Bitcoin's governance trajectory at the custody interface is shaped by institutional dynamics that operate independently of any participant's preferences. Two coherent institutional logics organize the interface: sovereignty-first preserves exit optionality through self-custody and minimization of asset specificity; stability-first builds out a financialization stack connecting Bitcoin to legacy financial governance through custodial intermediation, regulatory recognition, derivative markets, and fiduciary precedent. Williamson's fundamental transformation operates at the site of custody concentration, with the initial spot Bitcoin ETF approvals as exemplar, locking institutional holders into bilateral dependencies the permissionless architecture was designed to prevent concentrated economic interests from generating. The result is a structural paradox: institutional holders combine fiduciary obligations preventing credible exit with positions in a governance architecture that supplies no formal voice mechanism, leaving the participants with the largest economic stake possessing the least governance agency. Three structural asymmetries-in constituency formation, ratchet effects, and the endogeneity of regulatory pressure on the self-custody arena-bias the institutional environment toward stability-first regions of the scenario space regardless of any participant's preferences. Two counterweights operate against the bias: the gateway dynamic, an endogenous individual-level migration toward self-custody, and structural unwinding, an exogenous shift through which degradation of the institutional environment transforms the Coasean cost-benefit calculus. A hard-fork producing a financially-compliant variant of Bitcoin exists as a third trajectory.
Nadezhda Olegovna Sergeeva, Anastasia Albertovna Khairullina, T Dunaeva
The article explores the transformation of financial technologies under the influence of blockchain, focusing on changing the transparency of investment transactions. Based on the analysis of theoretical approaches to trust and empirical studies of the practices of using distributed ledgers in asset management, crowdfunding and syndicated lending, three key mechanisms for increasing transparency have been identified: cryptographic verification, smart contract automation of execution and role-based access differentiation. It is proved that blockchain transforms the institution of trust from interpersonal and institutional to algorithmic, reducing transaction costs, but creating new challenges in the field of privacy and regulatory regulation. It is shown that the introduction of distributed registry technologies leads to the emergence of “hybrid transparency” – a balance between public verifiability and maintaining the confidentiality of sensitive data.
Decentralized finance (DeFi) vaults-smart contracts that automate yield strategies across composable protocols-represent over $16 billion in total value locked yet lack standardized risk decomposition frameworks. We propose a graph-theoretic approach: representing vaults as directed acyclic graphs where nodes are typed by four atomic primitives (CONTRACT, ORACLE, GOVERNANCE, OPERATIONAL) and edges encode dependency relationships. This formalization enables node-level risk attribution, where every basis point of expected loss traces to a specific primitive. We calibrate base rates from a dataset of 449 documented exploits (2016-2026) totaling $15.7 billion in losses, sourced from DeFiLlama and validated against Rekt News. Key finding: CONTRACT failures dominate frequency (65%) while OPERATIONAL failures dominate severity (50% of losses)-a distinction invisible without formal decomposition. The framework provides: (i) a complete taxonomy covering all historical exploit root causes, (ii) transparent aggregation from node-level to vault-level risk, and (iii) crossprotocol comparison on a common basis. The framework does not predict exploits; rather, it provides the decomposition infrastructure that enables risk budgeting, concentration analysis, and board-level reportingcapabilities institutions require but DeFi currently lacks.
Decentralized finance (DeFi) entities represent collections of smart contracts (i.e. code) that execute autonomously. Many of these protocols comprise two separate sets of smart contracts. On the operational side a protocol, say a DEX, consists of an automated market maker (AMM), which implements liquidity pools and fee mechanisms. On the governance side, protocols use decentralized DAOs to support operations with an institutional structure that includes a collective governance mechanism. A central function of smart contracts at both layers is to lock funds (i.e. crypto assets) in the ecosystem. User funds that are deposited into liquidity pools are commonly measured through the TVL metric. It captures the amount of self-custodial funds, that is, user controlled assets in a protocol. Yet, several protocols maintain a separate set of DAO-controlled funds at the governance layer, to finance development. This study takes a corporate finance perspective in classifying on-chain token holdings, exploring the relationship between cash holdings and protocol valuations in a panel vector autoregression (VAR) . The study contributes insights to the blockchain and corporate finance literature.
Dr. Pankaj Malik, Mohit Kapoor, Akshat Gupta, Aman Singhai · 5 authors
The rapid expansion of decentralized finance (DeFi) platforms has been accompanied by a surge in rug pull scams, where malicious actors exploit liquidity pools and abandon projects, causing substantial investor losses. Existing detection approaches are largely centralized and platform-specific, limiting their effectiveness due to privacy constraints, fragmented data sources, and the dynamic behavior of blockchain ecosystems. This paper proposes a novel Federated Time-Series Learning (FTSL) framework for cross-platform rug pull detection that enables collaborative model training without sharing raw transaction data. The proposed system integrates federated learning with advanced time-series modeling to capture temporal patterns in token price volatility, liquidity changes, transaction frequency, and smart contract activities. A hybrid deep learning architecture combining Long Short-Term Memory (LSTM) networks with an attention mechanism is employed to effectively learn sequential dependencies and identify early indicators of fraudulent behavior. The federated setup ensures privacy preservation while enabling knowledge sharing across multiple decentralized platforms. Experimental results on multi-chain DeFi datasets demonstrate that the proposed FTSL model achieves 96.3% detection accuracy, outperforming traditional centralized models (91.2%) and single-platform approaches (88.7%). The model also improves precision (95.1%), recall (94.6%), and F1-score (94.8%), indicating robust and balanced performance. Furthermore, the system is capable of detecting rug pull events 6–12 hours earlier than baseline methods, providing critical early warning signals. Communication overhead is reduced by approximately 28% through optimized federated aggregation, while maintaining scalability across heterogeneous platforms. These findings highlight that Federated Time-Series Learning offers a scalable, privacy-preserving, and highly effective solution for real-time rug pull detection, contributing to enhanced security, transparency, and trust in decentralized financial ecosystems.
Blockchain technology has fundamentally transformed the financial technology (fintech) landscape since Bitcoin’s introduction in 2008, evolving from peer-to-peer digital currency into comprehensive financial infrastructure. While earlier reviews catalogued blockchain applications across individual fintech verticals, rapid developments in Decentralized Finance (DeFi), Central Bank Digital Currencies (CBDCs), real-world asset (RWA) tokenization, stablecoin payment rails, and AI-blockchain convergence have created significant literature gaps. This paper presents a technically grounded review of blockchain-fintech applications as of 2025, addressing deficiencies in existing work including absent unified taxonomies, insufficient regulatory analysis, limited interoperability coverage, and inadequate treatment of institutional-grade deployments. We examine architectural underpinnings across eight application domains, integrating current market data, security analysis, and scalability benchmarks. We additionally present an analysis of the evolving threat landscape, including $3.4 billion in cryptocurrency theft during 2025. Our findings indicate the global fintech blockchain market, valued at $3.4 billion in 2024, is projected to reach $49.2 billion by 2030 at a CAGR of 55.9%, driven by institutional DeFi adoption, stablecoin settlement infrastructure, and regulatory clarity.
Integrating artificial intelligence (AI) like the large language model (LLM) for smart contract auto-generation standardises performance and security, reduces human error, and offers accessibility for non-developers.In decentralised autonomous systems (DASs) like decentralised finance (DeFi), the ability to AI-generate smart contracts strengthens the decentralisation and automation characteristics of the applications.In order to increase the effectiveness of a smart contract's fully decentralised and autonomous development, this study benchmarks gas-saving patterns in AI-generated DeFi smart contracts.Three DeFI smart contract development scenarios: token generation (ERC-20), tokenised vault (ERC-4626), and flash loan (ERC-3156), and the state-of-the-art LLMs (Code Llama and Code Llama -Python) are explored to study the gas-saving patterns of AI-generated smart contracts.These results help optimise DeFi smart contracts created by AI regarding gas fees for the same operations.
This paper introduces Credance-Based Collateral Exchange (CBCE) as a formal category of financial instrument distinct from conventional repo and from existing distributed ledger collateral protocols. Building on the concept of credance-the collective anterior belief that makes a financial transaction possible before any track record exists (Laverriere, 2026)-we argue that a significant class of collateral exchange activity operates on the basis of credance rather than documentation. We formalise credance as a time-varying bilateral function C(P₁, P₂, t), define the credance threshold θ as a composite score of transaction history, temporal depth, and costly honouring, and propose a three-mode typology of CBCE instruments. We analyse the conditions under which each mode is optimal, examine the implications for Islamic repo market development and for distributed ledger technology design, and argue that blockchain-based collateral protocols have systematically failed to incorporate credance as a design variable. A credance-aware DLT architectureincluding a credance oracle, a zero-knowledge credance proof mechanism, and a variable collateralisation ratio governed by C(P₁, P₂, t)-would represent a genuinely novel class of financial instrument. The paper concludes with a research agenda including a call for collaboration between financial economists and DLT researchers to prototype the proposed architecture.
This paper provides a comprehensive examination of stablecoins, a class of cryptocurrency designed to mitigate the price volatility inherent in major digital assets like Bitcoin and Ethereum. By pegging their value to stable assets such as fiat currencies, commodities, or through algorithmic manipulation, stablecoins aim to serve as a reliable medium of exchange, unit of account, and store of value within the digital economy. Through systematic literature review methodology, this research traces the evolution of stablecoins, dissects their underlying mechanisms, and categorizes them into four primary types: fiat collateralized, commodity-collateralized, crypto-collateralized, and algorithmic. The paper analyzes their expanding use cases, from powering decentralized finance (DeFi) and revolutionizing cross-border payments to enhancing corporate treasury functions, while scrutinizing the significant risks they present, including de-pegging events, regulatory uncertainty, and systemic financial risks. The catastrophic collapse of the Terra/LUNA ecosystem serves as a critical case study, offering profound lessons on the vulnerabilities of algorithmic models. The research navigates the complex global regulatory landscape, comparing approaches from major jurisdictions including the United States GENIUS Act, European Union MiCA regulation, and UK FCA frameworks. By synthesizing market data, growth projections, and doctrinal analysis, this paper concludes with a forward-looking perspective on stablecoins' enduring role in the ongoing digitalization of finance and provides normative recommendations for balanced regulatory approaches that foster innovation while ensuring financial stability.
Private credit has grown into a multi-trillion-dollar asset class embedded within modern financial networks, yet the pathways through which stress in that sector can propagate into digital asset markets remain poorly understood. This paper examines two distinct contagion channels linking macroeconomic shocks to decentralized finance (DeFi): a macro deleveraging channel in which broad risk-off behavior spreads from traditional markets into cryptocurrencies, and a direct tokenization channel in which blockchain-based tokens representing private credit portfolios serve as collateral within automated DeFi lending protocols. Drawing on recent empirical developments, including the redemption restrictions imposed by a large BlackRock private credit fund in early 2026, the bankruptcy of First Brands Group in September 2025, and the associated stress in tokenized credit instruments on the Morpho lending protocol, the analysis constructs a conceptual contagion framework. The paper also situates these dynamics within the shadow banking theory of Gennaioli, Shleifer, and Vishny (2013), arguing that tokenized private credit instruments exhibit a liquidity paradox: while blockchain infrastructure enables continuous trading, the underlying credit exposures remain illiquid. The paper concludes that as tokenization expands the integration between traditional and digital finance, regulatory frameworks must evolve to monitor cross-market contagion channels, enforce transparency in tokenized asset structures, and account for the systemic implications of automated liquidation mechanisms.
Decentralized finance (DeFi) vaults are smart-contract-based asset management systems that pool deposits, execute programmable strategies, and mint tokenized shares representing claims on underlying assets and strategy performance. As vault designs have evolved from early yield aggregators to modular, actively managed systems, a new control layer, curation, has emerged to select strategies, configure risk parameters, and coordinate operational execution, introducing principal-agent dynamics and new failure modes. This paper systematizes DeFi vault architectures and curator-mediated control planes through (i) a unified system model and formal definitions for share accounting, roles, and operational dependencies, and (ii) three complementary taxonomies covering vault exposures and objectives, curator governance and accountability mechanisms, and strategy execution patterns together with their failure modes. We further map a representative set of production protocols to the proposed dimensions. The frameworks in this work aim to support rigorous analysis and safer design of blockchain-based financial applications.
This paper proposes a novel decentralized financial instrument-the Algorithmic Yield-Multiplier Note-to mathematically resolve the classical agency friction between debt and equity constituencies. Under legacy market microstructures, the strict fungibility constraints and asynchronous settlement latencies of traditional clearinghouses preclude the issuance of dynamic, cross-asset covenants, thereby exacerbating asset substitution and debt overhang during macroeconomic distress. We circumvent these architectural bottlenecks by migrating corporate liability to a programmable, tokenized infrastructure. We introduce a continuous, state-dependent yield function that algorithmically scales a bondholder's coupon rate relative to their cryptographically verifiable equity holdings, structurally coercing fixed-income investors into an Endogenous Capital Loop. To defend this mechanism against high-frequency decentralized finance (DeFi) exploits, such as flash-loan and snapshot arbitrage, we engineer a continuous, path-dependent knockout barrier, 𝑆 𝑖 (𝑡), that permanently collapses the yield premium upon any instantaneous breach of the requisite equity threshold. Furthermore, we resolve the resultant fungibility crisis by constructing a hybrid Decentralized Exchange (hDEX) utilizing atomic swaps to govern secondary market velocity. By algorithmically enforcing a liquidity tax (𝜏), a yield-surrender covenant (𝛾), and strict cryptographic vesting lock-ups (𝑇 penalty), the mechanism fundamentally traps institutional capital. Ultimately, we demonstrate that this programmable constraint system monetizes investor duration risk and artificially suppresses the realized covariance of the firm's stock. By fusing the fixed-income and equity constituencies, the corporate treasury engineers a Pareto-improving capital structure that dramatically lowers the effective Weighted Average Cost of Capital (WACC) and insulates the enterprise value from systemic market contagion.
Digital assets have become a significant and indispensable part of the modern financial system and have brought innovations in the areas of payments, investments, and financial intermediation. However, their expansion brings numerous regulatory challenges, particularly with regard to preventing money laundering, user identification, the legal treatment of decentralized finance, and privacy protection. Approaches to the regulation of digital assets vary significantly among jurisdictions - while some countries introduce comprehensive legislation, others apply restrictive or fragmented policies. Serbia has positioned itself as one of the first countries in the region to adopt a specific Law on Digital Assets (2020), thereby establishing a regulatory framework for this market. This paper analyses the legal challenges of digital assets, exploring national and international regulatory approaches, including the European Union's MiCA Regulation. It also examines the need to strike a balance between fostering innovation and ensuring the stability of the financial system. The key finding is that continuous international cooperation and a flexible regulatory framework are necessary to enable the sustainable development of digital assets and the technologies that support them.
DEX like Uniswap v3 has gained significant attention in the blockchain industry, and understanding the driving factors behind liquidity provision is crucial for the platform’s success and adoption in the decentralized finance space. This study investigates liquidityproviders (LPs) behaviour in Uniswap v3 and their response to key events and developments,such as the EIP-1559 and the FTX collapse, to provide a comprehensive picture ofthe dynamics in the DeFi ecosystem. We explore LPs behaviour by assembling a datasetof 746,438 pool-day records associated with 2,228 Uniswap smart contracts. Two hypotheses,the ”Fee reward hypothesis” and the ”Impermanent loss avoidance hypothesis”are examined to understand LPs’ motivations and strategies. We further study the impactof EIP-1559 on liquidity provision, revealing a convergence in capital efficiency betweenlow and high-efficiency swap pools following its implementation. Last, we assess howthe FTX collapse affected trading volume, uncovering a more notable decline in tradingactivity among pools comprising exclusively of unstable coins as opposed to those withstablecoins only.
This paper examines the various steps taken toward the tokenization of finance, made possible by distributed ledger technology (DLT), in the European and national contexts. In a context favourable to innovation and the use of enabling technologies, as outlined in the EU Strategy for Digital Finance, the European Commission is taking action on two complementary fronts that leverage the benefits of DLT: one focused on crypto-asset markets (MICA Regulation), the other relating to crypto-assets that qualify as financial instruments (Pilot Regime Regulation). The adoption of the sandbox model allows for the testing of DLT at both European and national level, where the adoption of the so-called FinTech Decree goes beyond the scope outlined by the EU Regulation to establish a legislative framework supporting the issuing and circulation of financial instruments in digital form via distributed ledger technologies. Despite the first instances of use and experiences in Italy, the current situation reveals a market still in the exploratory phase, hampered by the temporary nature typical of experimentation, but above all awaiting European action to establish a lasting framework for DLT.