement durations and op erational costs in various banks.

• Create process-mapping models to quantify the reduction of reconciliation steps in

interbank clearing attributable to blockchain (utilizing Business Process Mo del and

Notation “BPMN” and time–motion analysis).

• Perform cross-country econometric evaluations to determine how blockchain-based re-

mittance solutions impact transfer expenses and delivery times in developing compared

to developed nations.

• Employ UTAUT2 or TOE frameworks to pinp oint the factors inﬂuencing blockchain

adoption in retail versus corp orate banking sectors.

• Employ UTAUT2 or TOE frameworks to pinp oint the factors inﬂuencing blockchain

adoption in retail versus corp orate banking sectors.

• Conduct case studies in low-income nations to uncover obstacles to scalability, interop-

erability, and institutional integration.

[56],[61, 62],

[77],[79], [103],[105]

2 Decentralized Fi-

nance (DeFi) and

Cryptocurren-

cies Enabled by

Blockchain

• Model contagion and systemic risks within DeFi ecosystems through network analytics

and simulation metho dologies (e.g., agent-based modeling).

• Conduct studies on regulatory impacts, comparing the eﬀectiveness of various legal

frameworks in mitigating fraud and protecting consumers in DeFi lending platforms.

• Conduct studies on regulatory impacts, comparing the eﬀectiveness of various legal

frameworks in mitigating fraud and protecting consumers in DeFi lending platforms

• Evaluate the inﬂuence of DeFi credit markets on the liquidity, proﬁtability, and risk

parameters of commercial banks.

• Carry out behavioral studies to examine how cultural diﬀerences shap e motivations for

adopting cryptocurrencies (speculation versus utility).

[81–83],[85–87]

3 Blockchain as an

Enabler of Digital

and Financial Tech-

nology Convergence

• Design and evaluate blockchain–IoT prototypes for real-time Know Your Customer

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

• Assess the eﬀectiveness 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 partner-

ship with banks to gauge improvements in onboarding eﬃciency and KYC compliance.

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

4 Trust-Related

Dimensions in

Blockchain-Based

Banking

• mixed-methods surveys and interviews to evaluate the impact of human trust and or-

ganizational culture on blockchain adoption within banks.

• Establish a standardization readiness index to evaluate how system compatibility,

legacy systems, and regulations impede blo ckchain integration.

• Design blockchain-based credit scoring prototypes and assess their eﬀectiveness in di-

minishing information asymmetry in SME lending.

• Implement longitudinal studies to track how increased transparency through blockchain

inﬂuences customer trust over time.

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

5 Regulatory, Legal,

and Institutional

Frameworks for

Blockchain Gover-

nance

• Propose and evaluate blockchain-enabled AML/CFT (Countering the Financing of

Terrorism) monitoring systems and measure their detection accuracy compared to tra-

ditional systems.

• Examine the eﬃcacy of regulatory sandboxes by monitoring innovation outputs

(patents, pilots, startups) preceding and following sandbox involvement.

• Develop automated reporting and cryptographic proof systems for embedded supervi-

sion models in DeFi.

• Analyze real-world CBDC pilot projects (e.g., e-CNY) to gauge privacy risks, transac-

tion speeds, and impacts on monetary policy using macro-ﬁnancial models.

[26],[59],[97],[98],[101]

6 Strategic Mod-

ernization of

Banking Business

Model Enabled by

Blockchain

• Employ scenario analysis to illustrate how blockchain inﬂuences competition between

neobanks and traditional banks.

• Perform studies on the eﬀects of ﬁnancial inclusion by evaluating blockchain-based

microﬁnance initiatives in rural or underserved areas.

• Chart out policy, infrastructure, and institutional elements that contribute to success-

ful blockchain-driven transformation using the PESTEL (Political, Economic, Social,

Technological, Environmental, and Legal) framework and multi-country case research.

[16],[37],[102]

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