Artificial intelligence (AI) is altering the systemic risk topology of decentralized finance (DeFi). While prior studies examine vulnerabilities in each domain, their intersection remains undertheorized. This paper frames the AI-DeFi ecosystem as a complex adaptive system (CAS) to identify three mechanisms by which AI reshapes systemic risk: algorithmic homogeneity, which synchronizes agent responses; dynamic network rewiring, which amplifies structural fragility; and emergent multi-agent behavior, which produces contagion without centralized intent. Together, these forces introduce endogenous, path-dependent failure modes opaque to reductionist analysis. This framework provides a foundation for empirical analysis and anticipatory governance in AI-mediated financial systems.
Rodrigo Gonçalves Bueno, André Luiz de Souza Carneiro, João Paulo Aragão Pereira
Adoption of DeFi, Central Bank Digital Currency (CBDC), and Tokenized Multiassets necessitates new security architectures for Regulated Tokenized Multiasset Networks (RTMNs). Traditional approaches are insufficient for the distributed nature of decentralized finance, and Zero Trust models face compliance and efficiency challenges in financial networks. This paper proposes a novel framework for diverse use cases, guarantees composability, atomicity, settlement finality, and enforced compartmentalization, sharing minimal necessary information, enabling privacy-by-design. A detailed analysis of the framework’s application in RTMNs is presented, evaluating its characteristics in the context of tokenizing government securities.
Hanouf Al Ghanmi, Sabreen Ahmadjee, Rami Bahsoon, Hayatullahi Bolaji Adeyemo
Blockchain smart contract technology has revolutionised various industries by automating agreements through immutable and self-executing logic, reducing reliance on third-party intermediaries. However, despite its transformative potential, existing research has predominantly focused on technical aspects—particularly security—while largely neglecting human-in-the-loop concerns. Systematic efforts to explore these concerns from a human perspective have been limited which creates a gap in the literature. This study aims to address this gap by offering a comprehensive understanding of smart contracts from a human-centred perspective. To achieve this, we conducted a systematic literature review to examine human-related issues in smart contracts and their existing solutions. We found that concerns are primarily concentrated in two stages: development and interaction. During the development stage, issues arise in relation to programming languages, including complexity, readability and expressiveness, as well as the legality of smart contracts and their ethical and social implications. In the interaction stage, concerns focus on usability, human readability, trust, governance and cost. Additionally, we identified several quality attributes frequently associated with these concerns such as transparency, accountability, understandability, simplicity, learnability, compliance and fairness. We also uncovered new human-centred quality attributes that are overlooked in existing literature, such as explainability and interpretability. This research offers valuable insights for researchers, requirements engineers and designers by examining existing efforts to address human-centric concerns and proposing future directions and opportunities to improve smart contract design.
The emergence of blockchain technology has spawned a broader discussion of designs for digital currencies, with Central Bank Digital Currencies (CBDCs) - digital forms of fiat currency - being one of them. An important feature of digital currencies is facilitating transactions without network connectivity, which can enhance the scalability of cryptocurrencies and the privacy of CBDC users. However, in the case of CBDCs, this characteristic also introduces new regulatory challenges, particularly when it comes to applying established Anti-Money Laundering and Countering the Financing of Terrorism (AML/CFT) frameworks. This paper introduces a prototype for offline digital currency payments, equally applicable to cryptocurrencies and CBDCs, that leverages Secure Elements and digital credentials to address the tension of offline payment support with regulatory compliance. Performance evaluation results suggest that the prototype can be flexibly adapted to different regulatory environments, with a transaction latency comparable to reallife commercial payment systems. Furthermore, we conceptualize how the integration of Zero-Knowledge Proofs into our design could accommodate various tiers of enhanced privacy protection.
Cryptocurrency investment in India has quickly become a mainstream financial activity, but it is still highly prone to psychological factors that impact the decision-making of retail investors. This study examines the effect of personality traits on cryptocurrency investment behavior using the mediating variable of behavioral biases. Based on the Big Five Personality Model and the theory of Behavioral Finance, data were gathered from 716 Indian retail investors using a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was conducted to analyze the relationships among the variables. Results show that Openness to experience and Agreeableness significantly predict Availability Bias, whereas Extraversion and Agreeableness affect the Disposition Effect. The theoretical framework shows how bias-driven investment behavior in volatile markets such as cryptocurrency is triggered by personality-based predispositions. The study adds to the behavioral finance literature by taking psychological profiling outside the realms of traditional investment contexts into digital asset investing and provides practical insights for regulators, fintech platforms, and investment advisors to design interventions to mitigate bias and enhance investor education.
Loyalty points can be used to encourage customers to make new purchases and play an important role in maintaining the existing customer base. In essence, this is a discount system, using which consumers can receive reward points after shopping or purchasing certain products. Loyalty points are a virtual currency that can be earned through certain shopping activities. According to a modern approach, loyalty points could also be exchanged for tokens based on blockchain technology. Tokens can be customized according to business needs, thus increasing the effectiveness of marketing. Since the tokens are created in the blockchain network, they are unforgeable, thus excluding the possibility of fraud or abuse. The purpose of the research is to examine whether “traditional” loyalty points can be transferred to modern NFT-based tokens, thereby conveying uniqueness and unforgeability to consumers. As part of the practical implementation, the smart contract will be written using NFT (Non-Fungible Token) elements and the ERC 721 standard. However, to deliver consumer NFTs to their target, a smart contract-based airdrop-sending solution is also needed, which will be written in the research. On the company side, consumer NFTs are stored in an Ethereum-based sidechain before sending. As a further part of the practical implementation, a blockchain called PBTN (Private Blockchain Token Network) will be created by creating its genesis block. Until now, such a joint DAO-NFT(Decentralized Autonomous Organization) solution has not yet been implemented. The token loyalty point-based reward created in the crypto space is certainly a novelty these days.
R. Li, Srisht Fateh Singh, Andreas Park, Andreas Veneris
This paper presents a securities tokenization solution that brings the accessibility, transparency, efficiency, and innovation of blockchain and decentralized finance to real-world securities. Tokenization in principle seems straightforward—an intermediary holds assets and issues 1:1 tokens—but decentralized finance applications (DeFi) introduce significant complications. Even basic DeFi mechanisms, such as liquidity pools, pose challenges for tokenizing stocks and bonds because when assets are pooled in smart contracts, ownership becomes unclear, hindering asset owners to access their entitlements, such as dividends, coupons, or voting rights. Existing solutions often fail to address these challenges and are typically limited to specific security types. Our solution, by contrast, generalizes to any security and any holding rights through fungible tokens and using separate smart contracts for shareholders to redeem their entitlements. To address the decentralized ownership issue, our solution employs off-chain accounting with additional logic for liquidity pools. We implement this on Ethereum, demonstrating that it is 27% cheaper in gas costs than current alternatives. We also analyze the liquidity logic of over 90% of Ethereum's liquidity pools, confirming compatibility with our solution. Finally, we demonstrate its use for dividend-paying stocks, common stock, mergers, and coupon-paying bonds.
Markus Jungnickel, Ferda Özdemir Sönmez, Catherine Mulligan, William J. Knottenbelt
Decentralized autonomous organizations (DAOs) have emerged as a novel organizational structure, attracting growing interest due to their decentralized, transparent governance, which replaces traditional hierarchies with stakeholder-managed rules codified as smart contracts. Although various governance models exist, comparative research across dimensions remains limited, leaving the literature fragmented and offering little practical guidance for selecting suitable models. This article critically analyses existing governance mechanisms and their implementation to support the development of more effective DAO models. To address current gaps, we review prior quantitative studies and conduct exploratory data analysis on centralization, participation, and decision controversy. The findings show that reputation and share-based models can mitigate the centralization seen in token-based systems, though all models suffer from low member engagement, suggesting an over reliance on direct democracy. Our analysis can be replicated across platforms and time frames to refine and validate these insights.
Christian Zeiß, Lisa Straub, Maximilian Greiner, Marcel Neis · 7 authors
Purpose To promote acceptance of blockchain-based investment options and enhance confidence for new investors, the market must become more comprehensible and accessible to the broad masses. This requires transparency to build trust in web-based intermediaries, particularly given the multitude of websites that often advertise unrealistic returns in the crypto sector. Consequently, intermediaries within the decentralized finance ecosystem need to be clearly identified and categorized to facilitate mass-market adoption. Design/methodology/approach We employ a six-iteration taxonomy approach, establishing a data foundation through literature reviews, expert interviews and document analysis of 50 intermediaries. Archetypes are derived using a hierarchical clustering algorithm. Finally, a survey is conducted to evaluate the taxonomy and the archetypes. Findings The taxonomy encompasses three meta-characteristics (functionality, architecture, security) and 63 characteristics. Furthermore, the research findings reveal six archetypes of blockchain-based investment intermediaries, demonstrating significant discrepancies between them, particularly in terms of financial features and governance structures. Given the complexity of crypto intermediary platforms for novice users, the findings underscore the need to implement technology-based and institutional-based trust mechanisms, improve risk assessment and enable informed decision-making. Originality/value By increasing market transparency and fostering trust, this study contributes to the acceptance and adoption of blockchain-based financial intermediaries, drawing on the diffusion of innovation theory. The proposed taxonomy, particularly its dimensions, specifically addresses the requirements of both technology-based and institution-based trust, which are critical for crypto investments. Moreover, the findings emphasize the importance of educational resources and communicated trust features in strengthening user confidence and facilitating broader market participation.
Krzysztof Lorenz, Piotr Gutowski, Ewelina Gutowska, Anna Drab-Kurowska
Digital transformation is reshaping innovation processes and capital allocation models, fostering the emergence of alternative financing mechanisms such as crowdfunding platforms. This study investigates the spatial determinants of digital innovation development using Kickstarter campaigns in the United States as a case study. Empirical data were preprocessed and classified into digital and traditional categories. Advanced AI methods, including Deep Autoencoders and Self-Organizing Maps (SOM), revealed spatial clusters of digital innovation in crowdfunding. Cluster visualizations exposed geographic concentration patterns and links to local infrastructure. AI uncovered latent ties between campaign structure and regional context, underscoring the role of AI and crowdfunding in decentralized, localized digital transformation.
We investigate how transparency—crypto exchanges' verification of trader identities through Know-Your-Customer (KYC) and their transmission of trader and transaction data to tax authorities—shapes the effectiveness of tax policies in cryptocurrency markets. Using regulatory events and cross-exchange price variation, we provide initial global evidence that transparency amplifies the capitalization of statutory crypto-tax liabilities into prices. In the United States, Bitcoin prices on exchanges subject to new tax reporting obligations fall by an average of 0.34 % following announcements that raise expectations of information transmission, even without changes in statutory tax liabilities. Across jurisdictions, price declines are significantly larger where reporting systems are more transparent, and in cross-sectional analysis, exchanges that both enforce KYC and transmit information show the strongest price sensitivity to local tax liabilities, particularly where capital controls constrain arbitrage. These findings reveal a transparency–privacy trade-off unique to crypto markets and demonstrate how digital assets provide rare opportunities to test classic tax-capitalization theories under conditions of anonymity and regulatory heterogeneity, with implications for the design of effective tax policies.
Yongsheng Guo, Ezaddin Yousef, Mirza Muhammad Naseer
This study investigates the relationship between cryptocurrency adoption rates (CARs) and the development of central bank digital currencies (CBDCs) using a global panel of 109 countries from 2020 to 2024. The analysis employs pooled OLS, fixed effects, ordered logistic regression and GMM models with robust controls for macroeconomic indicators, institutional quality, and technological readiness. CBDC status is measured as an ordinal variable representing five development stages, while CAR is derived from the Chainalysis Crypto Adoption Index. The empirical results show that higher CAR significantly increases the probability of a country progressing to more advanced CBDC stages. Margins analysis further indicates that increases in CAR substantially reduce the likelihood of remaining in early CBDC phases and raise the probability of reaching the pilot or launched stages. Heterogeneity analysis reveals that this relationship is strongest in low- and middle-income economies and in countries with low levels of financial inclusion, where cryptocurrencies present greater competition to traditional financial systems. The study contributes new large-sample evidence to the debate on digital currencies and provides policy-relevant insights: central banks in financially constrained economies appear to adopt CBDCs as developmental tools to enhance financial access and preserve monetary sovereignty in the face of growing cryptocurrency adoption.
This paper presents a comprehensive comparative analysis of two dominant blockchain consensus mechanisms, Proof of Work (PoW) and Proof of Stake (PoS), evaluated across seven critical metrics: energy use, security, transaction speed, scalability, centralization risk, environmental impact, and transaction fees. Utilizing recent academic research and real-world blockchain data, the study highlights that PoW offers robust, time-tested security but suffers from high energy consumption, slower throughput, and centralization through mining pools. In contrast, PoS demonstrates improved scalability and efficiency, significantly reduced environmental impact, and more stable transaction fees, however it raises concerns over validator centralization and long-term security maturity. The findings underscore the trade-offs inherent in each mechanism and suggest hybrid designs may combine PoW's security with PoS's efficiency and sustainability. The study aims to inform future blockchain infrastructure development by striking a balance between decentralization, performance, and ecological responsibility.
Krithika Rao, Shakil Khan, Bruce Singh, Nagulapati Kiran · 5 authors
Regulatory sandboxes—controlled environments where firms test innovations under regulatory supervision—have been adopted globally to manage fintech and crypto experimentation. This paper compares sandbox approaches and policy effectiveness for decentralized finance (DeFi) across the European Union, the United States, and the Asia-Pacific. Using a mixed-methods design (document analysis, stakeholder reports, and an illustrative quantitative model), we assess objectives, design choices, risk controls, and outcomes (market access, investor protection, and innovation diffusion). Findings show the EU’s pan-European coordination aims to harmonize testing and legal clarity; the US displays fragmented, agency-led pilot initiatives with stronger enforcement posture; Asia-Pacific exhibits rapid, varied adoption with jurisdictional leaders (Singapore, Hong Kong, Australia) using sandboxes as precursors to more formal rulebooks. Policy effectiveness depends on clarity of legal scope, cross-agency coordination, and well-designed exit and scaling rules. We conclude with policy recommendations and a research agenda for empirically measuring sandbox effectiveness for DeFi.
Abstract - Donation fraud and lack of transparency are major challenges in traditional charity systems, where donors often have limited visibility into how their contributions are utilized. Centralized platforms are prone to data manipulation, unauthorized fund usage, and security breaches, reducing donor confidence. This study explores blockchain-based approaches for securing and accurately managing donation transactions. We review various systems that implement smart contracts, decentralized ledgers, and cryptographic techniques to ensure transparency, traceability, and accuracy in fund distribution. The analysis compares architectural designs, data validation mechanisms, accuracy levels, and security models across existing frameworks. Finally, we highlight current limitations and propose future enhancements to improve scalability, privacy, and real-world implementation of blockchain-based donation management systems. Keywords: Blockchain, Smart Contracts, Donation Security, Transparency, Decentralized Ledger, Cryptography, Ethereum, Zero-Knowledge Proofs, Data Accuracy, Trust Management.
The real estate sector stands at an inflection point where technological convergence fundamentally reshapes how properties are transacted, recorded, and verified. This chapter explores the integration of advanced cybersecurity protocols, artificial intelligence-powered analytics, and hybrid blockchain architectures to create immutable, transparent, and secure property transaction ecosystems. By merging predictive AI capabilities with distributed ledger technology, property records, ownership verification, and transactional security achieve unprecedented levels of trust and operational resilience. This convergence simultaneously addresses critical challenges in fraud prevention, regulatory compliance, and stakeholder confidence, while streamlining property transfers and risk assessment mechanisms across global real estate markets.
The convergence of blockchain and financial technology (FinTech) is changing the face of finance globally by offering safe, transparent, and affordable services to serve underserved groups of people. The study provides a systematic literature review, covering Payments, Asset Management, Financial Inclusion, and Other Innovations. A bibliometric analysis has the annual publication tendencies indicates the tendency of the increasing academic interest, according to a steep rise of eight articles in 2020 to 35 articles in 2025. The areas of research in Asia and the large journals (Sustainable Finance and World Sustainability Series) support the propagation of knowledge. The analysis of citations demonstrates the work that was foundational in the field of decentralized finance and the AIFinTech symbiosis. The thematic mapping of FinTech and blockchain also points to these two themes as the most important ones, with recent developments of interest in digital identity and regulatory compliance. The international system of cooperation revolves around India, with major collaborations occurring across the continent. These findings can provide researchers and practitioners a mechanism overview of current research dynamics and thematic developments, unlock the inclusive digital finance through blockchain-based Fintech innovations.
The integration of Bitcoin into corporate treasuries constitutes a critical strategic choice, motivated by its capacity to bolster liquidity and serve as an inflation hedge, while simultaneously being encumbered by pronounced financial volatility and regulatory ambiguity. This investigation examines sectoral variations in Bitcoin adoption, with particular attention to the manner in which financial risks, regulatory structures, and decentralized governance mechanisms shape corporate conduct across the technology, cryptocurrency mining, retail, healthcare, and e-commerce sectors. Drawing on a cross-sectional dataset encompassing 102 publicly traded firms collectively holding 1,001,861 BTC, the analysis employs MAD-based volatility, Firth logistic regression incorporating a U.S. regulatory dummy to account for the BITCOIN Act of 2025, and heatmap visualization to evaluate risk profiles and adoption patterns. Results demonstrate marked sectoral disparities: the technology and mining sectors command predominant holdings yet confront heightened risk exposure, whereas retail and healthcare sectors proceed with greater caution, guided by considerations of cost-value efficiency and regulatory adherence. The U.S. regulatory dummy is significant, indicating the BITCOIN Act facilitates high Bitcoin adoption, while recent transactional activity is marginally significant. The heatmap accentuates the technology sector’s pre-eminence in aggregate Bitcoin reserves and illuminates the differential influence of regulatory frameworks in non-U.S. jurisdictions. Anchored in Institutional Theory, the Technology Acceptance Model, and Transaction Cost Economics, the study advances the field by quantifying sector-specific risks and visually representing regulatory impacts, thereby furnishing actionable insights for treasury risk management and regulatory policy formulation within a decentralized financial ecosystem.
Jinghan Sun, H. L. Wang, Yusuf Shakhpaz, Junyu Zhang · 6 authors
Amid the rapid expansion of the Non-Fungible Token (NFT) market, X (formerly Twitter) has emerged as a crucial channel for communication between project creators and their communities. This study investigates the short-term effects of NFT project tweets on trading behaviors and price dynamics. Guided by Media Richness Theory (MRT), we con-ducted a quantitative analysis of tweets from nine leading NFT projects, categorizing them into three distinct clusters. Our findings reveal heterogeneous correlations between tweet content, NFT categories, and price fluctuations. The differing roles and functions of NFTs across categories shape both the distribution of tweets and their short-term pricing impacts. Furthermore, we employed three machine learning models using media richness as a predictive feature, achieving approximately 60 % accuracy in forecasting NFT price movements. Overall, this research highlights the predictive potential of social media for NFT price trends and its contribution to the NFT ecosystems sustainability.
The mining sector faces persistent funding challenges due to high risk, low liquidity, and limited transparency. Traditional financing methods are costly, slow, and inaccessible for small or early-stage ventures. This paper presents a platform Asteroid X, a blockchain-based Decentralized Finance (DeFi) platform tailored to these challenges. Asteroid X has an architecture that combines semi-centralized governance model to ensure rigorous projects on boarding and legal compliance – with fully on chain settlement mechanisms to facilitate transparent, secure, and efficient capital flows. Built on the ERC-1155 multi-token standard, Asteroid X tokenizes real-world mining rights and supports fractional ownership through a modular smart contract framework. Its layered architecture includes an API gateway, decentralized marketplace, and oracle integration to bridge off-chain geological data. Asteroid X is validated through test deployments on HashKey Chain and Ethereum Sepolia. Comparative analysis against traditional exchanges, such as the Australian Securities Exchange (ASX), highlights significant gains in cost efficiency, transaction speed, and investor inclusivity. The results substantiate the applicability and transformative potential of blockchain-driven DeFi frameworks within capital-intensive industries such as mining, offering enhanced security, transparency, and inclusivity.
Bambang Leo Handoko, Arta Moro Sundjaja, Dezie Leonarda Warganegara
The phenomenon of resistance to blockchain technology adoption as an underlying distributed ledger technology independent of cryptocurrency has been widely studied in institutional and auditing contexts, but relatively little attention has been given to its rejection among retail investors. While blockchain is the foundation of cryptocurrencies, paradoxically, some investors exhibit hesitation or resistance toward its broader applications due to perceived risks, uncertainty, and psychological barriers. This paper adapts Innovation Resistance Theory (IRT) to investigate resistance to blockchain among cryptocurrency investors. The research employed a descriptive quantitative approach using primary data collected through questionnaires distributed to auditors working in various public accounting firms. The data were analyzed using the Structural Equation Modeling technique with the Partial Least Squares (SEM-PLS) method to test the hypothesized relationships. The findings highlight that inertia, perceived susceptibility to threats, and threat severity significantly influence resistance. In contrast, threat of data ownership and switching costs appear to have weaker effects. Understanding these barriers is essential for designing better adoption strategies and building investor trust in blockchain ecosystems. Beyond its empirical findings, this study extends IRT by contextualizing psychological and functional barriers within cryptocurrency investment behavior, integrating behavioral finance and technology resistance perspectives.