Umar Yeni Suyanto, Ratna Rosita Pangestika, Kinanti Puja Prameswari, Heni Setiyaningsih
The integration of Artificial Intelligence (AI) into Small and Medium Enterprises (SMEs) has become a critical lever for achieving resilience, efficiency, and long-term sustainability in the digital era. However, despite AI’s transformative potential, empirical evidence suggests a persistent gap between technological capabilities and actual adoption within the SME sector. This study employs a bibliometric analysis using VOSviewer with the keywords "artificial intelligence" OR "AI" AND "Small and medium enterprises" OR "SMEs" AND "digital", encompassing 150 Scopus indexed articles from 2017 to 2025. The visualizations reveal six prominent thematic clusters, including AI based adaptive strategies, post-pandemic digital transformation, decentralized finance, digital literacy, and emerging concepts such as green cybersecurity. Notably, overlay visualizations indicate that sustainability-oriented digital practices are gaining scholarly momentum, signaling a future research trajectory focused on inclusive, secure, and environmentally conscious AI applications in SMEs. This article proposes a conceptual model SDRAIS (SME Digital Resilience through AI and Sustainability) that integrates three strategic dimensions: Strategic AI Integration, Digital Capabilities, and Sustainability Orientation. The model advances theoretical development by aligning with the Dynamic Capabilities and TOE (Technology Organization Environment) frameworks, while also responding to gaps in Triple Bottom Line (TBL)-driven technology adoption. The findings offer new perspectives for policymakers, SME stakeholders, and researchers by emphasizing the importance of interdisciplinary approaches to foster AI-driven innovation ecosystems that are both competitive and sustainable. This study contributes to the evolving discourse on digital transformation in SMEs and sets a robust foundation for future empirical exploration.
The rapid development of financial technologies and the spread of blockchain infrastructure have contributed to the emergence of new digital financial assets, among which stablecoins hold an important place. Unlike traditional cryptocurrencies, they are characterized by relative price stability, which is ensured by pegging to fiat currencies, commodity assets, or the use of algorithmic mechanisms for regulating token supply, creating conditions for their use in payment systems, international settlements, and decentralized financial services. The aim of the article is to study the economic essence of stablecoins, determine their role in modern payment systems, and analyze trends in the development of the stable digital asset market based on an assessment of their market capitalization. In the course of the research, general scientific and specialized methods of scientific knowledge were used, in particular methods of system analysis, generalization, comparative analysis, and structural study of the crypto-asset market. The article examines approaches to the classification of stablecoins depending on the type of their backing, in particular fiat-backed, commodity-backed, crypto-backed, and algorithmic stablecoins. The main directions of the use of stablecoins in the modern financial infrastructure are identified, including cryptocurrency exchanges, decentralized finance platforms, and cross-border payments. A comparative analysis of traditional payment systems and payment systems based on stablecoins was carried out, which made it possible to determine their advantages in transaction speed, global accessibility, and reduction of transaction costs. Special attention is paid to the analysis of the market structure of stablecoins. It was found that at the beginning of 2026, the total capitalization of this segment exceeds USD 300 billion, which indicates its rapid growth. At the same time, the market is characterized by a high level of capital concentration, as more than 80% of its volume is concentrated in the two largest stablecoins, namely USDT and USDC. As a result of the study, it was concluded that stablecoins are gradually transforming from an auxiliary tool of cryptocurrency trading into an important element of the global payment infrastructure. A further development of this segment will depend on the improvement of regulatory mechanisms, increased transparency of reserve backing, and the integration of stablecoins into the traditional financial system.
The increasing complexity of global financial systems has necessitated the adoption of more efficient and transparent mechanisms for combating money laundering (AML). Blockchain technology, with its decentralized, immutable, and transparent characteristics, presents a promising solution to address the limitations of traditional AML systems. This paper represents a review, exploring the potential applications of AI and blockchain in enhancing financial control systems, in particular, within AML compliance, focusing on key areas such as transaction monitoring, cross-institutional data sharing, and regulatory reporting. The integration of blockchain can streamline AML processes, reduce operational costs, and increase the effectiveness of detecting illicit financial activity. The combination of blockchain technologies and artificial intelligence algorithms in financial control is considered. It is shown how automation of transaction analysis can strengthen the stability of the banking system and prevent financial crimes. It is demonstrated that the convergence of Artificial Intelligence and blockchain technologies presents a transformative opportunity to strengthen AML frameworks, particularly in the face of rising crypto-enabled financial crimes. This research offers several important contributions to the academic literature. First, it presents a synthesis of the current status of artificial intelligence approaches used for compliance in detecting fraud in Bitcoin transactions. This review discusses the essential methodologies and tactics in a particular area that intersects finance and compliance but falls under the broader disciplines of AI-driven finance and decentralized finance (DeFi). The incorporation of AI into financial control marks a tremendous technological revolution that is affecting industries across the board. Second, the study assesses the current state of the publications, major trends, and research gaps, emphasizing areas that deserve additional investigation.
Predictive analysis has become an essential component in modern financial research and practice, driven by the rapid advancement of data analytics, machine learning, and artificial intelligence. This study aims to systematically map the intellectual structure, research trends, and key contributions in the field of predictive analysis in finance through a bibliometric approach. Data were collected from the Scopus database covering publications from 2000 to 2026 and analyzed using VOSviewer to examine co-authorship networks, citation patterns, and keyword co-occurrence. The results reveal a significant growth in research output, particularly in recent years, reflecting the increasing importance of data-driven decision-making in finance. Co-authorship analysis indicates the presence of collaborative research clusters, although the field remains partially fragmented. Citation analysis highlights that the most influential studies are those integrating advanced computational methods with practical financial applications, such as credit scoring, bankruptcy prediction, and stock market forecasting. Furthermore, keyword analysis demonstrates a clear shift from traditional statistical techniques toward machine learning, artificial intelligence, and emerging technologies such as blockchain and decentralized finance. This study contributes by providing a comprehensive overview of the evolution and current state of predictive analysis in finance, identifying key research themes and gaps. The findings suggest that future research should focus on enhancing model interpretability, integrating sustainability considerations, and expanding applications in real-time financial decision-making. Overall, this study serves as a valuable reference for researchers and practitioners seeking to understand the trajectory and future direction of predictive analytics in the financial domain.
Rongji Huang, Yifeng Ye, Gerui Wang, Mingchao Wan · 8 authors
Due to regulatory compliance and governance management, modern (permissioned) blockchains require flexible endorsement, which allows the endorsement policy for each contract or state object to be individually defined. To enable flexible endorsement, Hyperledger Fabric employs an execute-order-validate (EOV) paradigm, in which transactions first undergo speculative execution and endorsement, and are only then ordered and validated. Meanwhile, most blockchain systems, including the platform targeted in this work (i.e., ChainMaker), still follow a conflict-free order-execute framework. We argue that the EOV paradigm still faces several limitations, notably high abort rates in high-contention workloads such as those in Decentralized Finance (DeFi). To avoid refactoring our system and better suit DeFi applications, we try to integrate flexible endorsement into the classical order-execute architecture and accordingly propose a new framework. The key challenge is to deterministically remove problematic transactions from an ordered list, while preserving censorship resistance and decentralization for the remaining ones. We instantiate this framework on top of Tendermint, a seminal Byzantine fault-tolerant (BFT) protocol adopted in our system, and thereby propose FlexTender. By elegantly embedding endorsements into consensus, FlexTender incurs no additional messaging overhead in the normal case. Empirical evaluation using an Ethereum USDT workload demonstrates that FlexTender achieves up to $10.6\times$ speedup in throughput over an EOV simulation on the same platform.
Ignat Melnikov, Roman Vlasov, Vladimir Gorgadze, Andrey Seoev · 5 authors
Decentralized Finance (DeFi) is a rapidly evolving segment of blockchain technology that enables a transformative approach to financial services through Web3 applications. By leveraging smart contracts, DeFi allows developers to build flexible and innovative financial instruments. Among the most prominent DeFi primitives by liquidity are decentralized exchange~(DEX) swap protocols~(such as Uniswap, Curve, and Balancer) that facilitate fast token-to-token exchanges. However, new exchange mechanisms also introduce new market inefficiencies that can be systematically exploited by arbitrageurs. This paper focuses on swap protocols based on the Automated Market Maker~(AMM), where the product of reserves is preserved as an invariant. We analyze the interaction between arbitrageurs and AMM liquidity pools and develop a mathematical model grounded in empirical pool configurations. Using this model, we derive bounds on the joint revenue of liquidity providers~(LPs) and arbitrageurs, propose a method to estimate the expected number of blocks until the occurrence of Impermanent Loss~(IL), and obtain a lower bound on the pool fee required to achieve a fixed target probability of staying in the Impermanent Gain (IG) zone within a block. The proposed framework extends existing LP risk-assessment methodologies by quantifying symbiotic profitability zones, providing a principled basis for fee selection that aligns LP-arbitrageur incentives and enhances market stability.
Zhuoran Pan, Yue Li (102191), Zhi Guan, Jianbin Hu · 5 authors
The emergence of Large Language Models (LLMs) offers a transformative interface for Web3, yet existing benchmarks fail to capture the complexity of translating high-level user intents into functionally correct, state-dependent on-chain transactions. We present \textsc{Intent2Tx}, a high-fidelity benchmark featuring 29,921 single-step and 1,575 multi-step instances meticulously derived from 300 days of real-world Ethereum mainnet traces. Unlike prior works that rely on synthetic instructions, \textsc{Intent2Tx} grounds natural language intents in real-world protocol interactions across 11 categories, including diverse long-tail Decentralized Finance (DeFi) primitives. To enable rigorous evaluation, we propose an execution-aware framework that transcends surface-level text matching by employing differential state analysis on forked mainnet environments. Our extensive evaluation of 16 state-of-the-art LLMs reveals that while scaling and retrieval-augmentation enhance logical consistency and parameter precision, current models struggle with out-of-distribution generalization and multi-step planning. Crucially, our execution-based analysis demonstrates that syntactically valid outputs often fail to achieve intended state transitions, highlighting a significant gap in current "reasoning-to-execution" capabilities. \textsc{Intent2Tx} serves as a critical foundation for developing autonomous, reliable agents in intent-centric Web3 ecosystems. Code and data: https://anonymous.4open.science/r/Intent2Tx_Bench-97FF .
The digital money world is facing a massive security challenge. We have Decentralized Finance (DeFi), built on Smart Contracts-which are supposed to be self-executing and unbreakable-running on top of Cloud Computing, which is fast, scalable, but inherently centralized and has a big, easy-to-hit security perimeter. This awkward partnership creates a critical weak point. Hackers aren't breaking the blockchain itself; they are exploiting the connections, like manipulating data feeds (Oracles) or stealing cloud credentials, something old, siloed security checks simply miss. We've developed the Integrated Cloud-DeFi Resilience (ICDR) Framework to fix this. Think of it as a single, smart security bodyguard that protects your system from the cloud down to the code. The ICDR Framework seamlessly brings together three crucial defense layers: first, we automatically audit the Smart Contract code before it even launches; second, we use Cloud Security Posture Management (CSPM) to continuously monitor the cloud infrastructure’s health in real-time; and third, we use specialized Blockchain Technology (DLT) to create an unchangeable, honest record of every security event. The core innovation is its ability to play detective: it catches stealthy attacks by connecting a suspicious administrative action in the cloud (like a key change) with an immediate, shady transaction on the DeFi chain. In our tests on a simulated financial application, this unified approach reduced the time a system was vulnerable (Vulnerability Exposure Rate, or VER) by over 80% compared to separate monitoring tools. The ICDR Framework offers a crucial, practical model for the financial industry to build the resilient, compliant, and trustworthy digital banking systems of tomorrow. Keyword: Security Auditing; Decentralized Finance (DeFi), Smart Contracts, Cloud Computing, Cloud Security Posture Management (CSPM), Oracle Manipulation,Interoperability Risks, Cross-Stack Correlation, Immutable Audit Trail.
Decentralized Finance (DeFi) promised to eliminate traditional financial intermediaries and hierarchies, replacing them with trustless, automated, and decentralized systems. However, the reality of DeFi governance reveals how disintermediation does not equate to the absence of conflicts or trust issues; instead, it shifts them into new, less-regulated domains. Cryptoenterprises—known as financial Decentralized Autonomous Organizations (DAOs)—operate without traditional corporate governance mechanisms such as boards of directors or managerial oversight, which only rely on computer code for governance. Misaligned incentives, governance opacity, and unchecked insider control cause conflicts between insiders (cryptopromoters) and investors (cryptoasset holders). This article examines the emerging role of cryptogatekeepers: a new category of cryptointermediaries that counterbalance these governance failures. It explores the structural deficiencies of cryptoenterprises, including the absence of internal monitoring mechanisms, fiduciary duties, and investor protections. The analysis highlights how cryptopromoters—those in control of DeFi protocols—retain significant decision-making power while obscuring accountability, leading to agency problems reminiscent of traditional finance sans regulatory safeguards By assessing the function of cryptointermediaries as potential de facto governance enforcers, this article argues that cryptogatekeepers can introduce a layer of oversight that compensates for the governance void in DeFi. It outlines best practices for mitigating conflicts of interest, enhancing disclosure standards, and improving the monitoring of cryptointermediaries. The study also considers transnational regulatory approaches to bolster accountability in DeFi through proposing mechanisms such as cryptointermediary registries, mutual recognition of licensed cryptointermediaries, and standardized reporting frameworks. Ultimately, this article contends that while DeFi presents an innovative model for financial services, it cannot escape fundamental governance challenges. The rise of cryptogatekeepers suggests that some level of re-intermediation is inevitable and necessary to balance decentralization with maintaining investor protection and market integrity.
This paper presents a critical interpretation of modern monetary systems, arguing that centralized banking structures and debt-based finance concentrate economic power through mechanisms of money creation, interest, and inflation.It traces the historical evolution of money from commodity exchange and gold-backed systems to contemporary fiat currency regimes, emphasizing the role of fractional reserve banking and central bank monetary policy.The framework examines the creation of the U.S. Federal Reserve and the concentration of financial influence among banking and political elites, interpreting these developments as components of a broader “extraction architecture” embedded within global finance.It analyzes inflation, debt issuance, and wage dependency as systemic mechanisms that transfer value through interest-bearing monetary systems, while also discussing alternative economic models such as local currencies, cooperative economies, and decentralized finance.Positioned as a political economy critique and systems-level analysis, the work frames modern debt structures as socially constructed and institutionally reinforced systems of dependency, advocating documentation, decentralization, and reduced financial dependence as pathways toward greater sovereignty and resilience.
This research paper explores the critical challenge of verifiable execution integrity in modern cloud and serverless computing platforms. While services like Amazon Web Services Lambda and Google Cloud Functions provide scalable and efficient execution environments, they operate as opaque systems where users cannot verify whether their code is executed correctly or securely. The paper identifies a fundamental trust gap in current cloud architectures and presents a comprehensive threat model covering risks such as hypervisor compromise, malicious insiders, supply chain attacks, and output manipulation. It highlights how existing security certifications and auditing mechanisms fail to provide cryptographic guarantees of correctness. To address this problem, the paper proposes a novel framework called the CodeNet Integrity Layer (CIL). This system integrates multiple advanced technologies, including Trusted Execution Environments (TEEs), Zero-Knowledge Proofs (ZKPs), and blockchain-based audit mechanisms, to create a decentralized and trustless verification model. The framework ensures that computation outputs are provably linked to the correct code and inputs without relying on blind trust in the provider. The proposed solution is evaluated through experimental implementation, demonstrating that strong execution integrity can be achieved with minimal performance overhead, making it practical for real-world deployment. The research contributes to the future of secure, transparent, and trustless cloud computing, particularly for sensitive applications in finance, healthcare, and critical infrastructure.
This article explores how Thai men construct and perform masculine identities through cryptocurrency trading, using the concept of crypto-masculinity to examine how digital finance becomes a site for gendered self-making. While existing scholarship on masculinity in financial contexts often centers on transnational business masculinities in Western corporate settings, little attention has been paid to how masculinity is enacted in decentralized, digital financial spaces, particularly in non-Western contexts. Addressing this gap, this article draws upon in-depth interviews with 21 male traders in Thailand to analyze how masculinity is shaped by the internal instability of masculinity and local cultural norms. This study identifies three key themes through which Thai men's subjectivity is negotiated: valorizing failure, homosociality, and ‘becoming a good Thai man.’ As a result, this article challenges assumptions about the naturalized links between men and finance, suggesting the need for further research on how exclusions within digital finances are taking place to better support equality on crypto platforms.
As blockchain ecosystems grow, financially motivated attackers increasingly exploit decentralized finance (DeFi) protocols, causing frequent and severe losses. Unlike conventional cyberattacks, DeFi exploits propagate rapidly due to the transparent and composable nature of smart contracts. We identify a critical pattern, Imitative Attack Cascade: an initial successful exploit is quickly followed by mimicking transactions that reuse attack logic with minor modifications or parameter changes. Our empirical analysis shows that over 69% of DeFi attacks exhibit strong behavioral similarity to earlier incidents, often within hours or days of the initial attack. This exposes a fundamental limitation in current reactive detection. Initial attacks are typically flagged via heuristic alerts (Tornado Cash traces, anomalous nonce usage, exploiter labels), but turning these signals into detection rules requires manual validation and handcrafted trace analysis -- a labor-intensive, slow process that leaves follow-up attacks to spread. Our goal is to ensure that once an attack has been observed, even a single instance, it can be rapidly abstracted into an actionable, generalizable detection rule. We decompose the problem into two challenges: (I) abstracting the semantics of diverse, obscure function signatures, and (II) matching transaction logic in noisy, evasive traces. We leverage two insights: (i) the open-source nature of most DeFi protocols enables high-fidelity semantic classification of function signatures; (ii) contract labels isolate essential logic by filtering irrelevant calls and classifying attack intent. Building on these, we develop GenDetect, which achieves ACC 98%, FPR 1%, FNR 3% and discovers 56 previously unrevealed attacks from the past three years. Source code and dataset: https://github.com/NobodyIsAnonymous/GenDetect_ICSE2026
This study rigorously formulates the complex fund-scheduling problem as a Markov decision process (MDP). It constructs a state space that integrates real-time and forecast information, an atomic action space that conforms to business logic, and a reward function that balances long-term returns against immediate risk. To address the curse of dimensionality and the credit-assignment problem in coordinated scheduling among multiple fund units, a multi-agent deep deterministic policy gradient (MADDPG) algorithm is adopted. Under a centralized-training and decentralized-execution framework, the algorithm reconciles global optimization with decentralized decision-making. In addition, a difference-reward mechanism and Kalman filtering are used to accurately measure each agent’s individual contribution and reduce the impact of environmental noise on reward signals. The results show that, compared with a static rule engine and a conventional linear programming method, the proposed deep reinforcement learning strategy reduces average daily funding costs by 50.4%, lowers the payment failure rate to 0.002%, and maintains a high liquidity buffer adequacy ratio. The strategy also demonstrates clear advantages in decision timeliness, collaborative handling of complex instructions, and self-adaptation potential, thereby providing an innovative pathway for finance-company fund scheduling to progress from intelligentization to automation.
Engineering Next-Gen Financial Systems: Designing Cloud-Native Middleware for Scalable Trading Architectures Objectives:1. To explain the principles of cloud-native architecture and middleware design for buildingscalable, resilient, and high-performance financial trading systems.2. To provide a comprehensive understanding of microservices, containerization, orchestration,messaging systems, and distributed data management in modern financial platforms.3. To demonstrate how advanced technologies such as Apache Kafka, Kubernetes, Redis, gRPC,and AI-driven systems can improve real-time trading operations and financial servicedelivery.4. To guide software engineers, architects, and financial technology professionals in designingsecure, fault-tolerant, and low-latency trading infrastructures with strong observability andcompliance practices.5. To prepare readers for the future of financial technology by exploring emerging trendsincluding serverless computing, WebAssembly, AI/ML integration, decentralized finance(DeFi), and next-generation cloud-native trading ecosystems. Table of Contents CHAPTER 1 The Great Migration: From Monoliths to MicroservicesCHAPTER 2 Foundations of Cloud-Native DevelopmentCHAPTER 3 Financial Middleware: The Digital Nervous SystemCHAPTER 4 High-Performance Messaging PatternsCHAPTER 5 Data Persistence and Caching StrategiesCHAPTER 6 Service Communication and API ManagementCHAPTER 7 Architectural Deep Dive: Market Data SystemsCHAPTER 8 Architectural Deep Dive: Order Management Systems (OMS)CHAPTER 9 Architectural Deep Dive: Algorithmic Trading PlatformsCHAPTER 10 Building for Failure: Resilience and ObservabilityCHAPTER 11 Security, Compliance, and Emerging TechnologiesCHAPTER 12 Case Study: A Cloud-Native Equity Trading Platform
Awqaf (Islamic endowments) historically functioned as decentralized institutions financing education, healthcare, infrastructure, and social welfare across the Muslim world. Grounded in the principles of perpetuity and inalienability, they transformed private wealth into sustainable public goods, as highlighted by Monzer Kahf and Murat Çizakça, while also facing institutional rigidity concerns raised by Timur Kuran.This paper examines the evolution of Awqaf from classical asset-based models to innovative structures such as cash waqf, waqf sukuk, corporate waqf, and intellectual property waqf. It proposes the Integrated Digital Awqaf Ecosystem (IDAE) Framework to explain how digitalization enhances governance, transparency, financial integration, and socio-economic impact. The study concludes that digitally integrated Awqaf can become strategic pillars of sustainable development in contemporary Muslim economies.
In the classic model, data integrity assumes a simple sender-receiver channel where threats are limited and verifications are straightforward. However, the modern Internet has reshaped this paradigm. In an era of viral misinformation, encrypted messaging, and decentralized finance, integrity is no longer about just who sent the data, but what it really means and whether it can be trusted. For instance, can we verify the authenticity of a direct message screenshot? Is Signal's end-to-end encryption truly end-to-end when a central server distributes users' keys? Can decentralized protocols, which have attracted four trillions in capital, sustain trust under attacks that wipe out millions?In response, we present a modern perspective on data integrity across diverse systems, arguing for the need of comprehensive innovations from theory to practice along three axes: cryptographic foundation in which we borrow ideas from theoretical research and develop interesting cryptographic tools, protocol design in which we find and achieve novel application goals, and empirical security analysis in which we critically evaluate deployed systems to understand their strengths and exploit their blind spots.To ground these ideas, we discuss three cases: Cauchyproofs as a batch-updatable vector commitment, an analysis of proxying in TLS oracles revealing subtleties in AEAD context unforgeability, and attacks and improvements on the Tor directory protocol. These case studies illustrate both the fragility and opportunity in today's integrity landscape, and how an integrated approach can help guide us forward.
Behkish Nassirzadeh, Rui Xi, Karthik Pattabiraman, Vasisht L. Ganesh
Blockchain technologies have experienced rapid adoption across various sectors, including supply chain management, decentralized finance and cross-border payments. With this growth, however, the complexity and security risks of maintaining blockchain integrity and functionality have increased. Addressing these challenges requires a systematic and rigorous organization of knowledge in blockchain security. This paper presents a Systematization of Knowledge (SoK) study based on a structured survey of academic literature, industry reports and real-world case studies. The authors classify vulnerabilities into three layers: system-level, smart contract-level and application-level, analyzing their root causes, real-world prevalence and mitigation tradeoffs. The taxonomy encompasses blockchain-specific threats (e.g. gas-based DoS attacks, MEV) as well as vulnerabilities inherited from distributed systems and software (e.g. Sybil attacks, access control failures). The authors critically evaluate detection and mitigation techniques, including static and dynamic analysis, fuzzing, symbolic execution and formal verification, assessing their precision, recall, scalability and inherent limitations. The authors further review state-of-the-art auditing tools in terms of methodology, adoption and shortcomings. Finally, the authors discuss advanced approaches such as hybrid frameworks that combine AI with program analysis, SMT solvers, and zero-knowledge proofs, outlining how these can address current gaps in scalability, interpretability and runtime verification. Overall, this study systematizes the security landscape of blockchain technologies, synthesizes the limitations of current approaches, and identifies technically actionable future research directions toward building more robust and resilient blockchain systems.
Environmental sustainability transitions require robust indicator-based evidence to evaluate how technological, financial, and governance factors shape progress toward carbon neutrality. However, the environmental sustainability indicators literature still offers limited evidence on how these structural drivers jointly influence a core environmental indicator within a single advanced economy context . This study examines Canada’s carbon transition by assessing the long- and short-run effects of artificial intelligence (AI) innovation, stock market capitalization, fiscal decentralization, renewable energy consumption, and economic growth on CO 2 emissions over the period 1990 to 2023. Grounded in the integrated insights of the Environmental Kuznets Curve, Ecological Modernization Theory, and the Technology-Environment Nexus, the study employs autoregressive distributed lag (ARDL) bounds testing, which is well suited to mixed orders of integration and relatively small annual time-series samples , complemented by FMOLS, DOLS, and CCR estimators. The findings show that AI innovation and financial system expansion are associated with higher emissions in the long run, whereas fiscal decentralization and renewable energy consumption contribute to emissions reduction. These results suggest that technological and financial advancement do not automatically improve environmental performance unless supported by effective governance and sustainability-oriented policy coordination. The findings offer policy-relevant insights for designing governance and monitoring frameworks that better align innovation, finance, and decentralized decision-making with long-term environmental sustainability goals.
Automated Market Makers (AMMs), as a core infrastructure of decentralized finance (DeFi), uniquely drive on-chain asset pricing through a deterministic reserve ratio mechanism. Unlike traditional markets, AMM price dynamics is triggered largely by on-chain events (e.g., swap) that change the reserve ratio, rather than by continuous responses to off-chain information. This makes event-level analysis crucial for understanding price formation mechanisms in AMMs. However, existing research generally neglects the micro-structural dynamics at the AMMs level, lacking both a comprehensive dataset covering multiple protocols with fine-grained event classification and an effective framework for event-aware modeling. To fill this gap, we construct a dataset containing 8.9 million on-chain event records from four representative AMMs protocols: Pendle, Uniswap v3, Aave and Morpho, with precise annotations of transaction type and block height timestamps. Furthermore, we propose an Uncertainty Weighted Mean Squared Error (UWM) loss function, which incorporates the block interval regression term into the traditional Temporal Point Process (TPP) objective function by weighting the uncertainty with homoscedasticity. Extensive experiments on eight advanced TPP architectures across four representative DeFi protocols demonstrate that this loss function reduces the time prediction error by an average of 31.17% while maintaining the accuracy of event (transaction) type prediction, establishing a robust benchmark for event-aware prediction in the AMMs ecosystem. This work provides the necessary data foundation and methodological framework for modeling the discreteness and event-driven characteristics of on-chain price discovery. All datasets and source code are publicly available. https://github.com/finbrain-lab-hkustgz/Deep-AMM-Events
This case study examines the transformative impact of Decentralized Finance (DeFi) on India’s traditional banking sector through a multi-stakeholder perspective. Drawing on both quantitative performance indicators and qualitative stakeholder insights, the study explores how DeFi influences operational efficiency, financial inclusion, and regulatory compliance. The findings indicate that while DeFi enhances transaction efficiency and expands access to credit, its integration into India’s financial ecosystem is constrained by regulatory ambiguity, cybersecurity concerns, and infrastructural disparities. The case highlights the need for a hybrid financial architecture supported by collaborative governance and adaptive regulatory frameworks.
The rapid expansion of blockchain infrastructures, Web3 architectures, and immersive metaverse environments has reignited calls for a Universal Code of Digital Ethics. International organizations, technology leaders, and multilateral forums increasingly advocate for global standards capable of guiding decentralized innovation toward inclusion, transparency, and social good. Yet the normative ambition of universality confronts a structural contradiction: digital access, connectivity quality, and technological literacy remain profoundly unequal across the Global South.Ethical frameworks for Web3 and the metaverse often presuppose a baseline of connectivity, computational capacity, and institutional stability that large segments of humanity do not possess. The COVID-19 pandemic amplified these asymmetries, accelerating digital transformation in high-income countries while deepening infrastructural gaps elsewhere. Concurrently, geopolitical tensions and emerging techno-nationalist strategies have repoliticized digital infrastructure as a domain of strategic competition rather than global solidarity.This Opinion article argues that any claim to a "universal" digital ethics framework is normatively fragile unless it incorporates a structural critique of global capitalism, technological acceleration, and asymmetrical power. Drawing on critical theory-particularly Herbert Marcuse's concept of the "one-dimensional man"-as well as Marxian analyses of technology and capital, I contend that ethical discourse risks becoming ideologically functional to market expansion if it fails to address material inequalities in connectivity and digital capability (Marcuse, 1972;Marx, 2005;García Ramírez, 2021).proposals but also problematizes the concept of universality itself as a normative and political construct.Global ethics initiatives often frame digital transformation as inherently democratizing. Blockchain is described as decentralized, Web3 as user-empowering, and the metaverse as participatory. However, decentralization at the protocol level does not necessarily translate into equitable access at the societal level.In regions of the Global South, access to stable broadband remains limited, mobile data costs are disproportionate to income, and digital literacy gaps persist. Under such conditions, the ethical vocabulary of autonomy, self-sovereign identity, and tokenized participation becomes aspirational rather than operative.Marx's analysis of technology as a force embedded within relations of production remains instructive. Technology is not neutral; it is shaped by capital accumulation dynamics (Marx, 2005). Fumikazu (1983) similarly emphasized that technological evolution must be understood historically and politically. When applied to Web3 ecosystems, this suggests that blockchain infrastructures operate within global financial logics that may reproduce, rather than dissolve, structural dependency.Contemporary Science and Technology Studies (STS) and critical philosophy of technology further reinforce this perspective. Feenberg (1999) argues that technology is not merely instrumental but socially constructed and politically conditioned, shaped by dominant interests yet open to democratic transformation. Similarly, Yuk Hui (2020) challenges the presumed universality of technological rationality, proposing the concept of "technodiversity" to account for plural technological trajectories rooted in different cultural and cosmological traditions. These perspectives suggest that any ethical framework for digital technologies must recognize the multiplicity of socio-technical realities rather than assume a homogeneous global condition.Thus, a universal code of digital ethics risks functioning as what critical theory would describe as ideological abstraction-detached from the material preconditions required for ethical agency.Herbert Marcuse's One-Dimensional Man (1972) provides a compelling lens through which to interpret contemporary digital governance. Marcuse argued that advanced industrial societies generate a form of technological rationality that integrates dissent by absorbing it into the logic of efficiency and consumption.In the context of Web3 and the metaverse, ethical discourse may become one-dimensional when it focuses on procedural compliance (privacy standards, transparency metrics, algorithmic audits) while neglecting structural exclusion. The language of inclusion becomes embedded within market expansion strategies. As Daum (2018) argues, digital capitalism increasingly converts users into capital itself-data, attention, and participation become monetizable assets.From a constructivist perspective, technologies such as blockchain are not inherently emancipatory but acquire meaning through their social embedding (Bijker, 1995). This implies that ethical claims about decentralization and empowerment must be evaluated in relation to the socio-economic contexts in which these technologies are deployed. Without such contextualization, ethical discourse risks overstating the transformative potential of technological architectures. This dynamic is particularly visible when global institutions promote digital entrepreneurship and blockchain adoption in developing regions without parallel investments in public infrastructure, education, and regulatory sovereignty. The rhetoric of empowerment may conceal asymmetric dependency.Cañas Quirós (2023) emphasizes that ethics cannot be separated from political structures; morality detached from power analysis risks legitimizing unjust arrangements. In this sense, digital ethics frameworks must confront the political economy of connectivity rather than merely codify behavioral norms for technology developers.Digital governance is increasingly entangled with geopolitical competition. Infrastructure financing, cloud sovereignty, semiconductor supply chains, and cybersecurity alliances shape technological ecosystems. In this context, international organizations often advocate regulatory harmonization to "facilitate innovation" and "reduce market friction".While harmonization may lower barriers for cross-border digital services, it can simultaneously constrain policy autonomy in developing nations. Ethical frameworks that prioritize market efficiency risk subordinating universal connectivity goals to investor confidence and capital mobility.García Ramírez (2021) calls for a "Marx in the South," reinterpreting technology through the lens of rights, education, and structural inequality. From this perspective, Web3 adoption without universal broadband is analogous to building virtual property rights atop infrastructural scarcity. The promise of decentralized finance or immersive governance becomes utopian-or dystopian-when foundational digital rights remain unrealized.The acceleration principle of technological evolution -where innovation in wealthy nations compounds exponentially-renders access in peripheral regions inversely proportional to global advancement. Ethical frameworks that ignore this asymmetry may inadvertently normalize a tiered digital citizenship.The assumption that a single set of ethical principles can be universally applicable across diverse socio-cultural and technological contexts has been widely debated. From decolonial and pluralist perspectives, ethical frameworks are historically situated and epistemically conditioned (Escobar, 2018). What is considered "ethical" in one context may not translate directly into another, particularly when technological infrastructures, cultural values, and political systems differ significantly.In this sense, the concept of a Universal Code of Digital Ethics may be inherently paradoxical. Rather than a fixed and homogeneous set of principles, digital ethics may need to be understood as a plural and adaptive framework, capable of accommodating different technological ontologies and social priorities. This does not imply abandoning normative aspirations, but rather rethinking universality as negotiated, situated, and contingent.If a global digital ethics framework is to be normatively defensible-whether universal or plural-it must integrate structural and contextual dimensions:If universality is to be normatively defensible, digital ethics must integrate at least five structural components:If universality is to be normatively defensible, digital ethics must integrate at least five structural components:1.Material Preconditions Clause: Ethical standards should explicitly recognize connectivity, affordability, and digital literacy as prerequisites for meaningful participation.Political Economy Transparency: Frameworks must disclose how market incentives shape technological deployment.Geopolitical Reflexivity: Digital governance should account for power asymmetries between states and corporations.Public Infrastructure Commitment: Ethical guidelines must prioritize universal broadband as a public good, not merely a commercial opportunity.Critical Participation Mechanisms: Inclusion must extend beyond tokenized representation toward substantive decision-making capacity.5.6. Epistemic Pluralism: Ethical frameworks must recognize diverse knowledge systems, cultural values, and technological imaginaries, particularly from the Global South.Such principles align ethics with transformative social justice rather than technocratic governance.The aspiration to develop a Universal Code of Digital Ethics for Web3 and the metaverse is commendable. However, without structural critique, universality risks becoming rhetorical. Critical theory reminds us that technological systems embed power relations (Marcuse, 1972). Marxian perspectives reveal how capital shapes technological deployment (Marx, 2005). Contemporary analyses from the Global South highlight the need to situate ethics within historical and geopolitical realities (García Ramírez, 2021;Cañas Quirós, 2023). The ethical question is not merely how to regulate blockchain or ensure transparency in virtual worlds. It is whether digital transformation reproduces one-dimensional rationality-where market logic absorbs ethical discourse-or fosters multidimensional emancipation grounded in material equality.A truly global digital ethics must therefore begin not with code, but with conditions. Without universal connectivity and critical capacity, Web3 and the metaverse risk becoming architectures of selective participation. Ethics, to be universal, must first be infrastructural. Ethics, whether conceived as universal or plural, must first be infrastructural, contextual, and politically grounded.
Financial fraud across cross-border payment systems and blockchain-based transaction networks has grown in scale, sophistication, and velocity, driven by increased digitization, regulatory fragmentation, and the pseudonymous nature of decentralized infrastructures.This study presents a comprehensive examination of AI-driven anomaly detection techniques designed to address these evolving threats.From a broad perspective, the paper reviews the global financial ecosystem, highlighting vulnerabilities in traditional correspondent banking frameworks and emerging decentralized finance (DeFi) architectures.It then narrows to advanced machine learning and deep learning approaches, including supervised, unsupervised, and hybrid models such as autoencoders, graph neural networks, and reinforcement learning systems for real-time fraud detection.Particular emphasis is placed on transaction pattern analysis, behavioral profiling, and network topology modeling to uncover hidden relationships and detect anomalous activities across distributed ledgers and cross-border payment rails.The study further evaluates challenges such as data sparsity, class imbalance, adversarial manipulation, privacy constraints, and regulatory compliance, including AML and KYC requirements.By integrating AI with blockchain analytics and financial monitoring systems, the paper demonstrates how adaptive, scalable, and explainable detection frameworks can significantly enhance fraud prevention capabilities.The findings provide strategic insights for financial institutions, regulators, and fintech developers aiming to strengthen global financial security.
The article is devoted to the development of a hybrid strategy for the innovative growth of the Ukrainian neobank Monobank through the integration of cryptocurrency services in the context of the draft law on cryptocurrency legalization under consideration in the Verkhovna Rada. The relevance of the study is determined by the need to diversify neobanks’ income sources amid market saturation and regulatory changes in the field of digital assets. The classification of Monobank as a neobank is substantiated according to the criteria of the European Banking Authority: a fully digital model without physical branches, a client-centric business model, its own technological platform, and a methodology for rapid product development. A SWOT analysis of the bank’s competitive position revealed an imbalance between opportunities and threats under martial law, cyber risks, and regulatory uncertainty. A comparative analysis of the crypto-strategies of international neobanks Revolut and Nubank confirmed the advantages of the intermediary role over issuing a proprietary token. Revolut’s success is based on phased integration and obtaining regulatory licenses, while Nubank’s failure with its own token demonstrates the risks of hasty decisions without a clear regulatory strategy. The concept of the Monobank Crypto Hub has been developed with a three-phase implementation: the first stage focuses on basic functionality with mandatory transaction limits and an educational module to minimize reputational risks; the second stage provides for expanded functionality through staking and premium subscription; the third stage includes a full ecosystem with crypto-deposits and integrations with decentralized finance protocols. Financial modeling demonstrates a gradual achievement of break-even with emphasis on managing operational and reputational risks. The practical value of the study lies in the formation of a concrete roadmap for crypto-integration for Ukrainian fintech companies.