59
Finance, Accounting and Business Analysis
Volume 8 Issue 1, 2026
http://faba.bg/
ISSN 2603-5324
DOI:
https://doi.org/10.37075/FABA.2026.1.06
Blockchain Applications in Occupational Fraud Prevention: A
Structured Literature Review
Praise Mutoko
1*
, Ephraim Monde Faku
2
Tshwane University of Technology, Pretoria, South Africa
1
Tshwane University of Technology, Soshanguve, South Africa
2
* Corresponding author
Info Articles
Abstract
History Article:
Submitted 23 September 2025
Revised 12 April 2026
Accepted 8 May 2026
Purpose: The purpose of this study is to examine how blockchain
technology can mitigate occupational fraud in financial service
enterprises within emerging markets, with a particular focus on mid-
sized institutions in South Africa.
Design/Methodology/Approach: A systematic literature review was
conducted using Scopus and ScienceDirect databases. Peer-reviewed
articles published between 2016 and 2025 were selected through
predefined inclusion and exclusion criteria. The review followed
PRISMA 2020 guidelines, and thematic analysis was applied to
synthesise findings from 36 studies.
Findings: The review revealed that weak internal controls continue to
drive occupational fraud, especially corruption, asset misappropriation,
and financial statement fraud. Blockchain offers advantages such as real-
time auditability and improved transaction traceability. However,
regulatory uncertainty, integration costs, and heightened cybersecurity
requirements remain barriers to widespread adoption.
Practical Implications: The findings suggest that blockchain can
complement existing fraud risk management systems by enhancing
organisational transparency, accountability, and operational resilience.
Financial service providers in emerging markets can benefit from
integrating blockchain within context-specific regulatory and
technological frameworks.
Originality/Value: This study contributes to the growing body of
knowledge on blockchain and fraud prevention by focusing on its
applicability to financial institutions in emerging economies. In this
context, empirical research remains limited.
Paper Type: Research Paper
Keywords:
Occupational Fraud;
Blockchain Technology;
Auditing; Company
Finance; Financial
Enterprises
JEL: M4, O3, G3
*
Address Correspondence:
E-mail: praisemutoko84@gmail.com
1
FakuEM@tut.ac.za
2
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INTRODUCTION
Occupational fraud is a significant problem across financial service organisations worldwide,
including in emerging economies such as South Africa. Occupational fraud refers to fraudulent acts by
insiders or employees within an organisation, including the misappropriation of assets, corrupt practices,
and account manipulation (Association of Certified Fraud Examiners(ACFE) 2022). These unethical
behaviours not only reduce the operating effectiveness of financial firms but also lower investor confidence,
hindering sustainable growth and economic progress (PwC 2022). The current extended abstract provides
detailed reviews of the available literature that examines the drivers, characteristics, and consequences of
occupational fraud in financial services firms, particularly in South Africa. In addition, this article discusses
the role that blockchain technology can play as an agent in changing the design of fraud prevention practices
in such organisations. Accordingly, this study is guided by the following research question: What is the role
of blockchain technology in disrupting occupational fraud in financial service enterprises?. Blockchain
technology can serve as an agent that changes how fraud-prevention practices are designed within such
organisations. Accordingly, this study is guided by the following research question: What is the role of
blockchain technology in disrupting occupational fraud in financial service enterprises?
LITERATURE REVIEW
A review of the current literature includes numerous studies on occupational fraud in financial
institutions, which highlight issues such as asset misappropriation, corruption, and fraudulent financial
reporting. The literature indicates that internal control flaws, a lack of effective corporate governance
structures, and a poor understanding of fraud risks are significant determinants of fraudulent acts (Alagha
and Özçelik 2025; Byeon et al. 2025). Moreover, resource shortages, coupled with the volatile nature of
financial markets, often make traditional, resource-intensive anti-fraud initiatives such as audits and
regulatory announcements less effective against the ever-changing nature of fraud (ACFE 2022).
The lack of effective deterrents promotes an environment of impunity, which in turn leads to the
spread of fraudulent schemes and undermines trust in the sector (Singh et al. 2025). In this assessment, the
Fraud Triangle model is used, which outlines three key factors leading to occupational fraud: pressure,
opportunity, and rationalisation (Cressey 1953). The model is used as a basis for considering how
weaknesses in organisational structure, ineffective governance arrangements, and unhelpful regulatory
climates create an environment in which fraudulent activity is prone to occur.
Understanding financial services
Financial services businesses are essential to the world economy. They offer crucial financial
management systems and products, such as banking, insurance, investments, and financial technologies
(fintech). These businesses facilitate everything from small-scale financial infrastructure, such as stock
markets and international payments, to larger-scale operations, such as savings and loans. Because of their
significance, they are intricately linked to trust, development, and economic stability.
Definitions of financial services enterprises appear neither uniform nor fully articulated. In South
Africa, several studies extend conventional SME classifications. Fatoki (2014) defines medium-sized
financial enterprises by employee count (2–50 employees). Koppeschaar (2012) uses an IFRS for SMEs
framework, while Stainbank (2010) grounds the definition in corporate legal reforms. Other South African
studies omit explicit criteria.
Internationally, variations emerge in sector-specific practice. Mwega (2011) categorises banks as
small, medium, or large based on size and competitiveness, and Pearce and Helms (2001) define financial
services associations as shareholder-based entities operating at a community level. Beck and Cull (2014)
offer broader perspectives, with no detailed criteria, leaving definitions implicit.
Collectively, the studies indicate that definitions rely on general SME frameworks, supplemented in
some cases by sector-specific adjustments, rather than on clear financial thresholds or uniform size criteria.
For this study, Medium-sized financial services companies will use the definition by Fatoki (2014), which is
a range of 2-50 people.
Financial services firms are frequently targets of fraud, embezzlement, and cybercrime due to their
significance. The stakes are enormous not only for the businesses but also for the people and economies that
rely on them. They are, therefore, a crucial area of study for security and fraud prevention.
According to recent studies, blockchain technology can be used to detect fraudulent activity and
improve the security of financial transactions. For instance, Sen et al. (2024) solve a fundamental problem
in fraud prevention by introducing a blockchain-based federated learning system that identifies fake data in
financial contexts. Khan et al. (2025) propose a blockchain forensic approach that enhances traceability and
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evidence preservation in financial organisations, with a focus on preventing loan scams through blockchain
technology.
Recent research indicates that blockchain technology can be applied to enhance the security of
financial transactions and identify fraudulent conduct. For example, Nair and Rao (2025) introduce a
blockchain-based federated learning system that detects fraudulent data in financial contexts, thereby
resolving a key issue in fraud prevention. Vasudevan et al. (2025), who focus on financial crime
investigations involving embezzlement, suggest a blockchain forensic technique that enhances traceability
and evidence preservation in financial institutions.
Occupational Fraud in Financial Services
Occupational fraud is defined as the misuse of one’s role within an organisation for personal gain
through the deliberate misapplication of resources or assets. This continues to evolve in complexity as
financial systems become more digitised (Association of Certified Fraud Examiners 2022). For this study,
the focus will be on Corruption, Asset Misappropriation, and Financial Statement Fraud.
Corruption
Fraud in financial services continues to undermine institutional integrity, with corruption among the
most prevalent forms of occupational fraud. As defined by the ACFE (2022), corruption involves employees
abusing their positions of trust for personal gain, typically through bribery, conflicts of interest, or
embezzlement. Okewale et al. (2025) emphasise that corruption is deeply embedded in operational systems,
particularly within financial services institutions, and therefore necessitates context-specific internal control
mechanisms. Similarly, Byeon et al. (2025) argue that integrating governance, risk management, and
compliance (GRC) systems supported by high-quality internal audits and strong leadership can significantly
enhance the detection and prevention of corruption within state-owned enterprises.
Alagha and Özçelik (2025) extend the conversation to insider fraud in the UK policing system,
revealing that corruption and asset misappropriation remain dominant due to systemic oversight
weaknesses. In the South African context, the Financial Intelligence Centre (2024) and the National Money
Laundering Risk Assessment (2024) highlight ongoing risks, including the misuse of shell companies and
illicit financial flows, which disproportionately affect SMEs. These challenges are compounded by limited
access to affordable finance (Zarpala and Casino 2021) and persistent energy infrastructure issues, which,
according to Kroon et al. (2021), create regulatory blind spots and foster environments conducive to
corruption.
Asset Misappropriation
Asset misappropriation is widely recognised as the most common form of occupational fraud
globally, involving schemes where employees steal or misuse an organisation’s resources for personal benefit
(ACFE 2022). The Association of Certified Fraud Examiners reports that this category accounts for 86% of
occupational fraud cases worldwide. However, it typically results in lower financial losses per incident than
corruption or financial statement fraud. Nonetheless, its frequency makes it a critical concern, particularly
in emerging economies such as South Africa.
This type of fraud includes a range of activities such as payroll fraud, cash theft, billing schemes,
skimming, inventory theft, and expense report falsification (Wells 2017). In South Africa, independent audits
by leading professional services firms such as PwC, Deloitte, EY, and KPMG have highlighted that medium-
sized financial enterprises remain vulnerable to these schemes. The challenges are often linked to inadequate
internal controls, insufficient segregation of duties, and governance weaknesses, which create opportunities
for occupational fraud to flourish (PwC 2022).
Multiple studies have highlighted the structural and behavioural drivers of asset misappropriation and have
identified poor internal controls, collusion, lack of oversight, and weak ethical cultures as major contributors.
In South Africa, high unemployment, poverty, and social inequality. This is compounded by lax
enforcement and delayed prosecution, which reduce deterrence and increase vulnerability to internal fraud
(Transparency International 2025: Ziorklui, Nwachukwu, and Okafor 2024).
Globally, asset misappropriation is not limited to poorly governed sectors. Zhang et al. (2025) note
that even in highly regulated environments, small and medium-sized enterprises (SMEs) often fall victim
due to informal processes and over-reliance on trust. Similarly, Khan et al. (2021) stress that in local
government contexts, without tailored internal control systems, such fraud remains difficult to detect and
prevent
Despite these developments, a significant challenge persists in the uneven application of anti-fraud
measures. Under-resourced entities, such as non-profits and SMEs, often lack skilled personnel, robust audit
systems, or sufficient donor support to implement effective fraud mitigation strategies. This leaves them
exposed to long-term undetected losses, with broader implications for economic stability and organisational
sustainability.
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Financial Statement Fraud
Though less common than other types of fraud, financial statement fraud (FSF) causes the highest
financial losses, with median losses nearing $1 million and typical durations extending to 18–24 months
(ACFE 2022). FSF involves intentional misrepresentation to mislead stakeholders and is particularly
prevalent in finance and operations departments (Mongwe and Malan 2020). Its impact on investor
confidence and corporate sustainability has led to growing academic interest.
Research highlights motivations such as meeting financial targets and personal gain, often
underpinned by Cressey’s (1953) Fraud Triangle: pressure, opportunity, and rationalisation. This framework
remains relevant across contexts (Homer 2020). South African studies, such as those by Mongwe and Malan
(2020), emphasise additional contextual drivers, such as weak oversight and structural gaps in governance.
The consequences of FSF include financial collapse, reputational damage, and erosion of market
trust, as seen in cases like Enron, WorldCom, and Steinhoff (Mongwe and Malan 2020). Traditional
controls, such as audits and segregation of duties, are proving insufficient against complex fraud schemes.
Thus, attention has shifted toward machine learning (ML) techniques, such as artificial neural networks,
support vector machines, and autoencoders, which can identify anomalous patterns in financial data
(Mongwe and Malan 2020).
Global studies continue to explore the broader determinants of financial statement fraud. For example
Ding, Huang and Wang (2022) find that greater gender diversity in leadership correlates with lower
incidence of financial statement fraud. Indiraswari, Subekti and Rosidi (2025) link financial distress with a
higher risk of FSF, while ACFE (2022) highlights that although FSF occurs less frequently than other types
of occupational fraud, the financial losses it causes can be significantly larger. Shanikat and Aldabbas (2025)
further confirm that strong corporate governance practices play a critical role in reducing fraud risk,
especially in emerging markets. While AI-driven tools show promise in fraud detection, their success in
South Africa hinges on contextual adaptation, and research must prioritise accessible, interpretable systems
compatible with local constraints to bridge the gap between innovation and real-world application (Sreenu
and Verma 2024).
Theoretical Framework
Source: (Fraud Conference News 2026)
Figure 1. The Fraud Triangle
Recent research has deepened our understanding of occupational fraud by exploring its root causes,
the environments in which it thrives, and strategies to prevent it. A cornerstone in this field is Cressey’s
Fraud Triangle, which explains fraud as arising when pressure, opportunity, and rationalisation come
together. However, Tickner et al. (2021) challenge the model’s practical value, arguing that while it is helpful
as a basic framework, its simplicity may fall short in capturing the complex dynamics of real-world fraud
cases.
Studies have also shown that cultural and contextual factors significantly shape how occupational
fraud manifests. Chung et al. (2021), drawing on Hofstede’s cultural dimensions, reveal that national culture
influences both the likelihood and impact of fraud. Their work suggests that any effective fraud prevention
strategy must take cultural norms and values into account. In a related study, Darsono et al. (2024) explore
how the COVID-19 pandemic intensified fraud risks in the Financial Services sector, showing that factors
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such as pressure, opportunity, rationalisation, and capability interacted in new ways, particularly by enabling
asset misappropriation.
Organisational context plays a key role. Bruwer and Petersen (2022) examine South African SMMEs
and find that perceptions of fraud risk are closely tied to management practices and financial stability. Their
research underscores the role of leadership awareness in building fraud-resistant organisations. Similarly,
Bakar et al. (2023) report that in Malaysian SMMEs, strong internal controls, an ethical corporate culture,
and fraud awareness significantly reduce the likelihood of occupational fraud, supporting the idea that
governance and ethical leadership are vital in limiting opportunities for fraud.
METHODS
This research utilised a systematic literature review (SLR) methodology to investigate how the
adoption of sustainable technologies influences business growth and long-term sustainability in emerging
markets. To maintain a clear and rigorous review process, the study followed the Preferred Reporting Items
for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, which offer a standardised framework
for ensuring transparency, consistency, and completeness in reporting systematic review findings (Page et
al. 2021; Sarkis-Onofre et al. 2021).
Search Strategy
This study conducted a comprehensive literature search across Scopus and ScienceDirect, chosen for
their comprehensive indexing of high-quality, peer-reviewed literature across multidisciplinary fields
relevant to this study, including technology, finance, and business. The Boolean queries that were
implemented, respectively, were:
Blockchain AND Fraud AND Financial AND Service AND NOT Health AND
NOT Cryptocurrency AND NOT AI AND NOT Supply Chain
Blockchain AND Technology AND Financial Services NOT Supply Chain NOT Cryptocurrency
NOT Healthcare
The Boolean NOT was used in the research to refine and specify the kinds of research most suitable
for the current study, having observed that the most common areas of research were blockchain within the
supply chain and the cryptocurrency space. The time frame was restricted from 2016 to 2025, reflecting
Scopus’s availability from 2016 onward and the marking period when blockchain began gaining traction
beyond cryptocurrencies and was increasingly explored in business and finance contexts. Diagram 1 below
summarises the search:
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Figure 2. Search Strategy Diagram
Eligibility Criteria
To maintain methodological rigour and thematic focus, this review included a mixture of empirical
and conceptual peer-reviewed studies relevant to blockchain applications in occupational fraud prevention.
The following criteria were applied:
Inclusion:
• Peer-reviewed systematic, narrative, or integrative reviews addressing blockchain, fraud
detection/prevention, and business/enterprise applications.
• Empirical studies (e.g., case studies, experiments);
• Conceptual, editorial, or opinion pieces;
• Indexed in Scopus and Science Direct
• Published in English between 2016 and 2025.
Exclusion:
• Grey literature (e.g., white papers, blogs);
• Studies not addressing the intersection of blockchain, fraud, and business;
• Duplicate records or papers with inaccessible full text.
Study Selection and PRISMA Flow
The initial queries returned 106 records. After removing duplicates, titles, and abstracts underwent
screening, resulting in 36 full-text reviews. Ultimately, 36 articles met the inclusion criteria. This process
follows the four-stage PRISMA flow: Identification, Screening, Eligibility, and Inclusion.
Data Extraction and Synthesis
Data were extracted into a structured matrix covering author(s), year, review type, blockchain
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application, fraud focus, business context, methodology, and key findings. The data synthesis adopted
thematic analysis to identify patterns, research gaps, and practical implications for financial services
enterprises.
Risk of Bias and Quality Assessment
In alignment with PRISMA 2020 recommendations (Page et al., 2021), this review assessed potential
bias and methodological quality across the included studies. However, given that the review exclusively
included secondary research, namely, systematic, narrative, and integrative literature reviews. Formal
critical appraisal tools such as AMSTAR 2 or ROBIS were not systematically applied.
To mitigate bias, the review applied a series of safeguards. First, inclusion was limited to peer-
reviewed articles indexed in Scopus and ScienceDirect, databases known for their comprehensive and
quality-controlled indexing (Singh et al. 2020). This ensured that only studies with a minimum standard of
academic rigour were evaluated. Second, grey literature, opinion pieces, and conceptual papers were
excluded to minimise subjectivity and unsupported assertions.
While formal scoring was not conducted, articles were screened for methodological transparency, the
depth of analysis, and relevance to the core themes of blockchain and occupational fraud. Similar to the
approach recommended by Sarkis-Onofre et al. (2021), the clarity of the review objectives informed the
thematic synthesis, the use of structured data collection or synthesis frameworks, and the relevance to fraud
prevention in financial service enterprises.
Nevertheless, this approach does not eliminate all sources of bias. Publication bias may still exist,
particularly in favour of reviews reporting successful blockchain implementations. Additionally, language
restrictions (English-only) and database limitations could lead to the exclusion of regionally significant
literature, particularly from non-English speaking emerging markets (Visser et al. 2020).
Future reviews should consider applying structured critical appraisal tools to increase transparency
and facilitate reproducibility. Moreover, integrating empirical studies could provide deeper insights into the
effectiveness of real-world blockchain implementations in fraud prevention.
Limitations
This study relies on the Scopus and ScienceDirect databases, which, although comprehensive and
multidisciplinary, may omit domain-specific or emerging literature indexed in other databases such as IEEE
Xplore or Google Scholar. As a result, relevant publications outside Scopus and Science Direct’s indexing
criteria, particularly in the fields of blockchain engineering or forensic accounting, may have been excluded.
Additionally, only English-language articles were considered, potentially excluding valuable regional
studies, especially from non-English-speaking countries that may offer context-specific insights into fraud
and blockchain adoption.
A further limitation stems from the decision to include only review articles. While this approach
ensures conceptual breadth and synthesised findings, it excludes empirical studies and case-specific
implementations that could provide practical insights into real-world fraud detection systems in financial
enterprises. This may limit the granularity of insights into operational, technological, or regional
implementation challenges.
To mitigate some of these constraints, backwards and forward citation tracking was employed where
applicable to identify influential works that might have been missed in the initial search.
RESULTS AND DISCUSSION
The study outlines several key factors that cause occupational fraud in financial institutions, and there
are various ways of dealing with the issues as discussed below:
Weak Internal Controls
Many organisations continue to rely on internal audit and control systems that are fragmented or
insufficiently integrated into digital transaction environments, limiting their effectiveness in detecting and
preventing fraud in a timely manner (Alagha and Özçelik 2025). Prior research emphasises that fraud risk
management (FRM) fundamentally depends on the design and enforcement of robust internal control and
assurance mechanisms, particularly in technology-driven financial systems (Turker and Bicer 2020; Nathan
and Jacobs 2020). In this context, audit trails, continuous monitoring, and system-level accountability
mechanisms play a critical role in strengthening organisational oversight and governance (Alagha and
Özçelik 2025; Albaroodi and Anbar 2025).
However, as financial transactions become increasingly digital and decentralised, traditional control
mechanisms alone are often inadequate. Recent studies show that fraud in blockchain-enabled and fintech
environments increasingly manifests through smart contracts, transaction manipulation, and system-level
vulnerabilities, which require more advanced, technology-enabled detection approaches (Zarpala and
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Casino 2021; Liu et al. 2022; Nikkel 2020). This has shifted FRM from a purely procedural control function
toward a more data-driven and forensic-oriented discipline embedded within digital financial infrastructures
(Zarpala and Casino 2021; Liu et al. 2022).
Within this evolving landscape, blockchain-based systems are increasingly viewed as a structural
enhancement to internal control environments due to their immutability, transparency, and auditability,
which strengthen both preventive and detective controls (Turker and Bicer 2020; Nathan and Jacobs 2020).
Nevertheless, adoption and effective use of such technologies remain uneven across financial institutions
and enterprises, particularly in emerging and developing contexts, where organisational, technical, and
governance barriers persist (Neves et al. 2023; Jha and Dangwal 2024). This reinforces the need to view
fraud risk management not only as a control function, but as an integrated socio-technical system combining
governance, auditing, and digital infrastructure design.
Blockchain As a Disruptive Force
Given the limitations inherent in conventional anti-fraud mechanisms, the literature increasingly
positions blockchain technology as a structural departure from traditional control and assurance models in
financial systems. Across studies, blockchain-based infrastructures are shown to offer key features such as
transparency, immutability, and decentralised verification, which strengthen the reliability, traceability, and
auditability of financial records and significantly constrain the possibility of undetected data manipulation
(Turker and Bicer 2020; Nathan and Jacobs 2020; Alagha and Özçelik 2025; Singh et al. 2025). These
characteristics enhance both the credibility of financial transactions and the integrity of accounting
information by embedding verification mechanisms directly into transaction processes (Turker and Bicer
2020; Nathan and Jacobs 2020).
From a fraud risk management perspective, the reviewed literature indicates that the ability of
blockchain to provide a permanent, auditable, and shared ledger makes it particularly suitable for addressing
problems related to fraudulent misrepresentation, corruption, and asset misappropriation in digital financial
environments (Zarpala and Casino 2021; Liu et al. 2022; Vasudevan et al. 2025; Okewale et al. 2025).
Several studies further suggest that blockchain should not be viewed as a substitute for governance and
internal control systems, but rather as a technological layer that reinforces their effectiveness by embedding
accountability and verifiability directly into financial infrastructures (Turker and Bicer 2020; Nathan and
Jacobs 2020; Albaroodi and Anbar 2025).
Empirical and design-oriented contributions also illustrate the practical relevance of these arguments.
For example, Khan and Ahmad (2025) demonstrate how blockchain can be integrated with Internet of
Things technologies in loan-processing environments to reduce document manipulation, identity fraud, and
internal interference. Similarly, Vasudevan et al. (2025) and Trivedi (2023) show that blockchain-based
frameworks for cheque processing and document verification enhance the integrity of transactional records
and reduce opportunities for occupational fraud. Studies focusing on anomaly detection and forensic
analysis further indicate that blockchain environments support more effective, technology-enabled fraud
detection mechanisms when combined with advanced analytics and monitoring techniques (Liu et al. 2022;
Sen et al. 2025; Nikkel 2020; Zarpala and Casino 2021).
More broadly, the literature suggests that as financial systems become increasingly digital and
interconnected, fraud risk management must evolve from predominantly procedural control mechanisms
toward integrated, technology-enabled, and forensic-oriented architectures embedded within transaction
infrastructures (Nikkel 2020; Zarpala and Casino 2021; Liu et al. 2022; Hyvärinen et al. 2017). However,
adoption remains uneven, particularly in emerging and developing contexts, where organisational,
governance, and capability constraints continue to shape the uptake and effective use of such technologies
(Neves et al. 2023; Jha and Dangwal 2024; Byeon et al. 2025).
Benefits and Challenges in Implementing Blockchain Technology for Fraud Prevention
The literature consistently identifies blockchain technology as a potentially transformative tool in the
fight against fraud in financial enterprises, particularly in environments where traditional internal control
systems are fragmented or insufficiently adapted to digital transactions. At a foundational level, blockchain
provides a decentralised, transparent, and immutable ledger that reduces opportunities for data tampering,
record manipulation, and unauthorised transaction modification (Turker and Bicer 2020; Nathan and Jacobs
2020; Singh et al. 2025). Through distributed consensus mechanisms and the use of smart contracts,
blockchain-based systems can automate transaction execution and embed compliance rules directly into
financial processes, thereby reducing reliance on intermediaries and limiting opportunities for internal
interference and collusion (Turker and Bicer 2020; Langaliya and Gohil 2021; Xiong and Wan 2023).
From a fraud risk management perspective, the reviewed studies indicate that blockchain’s capacity
to generate permanent, auditable, and shared transaction records is particularly valuable for addressing
fraudulent misrepresentation, asset misappropriation, and financial manipulation in digital environments
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(Zarpala and Casino 2021; Liu et al. 2022; Vasudevan et al. 2025; Okewale et al. 2025). Several applied
studies demonstrate that blockchain-based systems enhance both preventive and detective controls by
strengthening traceability, reducing document tampering, and improving the reliability of transaction
evidence (Rajasekaran et al. 2024; Vasudevan et al. 2025; Khan and Ahmad 2025). In addition, research
focusing on forensic and analytical applications shows that blockchain infrastructures support more effective
post-incident investigation and continuous monitoring through immutable audit trails and technology-
enabled anomaly detection mechanisms (Nikkel 2020; Zarpala and Casino 2021; Liu et al. 2022; Sen et al.
2025).
However, the literature also highlights a number of significant challenges associated with the adoption
of blockchain for fraud prevention in financial enterprises. One recurring concern relates to technical
complexity, security vulnerabilities, and infrastructure risks within blockchain-based systems themselves.
Albaroodi and Anbar (2025) note that weaknesses in blockchain cloud infrastructure, governance
configurations, and access controls can expose organisations to new categories of operational and security
risk if not properly managed. Similarly, Hyvarinen et al. (2017) emphasise that while blockchain-enhanced
architectures improve fraud detection capabilities, their effectiveness depends heavily on the quality of
system integration, data governance, and cybersecurity controls embedded within the broader digital
ecosystem.
Beyond technical considerations, organisational and adoption-related barriers also constrain the
realisation of blockchain’s fraud prevention potential. The literature on digital financial services and fintech
adoption suggests that many financial institutions, particularly in emerging and developing contexts, face
limitations related to skills, governance capacity, regulatory uncertainty, and implementation readiness
(Neves et al. 2023; Jha and Dangwal 2024; Byeon et al. 2025). These constraints contribute to uneven uptake
and partial implementations that may weaken the expected control and assurance benefits of blockchain-
based systems.
Taken together, the reviewed studies suggest that while blockchain offers substantial advantages for
strengthening fraud prevention, detection, and forensic investigation in financial enterprises, its effectiveness
is contingent upon complementary investments in governance, cybersecurity, system design, and
organisational capability. Blockchain should therefore be viewed not as a standalone solution, but as a
component of a broader, integrated fraud risk management and digital control architecture (Nakashima
2018; Bibi et al. 2024; Alagha and Özçelik 2025).
An outlook on the Complex Digital Ecosystem
Fraud risk in modern financial enterprises exists within a complex digital ecosystem rather than as a
simple internal control problem. Financial systems increasingly rely on interconnected platforms, automated
decision-making, and data-driven infrastructures, which expand both the scale and sophistication of
potential fraud (Cosma 2023; Tian 2021; Arenas-Parra 2024).
Advanced technologies are reshaping financial operations. Robo-advisory systems and large-scale
data analytics improve efficiency but also create model risk, opacity, and governance challenges (Arenas-
Parra 2024; Cosma 2023; Tian 2021; Dar et al. 2024). Digital platforms such as crowdfunding and Islamic
social finance expand access while introducing opportunities for misrepresentation, information asymmetry,
and regulatory gaps (Ng and Kwok 2017; Jha and Dangwal 2024; Ghosh 2024).
Technological infrastructures are becoming more distributed and interdependent. Cloud computing,
federated learning, and edge-based systems change accountability and complicate oversight (Yan et.al 2021;
Jannat 2025; Zhang 2024). Emerging risks such as quantum computing and data marketplaces threaten
security, transparency, and auditability (Baseri 2024).
These trends show that fraud risk is a systemic, socio-technical challenge. Blockchain, forensic tools,
and audits are important but represent only one layer within a broader, digitally transformed financial
environment (Tian 2021; Cosma 2023; Arenas-Parra 2024; Jannat 2025).
Discussion
The reviewed literature increasingly frames blockchain-based and digital financial technologies as
components of a broader transformation of financial control, governance, and fraud risk management
architectures. Across studies, blockchain is not presented as a standalone solution, but rather as part of an
integrated socio-technical framework that combines transaction infrastructure, audit mechanisms,
governance arrangements, and organisational capability (Turker and Bicer 2020; Nathan and Jacobs 2020;
Alagha and Özçelik 2025; Singh et al. 2025). At the same time, the literature emphasises that realising these
benefits requires simultaneous attention to system integration, governance design, and regulatory alignment
within financial institutions (Albaroodi and Anbar 2025; Byeon et al. 2025).
Although blockchain and fintech technologies are widely discussed as tools for improving
transparency, data security, and fraud prevention, evidence from the reviewed studies suggests that adoption
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remains uneven and often fragmented, particularly in emerging and developing contexts. Research on digital
financial services and fintech adoption highlights persistent barriers related to organisational readiness,
regulatory uncertainty, skills constraints, and implementation complexity, which limit large-scale, systemic
deployment within financial sectors (Neves et al. 2023; Jha and Dangwal 2024; Ghosh 2024). Consequently,
many implementations remain pilot-oriented, experimental, or confined to specific use cases rather than
embedded as core components of financial infrastructure (Byeon et al. 2025; Singh et al. 2025).
At the same time, applied and design-oriented studies within the corpus demonstrate that where
blockchain is deployed, it is most often in targeted contexts such as document verification, cheque
processing, loan administration, and transaction validation, rather than as a fully integrated enterprise-wide
control architecture (Vasudevan et al. 2025; Rajasekaran et al. 2024; Khan and Ahmad 2025; Aracil et al.
2025). These applications nevertheless provide important evidence of blockchain’s capacity to strengthen
auditability, reduce record manipulation, and improve the reliability of transaction evidence within specific
operational domains (Turker and Bicer 2020; Nathan and Jacobs 2020; Okewale et al. 2025).
From a theoretical and control perspective, the literature consistently underscores the continuing
importance of internal control systems, audit functions, and governance structures as the foundation of fraud
risk management, even in technologically advanced environments (Turker and Bicer 2020; Nathan and
Jacobs 2020; Alagha and Özçelik 2025). However, as financial processes become increasingly digital and
platform-based, traditional procedural controls are shown to be insufficient on their own. Instead, effective
fraud risk management is increasingly conceptualised as a combination of governance, auditability, and
technology-embedded controls within transaction infrastructures (Zarpala and Casino 2021; Liu et al. 2022;
Nikkel 2020).
A growing stream of the reviewed literature further indicates that fraud in digital financial systems is
evolving toward more complex, system-level and transaction-level manipulation, requiring more advanced
forensic and analytical capabilities. Studies on anomaly detection, smart contract analysis, and blockchain-
based forensic models demonstrate that technology-enabled monitoring and investigation mechanisms are
becoming central to modern fraud risk management architectures (Zarpala and Casino 2021; Liu et al. 2022;
Sen et al. 2025; Nikkel 2020). These developments reinforce the view that fraud prevention and detection
are increasingly embedded within digital infrastructures rather than operating solely as ex-post control
functions.
Nevertheless, the literature also highlights that technological capability alone does not guarantee
improved fraud outcomes. Research on blockchain infrastructure and fintech systems points to ongoing
challenges related to cybersecurity, system vulnerabilities, governance weaknesses, and integration risks,
which can themselves become sources of new operational and control exposures if not properly managed
(Albaroodi and Anbar 2025; Alagha and Özçelik 2025). These concerns further strengthen the argument
that blockchain-based fraud prevention must be accompanied by robust governance, risk management, and
assurance frameworks rather than being treated as a purely technical upgrade.
The reviewed studies suggest that the evolution of fraud risk management in financial enterprises is
best understood as a transition toward integrated digital control architectures in which blockchain, analytics,
auditing, and governance mechanisms operate as mutually reinforcing components. While the potential
benefits are substantial, the literature consistently cautions that real-world impact depends on organisational
readiness, regulatory alignment, and the quality of implementation rather than on the technology itself
(Neves et al. 2023; Jha and Dangwal 2024; Byeon et al. 2025; Singh et al. 2025).
CONCLUSION
The study emphasises the importance of embracing an integrated strategy to fight occupational fraud
in financial institutions. Even though traditional methods, such as internal controls and audits, remain
paramount, their limitations in busy, resource-constrained environments justify the integration of advanced
technologies. Blockchain, with its transparent and secure nature, is seen as a vital tool for refining fraud
detection and prevention techniques. The study provides a foundation for continued investigation into the
role of blockchain in the evolving nature of monetary regulation and fraud supervision in financial
institutions. Even though traditional methods, such as internal controls and audits, remain paramount, their
limitations in busy, resource-constrained environments justify the integration of advanced technologies.
Blockchain, with its transparent and secure nature, is seen as a vital tool for refining fraud detection and
prevention techniques. The study provides a foundation for continued investigation into the role of
blockchain in the evolving nature of monetary regulation and fraud supervision.
Acknowledgments
The authors acknowledge that no additional support outside of the Author Contributions or Funding
sections was received for this study.
Praise Mutoko, Ephraim M. Faku / Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026
69
Funding
The authors declare that no financial support, grants, or external funding were received for the conduct of
this research, analysis, or publication of this article.
Data Available Statement
The data utilised in this study were derived from secondary sources, including Scopus and ScienceDirect
databases. These datasets are accessible through institutional or individual subscription-based access to the
respective platforms.
Conflict of interest
The authors declare that they have no known personal, professional, or financial conflicts of interest that
could have influenced the design, execution, analysis, or interpretation of the findings of this study.
AI Tools Statement
AI-based language editing tools were used to improve grammar and clarity. All intellectual content,
interpretation, and conclusions are solely the responsibility of the authors.
Author contribution
• Conceptualization: Praise Mutoko. The conceptualization of the study was primarily undertaken by Praise
Mutoko, who developed the initial research idea and framework guiding the study.
• Methodology: Praise Mutoko and Ephraim Faku. The research methodology was developed
collaboratively by Praise Mutoko and Ephraim Faku, focusing on the design of the approach and structure
of the secondary data analysis.
• Validation: Praise Mutoko. Validation of the study findings and analytical consistency was carried out by
Praise Mutoko.
• Formal analysis: Ephraim Faku and Praise Mutoko. Formal analysis of the secondary data was conducted
jointly by Ephraim Faku and Praise Mutoko.
• Resources: Ephraim Faku
• Writing – original draft: Praise Mutoko. The original draft of the manuscript was prepared by Praise
Mutoko.
• Writing – review & editing: Ephraim Faku . The manuscript was reviewed and edited by Ephraim Faku to
ensure academic quality and coherence.
• Visualization: Praise Mutoko. Praise Mutoko developed visualization of results and findings.
• Supervision: Ephraim Faku. The research process was supervised by Ephraim Faku, who provided
academic guidance throughout the study.
• Project administration: Praise Mutoko. Project administration was managed by Praise Mutoko, including
coordination of research activities.
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Appendix
Summary of Reviewed Literature
No.
Title
Journal/
Source
Main Theme
Methodology
Key
Contribution
1
Blockchain
efficiency in
financial
security
NIPES
Journal
Blockchain
security
Empirical
Improves
transaction
security
2
Blockchain
for audit trails
Digital
Strategy &
Governance
Auditing
Conceptual
Immutable
audit trails
3
Blockchain in
financial
services
AIP Conf.
Proc.
Financial
services
Review
Opportunities
and risks
4
Blockchain in
modern
banking
Book chapter
Banking
Conceptual
DLT impact
on banking
5
Big data &
malfeasance
AI & Big
Data
Fraud
mitigation
Analytical
Reduces
financial
misconduct
6
IoTBlockFin
loan model
J. Intelligent
Systems &
IoT
Loan fraud
System design
Prevents loan
scams
7
ML anomaly
detection
CCIS
Fraud
detection
ML model
Detects
anomalies
8
ChequeGuard
framework
IJIMT
Cheque fraud
Framework
Prevents fake
cheques
9
Blockchain
cloud security
J. Applied
Data
Sciences
Security
Review
Identifies
vulnerabilities
10
Blockchain
forensic
model
Digital
Finance
Financial
crime
Case model
Supports
investigations
11
Smart
contract fraud
detection
FGCS
Ethereum
fraud
Analytics
Detects
abnormal
contracts
12
Blockchain
against public
fraud
BISE
Public sector
Conceptual
Anti-fraud
framework
13
Smart
contract
applications
IJRI Trends
CC
Smart
contracts
Comparative
Evaluates use
cases
14
Investment
trust via
contracts
PLOS One
Investments
Model
Trust
mechanism
15
Blockchain in
finance
ICACITE
Finance
systems
Experimental
Implementatio
n evidence
16
Blockchain
for insurance
IJITM
Insurance
Framework
Improves
processes
17
Blockchain in
auditing
Mgmt
Science
Auditing
Conceptual
Assurance
guidance
18
Consortium
blockchains
JCAF
Governance
Case analysis
Improves trust
19
Digital
IJIM Data
FinTech
Meta-analysis
Identifies
Praise Mutoko, Ephraim M. Faku / Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026
73
No.
Title
Journal/
Source
Main Theme
Methodology
Key
Contribution
finance
adoption
Insights
adoption
barriers
20
FinTech &
green finance
IJ Islamic &
ME Finance
Sustainability
Bibliometric
Maps research
21
FinTech &
cybersecurity
JFRC
Cybersecurity
Conceptual
Early risk
insights
22
Tech impact
on
accountants
JOI
Professional
skills
SLR
Skill
transformation
23
SME
crowdfunding
barriers
IJ
Innovation
Science
SMEs
Qualitative
Identifies
obstacles
24
FinTech
forensics
FSI Digital
Investigation
Forensics
Review
Digital
evidence
methods
25
Technology
continuance
IJIM
User
behaviour
SLR
Explains
adoption
26
Trust &
inclusion
Heliyon
Financial
inclusion
Review
Trust as driver
27
Digital
inclusion
India
TCR
Economic
growth
Empirical
Growth impact
28
Governance
& inclusion
Heliyon
Governance
Quantitative
Moderating
role
29
Inclusion
bibliometrics
Sustainable
Futures
Inclusion
Bibliometric
Future trends
30
FinTech &
inclusion
JSTPM
Policy
SLR
Synthesises
evidence
31
Robo-advisors
Heliyon
AI finance
Relational
Maps field
32
FinTech, IoT
& credit
IATSS
Research
Credit
systems
Conceptual
Mobility-based
credit
33
Quantum-safe
security
Computers
& Security
Cybersecurity
Technical
review
Post-quantum
risks
34
Data-driven
FinTech
IDD
FinTech
analytics
Survey
Model
overview
35
Model risk
banking
IRFA
Banking risk
Knowledge
mapping
Risk mapping
36
Federated
edge learning
CMC
Distributed
learning
Survey
Resource
allocation