A Bibliometric Analysis of Digital Financial Literacy and Its Role in Reducing Online Financial Fraud in the European Union

Abstract

The rapid digitalization of financial services in the European Union (EU) has not only enhanced convenience and inclusion but also increased exposure to sophisticated online financial fraud. Digital financial literacy (DFL) is widely promoted as a key tool for empowering consumers and reducing fraud victimization. However, the empirical and conceptual landscape linking DFL to fraud reduction within the specific sociolegal context of the EU remains fragmented. This study uses bibliometric analysis to map the research area, define major themes within the field, and determine the role of DFL in reducing online financial fraud in the EU. Peer-reviewed journal articles were targeted to ensure academic rigor, with a publication window of 2010–2025 reflecting key fintech and regulatory developments. After adhering to PRISMA principles, 87 peer-reviewed publications were chosen out of a total of 568 records identified through OpenAlex and Web of Science, coauthorship, keyword co-occurrence, citation, temporal, and density representations were analyzed using VOSviewer. Findings indicate an increasingly diffuse research field with new clusters concentrating on macroeconomic policy, business technology, social psychology, and interdisciplinary foundations. Results demonstrate that successful implementation of DFL interventions combines behavioral insights, technological protection, and non-discriminatory policy considerations. The study concludes by identifying major gaps in research and providing a path forward for future evidence-based policy efforts toward enhancing consumer protection in the EU digital financial market.

1. Introduction

The financial sector digital transformation has radically changed the way citizens within the European Union (EU) save, invest, and transact. Emerging fintech, open banking, and online payment systems have vowed to bring unprecedented convenience and financial inclusion (European Banking Authority, 2022). A recent increase in sophisticated online financial frauds, including phishing and payment diversion fraud, and investment frauds have been keeping abreast with this change and have resulted in massive monetary loss and a lack of consumer trust (Europol, 2023).

This fact has been rewritten in response to this by policymakers and financial institutions, with digital financial literacy (DFL) being mentioned as one of the most critical defense mechanisms. Financial literacy is expanded by the fact that DFL also encompasses the skills and knowledge needed to access and use digital financial services securely and effectively (Goyal & Kumar, 2021). It entails risk awareness in the Internet domain and behavioral skills, which are necessary to detect and avoid scam schemes (Organisation for Economic Co-operation and Development, 2022). The European Union has explicitly associated high levels of DFL with the achievement of a competitive and robust digital single market with its Digital Finance Strategy (European Commission, 2020).

Although this policy focus is present, the empirical evidence between DFL and direct correlation to reduced online fraud victimization is disjointed. Although research indicates that financially literate people have an advantage in developing retirement strategy (Lusardi & Mitchell, 2011) and preventing high-price debt (Klapper et al., 2012), the mechanisms through which DFL is shielding consumers against nefarious Internet personalities remain less researched. A study on good participation in the stock market by van Rooij et al. (2011) points towards the importance of confidence and knowledge. Zaimovic et al. (2023) have already proposed the adoption of the concept of digital finance and financial literacy as converging areas, but a specific socio-legal context of the EU must be studied. The EU offers a distinct environment because of its unified regulatory frameworks such as PSD2 (Payment Services Directive 2) and the General Data Protection Regulation (GDPR) that define the fraud environment and consumer protection systems.

It is important to know the relationship between these regulations and DFL and fraud reduction.

In this study, it is proposed to fill this gap by performing a bibliometric analysis of the current body of the literature regarding DFL and online financial fraud in the EU. It aims to:

(1)

trace the history and the modern state of research in this field;

(2)

find the individuals, organizations, and partnerships;

(3)

conceptualize the research structure and primary research themes; and

(4)

summarize the results on the effectiveness of DFL interventions and define essential research gaps.

Through this overall account, this study aims to enlighten future research and evidence-based policy efforts which will help protect consumers in the EU during the digital era.

Nevertheless, although academic interest in fintech, financial literacy, and online financial crime has increased, a literature-wide analysis has not been conducted on the nexus of digital financial literacy and online fraud in the context of EU-specific regulatory and institutional framework. The current bibliometric research is usually based on bigger topics, i.e., general fintech development, financial literacy tendencies, or digital finance adoption not examining how DFL research relates to fraud prevention or how it is influenced by the EU-level regulations. This is a definite gap in the present literature.

A bibliometric study is especially suitable to fill this gap since it provides a systematic, transparent, and quantitative method of charting the intellectual hierarchy, thematic development, and coalition of networks within a discipline. Bibliometric techniques allow recognizing the most influential authors, institutions, publications, and research groups of people, which creates a complete picture of the way in which knowledge on DFL and online financial fraud has evolved over the years. It is why bibliometrics is highly appropriate in assessing a fractured field of research and building an evidence-based base on the subsequent works.

Therefore, the current study attempts to offer an organized and holistic overview of the field that can guide future research agenda and further help with evidence-based policymaking to enhance consumer protection within the digital financial landscape of the EU.

2. Literature Review

2.1. The Context: Digitalization, Literacy, and Fraud

The high rate of digital transformation of financial services in the European Union (EU) has transformed the way people save, invest, and conduct transactions. The increased rate of adoption of financial technology (fintech), specifically since the conclusion of the COVID-19 pandemic, has facilitated unparalleled amounts of convenience, accessibility, and financial inclusion (Ferilli et al., 2024). However, this technological change has also brought new opportunities for online financial fraud, which has resulted in a complicated balance between technology and consumer vulnerability.

Digital financial literacy (DFL) is a new defense mechanism that replaces these emerging risks. In contrast to traditional financial literacy that aims to acquire the knowledge of saving, investing, and budgeting, DFL incorporates technological literacy, cyber-sensitivity, and behavioral flexibility to operate safely in the contemporary digital economy (Mohd Zukry et al., 2024). Users who do not have these competencies have a high tendency towards online fraud, especially in Central and Eastern Europe (CEE) nations where the digital financial divide (DFD) is still large (Kovács & Terták, 2024).

Politically, DFL interventions are being regarded as a tactical tool for enhancing consumer protection, financial inclusion, and closing the digital capability gap among member states (Ferilli et al., 2024). Simply put, DFL creation is both a social and an economic necessity, which supports the safety and sustainability of the digital financial environment of the EU.

2.2. Digital Financial Literacy in the European Union

The association between digital literacy and financial innovation is complex within the EU. Although technological innovation has the propensity of minimizing costs of transactions and increasing efficiency, it may also lead to the opposite of this situation, widening the digital divide, since the user may not possess the relevant level of literacy skills to use the technology safely and effectively. According to post-pandemic evidence, the less financially literate regions had greater access to misleading information and digital exclusion; also, improving access to technology alone is not enough, and education and awareness should be improved (Ferilli et al., 2024).

Digital financial literacy is a multidimensional concept including cognitive, technical, and behavioral skills combined to facilitate safe online financial interactions.

Table 1. Key dimensions of digital financial literacy (DFL).

DFL Dimension	Description	Relevance to Fraud Reduction	Source
Financial Knowledge	Understanding fundamental financial concepts such as risk, saving, and investment.	Enables critical assessment of fraudulent investment and prize schemes, enhancing skepticism toward suspicious offers.	European Commission (2020)
Digital/Operational Proficiency	Ability to use digital devices, platforms, and online interfaces safely and efficiently.	Facilitates secure use of online banking systems and minimizes accidental exposure to fraudulent websites or links.	Mohd Zukry et al. (2024)
Cybersecurity Knowledge	Awareness of online privacy settings, secure browsing, password protection, and multi-factor authentication.	Reduces risks of identity theft, malware infection, and phishing attacks by reinforcing safe online behavior.	Mohd Zukry et al. (2024)
Threat Identification and Response	Cognitive and behavioral ability to recognize and respond to suspicious digital interactions.	Enhance self-protection against social engineering and impersonation of fraud through critical awareness.	Mohd Zukry et al. (2024)

Source: adapted from European Commission (2020); Mohd Zukry et al. (2024); Kovács and Terták (2024).

summarizes the main dimensions of DFL, which are applicable in reducing online fraud.

All these dimensions depict the fact that DFL is not just an educational and a protective ability combining cognitive knowledge with practical vigilance. A proper DFL thus serves as a behavioral barrier between the audience and fraudsters (Mohd Zukry et al., 2024).

2.3. Statistics and Trends of Online Financial Fraud in the European Union

Regardless of technological protection, online financial fraud is a continual and expensive problem in the European Economic Area (EEA). According to the European Banking Authority (EBA) and European Central Bank (ECB), payment fraud is still costing consumers and financial institutions heavily (European Banking Authority and European Central Bank, 2024).

Table 2. Key payment fraud statistics in the European Economic Area (EEA).

Metric	H1 2023 Value/Volume	Insight	Source
Total Fraud Value (2022)	€4.3 billion	Represents the overall cost of fraudulent transactions to the financial system.	European Banking Authority and European Central Bank (2024).
Total Fraud Value (H1 2023)	€2.0 billion	Indicates ongoing and significant economic losses despite regulatory efforts.	European Banking Authority and European Central Bank (2024).
Most Fraudulent Instruments (by Value)	Credit Transfers and Card Payments	These account for most fraud-related losses.	European Banking Authority and European Central Bank (2024).
Card Fraud Rate (EU/EEA Transactions, by Value)	0.031%	For every €100 transacted, 3.1 cents were fraudulent.	European Banking Authority and European Central Bank (2024).
Card Fraud Rate (Non-EEA Counterpart)	Approx. 10× higher than EEA transactions	Reflects the success of strong customer authentication (SCA) requirements under PSD2.	European Banking Authority and European Central Bank (2024).
Adults Who Experienced Fraud/Scam	56% (within two years, pre-2020 data)	Demonstrates the widespread nature of exposure to fraud among EU citizens.	European Commission (2020).
Most Common Scams (by Volume)	Lottery/Prize Scams (28%), Impersonation Fraud (22%), Computer Problem Fraud (21%)	Highlights fraudsters’ reliance on social engineering rather than technical system breaches.	European Commission (2020).

Source: European Banking Authority and European Central Bank (2024); European Commission (2020).

presents key statistics that capture the scope and evolving nature of financial fraud in the EU.

Although strong customer authentication (SCA) and Payment Services Directive 2 (PSD2) have decreased unauthorized card fraud, the human factor, particularly with social engineering and phishing attacks, has proved to be a huge susceptibility (European Commission, 2020). These trends indicate that technological security measures cannot be applied without some similar behavioral and cognitive defenses, and the role of DFL cannot be underestimated (European Banking Authority and European Central Bank, 2024).

2.4. Digital Financial Literacy as a Mitigator of Online Financial Fraud

The literature reviewed always notes that DFL has a protective effect that helps to minimize exposure to online financial fraud (Kovács & Terták, 2024). DFL enables people to notice, counter, and report instances of fraud, thus augmenting regulatory and technological controls. This is a multidimensional role whereby it involves behavioral, educational, and systemic aspects.

2.4.1. Vulnerability of Specific Demographics

Some groups of the population, especially elderly people, are overrepresented in terms of being victims of financial fraud online. The rise in digital banking by senior citizens in the post-COVID-19 period has subjected them to emerging risks because of reduced operational competence, cognitive aging, and reduced knowledge of digital security practices (Mohd Zukry et al., 2024). The identified demographic change underscores the importance of targeted DFL interventions based on vulnerable groups, particularly in the areas with aging population or low access to digital education (Kovács & Terták, 2024).

2.4.2. DFL as a Multi-Pronged Defense Mechanism

DFL is a multi-layered defense system, which combines education, technology, and regulation. High DFL people are better able to recognize fraudulent cues in communication, safe communicating with authentication tools, and are not affected by manipulative behavior like phishing or impersonation (Mohd Zukry et al., 2024). Practical programs can thus comprise educational programs (public awareness efforts and financial education), technological solutions (credible, easy-to-use interfaces), and regulatory controls (data protection by design and data standards compliance) to develop a strong, consumer-based protection ecosystem.

2.4.3. Synergy Between Fintech and DFL

The emerging literature has suggested the synergetic potential of fintech innovation and digital literacy improvement. Fintech applications, including mobile banking, e-wallets, and fraud detection with the help of AI, can be used in a safer, more inclusive manner when citizens are not only tech-savvy but also financially literate (Ferilli et al., 2024). The EU long-term vision is therefore the one whereby there is a growth of technological advancements and digital literacy and a digitally empowered citizenry that would be able to participate in the financial system without being overly exposed to fraud as shown in

Table 3. Conceptual model of the role of digital financial literacy (DFL) in reducing online financial fraud in the European Union.

Component	Key Mechanisms	Expected Outcomes
Digital Financial Literacy (DFL)	Knowledge, digital proficiency, cybersecurity awareness, and fraud response skills.	Increases user vigilance and resilience against social engineering and fraud.
Technological Safeguards	Implementation of strong customer authentication (SCA), AI fraud detection, and secure payment systems.	Reduces unauthorized transactions and enhances systemic trust.
Regulatory Framework	Enforcement of PSD2, GDPR, and EU cybersecurity directives.	Establishes legal and procedural protection for consumers.
Behavioral and Educational Interventions	Targeted DFL training, awareness campaigns, and inclusion programs.	Strengthens consumer confidence and reduces susceptibility among vulnerable groups.
Outcome: Reduced Fraud Vulnerability	Integration of literacy, technology, and regulation.	Sustainable fraud reduction and a more resilient digital financial ecosystem.

Source: author’s own (2025).

.

Altogether, the literature analysis shows that digital financial literacy is a behavioral and cognitive security system in the digital financial ecosystem of the EU. It is an addition to regulatory and technological response because it addresses the human aspect of the susceptibility to fraud. High DFL does not only increase consumer protection but also facilitates the wider objectives of the EU for digital inclusion and financial stability (Ferilli et al., 2024). Nevertheless, the existing differences between regions and population groups still dominate the consistency of DFL implementation, which is why it is necessary to invest in education over time and engage in specific training and cross-sector cooperation.

3. Methodology

Bibliometric analysis was selected as the methodology adopted to study, map, synthesize, and evaluate the available literature on the role of digital financial literacy (DFL) in reducing online financial fraud in the European Union (EU) because it facilitates the identification of dominant research themes, influential publications, leading authors, and collaboration networks, thereby clarifying the intellectual structure of emerging fields (Donthu et al., 2021; Zupic & Čater, 2015). Moreover, bibliometric analysis enables the detection of geographic and thematic gaps in research, providing a strong justification for further empirical inquiry and policy-oriented studies aimed at enhancing digital financial resilience among EU citizens.

To achieve methodological transparency, reproducibility, and scholarly integrity, the PRISMA 2020 (Preferred Reporting Items in Systematic Reviews and Meta-Analyses) framework Page et al. (2021) was followed to construct the methodological design. The procedure consisted of five major steps, such as determining the eligibility criteria, database search, screening and selection of studies, extraction and synthesizing data, and bibliometric mapping and visualization with the help of the VOSviewer software. All these phases are discussed below in Figure 1 below.

3.1. Eligibility Criteria for Study Inclusion

The inclusion and exclusion criteria were refined to ensure that the final corpus consisted of studies conceptually relevant, methodologically rigorous, and aligned with the socio-legal context of the European Union as shown in

Table 4. Summary of the inclusion and exclusion criteria applied in this study.

Category	Criteria Type	Description	Rationale
Population/Context	Inclusion	Studies focusing on populations, cases, or datasets originating from the European Union (EU) or any of its member states.	Ensures findings reflect the EU’s socio-economic, digital, and regulatory environment.
	Exclusion	Studies conducted outside the EU or that do not specify an EU context (e.g., global studies without EU data).	Maintains regional focus and relevance of results.
Concept (Thematic Focus)	Inclusion	Studies addressing digital financial literacy (DFL) and its subcomponents, including online risk awareness, digital competence, fraud prevention, and responsible financial behavior.	Focuses on DFL as an integrated construct linking financial literacy with digital security and decision-making.
	Inclusion	Studies analyzing or discussing online financial fraud types such as phishing, impersonation, APP fraud, or investment frauds.	Ensures inclusion of the human and behavioral dimensions of digital fraud.
	Exclusion	Studies focus solely on cybersecurity, blockchain, or IT systems without a behavioral or literacy component.	Avoids technical bias and centers on human capability and knowledge.
Publication Type and Quality	Inclusion	Peer-reviewed journal articles indexed in recognized databases (Web of Science, Elsevier, SpringerLink) published between 2010 and 2025.	Ensure academic credibility, reliability, and peer validation.
	Exclusion	Non-peer-reviewed materials such as conference papers, dissertations, book chapters, editorials, and preprints.	Eliminates non-academic or opinion-based materials lacking methodological rigor.
Language	Inclusion	Studies published in English.	Enhances accessibility and facilitates comparative synthesis across studies.
	Exclusion	Publications in other languages (e.g., French, German, Spanish) without English translation.	Minimizes translation bias and ensures interpretability.
Methodological Rigor	Inclusion	Empirical, conceptual, or bibliometric studies using clear methodologies (quantitative, qualitative, or mixed methods).	Guarantees that included studies contribute to credible, replicable findings.
	Exclusion	Opinion papers or commentaries lacking methodological detail or analytical depth.	Maintains consistency in analytical robustness.

Source: author’s own (2025), guided by the PRISMA 2020.

. Each criterion was designed to narrow the scope to research what meaningfully contributes to understanding how digital financial literacy influences online financial fraud within the EU’s unique regulatory and digital environment. A key justification for the EU-only focus is that the fraud landscape is shaped by region-specific regulatory frameworks such as PSD2, GDPR, and the EU Digital Finance Strategy. These instruments significantly alter user behavior, financial infrastructure, and fraud typologies, making non-EU data insufficiently comparable. The conceptual boundary of DFL in this study includes financial knowledge, digital operational competence, cybersecurity awareness, and behavioral capacity to identify and respond to fraudulent activity. Studies focusing solely on cybersecurity technologies or technical fraud detection systems without human behavioral or literacy components were excluded to maintain conceptual coherence. Peer-reviewed journal articles were selected to ensure academic rigor, with a publication window of 2010–2025 reflecting key fintech and regulatory developments.

These were used to ensure that the end corpus only contained studies that were contextually pertinent, conceptually oriented, and methodologically sound.

3.2. Information Sources and Search Strategy

It was in the OpenAlex database and Web of Science that the search was performed, as it has great coverage, metadata quality, and is suitable to perform a bibliometric analysis. It was chosen to use OpenAlex since it offers open-access and structured metadata which can be visualized with more sophisticated bibliometric visualization software, VOSviewer version 20 (Alperin et al., 2024).

Relevant publications were located with a carefully constructed Boolean search string to achieve both sensitivity and specificity. This search query was the following:

(Digital financial literacy) OR (digital finance literacy) OR (e-financial literacy). AND (online financial fraud) OR (cyber fraud) OR (payment fraud) OR (phishing) OR (authorized push payment fraud). AND (European Union OR EU OR names of specific EU countries that are its members).

Search was performed in title, abstract, and author keywords; lower limit of the year 2010 was set to reach the foundational studies and a cut-off date of May 2024. RIS and CSV files with the search results were exported to be further screened and subjected to bibliometric processing (Williams et al., 2017).

3.3. Study Selection and Screening Process

The process of selection of the study involved the PRISMA 2020 four-step process of identification, screening, eligibility, and inclusion as shown in

Table 5. PRISMA screening and selection summary.

Stage	Action	Number of Records	Details/Reason for Exclusion
Identification	Records identified through OpenAlex search	568	Comprehensive database search results
	Duplicates removed	72	Duplicate entries across datasets
Screening	Records screened by title and abstract	496	361 excluded for lack of relevance or non-EU focus
Eligibility	Full-text articles assessed for eligibility	135	36 excluded (18—cybersecurity only, 12—non-EU, 6—non-peer reviewed)
Inclusion	Studies included in the final review and bibliometric analysis	87	Final set of peer-reviewed studies meeting all inclusion criteria

Source: author’s own (2025).

. This provided a systematic, transparent, and replicable process. During the identification stage, 568 records were obtained in the database search. Then, 72 duplicate records were eliminated with the help of Zotero, and 496 distinct studies were left. In the screening stage, the titles and abstracts of the 496 records were examined regarding the eligibility criteria. Articles that were not pertinent to DFL, those that discussed traditional literacy, and those that were not based on an EU setting were filtered out. This gave 135 articles that were eligible for full-text review. During the stage of eligibility, the two independent researchers retrieved and reviewed the full-text versions of the 135 articles. Thirty-six studies were eliminated, eighteen of them had cybersecurity but without literacy, twelve of them did not have an EU focus, and six articles were not peer-reviewed. Lastly, during the inclusion phase, 87 studies were included in the final bibliometric analysis and all of them met the inclusion criteria. Disagreement among reviewers was solved either by a consensus or by consulting a third expert.

The multi-stage filtering process made sure that only good, contextually relevant, and analytically sound studies were included.

3.4. Data Extraction and Synthesis

A standardized data extraction framework was created to systematically extract and tabulate data from the studies included. The retrieved information included bibliographic information (author, title, journal, year, and DOI), research design (empirical, conceptual, or bibliometric), geographical area (focus on a particular member state or region of the EU), and conceptual definition of DFL and online fraud along with the major findings connected to fraud prevention and consumer protection. Narrative synthesis was used to synthesize the extracted information, which is appropriate in merging the results of various methodologies in studying a particular topic. This qualitative methodology made it possible to synthesize findings of empirical and theoretical research on a thematic level, which provided a logical insight into the processes by which DFL moderates fraud reduction in the EU settings. The synthesis revealed new patterns, recurring definitions, and gaps in the current research.

3.5. Bibliometric Analysis and Science Mapping

As the complement of the qualitative synthesis, a bibliometric analysis was applied in VOSviewer (version 1.6.19). This method will allow for obtaining quantitative data on the organization, dynamics, and development of study within DFL and online financial fraud.

Data that was exported using OpenAlex was standardized and cleaned prior to analysis. It involved the combination of synonymous keywords (such as digital finance literacy and digital financial literacy), harmonization of names of authors, and institutional variations (Williams et al., 2017).

The bibliometric analysis used five major methods:

• Coauthorship analysis: coauthorship was used to identify collaborative relationships between authors, institutions, and countries to map scholarly networks.
• Keyword co-occurrence analysis—explores the usage of key words and their association, showing prevalent themes and concept groups.
• Citation analysis—calculated citation frequency to determine the most effective studies and authors in the area.
• Temporal overlay visualization followed the chronological progression of research topics to determine emergent and decaying interests.
• Density visualization—used to identify areas of high research activity, indicating core and peripheral issues in the field.

Bibliometric mapping provided qualitative depth and quantitative accuracy, which provided an inclusive picture of how DFL research can help to minimize online financial fraud in the European Union. This mixed methodology has facilitated the determination of intellectual structures, key scholars, new themes, and gaps in research, thus providing a holistic evidence base on policy and scholarly development on digital financial education and consumer protection.

3.6. Marginal Contribution of the Selected Studies

The selective approach adopted in this review provides a marginal contribution that goes beyond the existing literature by integrating the following three dimensions not previously examined collectively: (1) digital financial literacy as a multidimensional capability, (2) online financial fraud as a behavioral and socio-technical phenomenon, and (3) the European Union as a unified regulatory environment with harmonized consumer protection laws. By selecting studies that explicitly address both DFL and fraud-related behavioral responses, and by excluding the purely technical cybersecurity literature, the review isolates the human-centered mechanisms through which literacy moderates fraud vulnerability. The bibliometric component further maps intellectual clusters, emerging themes, and fragmentation in current scholarship.

4. Results

4.1. Coauthorship Analysis

This has been achieved through the coauthorship network analysis featured in Figure 2, which gives a detailed mapping of a collaborative relationship between researchers in the study of digital financial literacy (DFL) and online financial fraud in the European Union. It is a useful visualization that provides an understanding of the social structure of the research community, as it shows clusters of collaboration, institutional centers, and powerful scholars who are defining the field. This enables the whole network to seem more decentralized with multiple, closely knit clusters, and not governed by one central group (Williams et al., 2017). This trend implies that studies in the field of DFL and online financial fraud are being conducted by several independent groups in different institutions and countries. It should be noted that the fact that there exist many small clusters and isolated authors in the form of single, unrelated nodes implies that the field is expanding but is still in the development phase where the research has not been consolidated yet.

Such a decentralized structure generates several prominent collaborative groups that become influential contributors. The major cluster is the “Gill Group” cluster, with its center being Parin Gill, and collaborators such as Brandalken and Sandra Schillo. This group is a focused research team, and it is a group of researchers from one institution or research center, with a high interest in the problem of DFL and fraud. There is another prominent cluster around Hole Leminen which works closely with Nistol Pajala and Canada Gangadharan. The close ties of this group indicate long-term cooperation on a regional or thematic basis in the EU context.

Similarly, another network is under operation as indicated by the group of Michael Weiss, Tony Balletti, and Mark Engelhardt. The fact that this population is represented by a broad spectrum of names, some of them German and Italian, implies that there are good cross-country collaborations. This is particularly critical when it comes to online financial fraud, which is a pan-European issue that requires the endeavors of multinationals. The other distinct teams are the teams of Megan Money, Peter Cartone, and Mika Westernlund. This group is also made up of many individuals of international origin, meaning it is a combined effort not limited to state boundaries. Their respective groups have several scholars that are the center of these clusters.

The key figures in their respective networks and the main players in the research agenda are researchers like Parin Gill, Hole Leminen, and Michael Weiss. Their centrality is high, which represents evidence of their impact on generating knowledge and enhancing collaboration among co-workers. The implications of the analysis on this research line’s development are immense. On the one hand, network decentralization is an indicator of strength: it allows the diversity of thought and methodology, and other centers of excellence are emerging throughout Europe. Such diversity is particularly advantageous as online financial fraud is a sophisticated and multi-dimensional phenomenon that needs the input of behavioral economics, cybersecurity, regulations, and digital literacy education.

On the other hand, the connectivity of clusters is weak, which indicates a drawback. Of course, the intra-cluster relationships are high, but inter-cluster relationships are fewer, and this is a potential threat of knowledge silos. This issue should be met by devoting more energy to inter-cluster cooperation. Cross-institutional initiatives funded by the EU, thematic conferences, and workshops run collaboratively have the potential to close existing gaps and hasten knowledge exchange and build a strong research community. In conclusion, the co-authorship analysis shows the social structures on which the research on DFL and online financial fraud in the EU is based. It also reveals new clusters, key players, and possibilities of creating interconnectivity that will prompt the field to become more cohesive.

4.2. Keyword Co-Occurrence Analysis

The co-occurrence keyword analysis, which is presented in Figure 3, provides an even better overview of the conceptual framework and intellectual foundation of the research linking digital financial literacy (DFL) and online financial fraud in the European Union. Through the frequency and pairing of keywords in the 87 selected studies, the analysis determines the recurring themes and goes on to map the relationships between them.

The analysis reveals four major thematic clusters, each reflecting a distinct perspective but remaining connected to others:

6.

Macroeconomic and Policy Cluster (Red): captures economic and institutional aspects, including fiscal crisis, monetary policy, globalization, and central banking.

7.

Business and Technological Cluster (Green): links to business, commerce, and process management with cybersecurity, databases, and cryptocurrency.

8.

Social and Psychological Cluster (Blue): highlights social development, financial inclusion, education, and gender dynamics in DFL.

9.

Foundational Cross-Disciplinary Cluster (Yellow): represents core analytical and conceptual constructs such as mathematics, identification, and ecosystems.

Connections among these clusters emphasize interdisciplinarity. For example, macroeconomic (red) links to business (green) via “financial market,” and social (blue) connects with macroeconomic (red) through “financial inclusion” and “economic growth.” Together, these interactions confirm that research on DFL and online fraud integrates economics, psychology, computer science, and sociology.

4.3. Overlay Visualization

The overlay visualization (Figure 4) illustrates the temporal development of research themes in DFL and online financial fraud across the EU. Each node of color corresponds to the average publication year of studies associated with that keyword. The gradient ranges from darker tones (older research, ~2019) to lighter tones (recent research, ~2021).

The visualization indicates a shift from foundational research (business, economics, and public finance) toward specialized and technology-oriented topics like cybersecurity and cryptocurrency. Newer nodes, such as financial inclusion, policy, and pandemic, highlight recent scholarly responses to the digital acceleration prompted by COVID-19.

This progress demonstrates that while DFL research initially focused on economic and behavioral aspects, it now increasingly integrates technology-driven and policy-based frameworks reflecting the dynamic adaptation of scholarship to emerging risks.

4.4. Density Visualization

The density visualization (Figure 5) illustrates the concentration of research themes by mapping the frequency and co-occurrence of terms across the 87 studies included in this review. In this representation, colors are used to signify varying degrees of thematic density as follows: yellow denotes the highest concentration of keywords, green indicates areas of high but slightly lower density, while blue and purple reflect lower-density regions where research activity is less frequent. This gradient makes it possible to identify the intellectual core of the field as well as its peripheral areas.

The image (Figure 5) reveals that the densest cluster is solidly centered on business and economics. The yellow core shows that most publications dealing with digital financial literacy (DFL) and online fraud projects are still rooted in traditional social science perspectives which have their disciplinary building blocks in the field of business and economics. These disciplines not only dominate the literature but also supply the conceptual and methodological underpinning through which most of the articles were produced. Around this core center, we see a dense green area that highlights related but less concentrated spheres of activity. Financial services and financial inclusion stand out, emphasizing the practical and societal relevance of DFL investigation. These themes include both the functional aspects of the financial systems and the broader social goal of ensuring equitable access to digital financial instruments. Coupled with these themes is a high-density compact area of associations with computer science and computer security; the digital and technological aspects of the subjects are important dimensions of the phenomena to understand and curb the excesses of online fraud. Interestingly, terms like the world wide web and epistemology also qualify for inclusion in this high-density area, which suggests that the digital environment and the study of knowledge itself are vital aspects of contemporary discourse.

By contrast, peripheral areas of visualization, shaded in blue or purple, contain themes that appear less frequently and are therefore less central to the field. These include unexpected terms such as biochemistry, transformation (genetics), and archeology, which are the result of broad keyword indexing rather than direct thematic relevance. Similarly, more isolated terms like financial institution and information and communications appear in these lower-density regions, indicating that while they are part of the discourse, they are not central drivers of the research agenda.

Overall, the density visualization demonstrates that scholarship on DFL and online financial fraud is coalescing around a core intersection of business and economics with computer science and cybersecurity, all framed within the context of financial services and financial inclusion. This pattern reflects the interdisciplinary nature of the field, where economic principles, technological safeguards, and social concerns converge to form the central focus of research. It also highlights the importance of maintaining this interdisciplinary balance, as effective solutions to online fraud require not only economic and financial expertise but also robust technological innovation and an inclusive social perspective.

4.5. Citation Analysis

The

Table 6. Top cited authors and publications.

Author(s)	Year	Title	Key Contribution
Lusardi & Mitchell	2011	Financial Literacy and Planning: Implications for Retirement Well-being	Seminal work establishes the importance of financial literacy.
van Rooij, Lusardi & Alessie	2011	Financial Literacy and Stock Market Participation	Linked literacy to financial behavior.
OECD	2022	International Survey of Adult Financial Literacy	Provided cross-country DFL metrics.
European Banking Authority	2022	Report on Financial Education and Digitalization	Guided EU-specific digital literacy policy.
Williams et al.	2019	Applying Behavioral Insights to Improve Fraud Resilience	Integrated behavioral economics into fraud prevention.

Source: compiled from the literature review (Lusardi & Mitchell, 2011; van Rooij et al., 2011; Organisation for Economic Co-operation and Development, 2022).

below, shows a citation analysis of the most significant authors and publications that underlie the discipline of digital financial literacy. It lists the classic studies and landmark policy documents that have determined the main concepts, created empirical connections between literacy and financial practices, and the measures and constructs that shape the modern policy, especially in the European context

5. Discussion

The results of this bibliometric analysis offer a structured panorama of the changing research frontiers on digital financial literacy (DFL) and online financial fraud in the European Union. In addition, the increase in the number of publications after 2018 is consistent with greater attentiveness to the EU’s digital single market and increased awareness of cyber-financial crime. The decentralized coauthorship network shows diversity and dynamism, but also a lack of cross-cluster connectivity, pointing towards efforts to achieve better EU-wide cooperation.

Keyword and density analyses further support the interdisciplinarity of research in this field, which involves economic policy, behavioral science (decision-making), and technological innovation. DFL has strong theoretical connections with fraud reduction, but empirical support in the EU context is weak and correlational rather than causal. It is necessary to consider this in future research using longitudinal and experimental designed research that can test the actual effects of DFL programs under specific EU regulations, including its own regulatory environments with respect to GDPR and PSD definitions.

To fill the gap, which was identified in the current literature, the findings point out the necessity to explain the way in which DFL can be translated into actual protection behaviors. Even though a lot of the literature implicitly postulates that a greater level of knowledge would ensure safer digital use, there has been minimal expression of the behavioral mechanism behind it. According to the trends revealed during the given bibliometric review, a conceptual mechanism may be suggested, where DFL affects the prevention of fraud in a series of cognitive and behavioral processes. First, DFL will improve the knowledge of individuals concerning digital platforms, frequent fraud schemes, and warning signs. Knowledge generates important psychological processes such as enhancing the perception of risk, enhancing threat perception, and augmenting the self-efficacy of coping with suspicious situations. Second, such cognitive transformations inform the intentions to behave, as they make one less prone to irrational reactions and more responsible in online communication. Third, the intention changes result into the manifestation of protective behaviors, which include checking the authenticity of messages, doubting before making unfamiliar links, checking transaction requests, and reporting suspicious activity. By such an avenue of cognition—mental processing behavioral reaction DFL eventually reduces the chances of being a victim of fraud.

This hypothetical mechanism offers a theoretical context in explaining how DFL works as a preventative measure, especially in the context of the regulatory framework in the EU, where consumers need to deal with technological threats in addition to legal requirements regarding data protection and validation. Further empirical research needs to test this mechanism explicitly to establish what elements of DFL, knowledge, self-efficacy, risk awareness, or behavioral skills, play the greatest role in avoiding fraud in the EU.

6. Conclusions

Bibliometric analysis has appropriately outlined the intellectual framework and development of the literature on digital financial literacy (DFL) and its impact in alleviating online financial fraud in the European Union. The paper proves that discipline is dynamic, interdisciplinary, and more oriented to the digital and security aspects of finance. It has recognized the main contributors, networked activities, and focal themes of research, with convergence in the economic, technological, behavioral, and social perspectives being identified. Two major conclusions can be drawn from the analysis.

To begin with, DFL is a vital, multi-dimensional element of consumer protection in the digital age, albeit its efficiency depends on well-crafted interventions based on behavioral science and specific to the threats of digital channels and the regulatory environment in the EU.

Second, although the research activity increases, the discipline needs increased interaction between insulated research groups and increased empirical research creating causal relationships between DFL interventions and quantifiable decreases in fraud victimization.

The findings show the necessity of policymakers to implement DFL in national strategies as a supplement to regulatory and technological security measures. The initiatives must be focused, evidence-based, and committed to working on vulnerable populations so that financial inclusion does not become a burden exposing them to fraud. To the researchers, this paper has determined that there are several gaps such as the need to conduct longitudinal studies, more specific studies in the consideration of the varying effect that DFL has on different demographics, and the investigation of the synergies between RegTech Solutions and human-oriented DFL education. With these gaps filled in, future studies can support even more empowerment of EU consumers, raise trust in digital finance, and help create a more dependable and secure financial ecosystem.

This review contributes to the literature by integrating research on DFL, online financial fraud, and the EU’s regulatory environment, offering insights that prior reviews have not captured collectively. Beyond demonstrating that DFL plays a multidimensional role in enhancing consumer protection, the review shows that the field remains conceptually fragmented and empirically underdeveloped—particularly concerning causal evidence linking DFL interventions to reduced fraud victimization. The selected studies highlight the importance of EU-specific regulatory frameworks, demographic vulnerabilities, and behavioral mechanisms, offering a meaningful advancement in understanding how literacy, technology, and regulation interact to shape fraud resilience.

Therefore, this study concludes that DFL is a supporting pillar of consumer protection in the digital financial ecosystem of the EU. Nonetheless, its efficacy relies on interventions which are context-sensitive, behaviorally informed, and consistent with the EU regulatory architecture. Fraud risks cannot be decreased with technological innovation, but improvements in consumer literacy must be made simultaneously. Despite the fact that PSD2 and SCA have minimized illegal transactions, the fact that social engineering attacks persist to date proves the human factor to be the center stage of vulnerability. The existing studies are mostly correlational. Causal evidence to show that DFL interventions directly lower the victimization of fraudsters in different demographic groups and different regulatory settings is lacking. Demographic inequalities, particularly in the elderly, low-income, digitally disadvantaged populations are always mentioned but seldom researched in detail.

The findings underscore the need to make DFL more entrenched in national and EU-wide approaches to financial education. Policymakers ought to develop specific, evidence-based interventions (especially to vulnerable populations) and combine them with technological protection and consumer education efforts. To bring together the financial institutions, cybersecurity agencies, education ministries, and civil society organizations, the regulatory bodies should promote the establishment of a unified and proactive ecosystem in fraud prevention.