Kátia Karolini Amaro El Alam, Jader do Nascimento Araújo, Israel Horácio Almeida Silva, Dyego Alexandre Girão de Souza Anjos · 6 authors
A expansão das fintechs e das plataformas de ativos digitais recolocou a tecnologia blockchain no centro do debate sobre modernização financeira. Este artigo investiga em quais circunstâncias uma infraestrutura de registro distribuído pode gerar valor para o sistema financeiro brasileiro sem enfraquecer a proteção do usuário, a integridade de mercado e a capacidade de supervisão. O estudo adota abordagem qualitativa e teórico-documental, combinando revisão narrativa estruturada de literatura acadêmica com análise de normas e documentos oficiais publicados entre 2008 e 31 de julho de 2026. A interpretação foi organizada em três dimensões de adequação: operacional, referente ao problema de coordenação que se pretende resolver; de governança, relativa à distribuição de direitos decisórios, responsabilidades e mecanismos de correção; e de interesse público, associada à concorrência, inclusão, proteção de dados e estabilidade. Os resultados indicam que a blockchain tende a ser mais útil em processos multilaterais com conciliações repetidas, exigência de rastreabilidade e possibilidade de liquidação programável. Os ganhos, contudo, podem ser anulados por integração incompleta, custódia frágil, opacidade contratual, concentração de infraestrutura e custos regulatórios subestimados. No Brasil, a consolidação do marco de ativos virtuais e os testes do Drex mostram uma passagem da experimentação para a governança regulada. Conclui-se que a vantagem da tecnologia não reside na descentralização como fim, mas na combinação entre arquitetura apropriada, responsabilização verificável e proteção efetiva dos participantes.
ABSTRACT Real Estate Tokenisation started with the introduction of blockchain technology. It is changing the world’s way of investing in assets by providing proportional ownership, improving liquidity and basically giving retail investors access to HNI investment opportunities they didn't have before. This technology is getting a lot of global attention but institutional adoption is largely dependent on the environment that regulatory bodies set for digital assets and tokenized securities. This study help to present the role of regulation in institutional adoption of real estate tokenization through a comparative analysis of three main jurisdictions India, IFSC GIFT City and the United Arab Emirates (UAE). Using secondary data the study analysed regulatory documents, policy reports and academic literature through a qualitative comparative policy analysis and thematic content analysis. The research looks at the impact of regulatory certainty, recognition through laws, investor protection, licensing, digital marketplace infrastructure and frameworks for foreign investments on institutional confidence. The finding show that institutions are more likely to participate where regulatory certainty, licensing frameworks and innovation-friendly policies can coexist. India has shown increasing regulatory engagement with digital asset innovation with IFSC GIFT City has given a more progressive regulatory environment for international financial activities whereas the UAE has supported itself by dedicated virtual asset regulations and innovation based policies and has established itself as a leading jurisdiction for institutional tokenization initiatives. Proposed by this study is the Institutional Regulatory Readiness Framework (IRRF) which is an six dimensional conceptual framework for measuring the institutional readiness towards real estate tokenization in various jurisdictions. The paper proposes a Regulatory Readiness Framework that combines legal, technological and institutional dimensions to provide knowledge of jurisdictions for large-scale real estate tokenization. By comparing three regulatory ecosystems, the study offers practical advice for policymakers, regulators, financial institutions and market participants who are seeking to improve institutional adoption. Index Terms: Real Estate Tokenization, Institutional Adoption, Blockchain, Regulation, IFSC GIFT City, United Arab Emirates, India, Real-World Assets (RWA), Digital Assets, Regulatory Readiness.
This study maps the development, collaboration patterns, citation structure, and thematic evolution of research on blockchain technology in the waqf sector. A bibliometric analysis of 417 Scopus-indexed publications published from 2006 to 12 July 2024 was performed using Bibliometrix in RStudio and VOSviewer. The analysis covered publication trends, influential sources and contributors, country productivity, citation impact, collaboration networks, and keyword co-occurrence. The results show increasing scholarly attention to the intersection of blockchain, Islamic finance, fintech, and waqf management. Malaysia and Indonesia emerged as the most productive and most cited countries, while an international co-authorship rate of 29.74% indicated moderate cross-border collaboration. Keyword analysis revealed that the field is anchored in Islamic finance, fintech, blockchain, and waqf, with growing attention to cash waqf, crowdfunding, financial inclusion, digital transformation, smart contracts, cybersecurity, and technology adoption. However, these patterns demonstrate scholarly attention and thematic associations rather than empirical proof of blockchain’s operational benefits in waqf institutions. This study identifies priority gaps in empirical implementation, Shariah governance, stakeholder adoption, technical feasibility, and socioeconomic impact evaluation of blockchain-enabled waqf systems.
This study is based on proliferation of IoT devices has created demand for high-rate, low-cost microtransactions, yet conventional blockchains impose fees, latency, and throughput limits that hinder scalable IoT finance. This study aimed to evaluate a hybrid architecture that places microtransactions on a lightweight DAG(IOTA/Tangle-style) plane while periodically anchoring compact commitments to Ethereum to reconcile performance with public auditability. The study implemented a reproducible simulation that ingests IoT telemetry (TON_IoT-style), a DAG transaction and tip-selection model at the edge and samples Ethereum fee/confirmation priors from Google BigQuery public datasets to generate realistic on-chain settlement costs and latencies. Scenario attacks (flooding, replay, recipient-entropy) were injected, and detection models (sequence + +graph features) were evaluated. DAG operation yielded near instant local confirmation (≈1.4 s) and ≈1200 tx/s throughput versus ≈13.2 s and ≈14 tx/s on Ethereum. Periodic anchoring reduced amortized per-payment cost from ≈$0.72 (naive on-chain) to ≈$0.0144 with modest finality delay (median ≈600s), a ≈98% cost reduction. F1 detection was high (≈0.85-0.91) with an acyclic graph (DAG). Ethereum is a practical approach for transparent, secure IoT financial transactions since it preserves DAG performance while providing immutable auditability at negligible amortized cost. Exploring privacy-preserving anchors as well as multi-gateway resilience has become a stepping stone for future research.
Abstract: The evolution of monetary systems has transformed human civilization from simple barter exchanges to sophisticated digital financial ecosystems powered by blockchain technology. This review examines how barter systems evolved into con-temporary virtual currencies across history and assesses how cryptocurrencies fit into the circular economy. The study explores the shortcomings of conventional monetary systems and looks at how decentralized, transparent, and effective forms of economic transaction have been made possible by digital currencies like Bitcoin. Additionally, the study examines how blockchain technology might be used to support waste reduction, sustainability, resource efficiency, and transparent supply chain management. The study also assesses the difficulties posed by virtual currencies, such as market volatility, cybersecurity threats, regulatory ambiguity, and environmental issues pertaining to cryptocurrency mining. The review identifies significant research gaps and future prospects for incorporating virtual currencies into sustainable economic systems by synthesizing the body of existing work. The results indicate that through openness, decentralization, and technological innovation, blockchain-enabled financial systems have a great deal of potential to promote circular economy goals. Keywords: Virtual Currency, Cryptocurrency, Bitcoin, Blockchain, Circular Economy, Sustainable Finance, Digital Economy, Decentralization, Green Finance, FinTech, Supply Chain Management
The tokenization of Real-World Assets (RWAs) represents a paradigm shift in bridging traditional financial instruments with decentralized infrastructures. However, as the market transitions from proof-of-concept to institutional scale, it faces a critical structural bottleneck: the "walled garden" liquidity crisis. Driven by stringent regulatory requirements, tokenized assets are currently deployed across fragmented, permissioned blockchain networks utilizing static, hard-coded compliance logic. This siloed architecture inherently restricts cross-chain mobility, fracturing secondary market liquidity and necessitating redundant authentication processes across jurisdictions. This paper proposes a comprehensive architectural framework to resolve the interoperability trilemma inherent in regulated digital assets. By synthesizing recent advancements in cross-chain messaging protocols and Zero-Knowledge Proofs (ZKPs), we present a model for dynamic compliance. This framework utilizes Decentralized Identifiers (DIDs) and off-chain verifiable credentials to decouple regulatory logic from underlying asset ledgers, enabling seamless asset transfer across heterogeneous blockchains without compromising privacy or jurisdictional adherence. Ultimately, this research provides a technical and regulatory roadmap for policymakers and protocol developers to foster a unified, globally liquid market for tokenized RWAs.
Abstract This research examines the adoption of blockchain and fintech innovation in emerging markets, focusing on the drivers, barriers, and regulatory dynamics. Using a cross-sectional quantitative survey of 114 fintech leaders and entrepreneurs across 60 emerging-market countries, the research examines perceptions of blockchain’s role in cost reduction, efficiency, and financial inclusion through decentralized finance (DeFi), tokenized assets, and digital wallets. Findings show respondents broadly agree that blockchain fosters new business models and competitive advantage, perceive strong benefits in transparency, cost reduction, and efficiency, and hold favorable views of regulatory support, clear guidelines, and sandboxes, while still recognizing regulatory, organizational, and technological barriers to adoption. Fintech leaders reported significantly higher familiarity and stronger belief in blockchain’s potential than entrepreneurs. The study applies Institutional Theory, the Technology–Organization–Environment framework, and Disruptive Innovation Theory to highlight policy, organizational, and technological implications. Because the sample was purposive and responses were uniformly positive, the findings describe the perceptions of engaged practitioners rather than statistically generalisable or audited adoption outcomes.
As the blockchain and decentralized finance (DeFi) ecosystems continue to expand and mature, rug pull scams involving meme coins are occurring with increasing frequency, posing a threat to the security of investors' assets and the healthy development of the industry. Rug Pull scams are characterized by extremely low deployment costs, covert execution, rapid fund transfers, and high detection difficulty. Traditional manual reviews or fixed rules struggle to meet real-time early warning requirements, and existing detection methods generally suffer from issues such as a single feature dimension, inadequate handling of class imbalance, and weak model generalization and interpretability. To address these shortcomings, this paper focuses on the detection of Ethereum-based rug pull scams. First, we clarify their definitions, types, and harm mechanisms, and construct a multi-dimensional feature system based on dimensions such as malicious smart contract design, on-chain transaction anomalies, liquidity manipulation, and social media disclosures. Next, using the "Second Uncle Coin"(token symbol: BOBU) case as an example, we reconstruct the attack process and derive quantitative detection metrics. Subsequently, a risk detection model based on a Multi-Layer Perceptron (MLP) is designed. We employ a combined strategy of SMOTE oversampling and Focal Loss to address the issue of sample imbalance, dynamically search for optimal thresholds to balance precision and recall, and incorporate gradient pruning and early stopping to enhance training stability. Experiments show that the model achieves an accuracy of 0.927, an F1 score of 0.787, and an AUC-ROC of 0.952 on the test set, outperforming traditional methods. Finally, a visualizable web-based detection system is developed using the Flask framework, enabling batch risk assessment, high-risk ranking display, and result export functions.
Blockchain technology, initially developed as a backbone for cryptocurrencies, has rapidly expanded into broader domains of finance and business. Its unique attributes – transparency, decentralization, immutability, and enhanced security – offer solutions to persistent challenges in financial services. This chapter examines blockchain applications beyond cryptocurrency, focusing on its role in transforming financial services such as Know Your Customer (KYC), cross-border payments, and compliance. A case-based exploration of blockchain-enabled KYC demonstrates how distributed ledgers can streamline identity verification while ensuring trust and efficiency. The chapter also outlines benefits, limitations, and potential applications, contributing to a holistic understanding for policymakers, financial institutions, researchers, and practitioners.
This study aims to provide a comprehensive science mapping and bibliometric analysis of the FinTech landscape within Islamic banking and finance. It deciphers the intellectual structure and thematic evolution of the field during the transformative window from 2017 to early 2026. Methodology: Utilizing the Scopus database, a dataset of 725 scholarly documents was extracted and analyzed. The research employs a multi-tool approach, integrating R-Bibliometrix (Biblioshiny) for longitudinal performance analysis and VOSviewer for visualizing keyword co-occurrence and institutional collaboration networks. The PRISMA 2020 protocol was followed to ensure methodological transparency. Findings. The results reveal an exponential surge in scientific production, characterized by an impressive annual growth rate of 28.42%. Malaysia and Indonesia emerge as the primary global knowledge hubs, with the International Islamic University Malaysia leading institutional contributions. The analysis identifies three core intellectual clusters: (1) Blockchain and Cryptocurrencies, (2) AI and Regulatory Compliance, and (3) Financial Inclusion and Institutional Stability. Thematic evolution indicates a strategic shift from basic FinTech adoption toward advanced applications in Artificial Intelligence, Ethical Technology, and the Sustainable Development Goals (SDGs). Originality,
This paper investigates whether prediction market settlements create incentives for temporary price pressure in Bitcoin spot markets. Using high-frequency data from February 2025 to January 2026 and actual contract-level data from Polymarket and Kalshi to identify economically relevant contract strikes, we document basis divergence between settlement oracle exchanges (Coinbase) and non-constituent exchanges (Binance) during expiry windows. Employing a difference-in-differences framework with month fixed effects, we find that a one standard deviation increase in strike proximity is associated with a 6.7 basis point constituent exchange price deviation during settlement windows. The estimate is precise under the baseline minute-level HAC specification, while exact paired-month permutation inference based on 12 settlement events yields p=0.0256; equal-weight event aggregation produces a larger negative estimate, indicating event heterogeneity. Monthly directional patterns are suggestive, though stricter event-level and above-versus-below-strike tests provide mixed evidence on directional asymmetry. Taken together, these findings provide reduced-form evidence consistent with settlement-related incentives and may raise broader settlement-design considerations for decentralized financial systems. However, the analysis does not directly observe trader intent or the underlying mechanism.
Shapour Shiranifar, Sayyed Mohammad Reza Davoodi, Saeid Aghasi
Purpose: This study aimed to identify and validate the factors influencing the transfer of Blockchain-based services in the digital transformation process of banks. The present study seeks to answer the fundamental question of how a comprehensive framework can be designed to facilitate the successful adoption and implementation of Blockchain technology in banking environments.Methodology: This study used a mixed qualitative approach combining content analysis and the Delphi method. In the first phase, semi-structured interviews were conducted with 20 experts from Saderat Bank of Iran, fintech companies, and IT service providers. The resulting data were analyzed using thematic content analysis, yielding 17 key factors across six thematic areas. These factors were evaluated, and a consensus was reached across three Delphi rounds involving 15 experts. The Delphi process ended with an agreement level of 80% as a reliability criterion.Findings: Components such as interoperability (92%), scalability (88%), digital governance (94%), change management capacity (90%), and customer-centric innovation (91%) play a pivotal role in successful technology transfer. It was found that Blockchain adoption alone will not lead to improved performance unless strong dynamic capabilities and organizational readiness support it. Among the most critical challenges identified are resistance to change (85%), inadequate technical infrastructure (82%), regulatory challenges (79%), and data privacy restrictions (87%). Based on the final findings, success in Blockchain technology transfer requires simultaneous attention to three key dimensions: a) the technical dimension by prioritizing system interoperability and solution scalability; b) the organizational dimension by focusing on developing dynamic capabilities and creating a culture of innovation; c) the environmental dimension by reforming regulatory frameworks and developing security standards. It is suggested that banks invest in specialized employee training, develop a data governance strategy, and partner with fintech startups to pave the way for the successful implementation of this technology.Originality/Value: This study bridges the gap between academic literature and management practice by providing a conceptual and validated framework for decision-makers. The principal value of this research is to outline the essential components for effective and sustainable technology transfer in digitally evolving institutions. This framework can be used as a guide for banks and financial institutions in successfully implementing Blockchain-based solutions. The findings of this study can also serve as a basis for future research on innovative applications of Blockchain in the financial services sector.
This chapter explores the transformative role of Financial Technology (FinTech) in advancing green finance, a crucial component in addressing global sustainability challenges. By integrating technologies such as blockchain, artificial intelligence (AI), big data analytics, and smart contracts, FinTech facilitates the efficient allocation of capital towards sustainable projects. The chapter examines how these innovations enhance transparency, optimize risk assessment, and enable decentralized financing models like peer-to-peer energy trading and tokenization. Additionally, it addresses the challenges posed by greenwashing, market volatility, and regulatory uncertainty, while highlighting the future opportunities for growth in green finance. Ultimately, the chapter underscores the potential of FinTech to drive systemic change and promote a low-carbon, sustainable economy.
This chapter explores the transformative potential of blockchain and artificial intelligence (AI) in revolutionizing green finance. It begins by examining the role of digital transformation in driving sustainable financial practices, highlighting the integration of blockchain and AI. The chapter delves into blockchain's applications in enhancing transparency, traceability, and security within green finance, particularly through smart contracts and decentralized finance solutions. It further discusses AI's contributions to improving risk assessment, ESG evaluation, and combating greenwashing. The synergies between blockchain and AI are explored, showing how their combined use optimizes sustainability-focused investments. Additionally, the chapter addresses regulatory and ethical considerations surrounding these technologies. Finally, it discusses emerging trends and opportunities in green finance, providing insights into the future of sustainable financial systems driven by technological innovation.
The rapid increase in cryptocurrency adoption among Generation Z in Indonesia has raised concerns regarding investment decision-making in highly volatile digital asset markets. This study examines the influence of herding behavior, social media exposure, and fear of missing out (FOMO) on cryptocurrency investment decisions, with financial literacy as a moderating variable. A quantitative approach was employed using survey data from 200 Generation Z cryptocurrency investors in Pontianak City. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The results show that herding behavior and social media significantly influence investment decisions. Fear of missing out also affects investor decision-making. Financial literacy moderates the relationship between herding behavior and investment decisions as well as between social media and investment decisions, but does not moderate the relationship between FOMO and investment decisions. These findings indicate that cryptocurrency investment decisions among Generation Z are influenced by social interactions and emotional biases.
Diana Bonilla Guzmán, Sofía de las Nieves García Gámez, Rubén Mora-Ruano, Alvaro-Antonio Salas-Suárez
This study aims to identify the extent to which a country's level of governance implicitly determines and encourages the use of cryptocurrencies, and the main elements associated with the use of alternative currencies to traditional ones. The methodology used is a descriptive analysis of the variables, an econometric analysis through an ANOVA, and the application of a truncated regression model, which aims to bring the research closer to the possible correlation between governance indicators and the rate of adoption of cryptocurrencies. The study concludes that countries with low levels of governance are directly related to the greater adoption of cryptocurrencies. To the best of our knowledge, this study is the first to analyse the relationship between cryptocurrency adoption and institutional governance by comparing two regions with different levels of development. The research is limited by the existence of other factors that influence the analytical framework of cryptocurrency adoption, but the availability of data has allowed the present study to focus on governance aspects. Now, despite the fact that the governance indicators present a global analysis in terms of their measurement, the relevant aspects of each country are not specified. The adoption of cryptocurrencies in some countries may not be strongly related to governance aspects but rather to the friendly regulations that have been implemented.
As financial fraud becomes more sophisticated and financial services are increasingly digitized, artificial intelligence (AI) and machine learning are emerging as pivotal technologies for risk management and compliance. While research into AI-driven fraud detection is advancing rapidly, the intellectual structure and theoretical underpinnings remain fragmented. This paper provides a systematic review of 118 peer-reviewed articles published between 2015 and 2025, combining bibliometric science mapping with the SPAR-4-SLR protocol to ensure rigour, transparency and replicability. Through co-word network analysis, thematic mapping and conceptual clustering, the study traces the field’s evolution from rule-based systems to adaptive anomaly detection, explainable AI and compliance models, with a focus on digital payment ecosystems and blockchain-enabled applications. The analysis highlights key theoretical anchors, including Fraud Triangle Theory, Agency Theory, Game Theory, Trust and Signalling Theories and regulatory compliance perspectives. It also identifies underexplored areas such as federated learning, algorithmic auditing and cross-jurisdictional intelligence. By mapping theoretical foundations and thematic development, this study offers an evidence-based account of how AI in fraud detection has evolved. It concludes by proposing a future research agenda emphasizing transparency, ethical assurance and global governance alignment, advancing financial risk management through conceptual clarity, methodological guidance and actionable pathways for responsible AI adoption.
Financial Technology (FinTech) is reshaping the worldwide financial industry by introducing innovations like digital transactions, artificial intelligence (AI), blockchain, mobile banking, data analysis, and integrated finance. These advancements are improving the effectiveness, openness, and availability of financial services, fostering financial inclusion, and decreasing reliance on traditional banking systems. This research investigates how FinTech plays a crucial role in stimulating innovation, inclusivity, and digital change in the financial landscape. It also delves into the opportunities arising from digital financial services and the obstacles related to cybersecurity, data protection, adhering to regulations, and ethical considerations. The research is grounded in an examination of recent literature, industry studies, and policy papers to grasp present trends and future advancements in FinTech. The results indicate that FinTech has emerged as a vital facilitator of sustainable financial expansion and economic progress. The research offers valuable perspectives for scholars, decision-makers, financial organizations, and industry professionals to comprehend the direction of digital finance.
Cryptocurrency has emerged as one of the most significant developments to accompany the digitization of global finance, and its footprint in India has expanded rapidly despite an unsettled regulatory environment. This paper examines how Indian investors perceive the opportunities and risks associated with cryptocurrency and blockchain technology, and evaluates whether their level of awareness shapes that perception. A structured questionnaire survey was administered to 158 respondents drawn from different age groups, educational backgrounds, occupations, and income levels in Karnataka, and the resulting data were analyzed using percentage analysis, frequency distribution, and the Chi-square test of independence. The findings indicate that a large majority of respondents, particularly those aged 21-30, view cryptocurrency and blockchain as tools capable of improving transparency, financial inclusion, and entrepreneurship, while simultaneously expressing concern over price volatility, cybersecurity threats, and unclear taxation rules. The Chi-square test confirmed a statistically significant association between investor awareness and perception of cryptocurrency (calculated value 19.41 against a critical value of 9.488 at 4 degrees of freedom and the 5 percent level of significance), leading to rejection of the null hypothesis. The study concludes that a clear, balanced regulatory framework combined with investor-education initiatives would allow India to capture the innovation potential of digital assets while containing the risks associated with their adoption.
Alternative finance platforms, including crowdfunding, peer-to-peer lending, equity-based platforms, and token-based fundraising mechanisms, have become important channels for financing entrepreneurial, social, and investment-oriented initiatives. Yet their reliance on digital intermediation, dispersed participation, and information asymmetry creates opportunities for fraud, undermining trust, investor protection, and platform sustainability. This study provides a systematic review of fraud detection and prevention in alternative finance, with crowdfunding emerging as the most extensively represented empirical domain. Methodologically, the paper combines a PRISMA-guided systematic literature review with a hybrid topic-modeling strategy that integrates neural topic modeling and probabilistic refinement, thereby supporting both transparent corpus selection and data-driven thematic synthesis. The findings show that Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and blockchain-based mechanisms are recurrently discussed as promising tools for detecting, preventing, or mitigating fraud. AI and ML approaches are mainly used to identify anomalies, suspicious textual patterns, behavioral signals, and transaction irregularities, while blockchain-based approaches are associated with transparency, traceability, smart contracts, and conditional fund release. The review also shows that fraud differs across alternative finance models, ranging from campaign misrepresentation and intentional and premeditated non-delivery in crowdfunding to borrower or platform misreporting in lending-based models and misleading disclosures or white-paper manipulation in ICO/STO contexts. A central challenge across the literature is the scarcity of labeled fraud data, which limits the use and benchmarking of supervised ML models. Overall, this study contributes by linking a reproducible hybrid SLR methodology to a structured synthesis of fraud types, platform-specific vulnerabilities, and AI-, ML-, and blockchain-based detection strategies in alternative finance.
This paper seeks to develop an empirically tested theoretical model that measures the block chain related awareness, confidence, and perceived relevance regarding finances among employees in the Turkish financial services sector. From the existing literature on blockchain adoption, the acceptance of fintech, and trust-based investment behavior, the authors developed an initial item pool consisting of 14 items. Content validation was done through experts followed by a pilot. Primary data was collected from 450 finance professionals working in the banking, treasury, risk, and accounting departments of different companies within Istanbul. The questionnaire was filled out by the respondents during the period March to April 2025 and was distributed online. Internal consistency was calculated using Cronbach’s alpha coefficient, while the structure of the underlying scale was investigated by Principal component analysis with oblique rotation. This analysis was complemented with item analysis through corrected item-total correlations and calculation of communalities. The data quality for conducting factor analysis were validated by KMO and Bartlett’s test of sphericity. From the results of the two-factor solution, the total variance explained was 85.83%. The first factor covered perceptions pertaining to blockchain awareness and informational engagement while the second predominately covered confidence in blockchains financial functionality and trustworthiness. The final structure is comprised of 14 items that have high loadings and little redundancy. The results indicate that the scale is not only clear-cut conceptually and statistically, but also provides a consistent measure for further studies regarding the perception and acceptance of technology in the finance domain.
As the growth of the FinTech platforms continues, there is an increasing demand for intelligent, secure and traceable solutions that can provide real-time detection of fraudulent transactions and shield financial records from manipulation. In this research, an Artificial Intelligence-powered blockchain framework, combining machine learning for fraud detection and permissioned blockchain for validation, was proposed. It was found that ensemble models performed better than a linear baseline. The overall best balance of precision, specificity and F1 score was obtained with the Random Forest model, and the highest precision–recall was obtained with the Extra Trees model, with fraud recall slightly better. In addition, feature-importance analysis revealed a small number of transaction attributes, which were anonymised, that most significantly affected fraud classification. The chosen model was then connected to a prototype of a chained hash blockchain that preserved the hashes of transactions, the time, the predicted probability of fraud, the validation result, and the version of the model. Through hash inconsistency, the prototype was able to detect any transaction modifications which might have been made on purpose and successfully ensured ledger integrity. The results illustrate how both AI and blockchain technologies complement each other. AI is effective in detecting fraud accurately and on time, and blockchain enhances the traceability, auditability and tamper resistance of transactions.