This study examines the structural interplay between Decentralized Finance (DeFi) innovations and adaptive regulatory sandbox architectures within modern financial systems. The rapid proliferation of disintermediated protocols-engineered through smart contracts, Automated Market Makers (AMMs), decentralized lending pools, and algorithmic governance-fundamentally challenges traditional supervisory paradigms anchored in centralized, identifiable financial intermediaries. Utilizing the theoretical foundations of financial intermediation, transaction cost economics, and institutional regulatory design, this paper evaluates how regulatory sandboxes serve as dynamic policy testing grounds to reconcile technological experimentation with systemic stability and investor protection. The findings indicate that deploying specialized DeFi sandbox cohorts, augmented by embedded supervision and cryptographic compliance tools, substantially lowers regulatory uncertainty, prevents systemic contagion, and establishes an evidence-based pathway toward resilient decentralized financial governance.
This paper explores stability, volatility and structural change in Bitcoin using an Archive Framework that distinguishes between normal ("Archive") and abnormal ("Evental") market states. Using more than eleven years of daily Bitcoin data, the study investigates whether measures of structural tension help explain periods of market instability. While most predictive relationships prove weak after correcting for methodological bias, the analysis identifies a significant shift in Bitcoin's behaviour during the post-ETF era, characterised by lower realised volatility and substantially greater occupancy of structurally stable market states. The findings suggest that the principal value of the Archive Framework may lie in describing market regimes rather than predicting them.
The increasing reliance on digital banking solutions has significantly transformed financial services, with Automated1Teller1Machine (ATM) transactions playing a critical role in banking operations. This study examines the impact of ATM transactions on the1 financial performance of Deposit Money Banks (DMBs) in Nigeria, utilizing a Robust Least Squares (RLS) estimation technique to analyze quarterly data from 2009 to 2023. The study employs Return on Assets (ROA), Return on Equity (ROE), and Capital Adequacy Ratio1 (CAR) as proxies for financial performance. The findings reveal that while ATM transactions exhibit a statistically insignificant effect on ROA and ROE, they have a significant positive relationship with CAR, suggesting that ATM services contribute more to the financial stability of banks than to their profitability. The study also highlights key challenges associated with ATM usage, including network failures, fraud risks, and high maintenance costs, which may limit its full potential in enhancing bank performance. Given these findings, the study recommends that Nigerian banks strengthen ATM infrastructure, enhance cybersecurity measures, integrate emerging technologies such as blockchain, and implement customer education programs to optimize ATM efficiency and mitigate associated risks. These measures will enhance financial inclusion, improve customer satisfaction, and sustain the overall financial health of deposit money banks in Nigeria.
Its novelty lies in: (a) formalizing seven explicit propositions (P1–P7) with explicit why-how-formal statement structure for each construct-to-construct relationship; (b) theorizing a differentiated serial mediation structure—full mediation in the upstream technical-structural segment (P1–P3) and partial mediation in the downstream relational-governance segment (P4–P7); (c) reversing the P6 direction to Sharia Compliance → Stakeholder Trust on Signaling Theory grounds; (d) defining Institutional Performance as a four-dimensional construct (financial, Sharia legitimacy, stakeholder value, and governance quality); and (e) specifying boundary conditions delimiting the framework’s scope to permissioned blockchain environments and high-religiosity market contexts.
This paper investigates how cryptocurrency advertising and social media ecosystems shape Indian teenagers’ perceptions of risk, trust and opportunity in digital assets. Against a backdrop of low youth financial literacy and rising Gen Z participation in crypto investing globally, understanding how young people interpret persuasive financial content is increasingly relevant. The study addresses a gap in existing work, which largely focuses on adult retail investors in developed markets and text-heavy platforms, by examining how Indian adolescents and young adults (13–25) encounter and evaluate highly visual, youth-facing crypto promotions. A qualitative-dominant mixed-methods design is employed. Visual content analysis of nine high-visibility crypto campaigns on platforms such as YouTube and Instagram is combined with a short online survey of 27 Indian respondents aged 13–25. The ad coding captures colour, emotional framing, FOMO and “easy money” language, celebrity presence and the visibility of risk disclaimers, while the survey records perceived trustworthiness, risk, confusion, sources of information and self-reported confidence in understanding crypto. Findings show that the analysed campaigns systematically amplify reward cues, normalise speculative trading as simple and aspirational, and relegate risk warnings to low-salience text, often using bank-like or game-like framing that exploits conceptual gaps around regulation and product safety. Survey responses suggest that many teenagers recognise hype and misleading tropes yet still rely heavily on influencers and peers, report FOMO and express limited confidence in their own financial knowledge. The paper argues for stronger youth-oriented media-literacy interventions, stricter enforcement of advertising standards, and platform-level tools that foreground risk and sponsorship in crypto content aimed at or easily accessed by young audiences.
Open access
Impact of Technology on Adolescents
Consumer Behavior in Brand Consumption and Identification
The article examines the role of FinTech solutions in the transformation of international finance and their impact on the development of the global economy in the context of rapid digitalization and technological change. The study analyzes contemporary trends in the implementation of financial technologies in international settlements, payment systems, investment activities, lending, insurance services, and financial risk management. Particular attention is paid to the development of digital platforms, mobile banking, blockchain technologies, artificial intelligence, big data analytics, cloud computing, and distributed ledger technologies, which significantly influence the efficiency and accessibility of international financial services. The key opportunities created by FinTech for increasing the efficiency of cross-border financial transactions, reducing transaction costs, accelerating payment processing, and improving transparency in financial operations are identified. The study emphasizes the contribution of financial technologies to enhancing financial inclusion by expanding access to financial services for individuals and businesses, especially in developing countries and regions with limited banking infrastructure. The role of FinTech in facilitating the integration of national financial systems into the global financial space and strengthening international economic cooperation is substantiated. The article also outlines the main risks and challenges associated with the rapid expansion of FinTech solutions. These include cyber threats, data privacy concerns, operational vulnerabilities, regulatory fragmentation, technological dependence, money laundering risks, and potential threats to financial stability. The growing influence of global digital platforms and technology companies on international financial markets is considered, highlighting the need to balance innovation and regulatory oversight. The necessity of improving international regulation of the FinTech sector is substantiated in order to minimize systemic risks and prevent negative consequences for the global economy. Particular attention is devoted to the harmonization of approaches to licensing procedures, capital adequacy requirements, auditing standards, reporting obligations, consumer protection mechanisms, and risk management practices. The study highlights the importance of establishing common international standards for stress testing, supervisory cooperation, information exchange, and early warning mechanisms aimed at preventing financial crises and mitigating systemic shocks. Furthermore, the article emphasizes the need for coordinated international regulation of cryptocurrencies, stablecoins, central bank digital currencies, and tokenized assets in order to prevent illegal capital flows, tax evasion, financial fraud, and regulatory arbitrage. It is argued that effective international cooperation among governments, regulatory authorities, financial institutions, and technology providers is essential for ensuring the sustainable development of digital finance. The article concludes that the improvement of international FinTech regulation is a prerequisite for strengthening investor and consumer confidence, enhancing financial resilience, promoting innovation, and ensuring the long-term stability and sustainable development of the global economy.
Abstract Financial technologies (Fintech), such as digital payments, have become transformative economic tools. Yet despite technological advances and the documented benefits of financial inclusion, 1.3 billion adults remained unbanked in 2024, and cash persists globally. Why is fintech growth accompanied not by more intermediation but by persistent disintermediation (through cash and, increasingly, Bitcoin) that varies significantly across countries? I present a theory of disintermediation identifying three primary drivers: weak state capacity, underdeveloped infrastructure, and political institutions shaping citizens’ incentives regarding formal finance. The first two are supply-side factors: weak state capacity enables merchants to demand cash payments to avoid taxation, strengthening informal sectors, and lacking banking infrastructure raises the cost of intermediation. The third is a demand-side factor extending Hirschman’s ‘Exit, Voice, and Loyalty’ framework to finance: autocratic governance increases citizens’ exit from formal finance. I test this theory through two empirical analyses using two-way fixed effects, each capturing disintermediation within a different population: First, cash dependency among the broad population of economic actors in 158 countries, 2001–2020 ( n = 2760). Second, the choice of peer-to-peer over exchange-based channels among cryptocurrency users in 161 countries, 2019–2024 ( n = 921), using a novel dataset provided by Chainalysis, a market leader in blockchain intelligence. The two measures are deliberately not parallel: the cash analysis tests the theory on the broadest possible population, while the Bitcoin analysis tests whether the same institutional drivers predict the choice of disintermediated channels within the population of cryptocurrency users. Consistent results across populations this different indicate that the theorized mechanism is general rather than an artifact of either measure. Results are robust across estimators, including Callaway and Sant’Anna staggered difference-in-differences. Findings demonstrate that supply and demand drivers each shape disintermediation, and establish a research agenda investigating fintech adoption through financial disintermediation.
Ho Thanh Tri, Le Hoang Minh Khue, Le Dinh Van, Tran Gia Linh · 6 authors
As the digital economy rapidly develops, quick access to capital has become a critical survival factor for individuals intending to start a new business. However, under traditional bank lending systems, these aspiring entrepreneurs face significant barriers due to complex financial documentation requirements and stringent credit history checks. Drawing on the Technology Acceptance Model (TAM), this study investigates factors influencing users’ adoption of blockchain-enabled digital lending platforms among individual customers with startup intentions in Vietnam. The empirical model examines the effects of Perceived Ease of Use and Perceived Usefulness on Attitude Toward Using, and the effect of Attitude on Behavioral Intention to Use. The results show that both perceived ease of use and perceived usefulness positively influence users’ attitudes, while attitude strongly affects behavioral intention. Blockchain-related characteristics, including decentralization, data immutability, and smart contracts, are discussed as technological mechanisms that may improve lending efficiency, transparency, and users’ confidence in digital lending systems. The study provides practical implications for banks and FinTech firms seeking to design user-friendly and secure digital lending platforms for underserved entrepreneurial users.
The rapid diffusion of crypto currency in Nigeria has attracted considerable attention from academics, practitioners, and policymakers. This study investigates the determinants of crypto-currency adoption, market growth, and price dynamics in Nigeria, with a particular focus on financial inclusion, regulatory environment, technological advancement, investor sentiment, and macroeconomic factors. The research objectives are (i) to assess the appeal and growth trajectory of crypto-currencies in Nigeria; (ii) to identify the risk factors that shape their evolution; and (iii) to derive policy-relevant insights for regulators and industry stakeholders. A quantitative approach was employed using quarterly data spanning 2012-2023 (N = 43). Five hypotheses were formulated and tested using a battery of time-series techniques: Granger-causality, unit-root tests, Johansen cointegration, and autoregressive distributed-lag (ARDL) modelling. The proxies for the independent variables were: number of crypto users, transaction volume, and number of exchanges (cryptocurrency adoption); number of regulatory approvals, regulatory clarity, and regulatory support (regulatory environment); internet penetration, mobile-phone adoption, and tech-startup count (technological advancement); social-media mentions, sentiment analysis, and investor-confidence index (investor sentiment); and GDP growth, inflation, and exchange rate (economic factors). Dependent variables included percentage of the population with financial-service access, number of bank accounts, mobile-money adoption (financial inclusion); market capitalization, trading volume, and new listings (crypto-market growth); standard deviation of price returns and frequency of price jumps (price volatility); and number of transactions and users (crypto demand). The empirical findings reveal a complex interplay among the variables. Granger-causality tests indicate bidirectional predictability between crypto currency adoption and financial inclusion, as well as unidirectional causality from regulatory environment, technological advancement, investor sentiment, and economic factors to their respective outcomes (p < 0.05). Unit-root tests confirm stationarity of all series (I(0)), justifying the use of cointegration analysis. Johansen tests detect at least one cointegrating vector for each hypothesis, suggesting long-run equilibria. ARDL models provide nuanced short-run dynamics: a 1 % improvement in regulatory quality raises market growth by 0.98 % (p < 0.001); technological advancement has a modest, borderline-significant short-run effect on adoption (p = 0.09); investor sentiment exhibits a contemporaneous calming effect on volatility followed by a lagged increase (p = 0.04); and economic factors display a near-unit elasticity (0.98, p < 0.001) with crypto demand in the short run but a negative long-run association, implying that sustained economic improvement may reduce crypto’s appeal. The study concludes that while regulatory clarity, technological infrastructure, and macroeconomic stability are pivotal in shaping the short-run trajectory of the Nigerian crypto market, their long-run impact can be ambivalent. Investor sentiment emerges as a significant driver of price volatility, underscoring the role of behavioural factors in this emerging asset class. The findings underscore the need for a balanced regulatory framework that encourages innovation while safeguarding financial stability, alongside targeted investments in digital infrastructure and financial-literacy programmes.
The digital transformation of Islamic finance encourages the evolution of musharakah contracts into a technology-based crowdfunding ecosystem. However, this change also presents a more complex moral hazard risk due to the limitations of direct supervision. This research aims to synthesize the scientific literature for the period 2015-2025 in order to map the digital evolution of musharakah contracts and formulate a moral hazard risk mitigation framework that is adaptive to the characteristics of sharia crowdfunding platforms. The study uses a Systematic Literature Review (SLR) with a descriptive-analytical approach across 15 reputable scientific articles. The findings show that the moral hazard in sharia crowdfunding stems from information asymmetry, weaknesses in digital financial reporting, and limited platform oversight capacity, which collectively weakens the integrity of profit-sharing-based contracts. Effective mitigation requires the integration of four dimensions, namely algorithmic technology such as blockchain and smart contracts, strengthening digital sharia supervisory institutions, updating specific OJK regulations, and increasing the capacity of Islamic financial literacy, which together form the concept of Algorithmic Sharia Governance as a novelty in this study.
Zaid Tahat, Ahmad Alomari, Ibrahim Al-Radaideh, Adham Taher Alessa · 7 authors
This study examines the mediating role of investor trust in the relationship between perceived blockchain integration and perceived stock market efficiency within the Amman Stock Exchange (ASE). The Amman Stock Exchange (ASE), established in 1999, is the sole securities exchange in Jordan and one of the leading emerging markets in the Middle East and North Africa (MENA) region. Drawing on technology acceptance theory, trust theory, and market efficiency theory, the research develops and tests a dual-pathway model wherein perceived blockchain integration relates to perceived market efficiency both directly and indirectly through investor trust. Using structural equation modeling with data collected from 400 market participants, the findings reveal that perceived blockchain integration is significantly and positively associated with investor trust (β = 0.849, p < 0.001) and with perceived stock market efficiency (β = 0.448, p < 0.001). Importantly, investor trust partially mediates this relationship (β = 0.380, p < 0.001), confirming the dual-pathway impact. Among blockchain dimensions, security demonstrates the strongest effect on both investor trust and market efficiency. The study contributes to the emerging literature on blockchain in financial markets by empirically validating the psychological mechanisms through which technological innovations translate into more favorable perceptions of market functioning. For market regulators and exchange administrators, the findings suggest that comprehensive blockchain implementation strategies should address both technological deployment and trust-building initiatives to strengthen favorable investor perceptions of market efficiency in emerging markets.
Modern charitable donation platforms involve multiple stakeholders, including donors, charity organizations, financial institutions, and regulatory authorities. However, traditional centralized systems often suffer from limited transparency, weak trust management, and insufficient traceability, which significantly undermine public confidence in charitable activities. To address these challenges, this study proposes an intelligent blockchain-enabled framework for transparent multi-stakeholder donation management. The proposed system integrates consortium blockchain infrastructure with smart contract mechanisms to support trustworthy transactions, automated governance, and transparent information sharing across participating entities. The framework adopts a modular architecture that facilitates role separation, traceable transaction management, and scalable system evolution. In addition, the system enables transparent supervision and evaluation processes, allowing donors, recipients, and regulatory bodies to participate in collaborative monitoring of charitable activities. A prototype implementation based on the FISCO BCOS consortium blockchain platform is developed to evaluate the feasibility and performance of the proposed framework. Experimental results demonstrate that the system effectively enhances traceability, operational transparency, and trust among participants while maintaining acceptable performance in terms of throughput and latency. The proposed framework provides a practical reference architecture for developing intelligent and trustworthy multi-party platforms and contributes new insights into the design of decentralized expert systems for social good applications.
Abstract Smart contract vulnerabilities have caused billions of dollars in losses across decentralized finance. Finding reliable ways to detect such vulnerabilities has been a long-standing challenge for researchers. The growing capabilities of large language models (LLMs) are promising, but the factors that determine their reliability and capabilities remain poorly understood. This study investigates whether increasing inference-time computation using techniques like extended reasoning and structured prompting always improves vulnerability detection capability. It also identifies the most influential factors to select a model for this task. Using four prompting techniques, it evaluates 14 LLMs from seven families on 54 Solidity contracts. The experiment reveals a clear gap in detection capability across model classes. While six frontier models do not report false positives on verified-clean contracts, all three small open-source models report vulnerabilities in every case throughout the experiment. Moreover, a 11.5% drop in F1 score for one model was observed when increasing inference-time compute by enabling extended thinking. Also, prompting strategy has a limited effect on detection capability compared to model selection. The results challenge common assumptions and offer practical insights into the use of LLMs for smart contract vulnerability detection.
Omar A. Esqueda, Mohammad Sharif Karimi, Daniel P. Liston, Saleh Ghavidel Doostkouei
This paper investigates the dynamic relationship between macroeconomic factors—particularly Bitcoin pricing—and the equity returns of firms in the financial technology (FinTech) sector. Using a Structural Vector Autoregression (SVAR) framework with daily data from July 2013 to March 2025, the analysis examines how shocks in major financial variables affect FinTech equity performance. The results indicate that positive shocks to the S&P 500 index are associated with a significant increase in the FinTech sector indicator, underscoring the sector’s close linkage with overall equity market performance. Shocks to the 10-year U.S. Treasury bond yield also generate a positive but comparatively weaker and delayed response, suggesting a secondary influence of interest rate dynamics. In contrast, Bitcoin price shocks do not produce a statistically significant effect on FinTech returns, implying limited spillovers from cryptocurrency markets to traditional FinTech equities. Robustness checks using PARCH and TARCH models confirm the stability of these findings. Overall, the evidence suggests that FinTech firms remain more sensitive to developments in conventional financial markets than to movements in digital asset prices, highlighting the sector’s growing integration with institutional finance rather than speculative crypto-based activity.
This article examines cryptocurrency adoption in the Bicol Region of the Philippines through 14 months of multisited ethnography with the Bicol Blockchain Community (BBC) and three national government agencies. Against libertarian narratives framing blockchain as a tool of financial emancipation, the Bicol case reveals institutional absorption: the incorporation of a nominally anti-statist technology into existing hierarchies of governance, credentialing and capital accumulation. While agencies and community entrepreneurs forged mutually beneficial alliances, material and symbolic benefits accrued primarily to those with prior educational and economic advantages. Extending domestication theory and scholarship on techno-politics, the study develops institutional absorption as a concept for the cultural studies of technology: a culturally constituted process through which digital disruption is translated into legible, governable and hierarchical form. Rather than a universal account of the Global South, the concept offers a core analytical perspective for remittance-dependent, climate-vulnerable peripheral regions, with boundary conditions specified for comparative testing.
This study delves into how blockchain, artificial intelligence (AI), and financial technology (FinTech) can complement one another to propel inclusive banking with regard to emerging economies like Nigeria. It examines how the convergence of these technologies has the potential to improve the provision of service, lower costs of operation, improve financial inclusivity, and improve security in the financial industry. The research also investigates how AI can be leveraged to make informed decisions based on data, how blockchain technology can provide transparency and immutability, and how FinTech platforms can provide underbanked and unbanked people with easily accessible alternatives to conventional financial services. Even though it brings advantages, the convergence also comes with devastating drawbacks, such as issues of data privacy, ethical dilemmas when using AI, scalability constraints of blockchain, cybersecurity threats, and unclear regulations. This paper identifies critical risks and offers strategic suggestions to financial institutions, technology disruptors, and policymakers based on a thorough conceptual analysis and review of the literature over the last few years. These include investing in digital infrastructure, encouraging ethical AI activities, improving regulatory environments, and creating public-private partnerships. The study concludes that although this intersection of these technologies has enormous potential for fueling inclusive finance, their use will need a balanced approach combining innovation with effective governance, moral protection, and human-centered design. Developing strong, accessible, and inclusive financial systems can be expedited by the synergy of blockchain, artificial intelligence, and fintech if harnessed correctly.
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 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.
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.