Cryptocurrencies originate from critical reflections on the traditional monetary system. Supported by blockchain technology, they break the shackles of the traditional financial system via decentralization. While cryptocurrencies bring prospects for financial innovation, they also induce latent risks including market volatility and cross-border regulatory conflicts. Taking cryptocurrencies as the research object, this paper elaborates on their basic theories, clarifies their asset attribute rather than legal tender, and identifies decentralization as their core feature. It sorts out China’s existing financial supervision practices and the prominent dilemmas of legal governance triggered by cryptocurrencies, and compares differentiated regulatory systems of the European Union, Japan and the United States. Finally, this paper puts forward targeted legal governance paths compatible with China’s national conditions from three dimensions: clarifying supervision responsibilities, optimizing tax collection and administration, and tackling stablecoin risks, so as to provide theoretical support and practical references for promoting law-based governance of the socialist financial system with Chinese characteristics.
Artificial Intelligence (AI) has transformed the fintech services and created a robust business canvas elevating various personalized and automated services with lightning speed satisfying ever changing needs of a person and market. AI triggered financial models and Chatbots are changing the investment environment in India. The quantum computing enabled with the AI is able to design tailor made risk management models in the financial services front. On the other hand, AI is empowering the fintech models face the challenges of frauds and cybercrimes. Automated documents and know your customer verifications, e signatures, faster clearings are some of the inventions in the Fintech arena supported by AI driven technologies. Credit score calculations and data maintenance of customers, identification of risks in finance and credit portfolios are other tools minimizing the frauds in lending portfolios of the banking and non-banking institutions. Market, investors behaviours, funds-flow trends’ analysis are other important operational efficiency tools that the bankers enjoying. The decentralized platforms, mechanized and smarter modes of financial services designed by the technology are contributing to the growth of the financial services including the insurance, capital markets. Banking services blessed with technological inventions are transforming the traditional banking into new-age businesses by reducing the operational cost and minimized operational time. The digital payments, real time credit of cheques, UPI payments are contributing for secured transactions, faster mode of authentications, encryptions and many more. The dependence on natural human resources is becoming less even after with expanding base of customers and variety of financial services. Anytime, anywhere banking models, digital platforms, and digital channels dedicated for the financial transactions are other contributions of the technological developments. The Fintech is witnessing a remarkable transformation with the induction of AI and other technologies into designing, operational and distributive models of financial products. Inventions in this field of financial sector are continuous. Emerging computing technologies are adding value to fintech facilitating faster developments in the services sector and contributing the growth of the economy.
Open access
FinTech, Crowdfunding, Digital Finance
Innovations and Analysis in Business and Education
This study examines how fairness perceptions influence cryptocurrency investors and market behavior, using the Ultimatum Game as the conceptual anchor. We specify a framework that links distributive, procedural, and informational justice to buy and sell intentions, holding horizons, and community participation, with emotions such as anger and trust acting as mediators. To address the distinction between investor-level perceptions and market-level volatility, the revised design combines online survey responses with token-day trading data, event indicators, on-chain concentration measures, disclosure records, and community-activity proxies. Survey data are used to test individual behavioral and emotional channels, whereas market data are used to estimate abnormal returns, realized volatility, and difference-in-differences effects around fairness shocks. The revised analysis therefore avoids inferring market volatility directly from respondent opinions. Findings indicate that perceived unfairness raises selling intention and shortens holding horizons, while objectively observed fairness shocks are associated with higher realized volatility. Heterogeneity checks show stronger effects for assets with high decentralization and active communities. The study offers design levers for transparent rules, governance safeguards, and clear disclosure cadence.
The paper focuses on the interaction between the fields of financial technologies and sustainable development, highlighting the contribution of technological advancements in the financial field towards economic development, social inclusion, and environmental protection. Financial technologies (FinTech), utilizing blockchain, mobile banking, and artificial intelligence technologies, have completely transformed the world of finances making it more efficient, transparent, and accessible. The application of FinTech in sustainability projects is essential for the accomplishment of important SDGs such as financial inclusion, poverty reduction, and the establishment of green finance mechanisms, including carbon trade and green bonds. Yet, the study notes several barriers to the successful integration of the two spheres that can include regulatory uncertainty, data protection problems, and the problem of digital divide.
This article develops a finance-oriented conceptual assessment of Sui, an object-centric Layer-1 blockchain. The analysis draws on peer-reviewed research on scalability, smart contract execution, tokenomics, decentralized finance risk, market microstructure, sustainability, and regulation. It also uses a limited set of Sui-specific academic and official technical sources to interpret protocol design. The review focuses on three features: an object-centric state model that can support parallel execution when transaction states remain sufficiently partitioned; the Move language, which uses resource-oriented semantics to constrain selected asset-handling risks; and a directed acyclic graph-based consensus pipeline intended to reduce unnecessary coordination for suitable workloads. These features are linked to finance-relevant outcomes, including execution reliability, liquidity formation, adoption persistence, market resilience, and institutional investability. The assessment remains conditional. Shared-object contention may weaken realized performance, composability may preserve important classes of smart contract risk, and token emissions may dilute the value created by ecosystem growth. Regulatory uncertainty and sustainability scrutiny also influence the institutional perimeter of the asset. The article contributes an evaluation matrix, a conceptual framework, and a set of propositions for future empirical testing. No causal or statistical inference is claimed. The central conclusion is that Sui's architecture is economically relevant only when technical performance, assurance capacity, tokenomics discipline, and institutional conditions develop together. Received: 14 April 2026 | Revised: 8 July 2026 | Accepted: 27 July 2026 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Low Jun Yan: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft. Md Sharif Hassan: Methodology, Validation, Writing – review & editing, Supervision, Project administration. Nguyen Mai: Resources, Writing – original draft, Visualization.
The exploratory data analysis results provide important insights into the dataset characteristics that guide the design of the proposed AI-enabled blockchain framework. The class distribution graph shows a strong imbalance, with approximately 86.2% genuine samples and 13.8% forged samples, reflecting real-world conditions where fraudulent cases are relatively rare. This imbalance necessitates the use of robust machine learning strategies, such as class-weighted learning and advanced evaluation metrics beyond simple accuracy, to ensure reliable detection of forged instances. The file size distribution further indicates that most samples are lightweight, with an average size of 42.6 KB and a long-tailed distribution extending up to 295 KB, supporting the adoption of a hybrid on-chain/off-chain storage strategy to optimize blockchain storage costs and network performance. Dimensionality reduction and visualization results obtained using PCA and t-SNE highlight the complexity of the classification problem addressed in the proposed work. The PCA projection reveals partial overlap between genuine and forged samples, indicating that linear feature separation is insufficient for accurate classification. Similarly, the t-SNE visualization shows localized clustering of forged samples but noticeable overlap with genuine data, confirming the presence of non-linear relationships in the feature space. These observations justify the integration of deep learning models and ensemble classifiers within the AI layer to capture complex patterns and improve generalization. The image resolution distribution further demonstrates that most images fall within a consistent resolution range of approximately 300–700 pixels (width) and 200–550 pixels (height), ensuring stable model training while still requiring standardized preprocessing to handle resolution variability across training, validation, and test splits. Based on these data characteristics, the proposed AI-enabled blockchain framework is designed to deliver measurable improvements in performance, security, and efficiency. Experimental evaluation shows that the AI-driven valuation and classification modules achieve a fraud detection accuracy of 94.1%, with a precision of 91.6%, recall of 89.3%, and an F1-score of 90.4%, demonstrating reliable performance despite class imbalance. The blockchain layer achieves an average throughput of approximately 420 transactions per second with a confirmation latency of 2.6 seconds, while maintaining a low transaction cost of ₹18–₹25 per transaction through Layer-2 scaling and off-chain storage optimization. Smart contracts exhibit a 99.1% execution success rate and high vulnerability detection coverage during security analysis, validating the robustness of automated transaction execution. The expected outcomes of the proposed system include reduced transaction settlement time, enhanced fraud resistance, improved valuation transparency, and greater market accessibility through tokenization and fractional ownership. By combining AI-driven intelligence with blockchain-based trust and automation, the framework is expected to significantly reduce manual intervention, operational costs, and regulatory non-compliance risks in real estate transactions. Overall, the results and projections confirm that the proposed approach is well-suited for real-world deployment, offering a scalable, secure, and intelligent solution for next-generation real estate asset management systems.
Persuasive textual narratives, bogus visual evidence, disreputable update patterns and absent accountability systems are being increasingly used to deceive backers in fraudulent crowdfunding campaigns. Current fraud detection techniques are primarily based on static information, on text-only indicators, or on very shallow fusion of multimodal information, and they are not able to detect deceptive information that evolves over time or is inconsistent across different modalities. This study presents a Temporal Cross-Modal Trust Intelligence Framework to mitigate reward-based crowdfunding fraud that is explainable. The framework combines Hidden Method-of-Moments Markov modelling for latent temporal behaviour analysis, Polynomial Expansion Canonical Correlation Analysis for nonlinear text–image consistency evaluation and a Frequency-Gated GRU classifier to distinguish subtle drift in behaviour from sudden suspicious behaviour anomalies. Local Outlier Factor-based risk refinement is also added to detect rare and locally abnormal fraud patterns, and a blockchain-auditable layer ensures prediction outcomes are transparent and tamper-proof, enhancing the decision-making process. Experimental results on a multimodal crowdfunding dataset created from the Kickstarter platform show that the proposed model achieves better accuracy, recall, F1-score, ROC-AUC, PR-AUC, and calibration reliability than conventional multimodal, transformer-based, and recurrent neural network models and classical machine learning. The results validate the proposed solution, which is built on the four temporal dynamics, cross-modal consistency, anomaly refinement and auditability, to be a comprehensive and interpretable solution for detecting early crowdfunding fraud.
The rapid digitalization of financial services has increased the importance of blockchain, artificial intelligence (AI), and cybersecurity in strengthening operational efficiency, transaction security, fraud detection, and financial risk management. This study examines the relationship between blockchain technology adoption, AI-driven financial service adoption, cybersecurity capability, and financial risk reduction in the Indian financial-services context. Drawing on recent literature on blockchain-enabled financial services, AI-based risk management, cybersecurity, and digital banking, the study develops an empirical framework linking technology adoption with financial risk management effectiveness. Primary data were considered from 157 respondents comprising banking professionals, financial-service employees, FinTech professionals, IT specialists, and finance managers in India. Data were analyzed using descriptive statistics, Cronbach’s alpha, Pearson correlation, multiple regression, and ANOVA. The illustrative results indicate that blockchain adoption, AI adoption, and cybersecurity capability are positively associated with financial risk reduction. The regression model explains approximately 64.2% of the variance in financial risk reduction, with AI adoption emerging as the strongest predictor, followed by cybersecurity capability and blockchain adoption. The findings suggest that Indian financial institutions should adopt an integrated technology strategy rather than treating blockchain, AI, and cybersecurity as independent technological investments. Strong governance, employee capabilities, cybersecurity controls, regulatory alignment, and responsible AI practices are essential for converting technology adoption into sustainable financial-risk reduction.
Feeroj Nasirkhan Pathan, Amarsingh Udhavrao Solanke, Mr. Wasim Taher Khan, Dr. Mangesh Manohar Dasare
The vision of Viksit Bharat 2047 seeks to transform India into a developed, inclusive, and globally competitive nation by the centenary of its independence. Achieving this vision requires a digitally enabled financial system that promotes innovation, expands financial inclusion, and supports sustainable economic growth. In this background, Financial Technology (FinTech) has emerged as a key driver of India's digital transformation. India's FinTech ecosystem has grown quickly with the support of Digital Public Infrastructure (DPI), including Aadhaar, Pradhan Mantri Jan Dhan Yojana (PMJDY), Unified Payments Interface (UPI), DigiLocker, India Stack and e-KYC. These initiatives have expanded access to financial services, accelerated digital payments, enhanced access to formal credit, strengthened public service delivery, and encouraged wider participation in the Indian economy. Emerging technologies such as artificial intelligence, blockchain, cloud computing, big data analytics, and application programming interfaces (APIs) have additionally enhanced the efficiency and accessibility of financial services. This chapter examines the role of FinTech in advancing the vision of Viksit Bharat 2047 by promoting financial inclusion, strengthening Digital Public Infrastructure, supporting entrepreneurship, improving governance, and fostering sustainable economic development. It also examines key challenges, that influence the long-term growth of the sector. It concludes that FinTech is more than a technological innovation; it is a strategic move of India's economic transformation.
Purpose Rapid technological advancement has accelerated the integration of financial technology (FinTech) into traditional banking systems. Banks have adopted digital payments, artificial intelligence, blockchain solutions and open banking frameworks, thereby increasing competition and prompting regulatory adaptation. This study conducts a theory guided systematic literature review and bibliometric analysis of FinTech banking research (2019–2024) to map the intellectual structure, thematic evolution and research gaps. Design/methodology/approach The review analyses 224 peer reviewed journal articles indexed in the Web of Science Core Collection. Using BibExcel and VOSviewer, the study employs co-citation analysis, keyword co-occurrence mapping, clustering techniques and temporal overlay analysis. The review protocol follows explicit search strings, inclusion criteria and screening procedures to enhance transparency and replicability. Findings Six major thematic domains emerge: competition and risk-taking dynamics, financial inclusion and regulatory boundaries, institutional technology integration, performance and efficiency outcomes, innovation and regulatory economics and digital transformation and adoption behaviour. Temporal analysis reveals a progression from adoption focused inquiry toward governance, competition and systemic stability debates. Despite increasing empirical sophistication, the field remains fragmented across behavioural, institutional and macroprudential levels. Originality/value This study embeds bibliometric mapping within a multi-level theoretical framework integrating diffusion, disruptive innovation and ecosystem perspectives. The research provides a critical synthesis of the evolving FinTech banking literature. The findings identify key research gaps, reveal emerging thematic patterns in FinTech banking research and outline directions for future research while offering implications for banking practitioners and regulators.
In the rapidly evolving landscape of financial technology (FinTech), the intersection of digital innovation capabilities (DICs) and Islamic social finance presents a fertile ground for enhancing sustainability in financial practices. This study employs a qualitative approach, specifically content analysis of existing literature sourced from journal databases. This theoretical review explores how DICs encompassing digitalization and digital transformation can influence the sustainability of Islamic social finance initiatives. Islamic social finance, rooted in principles of social justice and equitable distribution, aims to address socio-economic challenges while adhering to Shariah compliance. By synthesizing current literature and theoretical frameworks, this review elucidates the potential strategies in optimizing Islamic social finance mechanisms, improving transparency, efficiency, and reach. The analysis highlights key digital innovations, such as blockchain, artificial intelligence (AI), and cloud computing (CC). The review also proposes a conceptual model for integrating DICs with Islamic social finance to foster greater sustainability. This theoretical examination offers insights into how digital advancements can support the long-term goals of Islamic social finance, contributing to both economic development and social welfare.
The rapid growth of cryptocurrencies and increasing instability in traditional financial systems have significantly transformed global investment behaviour in recent years. In developing countries experiencing economic crises and currency depreciation, investors increasingly seek alternative financial assets that can preserve value and generate higher returns. Sri Lanka has recently experienced severe economic instability characterised by inflation, foreign-exchange shortages, sovereign debt problems, and rapid depreciation of the Sri Lankan rupee. Under these conditions, interest in cryptocurrency investment has increased, particularly among younger and technologically aware investors. Therefore, this study examines whether fiat currency devaluation shifts investment from the stock market to the cryptocurrency market among university students in Sri Lanka. The study adopts a quantitative research approach and uses primary data collected through a structured questionnaire from 150 final-year undergraduate students at the University of Sri Jayewardenepura. Stratified random sampling was used to select respondents from the Faculty of Humanities and Social Sciences, the Faculty of Management Studies and Commerce, and the Faculty of Applied Sciences. Descriptive statistics, chi-square analysis, and binary logistic regression were employed to analyse the relationship between rupee depreciation and cryptocurrency investment behaviour. The findings reveal that depreciation of the Sri Lankan rupee significantly influences investment decisions among university students. Most respondents perceived cryptocurrency investment as more profitable than stock-market investment during periods of economic uncertainty. The chi-square analysis identified significant relationships between cryptocurrency investment behaviour and age, income, stock-market investment, and perceptions of rupee depreciation. Furthermore, the binary logistic regression results confirmed that rupee depreciation positively and significantly affects cryptocurrency investment, whereas stock-market investment had a negative relationship with cryptocurrency investment behaviour. The study concludes that economic instability, declining confidence in fiat currency, and increasing awareness of digital financial systems encourage university students in Sri Lanka to shift their investment preferences from the traditional stock market to cryptocurrency.
Cahya Kamila Maharani, Relit Nur Edi, Ismail Septayanto Utama
The 4.0 Industrial Revolution has transformed the global economic landscape through the digitalization of financial services, trade, and industrial activities. This transformation has accelerated the growth of the Halal Market, making it one of the fastest-growing economic sectors, driven by the expanding Muslim population, increasing awareness of halal consumption, and rising demand for ethical and sustainable products. In this context, Islamic Fintech has emerged as a strategic innovation that integrates digital financial technologies with the principles of Islamic law and economics. Although studies on Sharia Fintech and the halal industry have grown substantially, research integrating these two domains from the perspectives of Islamic law and Islamic economics remains limited. This study aims to examine the strategic role of Islamic Fintech in strengthening the global Halal Market through an interconnective analytical framework. Employing a qualitative library research approach, the study critically analyzes scholarly literature, regulatory documents, international reports, and previous empirical studies. The findings indicate that Sharia Fintech enhances financial inclusion, transparency, halal traceability, value chain efficiency, and digital governance through the adoption of blockchain, artificial intelligence, smart contracts, and digital payment systems. These innovations contribute to the realization of Maqashid al-Shariah, particularly the protection of wealth (ḥifẓ al-māl) and the promotion of public welfare (maṣlaḥah). The novelty of this study lies in the development of a comprehensive conceptual framework that integrates Islamic law, Islamic economics, digital financial innovation, and Halal Market governance into a unified analytical model.
Rejaul Karim, Md. Mustaqim Roshid, Bablu Kumar Dhar, Abdul Waaje
This study explores the evolving role of green financial technology (Fintech) in sustainability-oriented financial innovation, with a particular focus on climate finance, digital innovation, and environmental governance. Using bibliometric methods, we analyze 72 peer-reviewed publications indexed in Scopus from 2019 to 2024 to map the intellectual structure and emerging trends of green Fintech research. Key technological domains, including blockchain-based carbon markets, AI-powered ESG analytics, and green digital payment systems, are frequently associated in the literature with several Sustainable Development Goals (SDGs), notably SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 8 (Decent Work and Economic Growth). This analysis reveals how digital financial innovations are conceptualized as mechanisms for facilitating access to green capital, strengthening carbon credit ecosystems, and enhancing transparency in climate-aligned investment. However, persistent barriers such as fragmented regulatory frameworks, cybersecurity risks, and digital divides are recurrently identified in the literature as constraints, particularly in emerging economies. Interpreted through Institutional Theory and Stakeholder Theory, the study highlights the importance of coordinated policy innovation, inclusive digital infrastructure, and harmonized ESG standards in shaping the diffusion and governance of green Fintech solutions. By positioning theory as an interpretive lens rather than an empirical test , this research offers a theory-informed, data-driven synthesis that contributes to the growing interdisciplinary discourse on digital finance as a potential enabler of low-carbon, inclusive, and resilient sustainability transitions.
Research methodology This case was developed using secondary research methods. Information was collected from publicly available sources including company annual reports, investor presentations, regulatory publications, analyst commentary and reputable media outlets such as Bloomberg and the Financial Times. Industry reports from consulting organizations and international institutions were also used to contextualize developments in the global fintech ecosystem. No primary interviews or confidential company data were used in preparing this case. This case contains no disguised information; all organizations, individuals, financial data and events referenced are real and drawn exclusively from publicly available sources. As this case was developed entirely from publicly available secondary sources and involved no human participants, institutional ethics review board approval was not required. This case offers a distinctive contribution to the published teaching case literature on fintech strategy and platform renewal. While existing cases on fintech strategy tend to focus on a single dimension of disruption, such as Stripe’s developer-led payment infrastructure, Apple’s device ecosystem lock-in or the regulatory challenges facing individual cryptocurrency platforms, this case uniquely combines three simultaneous strategic challenges within a single narrative: the deployment of artificial intelligence (AI)-enabled commerce capabilities, the early-stage integration of stablecoin infrastructure through PYUSD and the organizational complexity created by a decade of acquisition-driven expansion across Venmo, Braintree, Honey and Xoom. No published case in the fintech or platform strategy literature, to the author’s knowledge, addresses this particular combination of AI governance, digital asset experimentation and acquisition integration fragmentation within the context of a large, regulated incumbent facing embedded finance disruption. This case therefore provides a pedagogically distinctive vehicle for exploring strategic renewal in digitally regulated industries. Case overview/synopsis This case places students in the position of Alex Chriss, the newly appointed Chief Executive Officer of PayPal, as he prepares for a critical board strategy review in October 2024. Despite leading one of the world’s largest digital payments platforms, processing over $1.5tn in total payment volume annually and serving more than 430 million active accounts globally, Chriss inherited a company under significant strategic pressure. Revenue growth had slowed, share price performance was deteriorating and analysts were increasingly describing PayPal as a mature incumbent rather than a platform innovator. The organizational inflection point is a dilemma with no comfortable resolution. Chriss must choose a strategic direction to present to the board ahead of PayPal’s quarterly earnings announcement, but every available path carries a different form of risk. Moving aggressively into AI and decentralized finance offers innovation momentum but risks operational disruption and regulatory overexposure across dozens of regulated markets. Consolidating the core platform is operationally safer but risks confirming the narrative that PayPal has lost its competitive edge. Pursuing fintech partnerships accelerates capability building but reduces strategic control. Leading on Environmental, Social, and Governance (ESG) and responsible digital finance builds long-term legitimacy but delivers limited near-term growth. Investors want visible transformation. Merchants need stability. Regulators demand discipline. Employees are already stretched from restructuring. No single option satisfies all of these demands simultaneously, and PayPal’s resource constraints mean Chriss cannot pursue all four directions at once. The case draws on dynamic capabilities theory, the resource-based view, platform ecosystem theory, stakeholder theory and embedded finance literature, and requires no prior knowledge of fintech or payment systems. Complexity academic level This case is appropriate for MBA and Executive MBA courses in strategic management, innovation management and financial technology. It may also be used in final-year undergraduate courses addressing platform strategy, digital transformation or fintech ecosystems. The case is suitable for both in-person and online classroom delivery.
FinTech, Crowdfunding, Digital Finance
Innovations and Analysis in Business and Education
Initial Coin Offerings (ICOs) have emerged as an innovative mechanism for raising capital, particularly for blockchain-based projects. However, the lack of regulatory oversight and the prevalence of low-quality information raise important questions about what truly drives ICO success. While existing literature focuses predominantly on technical and signalling variables, the role of investor decision-making remains theoretically underdeveloped and empirically underexplored. This paper addresses this gap by pursuing two objectives. First, we identify the drivers of ICO success using a probit model applied to an original sample of 535 ICOs conducted between January 2016 and May 2021. Second, we investigate investor decision-making patterns using a novel dataset of 200 active crypto-forum participants over the same period. Our results have three main findings, though with modest statistical strength than initially estimated. (I) Marketing channels are the most consistent predictor of ICO success across the sample period, clearing conventional significance thresholds only in the pooled sample (z = 1.90, p<0.10), with each additional channel raising the probability of soft-cap achievement by approximately 1.0 percentage point. (II) Team presentation and video presentation show no meaningful influence on success in any period. (III) Whitepaper availability is not statistically significant even in pooled sample, reinforcing rather than qualifying its irrelevance as a predictor; the number of accepted cryptocurrency price speculation rather than project fundamentals, consistent with mood and sentiment dominating information-based decision making in ICO markets, though this finding should be read alongside the data limitations discussed in 3.B. These findings contribute to the behavioural finance literature by providing an operational definition of ‘investor mood’ and demonstrating its empirical relevance in crypto markets. We conclude that understanding investor mood is not a secondary question but a necessary complement to technical analysis of ICO success.
Tokenized representations of cash-like instruments, comprising stablecoins, tokenized money market funds, and tokenized real-world assets, are increasingly positioned as core on-chain financial infrastructure, yet empirical evidence on how these instruments behave in practice remains limited. This paper reports a comparative empirical examination of public transaction-level blockchain data, covering adoption patterns, usage dynamics, and operational characteristics across three parallel case studies: USDC (stablecoin, Circle), BENJI (tokenized money market fund, Franklin Templeton), and BUIDL (tokenized U.S. Treasury, BlackRock via Securitize). On-chain metrics covering issuance and redemption activity, transfer behavior, wallet concentration, velocity proxies, and cross-chain deployment are interpreted against a four-layer reference architecture (asset representation, control-plane governance, settlement and finality, and composability). Results reveal systematic behavioral differences aligned with product intent and governance design: stablecoins function as high-velocity settlement instruments with broad address distribution, while tokenized investment products exhibit batch-oriented issuance, low circulation intensity, and concentrated holdings consistent with institutional custody and regulatory constraints. A live-pipeline extraction for BUIDL on Ethereum over the 90-day window ending 31 January 2026 yields a holder-level Gini coefficient of 0.8706 with a bootstrap 95% confidence interval of [0.7672, 0.9208] and a top-ten concentration share of 98.96%. Cross-chain deployment expands access but preserves reliance on dominant settlement layers. These patterns constitute an evidence-based framework for evaluating tokenized finance as production-grade financial market infrastructure.
Decentralised finance (DeFi) is a relatively new trend in finance that uses blockchain, smart contracts, and distributed ledger technology to offer financial services in a decentralised manner. Although scholars have made many theoretical advances in decentralised finance in recent years, knowledge of its theoretical structure and future research areas remains limited. This is why this study provides a bibliometric analysis of 1002 articles on DeFi published in Scopus between 2012 and 2026. The analysis uses performance analysis and a science mapping approach based on citation analysis, co-authorship, bibliographic coupling and keyword co-occurrence analysis. The results reveal a remarkably high annual growth rate of 39.34% and DeFi’s dynamism and interdisciplinary nature. The three main countries involved in DeFi research are the USA, China, and the UK. Management Science, Energy Economics and Technological Forecasting and Social Change became the main scientific journals for disseminating knowledge about DeFi. Analysis of thematic changes showed a transition of scientific interests from blockchain and cryptocurrencies to new topics, like artificial intelligence, sustainability, governance, and financial inclusion. Overall, the current study provides a better understanding of the intellectual, conceptual, and social basis of DeFi and highlights possible research areas in the use of artificial intelligence in DeFi, decentralised governance, and sustainable digital financial system development.
This informative document explores the evolving digital asset landscape, covering cryptocurrency, NFTs, blockchain technology, Web3, and emerging market trends. It provides readers with practical insights into digital ownership, market developments, and the importance of research when evaluating opportunities in the growing blockchain economy. Collective Shift
Decentralized Finance (DeFi) refers to an open financial ecosystem built on blockchain technology that does not require the participation of centralized institutions. The technology and operational mechanisms it employs represent a significant "paradigm mismatch" with the current financial regulatory framework. This paper examines the comprehensive impact of DeFi on existing financial regulation from multiple perspectives, including the blurring of regulatory authority and a lack of accountability; the difficulty in identifying regulatory targets and the ambiguity in determining their nature; the ineffectiveness of regulatory rules and the absence of relevant provisions; overlapping jurisdictions, and difficulties in enforcement. Through a comparative study of regulatory experiences in the United States, Europe, and other regions, this paper proposes solutions such as shifting the existing regulatory philosophy toward functional regulation, embedding compliance requirements into the underlying technology at the institutional level, and strengthening international cooperation at the operational level, while also discussing the specific context in China. This paper identifies a threefold paradigm mismatch between decentralized finance and traditional financial regulation, giving rise to multiple regulatory challenges such as difficulties in holding entities accountable, ambiguity in defining regulatory targets, ineffective regulatory rules, and obstacles to cross-border enforcement. A comparison of regulatory practices in the U.S. and Europe reveals that it is difficult for any single country to independently manage the risks associated with globalized DeFi.
Tapasi Bhattacharjee, Amalendu Singha Mahapatra, Dipika Pramanik
Educational crowdfunding has emerged as a promising approach to provide educational resources to underprivileged communities. Conventional systems often suffer from a lack of transparency, weak accountability, inefficient allocation of funds, and inadequate traceability of resource use. To address these issues, the present study proposes an intelligent and efficient educational supply chain management system, “EduDonateBlock.” It uses a blockchain-based crowdfunding framework to ensure transparency, accountability, and efficiency. Decentralization, immutability, and verifiable transactions are supported in educational campaigns. The entire workflow is decomposed into modular smart contracts. These are the identity and access contract (IAC), campaign and donation contract (CDC), verification and allocation contract (VAC), and supply chain and tracking contract (SCTC). These contracts are designed to ensure traceability, accountability, and efficient resource allocation among donors, educational institutions, and administrators. The mathematical framework of EduDonateBlock determines the optimal level of blockchain transparency. This minimizes the Total Expected Cost (TEC) of smart-contract operations. Numerical analysis identifies an optimal transparency level of 87.16% on-chain integration. This finding underscores the economic trade-off between transaction costs and the benefits of automation, operational efficiency, and reduced fraud risk. The proposed framework achieves a campaign success probability of 89.45% and an institutional payoff of Rs. 11,335.99. Furthermore, executing smart contracts requires 0.0044 ETH, and the average latency remains at 6.25 s. The simulation results show that EduDonateBlock offers a more efficient, reliable, and transparent solution for decentralized educational crowdfunding and socially impactful digital supply chains.