Background: Early childhood caries remains a major public health burden in Thailand, particularly among preschool children, despite the implementation of national oral health policies. With the decentralization of child development centers (CDCs) to local adminis-trative organizations (LAOs), understanding system-level determinants of oral health ser-vice effectiveness has become critical. This study aimed to identify key determinants in-fluencing the effectiveness of oral health care systems for preschool children within CDCs in northeastern Thailand. Methods: A cross-sectional analytical study was conducted among 270 stakeholders across urban, peri-urban, and rural CDCs in Ubon Ratchathani Province. Participants were selected using multi-stage random sampling. Data were col-lected between November 2023 and January 2024 using a structured questionnaire with established content validity (IOC > 0.50) and reliability (Cronbach’s alpha = 0.71–0.77). Variables were organized within an Input–Process–Output (IPO) framework. Descriptive statistics, Pearson’s correlation, and multiple linear regression analyses were performed to identify significant predictors of system effectiveness. Results: The oral health care system demonstrated strong performance in preventive service delivery, including universal oral health examinations and fluoride varnish application (100%), and high personnel readi-ness (99.63%). However, critical gaps were identified in monitoring and evaluation sys-tems (8.15%), budget adequacy (60.37%), and continuity of treatment follow-up (48.89%). The prevalence of dental caries among preschool children was 57.83%. Multiple regression analysis revealed that service delivery processes (β = 0.458, p < 0.001) and home visits by public health and dental personnel (β = 0.303, p = 0.008) were significant determinants of system effectiveness, jointly explaining 11.1% of the variance (R² = 0.111). Conclusions: The effectiveness of preschool oral health care systems in decentralized settings is driven pri-marily by the quality of service delivery processes and the integration of proactive commu-nity outreach through home visits. Strengthening monitoring and evaluation mechanisms, ensuring sustainable financing, and enhancing continuity of care between CDCs and households are essential for improving oral health outcomes. These findings provide ac-tionable evidence for policymakers and local health administrators seeking to optimize oral health systems under decentralized governance structures.
Dappfort is a blockchain-focused Web3 development company that helps businesses harness the power of decentralized technologies to build secure, scalable, and future-ready digital solutions. Headquartered in Madurai, India, with additional presence in London, Dappfort works across a broad range of industries — including finance, healthcare, gaming, retail, and supply chain — delivering tailored blockchain and Web3 applications to startups, enterprises, and global organizations. The company’s core services include the design and development of decentralized applications (DApps), crypto exchanges (centralized and decentralized), crypto wallets, NFT marketplaces, DeFi platforms, token creation, smart contract development, and enterprise Web3 integration. Dappfort also expands into related areas such as Web3 e-commerce, AI-powered blockchain solutions, and metaverse experiences, supporting clients from strategy and consulting through deployment and ongoing support. With expertise in major blockchain networks like Ethereum, Solana, Binance Smart Chain, and others, Dappfort positions itself as a full-stack partner for businesses aiming to enter or grow in the decentralized digital economy. While the company promotes a strong innovation- and security-oriented approach, external reviews on third-party platforms show mixed feedback from users about project delivery and quality.
Open access
2 source records
Internet of Things and AI
Blockchain Technology Applications and Security
Innovations and Analysis in Business and Education
Cryptocurrency has emerged as a transformative asset class, reshaping traditional investment and portfolio management strategies. This study explores the impact of cryptocurrencies on modern investment portfolios, highlighting their potential for diversification, risk management, and return optimization. The decentralized nature of digital assets, combined with blockchain technology, has introduced a new paradigm in financial markets. However, the high volatility of cryptocurrencies remains a significant challenge, affecting portfolio stability and investor confidence (Brière, Oosterlinck, & Szafarz, 2015). This research examines key factors influencing cryptocurrency investments, including market trends, risk exposure, regulatory developments, and institutional adoption. By utilizing statistical analysis and market data, the study evaluates the correlation between cryptocurrencies and traditional asset classes such as stocks, bonds, and commodities. The findings indicate that while cryptocurrencies can enhance portfolio diversification, they also exhibit greater price volatility than conventional financial assets (Corbet, Meegan, Larkin, Lucey, & Yarovaya, 2018). Additionally, the study investigates how institutional investors are integrating digital assets into their portfolios and examines the impact of regulatory policies on market stability. The results suggest that regulatory clarity significantly influences investor confidence and risk mitigation strategies (Auer & Claessens, 2020). Furthermore, Bitcoin’s role as an inflation hedge is analyzed, with evidence supporting its potential as a store of value during periods of economic uncertainty (Yermack, 2015). The study concludes that cryptocurrencies continue to represent an emerging yet highly uncertain asset class within modern portfolio management. While investors acknowledge the potential benefits of cryptocurrencies, including high return opportunities and portfolio diversification, significant concerns remain regarding market volatility, regulatory uncertainty, and long-term sustainability. The findings reveal that investors perceive cryptocurrencies as high-risk investments and remain cautious about their consistent performance compared to traditional financial assets. The study further highlights that uncertainty surrounding global cryptocurrency regulations and market stability limits broader investor confidence and adoption. Although digital assets possess the potential to transform investment strategies through technological innovation and decentralized finance, investors continue to adopt a balanced and risk-conscious approach toward cryptocurrency investments. Therefore, effective regulatory frameworks, investor education, strategic asset allocation, and continuous monitoring of market developments are essential for the sustainable integration of cryptocurrencies into modern investment portfolios.
Andreas Polyvios Delladetsimas, Elias Iosif, Stamatis Papangelou, George Giaglis
This article examines blockchain as an enabling technological component for data management tasks that are independent of currency-related functionality, a less-discussed aspect of a technology commonly associated with cryptocurrencies and decentralized finance (DeFi). Drawing on empirical findings from the DIGI4ECO project as a case study, we present a structured literature review and cross-domain analysis of blockchain-based data management systems (BDMSs), examine a representative permissioned BDMS implementation, and synthesize practical design guidelines and implementation insights for BDMS development. This perspective is motivated by core blockchain properties such as immutability and transparency, as well as by the observation that existing resources for BDMS development, including methods, tools, and best practices, remain fragmented and less developed than those available for more mature technologies.
Daniel González Cortés, Monomita Nandy, Suman Lodh
Abstract This research analyzes the performance and interconnectedness of major global stock market indices and decentralized finance assets, specifically cryptocurrencies, over the period from 2015 to 2025. The study includes indices such as the S&P 500 and Nasdaq Composite from the United States, the FTSE 100, DAX, and CAC 40 from Europe, and the Nikkei 225 from Japan, and two more indices from China and India representing different economic regions. Additionally, Bitcoin and Ethereum are included to assess the impact of decentralized finance on traditional financial indices and asset allocation strategies. By employing Artificial Intelligence algorithms like ConvLSTM, the research measures the dynamic asset allocation and volatility management through an interconnected spillover matrix. The findings reveal that integrating ConvLSTM enhances the understanding of the interconnectedness between cryptocurrencies and traditional assets, offering improved diversification opportunities due to their low correlation, decentralization, and inflation-hedge characteristics. The study’s results suggest that investors can make more informed decisions regarding dynamic asset allocation in high-volatility portfolios, providing indicators of rising systemic risk and market stress.
The rapid evolution of Decentralized Finance (DeFi) has introduced unprecedented financial innovations alongside complex fraud vectors that challenge conventional security mechanisms.Traditional fraud detection systems rely heavily on centralized data aggregation and opaque machine learning models, which are fundamentally incompatible with the decentralized and trust-minimized architecture of blockchain ecosystems.Emerging paradigms such as Federated Learning (FL) and Explainable Artificial Intelligence (XAI) have been independently proposed to address privacy and transparency concerns in financial systems.However, despite significant progress in each domain, the literature reveals methodological fragmentation and architectural disconnection among blockchain-based fraud detection, privacy-preserving learning, and explainability mechanisms.This study critically reviews existing research on traditional finance fraud detection, blockchain analytics, federated learning security, XAI applications, and blockchain-FL integration frameworks.Through comparative and analytical synthesis, it identifies critical research gaps, including the absence of unified decentralized fraud architectures, insufficient explainability in on-chain systems, and limited governance models for federated financial intelligence.This study establishes a theoretical and technological foundation for an integrated blockchain-driven FL-XAI framework tailored for DeFi fraud detection.
Decentralized finance (DeFi) has been studied mainly as a financial and technological system, while the role of digital entrepreneurial capability in shaping sustainable user traction remains underexplored. This study repositions DeFi as a digitally mediated entrepreneurial ecosystem and examines whether retention-oriented user behavior is associated with three capability dimensions—entrepreneurial visibility, network embeddedness, and organic acquisition efficiency—together with ecosystem-finance conditions such as total value locked and decentralized-exchange activity. Using an exploratory, correlational design with monthly aggregated data from five incumbent DeFi platforms during the post-FTX recovery period (October 2022–September 2023), the analysis combines canonical correlation analysis, partial least squares regression, and ridge regression. Results indicate a significant multivariate association between ecosystem-finance conditions and the entrepreneurial-capability block, and show that returning-visitor behavior is more coherently linked to the predictor set than broad visitor inflow. Entrepreneurial Visibility Capital and Network Embeddedness emerge as the most stable positive correlates of user retention, while Organic Acquisition Efficiency shows a directionally mixed pattern. Because the sample is small, the findings are interpreted as preliminary evidence rather than confirmatory claims. Overall, the study offers an integrative framework that connects DeFi, digital entrepreneurship, and sustainability-oriented business-model research, and identifies the joint configuration of digital capability and financial conditions as a promising direction for future, larger-scale investigation.
The purpose of this paper is to identify the industry-specific and geographic patterns that shape the adoption of Web 3.0 technologies among Fortune Global 500 companies. The study addresses a gap in the existing literature by shifting attention from isolated technological applications such as blockchain, decentralized finance, artificial intelligence, and immersive environments toward a broader comparative analysis of how large multinational corporations adopt Web 3.0 across sectors and countries. Methodology. The paper is based on an empirical classification of Fortune Global 500 companies for 2024 into adopters and non-adopters of Web 3.0 technologies. The dataset includes 500 firms and covers sector affiliation, country of origin, employee counts, selected financial indicators, company characteristics, and a binary indicator of adoption status. The analysis applies descriptive statistics, comparative analysis, and cross-tabulations using publicly available data from annual reports, strategic plans, press releases, marketing materials, news coverage, and business databases. Results. The findings show that Web 3.0 adoption is significant but uneven: 216 companies are identified as adopters, while 284 are classified as non-adopters, indicating that Web 3.0 remains in a transitional stage of corporate diffusion. Adoption is concentrated in digitally intensive sectors such as Information Technology Services, Computer Software, Entertainment, Apparel, and selected Health Care activities, whereas sectors such as Transportation and Logistics, Real Estate, Homebuilders, and Medical Products and Equipment demonstrate limited or no adoption in the dataset. Geographic differences are also substantial, with adoption present in 25 out of 35 countries represented in the sample, although the intensity of adoption varies across national contexts. The results confirm that Web 3.0 diffusion is shaped by the interaction of sectoral structure, strategic fit, and geographic environment rather than by a uniform technological trajectory. Practical implications. The paper suggests that managers should approach Web 3.0 as a strategic option whose relevance depends on alignment with the firm’s business model, customer value proposition, governance needs, and innovation capabilities. Value/originality. The originality of the study lies in its cross-sectoral and cross-national perspective on Web 3.0 adoption among the world’s largest corporations, offering a more nuanced understanding of digital transformation in the Web 3.0 era and demonstrating that adoption is patterned, selective, and contingent rather than universal.
Sovereign AI-Native Multi-Asset Trading, Execution, and Financial nfrastructure Charter Sovereign AI‑Native Financial Execution Infrastructure PARRALAX‑AIHFTFUND is a multi‑asset, AI‑native financial organism engineered to operate across traditional and blockchain‑based markets. It provides a unified execution layer where autonomous agents can observe markets, interpret structure, execute trades, manage risk, govern portfolios, issue digital assets, coordinate token economies, and maintain verifiable proof‑of‑computation. This repository contains the core infrastructure, protocol stack, and governance architecture for building sovereign, agent‑driven financial systems. Mission To build a sovereign AI‑native financial infrastructure capable of coordinating autonomous trading agents, multi‑asset execution, fund governance, risk control, digital‑asset creation, and market intelligence across both traditional and blockchain‑native markets. The system exists to move beyond bots, dashboards, and scripts. Its purpose is to become a real execution organism for financial markets. Vision PARRALAX‑AIHFTFUND aims to create a long‑horizon financial intelligence layer where AI agents can: Observe and interpret global market structure Execute trades across heterogeneous venues Manage risk and exposure Govern portfolios and internal policy Issue and manage digital assets Coordinate internal token economies Maintain proof‑of‑computation and decision lineage Operate across crypto, fiat, equities, FX, derivatives, AI tokens, NFTs, and future asset classes Build market memory over time The system is designed to evolve as markets evolve. Foundational Premise Modern markets are: Machine‑driven Fragmented Multi‑asset Tokenized Agent‑mediated A serious financial infrastructure must therefore operate across: Traditional finance (equities, FX, derivatives, funds) Decentralized finance (DEXs, AMMs, on‑chain liquidity) Tokenized and synthetic assets AI‑native markets Autonomous agent economies High‑speed execution environments Governance‑controlled fund structures Programmable financial instruments PARRALAX‑AIHFTFUND is built to bridge old‑world and new‑world markets. What PARRALAX‑AIHFTFUND Is A sovereign trading infrastructure framework An AI‑native market execution system A multi‑asset financial operating layer A protocol stack for autonomous trading agents A fund governance and charter framework A digital‑asset issuance and management environment A blockchain‑compatible coordination layer A risk‑aware execution engine A compute‑receipt and proof‑trace system A foundation for future AI‑managed financial organisms It is built for real execution, not passive analysis. What PARRALAX‑AIHFTFUND Is Not Not a research repo Not a toy trading bot Not a simulation Not a dashboard Not a signal script collection Not a crypto hype project Not a single‑asset system Not a prediction‑only model Research supports the system. Research does not define the system. Status Active development. Core modules stabilizing. Execution layer expanding. Governance and digital‑asset subsystems in progress. PARRALAX‑AIHFTFUND is an AI‑native financial execution framework designed to coordinate autonomous agents across traditional and blockchain‑based markets. The system provides a unified operating layer for multi‑asset execution, risk management, fund governance, digital‑asset issuance, and verifiable compute‑traceability. System Mission To construct a sovereign financial intelligence layer capable of continuous operation across heterogeneous markets, enabling agents to observe market conditions, interpret structure, execute trades, manage exposure, and maintain internal governance. Operational Scope The system is engineered to function across: Traditional finance (equities, FX, derivatives, funds) Decentralized finance (DEXs, AMMs, on‑chain liquidity) Tokenized and synthetic assets AI‑native markets and agent economies Governance‑controlled fund structures High‑speed execution environments Programmable financial instruments System Definition PARRALAX‑AIHFTFUND comprises: A sovereign trading and execution infrastructure A multi‑asset financial operating layer A protocol stack for autonomous trading agents A governance and charter framework A digital‑asset issuance and management environment A blockchain‑compatible coordination layer A risk‑aware execution engine with compute receipts Non‑Scope The system is not a research‑only repository, simulation toy, dashboard, signal script collection, or prediction‑only model. It is infrastructure‑first and execution‑oriented.
The results of this research are based on Law Number: 1 of 2022 concerning Financial Relations between the Central Government and Regional Governments regulating the new design of transfer funds to regions, regional income and expenditure. Likewise, it regulates how to monitor and provide evaluation of regional spending so that any existing budget can be used effectively and efficiently. The Ministry of Finance continues to strive to solve and eliminate gaps in the misuse of transfer funds to regions and village funds while seeking harmony between central and regional fiscal policies. This research aims to evaluate the level of transparency and accountability of transfers to regional and village funds through cash account management and assess the quality of government cash management and also evaluate government account management in increasing government revenue. This research uses a qualitative descriptive method by utilizing secondary primary data originating from various literature. From 2022 to 2023, it is even estimated that by the end of 2024, transfer funds deposited in regional government accounts throughout Indonesia at regional banks will average more than IDR 100 trillion. Deposition of funds will disrupt development and public service activities. In fact, it is hoped that government spending will be realized, which is the main stimulus for regional economic movements. By joining regional governments in the Treasury Single Account (TSA), all aspects of financial resource mobilization and expenditure can be managed as a whole by the government for the benefit of the people. Apart from strengthening and responding to the challenges of limited government financial resources. Existing idle cash can generate income. The participation of the Regional Government in implementing the Treasury Single Account (TSA) does not reduce the autonomy that has been mandated.
This paper is dedicated to a complex analysis of the fiscal decentralization process in Georgia and its causal relationship with the level of municipal financial sustainability. The relevance of the research is driven by the legislative changes implemented over the last decade, including the transition to a new Value Added Tax (VAT) distribution model since 2019, which fundamentally altered the budgetary architecture of local self-governments. The aim of the paper is to determine the extent to which the existing fiscal model ensures real financial autonomy for municipalities and whether it reduces vertical fiscal imbalance. The study employs quantitative methodology, specifically a panel data analysis of the budgetary figures of Georgia's 64 municipalities for the period 2018-2024. To evaluate financial sustainability, a system of indicators is utilized, encompassing the self-sufficiency ratio, the transfer dependency index, and the capacity for capital expenditure financing. The research findings reveal that despite the declared progress in decentralization, the majority of Georgian municipalities still experience fiscal illusion and a high level of dependency on central transfers. The analysis shows that while the VAT distribution formula has increased the predictability of municipal revenues, it has failed to ensure the complete leveling of regional inequalities. The paper argues that to achieve financial sustainability, it is essential to optimize the local property tax base and diversify municipal borrowing authorities. The study concludes with practical recommendations focused on refining fiscal policy in accordance with the standards of the European Charter of Local Self-Government.
Central bank digital currencies (CBDCs) integrated with decentralized finance (DeFi) represent a transformative development in digital financial systems. However, there is a lack of systematic frameworks for prioritizing the determinants of effectiveness and sustainability in DeFi-integrated CBDC platform investments. This study develops an integrated multicriteria decision-making framework to identify critical evaluation criteria and rank alternative platform architectures under uncertainty. The proposed model combines objective expert weighting, interaction-sensitive criteria evaluation, and fuzzy-based alternative ranking within a unified analytical structure. The results indicate that technological infrastructure (0.168) and liquidity (0.167) are the most influential criteria, while hybrid and privacy-focused platforms emerge as the most suitable investment alternatives. These findings highlight the importance of balancing technological robustness, liquidity depth, and privacy considerations in CBDC design. The study contributes by offering a structured and uncertainty-sensitive decision framework to support strategic platform selection and policy formulation in evolving digital currency ecosystems.
Muhammad Imamul Muttaqin Arisandi, Bustomi Arisandi, Bahrul Ulum, M. Khodimul Wahib · 5 authors
This study examines the construction of an Islamic digital asset governance framework within the context of blockchain integration for zakat transparency and digital estate planning in Indonesia. The research responds to the growing tension between rapid technological transformation in Islamic finance and the absence of comprehensive sharia-oriented regulatory mechanisms governing crypto assets, decentralized transactions, and digital inheritance systems. Employing a non-empirical juridical-normative method, the study analyzes statutory regulations, DSN-MUI fatwas, comparative international regulatory models, and interdisciplinary scholarly literature concerning Islamic fintech, blockchain governance, and Maqasid Shariah. The findings indicate that existing regulatory approaches remain fragmented because financial supervision, sharia compliance, and inheritance governance operate within disconnected institutional frameworks. Blockchain technology demonstrates significant potential to enhance transparency, accountability, and efficiency in zakat and waqf management through immutable ledgers and automated smart-contract mechanisms, although unresolved cyber risks, speculative volatility, and succession vulnerabilities continue to threaten the principle of hifzh al-mal. The study formulates the Islamic Digital Asset Governance Framework (IDAGF), integrating technical supervision, sharia certification, judicial authorization, and social-finance accountability into a multilayered governance structure capable of harmonizing algorithmic innovation with Islamic legal certainty and sustainable digital financial ethics.
Eunchan Park, Kyonghwa Song, Won Hoi Kim, Wonho Song · 5 authors
Traditional blockchain untraceability schemes, such as mixers and privacy coins, obscure the sender-receiver relationship by placing transfers within an anonymity set. This paper studies a stronger goal: whether the transfer event itself can be made unobservable by blending into common decentralized-finance (DeFi) activity. We introduce Deniable Covert Asset Transfer (DCAT), a class of transfers that stage common loss-producing events, such as sandwich and arbitrage operations, so that a sender appears to suffer an ordinary loss while the receiver appears to profit from it. We design and validate two DCAT instantiations: a sandwich-based transfer on Ethereum and an arbitrage-based transfer on Arbitrum. Our experiments show that, under the evaluated settings, DCAT transfers are empirically unobservable on both chains. They are syntactically identical to corresponding maximal extractable value (MEV) activities, classified as ordinary extractions by standard MEV detection tools, and leave the sender and receiver unlinked under representative forensic tools. Since syntactic inspection cannot distinguish DCAT from ordinary MEV activity, we examine whether economic semantics provide useful forensic signals. Through a large-scale study of MEV losses on Ethereum and Arbitrum, we show that key semantic features follow power laws. Extreme losses and repeatedly exploited addresses occur in the wild, and thus are not by themselves definitive evidence of collusion. This gives staged transfers plausible deniability and makes fixed-threshold detection prone to false positives. We therefore develop a multivariate statistical method for forensic triage that ranks incidents by the joint rarity of their economic footprint. Applied to real-world DeFi activity, our method narrows a large search space to suspicious cases for manual investigation; we present three such cases to illustrate this prioritization.
We introduce the State Twin: a typed, in-memory, replayable replica of an on-chain automated market maker (AMM) pool that serves as a substrate for agentic reasoning over decentralized finance (DeFi) protocols. Agentic DeFi stacks today couple reasoning to chain time, since every "what if?" query incurs a new RPC read or a real transaction, so the agent's effective action space is bounded by block confirmation latency and gas. We argue this coupling is a structural problem rather than a performance one, and that the missing layer is an off-chain substrate that preserves the protocol's exact mathematics while admitting the operations on-chain state cannot: forking, replay, branching, counterfactual rollout. We formalize each AMM family (Uniswap V2, V3, Balancer, Stableswap) as a discrete-time controlled dynamical system, prove a quantitative fidelity bound on the divergence between twin and chain, and give the open architecture used in DeFiPy v2, an open-source Python toolkit that ships the State Twin substrate and a reference Model Context Protocol server exposing typed analytical primitives as LLM tools. The same primitive (i.e., one Python class, one calling pattern) serves a notebook quant, a backtest, and an LLM agent without modification. We close with a fork-and-evaluate worked example: a single live RPC read seeds N independent in-memory twins under distinct price-shock scenarios, in sub-second wall-clock time. The contribution is the substrate, not a particular agent, which is what the specification of what an agentic DeFi substrate must look like
Victor James Uko, Sharon Oluwaseun, Amarachi Nelly Charles, Emurode Williams · 5 authors
The rapid proliferation of digital technologies has profoundly reshaped the financial services sector, introducing novel service delivery models, market participants, and transactional infrastructures that challenge the foundational premises of existing regulatory frameworks. This review examines the multidimensional dynamics of digital transformation in financial services, with particular attention to the regulatory and consumer protection implications arising from the emergence of fintech ecosystems, artificial intelligence-driven financial products, decentralized finance platforms, open banking architectures, and embedded financial services. Drawing on a synthesis of contemporary academic literature, regulatory reports, and industry analyses, the review maps the evolution of digital financial services across developed and emerging economies, identifies structural gaps in regulatory capacity, and evaluates the adequacy of prevailing consumer protection mechanisms in the face of accelerating technological change. Key themes include the challenge of regulatory arbitrage, the governance of algorithmic and AI-based financial decision-making, data privacy and cybersecurity risks borne by consumers, the financial inclusion implications of digital transformation, and the emerging paradigms of regulatory technology and supervisory technology as adaptive governance tools. The review concludes by proposing a research agenda oriented toward the development of adaptive, proportionate, and technology-neutral regulatory frameworks capable of fostering innovation while safeguarding systemic stability and consumer welfare.
Abstract Crypto-asset services without governance mechanisms maximize transparency and censorship resistance through automation but may sacrifice adaptability to changing market conditions, depending on their institutional design. This study examines the consequences of user adoption for a fully automated stablecoin bank that offers zero-interest loans: Liquity Protocol. Using 1586 daily observations from April 2021 to August 2025, this paper investigates whether user decline stems from portfolio allocation rationale or internal design constraints, under heightened competitive pressure and a tight monetary policy environment. We employ probit specifications to analyze the relationship between stablecoin (LUSD) peg deviations and three behavioral outcomes: collateralization adjustments, loan position closures, and capital withdrawals. Results provide strong evidence that negative peg deviations predict defensive position management, with marginal effects that are 4–6 times larger during post-competitive shock periods. The closure of loan positions exhibits the greatest sensitivity, with 8.7 percentage points across the pre-shock period versus 51.8 percentage points post-shock. In comparison, collateralization ratios increased significantly by 6.0 percentage points, versus 38.8 percentage points in the same periods, indicating a systematic deterioration in capital efficiency. By contrast, the directional probability of capital flight during the post-shock period remains comparatively insignificant. An extension analysis incorporating yield differentials from major competing services is implemented using both probit and OLS specifications. The OLS results show that yield differentials predict larger capital outflows in the pre-shock period ( $$p = 0.023$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0.023</mml:mn> </mml:mrow> </mml:math> ), while full-sample and post-shock specifications are not significant. Concurrently, the probit results reveal significant links with the direction of capital withdrawal in the pre-shock period ( $$p = 0.007$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>=</mml:mo> <mml:mn>0.007</mml:mn> </mml:mrow> </mml:math> ), with no further significant associations in the post-shock period. However, yield differentials show no significant predictive power for the magnitude or direction of position management or collateralization behavior in any specification. The evidence points to a coexistence of mechanisms throughout different temporal periods: yield competition acts as a magnitude amplifier for capital flows prior to 2024, when competitive pressure had not reached its peak. In contrast, as competition reaches a high point for stablecoin saving instruments by early 2024, the systematic day-to-day behavioral dynamics of position management (loan positions and collateral) becomes more consistent with protocol-internal design frictions. Regime-based robustness checks examining Federal Reserve tightening and major crypto market shock periods reveal distinct temporal patterns, with macro stress periods leading to capital flight, whereas active position management in the subsequent period of increasing competitive stress does not. These findings provide insight into the critical design trade-offs between deterministic automation and adaptive governance in the decentralized finance industry, particularly for decentralized banks, with implications for protocol developers and researchers studying the viability of governance-free design subject to alternating external market conditions.
This study aims to analyze and synthesize prior research on navigating human resource capacity and accountability challenges in decentralized public finance through a Systematic Literature Review (SLR). The review focuses on how human resource capacity, fiscal autonomy, digital governance, and accountability mechanisms interact in shaping the effectiveness of decentralized public financial management. The SLR method was employed because it allows a structured and transparent synthesis of previous findings, identifies recurring patterns, and clarifies inconsistencies across studies. Literature was searched through the Directory of Open Access Journals (DOAJ), covering publications from 2022 to 2026, using combinations of keywords related to fiscal decentralization, human resource capacity, accountability, transparency, local government finance, and public financial management. The initial search identified 63 records, which were then screened based on title relevance, abstract suitability, research focus, publication year, full-text availability, and substantive alignment with the topic. After the selection process, 11 articles were retained for final review and analyzed through descriptive-qualitative synthesis. The findings indicate that decentralized public finance becomes more effective when supported by competent human resources, merit-based administration, strong internal control, adequate digital systems, and meaningful citizen participation. In contrast, weak technical capacity, fiscal dependence, fragmented institutions, and limited managerial autonomy repeatedly hinder accountability outcomes. This review contributes to the literature by reinforcing the capacity–accountability linkage as a central explanatory framework and by offering practical insight for policymakers and public administrators seeking to strengthen local fiscal governance in decentralized settings.
Swati Sachan, Dale Fickett, Richard Buchinger, Theo Miller
Recent advances in error-corrected qubits have accelerated the timeline for practical quantum computing. It poses a threat to cryptographic primitives used to secure financial systems, government infrastructure, communication networks, and DeFi (Decentralized Finance) ecosystems. This paper introduces a post-quantum secure federated DeFi framework that enables inter-bank collaboration to improve the inclusivity of individuals underserved by local lenders due to limited financial histories. Multiple banks contribute encrypted information batches to a virtual server, where lattice-based Fully Homomorphic Encryption (FHE) enables end-to-end homomorphic computation. The server fuses local data-driven probabilistic assessments, expert beliefs, and verifiable evidence generated by the NASA-IBM Prithvi Geospatial Foundation Model (GFM), in encrypted format. Decentralized technologies are employed to ensure tamper-proof evidence and auditable accountability for all encrypted data exchanges between institutions and the server. The framework is tested on agricultural lending decisions for rural borrowers in Virginia.
The growth of crypto-asset markets and the rise of environmental, social, and governance (ESG) investing reflect two significant transformations at the intersection of technology and finance. While crypto markets are driven by decentralized digital innovation, ESG investment is shaped by societal demands for sustainable capital allocation. This study examines how participation in a high-risk technology-driven market, such as crypto-assets, is associated with sustainability-oriented investment preferences through the development of both financial and digital finance skills. Using survey data collected in February 2024 in Thailand, a country characterized by strong policy support for ESG investment products and rapid crypto adoption, we employed partial least squares structural equation modeling (PLS-SEM) to test a sequential mediation model. The results reveal that crypto-asset ownership is positively associated with financial literacy, which in turn enhances digital financial literacy, leading to stronger ESG investment preferences. The study's findings highlight how technology-enabled financial engagement can foster the skills required for responsible investing, suggesting that digital finance participation and sustainable investment promotion are interconnected pathways rather than separate domains. Policy implications include integrating digital capacity-building into ESG promotion and leveraging technologically engaged investors as a channel for advancing sustainability goals in capital markets.
Automated market makers (AMMs) quote prices from pool state rather than from a limit order book. AMM pools often stay close to a reference price because arbitrageurs correct profitable mispricing. A large part of decentralized finance therefore relies on a simple economic premise: once the AMM price drifts away from the reference price, arbitrage incentives push it back. This paper studies when that premise is strong enough to guarantee block-scale stability. We model the gap between the reference price and the AMM price as a stochastic tracking error, treat arbitrage as the corrective input, and place blockchain execution inside the loop through fees, discrete blocks, transaction ordering, delays, and transaction failure. The detailed execution layer is reduced to the total successful correction confirmed in each block. Under a block-level correction condition, we prove geometric ergodicity of the tracking error and obtain explicit one-step bounds that connect tracking quality to liquidity and execution quality. We also show in a constant-product example how fees, fixed execution costs, and local liquidity map into the no-trade band and the optimal corrective trade. Finally, we build empirical proxies for the theorem quantities from realized block data and use them to organize reduced and mechanism-focused simulations whose comparative statics are consistent with the theory. The contribution is to turn a basic economic intuition behind decentralized finance into a quantitative stability statement together with a tractable calibration interface.
Abstract The relationship between Fintech and Financial inclusion has emerged dramatically in the last five years as this study presents detailed bibliometric research on the interactions between Fintech and financial inclusion. The major goal of this study was to map the intellectual trends, influential work, and current research topics in this fast-developing field. Based on the data obtained from the Scopus database (2020–2025) and processed using VOSviewer, this study elaborates on descriptive, keyword co-occurrence, and bibliographic coupling analyses. The most important findings are that there has been immense growth in Fintech-FI research since 2020, and the research is mainly concentrated in China, India, and the USA, where most research and articles have been published. This study identified nine thematic clusters such as decentralized finance and AI in banking and the significance of financial literacy. The fast increase in publication but a gap appears between the number of publications and the number of publications that are impacted, which means that there is still a necessity to make some significant, long-lasting contributions. It would be curious to explore the use of behavioral finance, regional comparisons of the regulatory environment, EFT application in empowering SMEs and embracing ESG, and the significance of ethics in the context of digital finance in improving fair and sound financial systems in the world in future.
Decentralized finance (DeFi) protocols now intermediate over USD 100 billion in value, including regulated stablecoins and tokenized assets deployed as collateral, yet no widely adopted framework operationalizes risk assessment at the rigor institutional adoption demands. Existing approaches emphasize protocol-specific parameter optimization or conceptual taxonomies without providing explainable, composability-aware, and structurally independent assessment methodologies. We propose a nine-dimension DeFi risk assessment framework extending the six-dimension taxonomy introduced by Moody's Analytics and Gauntlet with three novel dimensions: composability risk, comprehension debt, and temporal risk dynamics. We additionally introduce a transparency confidence modifier separating assessment reliability from risk severity. The framework is grounded in structural analysis of protocol dependencies conducted through an ontology-based protocol intelligence infrastructure covering more than 8,000 DeFi protocols. We retrospectively analyze 12 major DeFi-related incidents from 2024-2026 representing approximately USD 2.5 billion in direct losses. Five of the 12 incidents require at least one novel dimension for complete root-cause characterization, including the two highest-systemic-impact events in the dataset.