Purpose: This research analyzes the comparative risks, scalability, and adoption of decentralized finance (DeFi) versus centralized fintech solutions in the context of Saudi Arabia. It seeks to explain the models' acceptance and intended focus on the challenges and opportunities each model presents within the financial landscape of the Kingdom. Methodology: The research followed a survey-based design which fit the systematic collection of data to be analyzed quantitatively. Stratified random sampling was used to select a representative diverse demographic sample of 525 participants. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) which assessed the interplay between DeFi and centralized fintech platforms through perceived risks, scalability, and adoption factors. Findings: The results demonstrated that Centralized Fintech has a marked impact on fintech adoption in Saudi Arabia, noting importance of trust and regulation. DeFi did not have any appreciable impact on adoption. Perceived Trust and Security and Financial Literacy does not appear to mediate or moderate the relationship these models have with adoption suggesting stronger external influences, such as regulatory environment, drive change. Limitations/implications: The scope of this study is limited by Saudi Arabia’s context and the use of self-reported data. Other regions could be studied along with the undergoing regulatory change, along with socio-economic factors concerning fintech adoption. Originality/value: This research is unique in focusing on the comparative analysis of DeFi and Centralized Fintech in Saudi Arabia. It also serves as an information source for policymakers and fintech developers in formulating policies aimed at increasing the region’s fintech adoption.
This thesis investigates how technological innovation influences the valuation of cryptocurrencies, focusing on the top 50 DeFi tokens by market capitalization. To capture the multifaceted nature of blockchain innovation, I construct three distinct indicators: a Whitepaper Innovation Index based on word embedding and clustering techniques, a standardized Audit Security Score derived from rubric-guided evaluation of audit reports, and a Code Maturity Proxy based on GitHub fork counts. These metrics are combined with financial data from CoinMarketCap and project-level metadata including blockchain architecture classification, academic involvement, historical volatility, and token age. Cross-sectional regression analysis shows that the proposed innovation indicators—while theoretically meaningful—do not exhibit statistically significant relationships with either market capitalization or trading volume. Instead, token age emerges as the most robust and consistent predictor across specifications, indicating that investor behavior is more responsive to project longevity than to technical complexity. Historical volatility is also negatively associated with market capitalization, suggesting that market participants tend to penalize assets with unstable pricing histories. The results suggest that, within the current market landscape, signals of maturity and stability outweigh detailed technical disclosures in shaping investor perception. This study contributes to the empirical literature by introducing a structured, multi-dimensional framework for evaluating technological innovation in crypto assets and by shedding light on the behavioral cues that dominate pricing dynamics in decentralized finance.
The subject of the research is the socio-economic relations arising from investment financing for small and medium enterprises (SMEs) and large businesses using digital financial assets (DFAs). The object of the research is the economy of Russia under conditions of limited investment and credit resources. The aim of the research is to create and utilize new innovative investment tools to support and develop the Russian economy. The digitalization of the Russian economy includes the active implementation of DFAs, which represent a new form of digital rights. DFAs play a crucial role in financing projects, attracting liquidity, optimizing payments, and structuring claims. This significantly changes traditional mechanisms of corporate and investment finance, making them more efficient and flexible. The methodological framework of the research is based on empirical and statistical analysis methods, synthesis, and systematization of information to identify new trends and best domestic practices in the formation and use of digital financial assets in the Russian Federation. The novelty of the research lies in the fact that digital financial assets act as one of the innovative tools of digital technologies, combining the properties of an investment solution and an intermediary in conducting settlements between economic entities. The issuance and circulation of digital assets is a new trend in the financial market. Digital assets are based on distributed ledger technology. They reduce the role of intermediaries and automate transactions through smart contracts. The main findings of the research indicate that the introduction of DFAs in small and medium businesses, as well as in large companies, improves access to capital and enhances the efficiency of financial processes. Under conditions of stringent restrictions and external pressure, DFAs become an alternative to traditional financing channels and a flexible tool for structuring transactions. However, the spread of DFAs faces significant obstacles, including incomplete and changing regulations, vulnerabilities in the cyber environment, a lack of secondary markets, and differences in infrastructure solutions. To overcome these limitations, it is necessary to develop measures for the standardization of the issuance and circulation of DFAs, ensure regulatory alignment, and provide technological support from the government, industry associations, and information system operators. This will reduce regulatory and operational uncertainty, increase investor confidence, and accelerate the development of the Russian DFA market.
Decentralized finance is often perceived as an alternative to the securities market, which does not require the participation of intermediaries; however, their participation can significantly facilitate the functioning of the crypto-asset market, among other things. This is especially relevant for the Russian digital financial assets market, which is built following a model very similar to the traditional securities market. At the same time, there are currently a significant number of legal obstacles to the functioning of intermediaries in the digital financial assets market. The paper examines some ways to build the infrastructure of the digital financial assets market and proposes changes to the regulatory framework that will help achieve this goal. Legislative barriers to the functioning of intermediaries in the digital financial assets market have been identified. A conclusion is made about the possibility of building an infrastructure of intermediaries in the digital financial assets market by bringing together the regulation and legal regime of digital financial assets and uncertificated securities.
The proliferation of FinTech platforms has transformed global financial systems by offering innovative, real-time services.However, this evolution has also expanded the surface area for cyber-enabled financial fraud, especially across multi-layered infrastructures comprising mobile banking apps, decentralized finance (DeFi) platforms, digital wallets, and cloud-based services.Traditional machine learning and rule-based systems have demonstrated limited adaptability in detecting increasingly sophisticated attack vectors that span multiple digital layers.This paper presents a comprehensive exploration of explainable deep learning (XDL) models tailored to detect complex cyber-enabled fraud schemes across interconnected FinTech ecosystems.The study begins with an overview of the structural and technological evolution of FinTech infrastructure, followed by an examination of the most prevalent and emerging fraud typologies including synthetic identity fraud, account takeover, transaction laundering, and insider collusion.Emphasis is placed on the limitations of black-box AI models in high-stakes financial environments where interpretability is critical for regulatory compliance, stakeholder trust, and legal recourse.We introduce an explainable deep learning framework incorporating convolutional neural networks (CNNs) for behavioral biometrics, graph neural networks (GNNs) for multi-entity relationship mapping, and attention-based mechanisms for anomaly prioritization.The model integrates SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) to improve transparency without compromising predictive performance.Evaluation is conducted using real-world transaction data from anonymized FinTech institutions, with metrics highlighting accuracy, false positive reduction, and interpretability scores.The paper concludes by discussing policy implications, ethical considerations, and future research directions in explainable AI for secure financial innovation.
Chanuka Wijayakoon, Hai Dong, H. M. N. Dilum Bandara, Zahir Tari · 5 authors
Smart contracts can implement and automate parts of legal contracts, but ensuring their legal compliance remains challenging. Existing approaches such as formal specification, verification, and model-based development require expertise in both legal and software development domains, as well as extensive manual effort. Given the recent advances of Large Language Models (LLMs) in code generation, we investigate their ability to generate legally compliant smart contracts directly from natural language legal contracts, addressing these challenges. We propose a novel suite of metrics to quantify legal compliance based on modeling both legal and smart contracts as processes and comparing their behaviors. We select four LLMs, generate 20 smart contracts based on five legal contracts, and analyze their legal compliance. We find that while all LLMs generate syntactically correct code, there is significant variance in their legal compliance with larger models generally showing higher levels of compliance. We also evaluate the proposed metrics against properties of software metrics, showing they provide fine-grained distinctions, enable nuanced comparisons, and are applicable across domains for code from any source, LLM or developer. Our results suggest that LLMs can assist in generating starter code for legally compliant smart contracts with strict reviews, and the proposed metrics provide a foundation for automated and self-improving development workflows.
In today’s fast-paced digital world, NFT have become mainstream, reaching a market value of $50 billion. They act as digital certificates of ownership of online resources, reshaping how we perceive ourselves to be on the digital realm. Our plan is to have a BidCraft NFT Hub, a marketplace where people can easily buy, sell and trade NFT. We simplify the process by using blockchain technology. For the user interface, we use web3.js for a smooth experience. In the background, Node.js and Express.js ensure smooth operation. We integrate MetaMask, a trusted digital wallet for account management and secure transactions. To ensure security and transparency in transactions, the platform relies on contract written in Solidity. Testing is done on the Hardhat network, which is planned to run on the Polygon blockchain in the testing environment. In summary, the BidCraft NFT Hub aims to make blockchain technology and NFTs accessible to everyone by leveraging the Polygon blockchain and prioritizing user friendliness while maintaining safety and security
The advance of Information Technology is closely related to and has a direct impact on the development of people’s lives. One of the real technological advancements that plays a major role in creating evolution in the community life order is Internet progress. As time passes, the internet world continues to experience rapid development, such as Metaverse, Non-Fungible Tokens (NFTs), and Cryptocurrency. Meanwhile, the change of regulations and legal products that are not as fast as the advance of the internet and the business world raises their abuse potential as means of Money Laundering Crime. The research method used was normative juridical with analytical descriptive research specifications. Metaverse, NFTs, and Cryptocurrency are relatively new phenomena in this globalization era. The lack of regulation and the high volatility of price characteristics that are strongly influenced by public interest make them potential as means to hide or disguise the origin of assets from criminal acts. So, this research was conducted to analyse the potential use of Metaverse and Non-Fungible Tokens as means of money laundering.
ABSTRACT This paper examines the potential and inherent difficulties of initial coin offerings (ICOs), a different approach to startup funding. It investigates investor attitudes, startup motives, and the legal environment around initial coin offerings (ICOs) using a mixed-methods methodology that includes survey responses and literature research. The findings indicate that initial coin offerings (ICOs) provide quick, decentralized funding options and a broader global reach, particularly for firms focused on technology. Nonetheless, worries about investor safety, fraud, and a lack of regulation continue. The study comes to the conclusion that although initial coin offerings (ICOs) have the potential to be revolutionary, their full potential can only be achieved with organized governance, transparency, and investor education. Initial Coin Offerings (ICOs) have become a cutting-edge way for entrepreneurs to raise money, especially in the technology and blockchain industries. This paper looks at ICOs' dual nature, emphasizing both the hazards related to investor protection and regulatory ambiguity as well as its promise as a decentralized fundraising strategy. This study highlights the main opportunities and difficulties faced by investors and entrepreneurs using a mixed-methods approach that includes surveys and a review of the literature. The results show that although initial coin offerings (ICOs) provide quick and worldwide access to cash, trust and openness are still essential to their long-term survival.
In recent years, the cryptocurrency market in Indonesia has grown rapidly. Along with this trend, investor behavior is frequently influenced by cognitive shortcuts known as heuristics. The purpose of this study is to look at how heuristic biases such as representativeness, overconfidence, anchoring, availability bias, and the gambler's fallacy affect retail investment decisions in the Bandung Raya area. A quantitative approach with a survey method was used to collect data from 139 respondents, which were then analyzed using statistical techniques such as correlation tests and simple linear regression. The findings show that heuristic biases have a significant impact on investment decisions, emphasizing the significance of raising investor awareness of psychological factors that may interfere with rational judgment when making cryptocurrency investments.
As blockchain technology drives the global expansion of the digital currency market, the widespread adoption of high-frequency trading and cross-market arbitrage strategies poses dual challenges to traditional regulatory measures in terms of timeliness and accuracy. This study constructs a hybrid neural network model that integrates supervised and unsupervised learning to explore multi-dimensional feature fusion paths between on-chain data from blockchain and secondary market price data. Based on dynamic game theory, an intelligent regulatory sandbox system is designed, incorporating on-chain address reputation scoring mechanisms and liquidity smart contract circuit breakers to achieve real-time warnings and responses to market manipulation behaviors. Furthermore,a distributed regulatory framework built on zero-knowledge proof technology is proposed, providing a feasible solution for establishing a penetrating regulatory system while ensuring transaction privacy.
Hong Qu, Krzysztof Gogol, Florian Grötschla, Claudio J. Tessone
Decentralized Finance (DeFi) lending enables permissionless borrowing via smart contracts. However, it faces challenges in optimizing interest rates, mitigating bad debt, and improving capital efficiency. Rule-based interest-rate models struggle to adapt to dynamic market conditions, leading to inefficiencies. This work applies Offline Reinforcement Learning (RL) to optimize interest rate adjustments in DeFi lending protocols. Using historical data from Aave protocol, we evaluate three RL approaches: Conservative Q-Learning (CQL), Behavior Cloning (BC), and TD3 with Behavior Cloning (TD3-BC). TD3-BC demonstrates superior performance in balancing utilization, capital stability, and risk, outperforming existing models. It adapts effectively to historical stress events like the May 2021 crash and the March 2023 USDC depeg, showcasing potential for automated, real-time governance.
Muhammad Mukhlis Kamarul Zaman, Zahari Md Rodzi, Yusrina Andu, Nur Aima Shafie · 7 authors
Blockchain integration in microfinance is beginning to reshape the scenario of financial inclusion and economic empowerment in emerging markets. To support a strategic decision on adoption, the study introduces the Adaptive Utility Ranking Algorithm (AURA), a newly established Multi-Criteria Decision-Making (MCDM) method to be used in evaluating blockchain-based alternatives relevant to microfinance in Malaysia. AURA stands apart from traditional MCDM techniques in that it has a distance function that is flexible and a normalization scheme that is dynamic by nature, thereby making it capable of offering the decision maker more leverage in terms of adaptability to actual economic conditions. For demonstrating the methodology, a simulated dataset based on eight blockchain-modeled alternatives and six criteria considered important in economic performance was constructed. These criteria were used for sensitivity analysis; the application of comparative evaluation of well-known MCDM methods such as TOPSIS, VIKOR, and COBRA; and robustness checks with the simulation methodology, all of which helped attest to the reliability of AURA. Even though it was based on synthetic data, the study has provided strong conceptual insight into the possibility of financial institutions being able to prioritize options from the technology perspective under complex economic constraints. Portraying AURA as a competitive decision-support tool for technology evaluation in microfinance will certainly make an impact.
The article examines the main regulatory provisions governing digital legal relations, including the norms of civil legislation and legislation on digital assets. Particular attention is paid to the definition of the features of digital rights that distinguish them from other objects of turnover, as well as to the analysis of the conditions for the emergence, exercise and transfer of such rights in the framework of distributed registers. The legal peculi-arities of smart contracts as software constructions replacing traditional forms of contractual interaction and ensuring the fulfillment of obligations without the participation of the parties after the activation of the algorithm are considered. Legal risks arising in the absence of normative regulation of smart contracts are substantiated, including the impossibility of judicial correction of performance, loss of access to digital assets and uncertainty of identification of subjects. Measures to improve legislation are proposed, including the regulatory consolida-tion of the concept of a smart contract, the establishment of a presumption of ownership of a digital right for a person with access to a key, as well as the recognition of the legal significance of blockchain records in judicial protection. Сonclusion is made about the the necessity of systemic adaptation of civil legislation to new forms of digital interaction and technological autonomy of turnover.
This article evaluates the regulatory legal landscape of smart contracts within the EU and examines a few essential legal challenges related to the need to harmonize smart contract regulations across the EU. It starts with analysis of some legal and technical aspects of the smart contract term form and arrives at the conclusion that there is no universal and unified term that contains technical aspects of the smart contract. This creates legal uncertainty, as the currently existing legal frameworks in many EU member states are not equipped to address these characteristics of smart contracts.Another issue of importance is the varied approaches to smart contract regulation across the EU member states. The paper reveals that, currently, there is a spectrum of regulatory strategies from pioneering to conservative, and identifies the main obstacles to regulatory harmonization within the EU. Without a common legal framework, a smart contract deemed valid and enforceable in one state may not be recognized in another member state.Finally, the current EU legislation is not specifically designed for smart contracts. However, it impacts their regulation by addressing critical aspects of digital operations like data ownership, access and control. Thus, successful integration of smart contracts into the EU’s regulatory environment will require a concerted effort to address these complex challenges.
A persistent semantic gap separates the low-level revert data emitted by smart contracts from the high-level explanations Web3 users need when a transaction fails. Existing automated analyzers treat such reverts as hints of hidden vulnerabilities and do not tell users what actually went wrong. To close this gap and give users useful feedback, I present ErrorExplainer, an automated error-explanation framework rather than another bug detector. ErrorExplainer takes a novel two-phase approach. A lightweight static analysis of verified source code lifts every transaction-reverting statement into a canonical error representation of an origin function, a guard condition, and an expected error message. At runtime, when a failure occurs, ErrorExplainer first checks the invariant part of the error data with the error representation of the called function. If no hit appears, it expands the candidates to call traces until a match is found and then shows the matched record as a clear, human-readable explanation. The evaluation results show that ErrorExplainer could effectively identify 6284 normalized error records from a reverting-related dataset of SC-Bench. The high information completeness (0.952) and matching fitness (0.954 and 0.604 at the function and trace levels, respectively) indicate that the extracted error context of ErrorExplainer can provide more understandable information to users on failed operations.
The prosperity of Ethereum has led to a rise in phishing scams. Initially, scammers lured users into transferring or granting tokens to Externally Owned Accounts (EOAs). Now, they have shifted to deploying phishing contracts to deceive users. Specifically, scammers trick victims into either directly transferring tokens to phishing contracts or granting these contracts control over their tokens. Our research reveals that phishing contracts have resulted in significant financial losses for users. While several studies have explored cybercrime on Ethereum, to the best of our knowledge, the understanding of phishing contracts is still limited. In this paper, we present the first empirical study of phishing contracts on Ethereum. We first build a sample dataset including 790 reported phishing contracts, based on which we uncover the key features of phishing contracts. Then, we propose to collect phishing contracts by identifying suspicious functions from the bytecode and simulating transactions. With this method, we have built the first large-scale phishing contract dataset on Ethereum, comprising 37,654 phishing contracts deployed between December 29, 2022 and January 1, 2025. Based on the above dataset, we collect phishing transactions and then conduct the measurement from the perspectives of victim accounts, phishing contracts, and deployer accounts. Alarmingly, these phishing contracts have launched 211,319 phishing transactions, leading to 190.7 million in losses for 171,984 victim accounts. Moreover, we identify a large-scale phishing group deploying 85.7% of all phishing contracts, and it remains active at present. Our work aims to serve as a valuable reference in combating phishing contracts and protecting users' assets.
The financial services industry is undergoing a profound transformation, driven by the emergence of the API economy. Application Programming Interfaces (APIs) have become fundamental building blocks, enabling seamless integration between traditional financial institutions, innovative fintech startups, as well as businesses across diverse sectors. This article examines how APIs are reshaping the financial landscape through open banking frameworks and embedded finance solutions. It explores the technical foundations of financial APIs, including RESTful versus GraphQL architectures, security standards such as OAuth 2.0 and FAPI, and emerging event-driven approaches. The regulatory catalysts accelerating API adoption are analyzed across different regions, highlighting varied implementation approaches and their impacts. The article also investigates Banking-as-a-Service models, embedded finance categories, technical implementation challenges, and real-world case studies demonstrating successful API implementations. Finally, it evaluates future directions, including decentralization and blockchain technologies that may further democratize financial services through API-enabled innovations.
Traditional voting systems face significant challenges, including susceptibility to fraud, lack of transparency, and privacy concerns. Centralized electronic voting systems, while improving accessibility, often suffer from vulnerabilities such as tampering, single points of failure, and insufficient auditability. This project proposes a blockchain-based distributed electronic voting system that leverages smart contracts to ensure voter privacy, ballot integrity, and decentralized verification. The system employs cryptographic techniques such as zero-knowledge proofs (ZKPs) to anonymize voter identities while maintaining a verifiable audit trail on an immutable blockchain ledger. Smart contracts automate vote tallying, enforce voting rules (e.g., eligibility checks, one-vote-per- voter), and ensure tamper-proof execution of electoral processes. A permissioned blockchain network enhances scalability and reduces energy consumption compared to public blockchains. The system also incorporates multi-factor voter authentication and end- to-end encryption to safeguard against unauthorized access. By decentralizing control and enabling real-time transparency, this solution addresses critical flaws in existing systems, reduces electoral fraud, and strengthens public trust in democratic processes. The proposed architecture is implemented using Hyperledger Fabric for blockchain operations and Ethereum-based smart contracts, ensuring high performance, security, and compliance with electoral regulations.
Sung-eun Heo, Manho Kim, Wijin Kim, Jongseok Choi · 12 authors
Biometric data has the potential to revolutionize health analytics and pharmacology by providing personalized insights into drug efficacy and health trajectories. However, its governance presents significant ethical challenges, particularly around individual ownership and privacy. This study addresses these challenges by proposing a sustainable and ethical framework that integrates biometric data with non-fungible tokens (NFTs). We developed a customized NFT framework with advanced smart contract functionalities that enhance privacy protection and decentralized authentication of biometric data ownership. This approach ensures the secure and ethical management of digital health data while reinforcing individuals' control over their biometric information. By leveraging cryptographic techniques for privacy protection, this framework enhances both the security and efficiency of personal health data management, offering a new perspective on ownership in digital health. Furthermore, a sustainable economic model is proposed to facilitate ethical transactions of tokenized biometric data within the NFT marketplace. The implications of this study extend beyond technology and commerce, offering valuable insights into human behavior in emerging digital economies and contributing to the creation of a more sustainable and equitable digital health ecosystem.
Cryptocurrencies are decentralized digital currencies secured by blockchain technology. Their growing popularity has a significant impact on traditional financial markets. The purpose of this paper is to examine the impact of cryptocurrency investment on stock financial development. Our empirical evidence is conducted on (30) Canadian firms during the period August 2017- May 2023. The firms are the most important companies in the financial sector. The results of the VECM estimation show a positive and significative impact of Bitcoin Value on each variable assessing stock market development in long term as Market Liquidity, Market Size, Market Capitalization. In short term, this same relationship is observed with Market Size and Market Liquidity. Bitcoin value has a negative impact on Market Capitalization. The Exchange Rate and Unemployment Rate provide a negative and significant relationship towards stock market development in the long-term. In contrast, the short-term relationship results show that Exchange Rate acts positively only on the Market Capitalization. In contrast, Market Liquidity has a positive impact on the Exchange Rate. Moreover, we find the absence of the impact of Unemployment Rate on Stock Financial Development in short term. But, there is a significant and negative incidence of Market Liquidity and Market Size on Unemployment Rate. Our results demonstrate also the positive and significant impact of Unemployment Rate on Bitcoin Value.
This thesis examines how blockchain-based fundraising mechanisms like ICOs and IEOs reshape startup finance by offering decentralized access to capital. Analyzing 100 projects from 2019–2025, it identifies key success drivers using regression analysis. Findings show that strong community presence, top-tier investor backing, and compliance measures (e.g., KYC) significantly influence fundraising success. ICOs raise more than IEOs, despite looser oversight, highlighting a trade-off between decentralization and trust. Interaction effects reveal that credibility signals are especially effective in fragmented regions like APAC, and that compliance enhances ICO outcomes, while offering minimal added value in IEOs due to existing exchange-level due diligence.
Abstract: This e-commerce platform is specifically designed for agriculture-based trade, leveraging advanced blockchain technology and decentralized file storage to create a transparent, secure, and efficient marketplace for farmers, buyers, and suppliers. The platform utilizes Ganache, a simulation of Ethereum transactions, to ensure that all transactions are secure, immutable, and verifiable on the blockchain. The decentralized architecture is further enhanced with IPFS (Interplanetary File System), enabling farmers to securely store their product information, including images and descriptions, in a way that prevents alteration or loss. This ensures that the product listings are transparent and tamper-proof. The platform also incorporates cryptocurrency payments, enabling fast, secure, and borderless transactions between buyers and sellers. Utilizing smart contracts, the system automates payment flows based on predefined conditions, reducing the reliance on intermediaries and minimizing fraud risks. This fosters a trusted environment for agricultural trade, where both buyers and sellers can engage in transparent, efficient, and secure transactions. In addition to these core features, the platform includes a staking mechanism, allowing users to lock tokens to gain transaction privileges, influence governance decisions, and access premium features. This incentivizes long-term commitment and creates a sense of ownership within the platform. Active participants, such as those verifying transactions or maintaining data integrity, are rewarded with tokens, further promoting continuous engagement. The system also supports multilingual user interfaces, making it accessible to a global audience, and includes real-time updates for seamless interaction. Through transparent governance, decentralized voting, and economic incentives, the platform ensures a resilient and future-ready ecosystem for agro-commerce, empowering stakeholders to participate in decision-making and market dynamics, while addressing the challenges faced by farmers in accessing reliable markets and efficient payment systems.
Kevin Darmawan, Lastuti Abubakar, Tri Handayani, Dewi Kania Sugiharti
The development of financial technology has driven the emergence of digital assets such as Bitcoin, which challenge the conventional legal framework of property law. Although not recognized as legal tender, Bitcoin has been acknowledged as a legal asset by Indonesia's Commodity Futures Trading Regulatory Agency (Bappebti). This study aims to examine the legal status of Bitcoin as collateral in Indonesia’s property law framework, as well as assess the adequacy of current regulations in accommodating this function. This research employs a normative juridical method with a qualitative approach and deductive reasoning. The findings indicate that Bitcoin fulfills the legal criteria of an intangible object and, in theory, can be used as an object of fiduciary security. However, the absence of explicit legal recognition and a digitally integrated collateral registration system has led to legal uncertainty. Although regulations in Indonesia have provided a degree of legality and oversight, systemic institutional integration remains lacking. Therefore, legal reform is needed in the area of digital asset-based collateral, along with the establishment of a comprehensive administrative registration system to ensure the validity of security interests in digital assets.