Oracle-dependent DeFi protocols execute collateral valuations, liquidations, and settlements based on reported data. We model oracle integrity and attack pressure as coupled positive states in a controlled jump-diffusion. Multiplicative shocks preserve the integrity state space while separating continuous variation from discrete attack windows. Scenario inputs are anchored to 24 documented oracle-related incidents, an oracle-consumer exposure panel, and Chainlink metadata covering 1,669 feeds across 29 networks. A positivity-preserving log-Euler scheme simulates Baseline, Stress, and Controlled configurations. The corresponding 10-year collapse probabilities are 10.1%, 93.0%, and 0% across 4,000 paths, with a one-sided 95% upper bound of 0.09% for the Controlled configuration. Within the sampled parameter ranges, pressure decay has the strongest rank association with simulated collapse probability. These results are scenario diagnostics, not causal estimates of protocol controls.
Stablecoins and central bank digital currencies (CBDCs) represent two distinct approaches to the digitalisation of money. While CBDCs are designed as sovereign digital cash, fiat-backed stablecoins have rapidly evolved into practical tools for payments, cross-border transfers, and decentralised finance. Although often framed as competitors, their development trajectories suggest that they perform distinct functions and are unlikely to replace one another directly. The existing literature has identified the complementarity thesis in broad terms, yet a significant gap remains: there is no systematic account of the specific regulatory, infrastructural, and macroeconomic conditions under which this complementarity actually materialises in practice, nor a consolidated framework that captures the interaction between these layers in real-world jurisdictions. This paper fills that gap. It introduces a five-layer digital money architecture and evaluates whether complementarity holds empirically across multiple regulatory environments and market contexts. Drawing on comparative analysis of regulatory frameworks—including MiCA, VARA, and developments in the United Kingdom, United States, and Singapore—as well as industry integrations by Visa, Mastercard, and Circle, and granular adoption evidence from Argentina and Nigeria, the paper shows that regulated stablecoins are progressively embedded in mainstream financial systems. Evidence from inflation-affected economies highlights their role in value preservation and payments, in contrast to the limited adoption of retail CBDCs. The findings suggest that stablecoins are best positioned as the programmable, user-facing layer, while CBDCs function as settlement-grade public infrastructure. The paper further identifies tokenised deposits and tokenised real-world assets as an emerging third dimension of this architecture, setting out the conditions under which future research should examine their integration.
Muhammad Tukur, Wala Elsharif, Ahmad Sani Bello, Babatunde Abiodun Salami, Isa Ali Ibrahim, Mowafa Househ, Jens Schneider, George Mikros, Marco Agus
The convergence of Metaverse technologies and Generative AI (GenAI) is reshaping immersive digital education. This study presents a scoping review of Metaverse and GenAI-enabled education following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search of ACM Digital Library, IEEE Xplore, Scopus, ScienceDirect, and SpringerLink identified 114 primary studies published or indexed from January 2022 up to the respective database search dates in 2026. Based on the synthesized evidence, we propose a comprehensive taxonomy that classifies existing research across application domains, Metaverse technologies, GenAI categories, target user groups, degrees of freedom (DoF), pedagogical foundations, evaluation practices, technical limitations, and future research directions. The reviewed studies show that Virtual Reality (VR) is the predominant immersive modality (61%), while OpenAI-based models represent the most widely adopted GenAI ecosystem (60%). Applications are concentrated primarily in STEM, higher education, and healthcare, where immersive learning environments increasingly incorporate intelligent tutoring, adaptive feedback, virtual agents, and automated content generation. Although 68% (77 articles) of the reviewed studies reported user perceptual evaluations, these predominantly focused on short-term usability and engagement, with comparatively limited attention to longitudinal learning effectiveness, knowledge retention, cognitive outcomes, AI trustworthiness, accessibility, inclusivity, and real-world deployment. This imbalance reveals a central maturity gap: technological sophistication is advancing faster than the educational evidence needed to establish sustained learning effectiveness and real-world readiness. Commonly reported challenges include limited empirical validation, system maturity, scalability, interoperability, AI trustworthiness, immersive performance, accessibility, and ethical governance. Based on these findings, we identify key priorities for future research, including longitudinal and pedagogically grounded evaluation, scalable and interoperable system architectures, trustworthy AI, inclusive and ecologically valid validation, and stronger integration of pedagogical and governance considerations. The proposed taxonomy provides an evidence-based framework to support future research, comparative analysis, and the design of Metaverse and GenAI-enabled educational systems.
Modern financial systems are becoming increasingly digital, automated and data-driven. Yet the infrastructures linking trusted representations of real-world social and ecological performance to financial decision-making remain underdeveloped. This challenge is particularly acute within sustainable, impact and development finance, where capital allocation continues to rely heavily on retrospective reporting, proxy indicators and fragmented information flows. This study addresses this gap through a design science approach, developing an Impact-Finance Protocol as a conceptual systems architecture for Digital Sustainable Finance. Drawing on systems mapping, comparative protocol analysis and the Integrated Capitals Assessment (ICA) framework, the research identifies the functional requirements for translating verified non-financial performance into adaptive financial processes. The resulting architecture comprises six interdependent protocol layers encompassing data, logic, value, governance, community and assessment. Together, these establish an integrated infrastructure through which verified impact information can inform financial decision-making, capital allocation and institutional governance within continuous feedback systems. Rather than proposing a new financial instrument, the protocol reconceptualises finance as an adaptive information system in which trusted digital infrastructure enables financial flows to respond dynamically to verified real-world conditions. The paper contributes a novel systems architecture for Digital Sustainable Finance and provides a conceptual foundation for future empirical research into blockchain-enabled, AI-enabled and other programmable financial infrastructures supporting sustainable, impact and development finance.
William Villegas-Ch, Aracely Mera Navarrete, Rommel Gutierrez, Paul Sarango-Lalangui
Blockchain, decentralized finance (DeFi), and artificial intelligence are converging into an economic ecosystem whose concentration, risk, and mechanism design have rarely been examined within a unified empirical framework. This study integrates five publicly available data sources: Uniswap decentralization indices, the Elliptic Bitcoin dataset, a multi-year sample of ERC-20 trading activity, Bitcoin incentive series, and DeFiLlama Total Value Locked (TVL) data. We processed four sources through a common audit and canonicalization protocol, while adopting the Uniswap decentralization indices as published derived series and harmonizing them within the same analytical framework. The results reveal extreme inequality in the protocol-level distribution of Total Value Locked (Gini = 0.985 for aggregated TVL; Gini excluding CEX = 0.978), although the corresponding Herfindahl–Hirschman Index does not indicate high protocol-level market concentration under conventional thresholds. A Random Forest classifier identifies illicit Bitcoin transactions with a precision of 0.988 and a recall of 0.692, consistent with the original Elliptic benchmark. SHAP analysis assigns 74.4 % of the aggregate mean absolute attribution to transaction-level features and 25.6 % to neighborhood features. In addition, Aave V3 exhibits a higher borrowed-to-deposited ratio than Compound V3 (0.410 vs. 0.300), while the observed utilization–volatility associations do not establish a uniform relationship across protocols. Taken together, these findings show that inequality, risk, and mechanism-design characteristics remain jointly observable across the blockchain and DeFi systems examined. Beyond the empirical findings, this study introduces a reproducible audit protocol for evaluating blockchain-based economic systems through explicit cross-source verification, result traceability, and scope-calibrated inference.
