The rapid evolution of the digital finance market, driven by the proliferation of cryptocurrencies, decentralized finance (DeFi), and financial technologies (fintech), has opened new investment opportunities while simultaneously presenting serious risks. These include high market volatility, cybersecurity vulnerabilities, and significant regulatory uncertainty. This paper explores the dual challenge of managing investment risks and building reliability within digital finance ecosystems. Using a mixed-methods approach combining a systematic literature review and qualitative expert interviews, the study examines key risk categories—technological, operational, behavioral, and institutional—and how they affect investor confidence. Findings show that the lack of standardized regulation, frequent security breaches, and insufficient investor education contribute to instability and distrust. In response, the paper proposes a multi-layered framework for mitigating these challenges through digital infrastructure enhancement, risk governance reforms, and financial literacy promotion. It also draws on International case studies to identify best practices applicable to emerging markets. The study contributes to academic and practical discourse by offering policy recommendations aimed at developing a more secure, transparent, and inclusive digital financial environment that aligns with sustainable investment goals.
Isaac David, Liyi Zhou, Dawn Song, Arthur Gervais · 5 authors
The widespread lack of broad source code verification on blockchain explorers such as Etherscan, where despite 78,047,845 smart contracts deployed on Ethereum (as of May 26, 2025), a mere 767,520 (< 1%) are open source, presents a severe impediment to blockchain security. This opacity necessitates the automated semantic analysis of on-chain smart contract bytecode, a fundamental research challenge with direct implications for identifying vulnerabilities and understanding malicious behavior. Prevailing decompilers struggle to reverse bytecode in a readable manner, often yielding convoluted code that critically hampers vulnerability analysis and thwarts efforts to dissect contract functionalities for security auditing. This paper addresses this challenge by introducing a pioneering decompilation pipeline that, for the first time, successfully leverages Large Language Models (LLMs) to transform Ethereum Virtual Machine (EVM) bytecode into human-readable and semantically faithful Solidity code. Our novel methodology first employs rigorous static program analysis to convert bytecode into a structured three-address code (TAC) representation. This intermediate representation then guides a Llama-3.2-3B model, specifically fine-tuned on a comprehensive dataset of 238,446 TAC-to-Solidity function pairs, to generate high-quality Solidity. This approach uniquely recovers meaningful variable names, intricate control flow, and precise function signatures. Our extensive empirical evaluation demonstrates a significant leap beyond traditional decompilers, achieving an average semantic similarity of 0.82 with original source and markedly superior readability. The practical viability and effectiveness of our research are demonstrated through its implementation in a publicly accessible system, available at https://evmdecompiler.com.
In today's digital era, technological advances have brought major changes in various fields, such as the creative economy. The emergence of crowdfunding platforms and Non-Fungible Tokens (NFTs) as creativeoptions for creative funding is one of the latest developments. Artists, musicians, and other creators have seen how they advertise their work by using NFTs which are unique asset holdings on the blockchain. Incontrast, crowdfunding platforms like Patreon and Kickstarter allow creators to get funding directly from their fans without using conventional intermediaries. The purpose of this research is to find the problems and prospects faced by investors and creators when using NFTs and crowdfunding. Qualitative and quantitative methods were used, with case studies and secondary data analysis. The results show that the main challenges to be faced include legal and regulatory uncertainty, marketvolatility, copyright infringement, digital divide, high transaction costs, and environmental impact. Uncertainty regarding ownership rights and consumer protection is caused by regulatory uncertainty.Both creators and investors face significant risks due to the volatility of the NFT market. The case of plagiarism in NFTs shows that copyright must be strengthened. Some creators cannot use this technology due to the limitations of digital technology. A more environmentally friendly solution is also needed due to the high transaction fees and the impact of the Ethereum blockchain on the environment. In addition, many creators still have difficulty maintaining crowdfunding funding.
Pasquale De Rosa, Pascal Felber, Valerio Schiavoni
Smart contracts have transformed decentralized finance by enabling programmable, trustless transactions. However, their widespread adoption and growing financial significance have attracted persistent and sophisticated threats, such as phishing campaigns and contract-level exploits. Traditional transaction-based threat detection methods often expose sensitive user data and interactions, raising privacy and security concerns. In response, static bytecode analysis has emerged as a proactive mitigation strategy, identifying malicious contracts before they execute harmful actions. Building on this approach, we introduced PhishingHook, the first machine-learning-based framework for detecting phishing activities in smart contracts via static bytecode and opcode analysis, achieving approximately 90% detection accuracy. Nevertheless, two pressing challenges remain: (1) the increasing use of sophisticated bytecode obfuscation techniques designed to evade static analysis, and (2) the heterogeneity of blockchain environments requiring platform-agnostic solutions. This paper presents a vision for ScamDetect (Smart Contract Agnostic Malware Detector), a robust, modular, and platform-agnostic framework for smart contract malware detection. Over the next 2.5 years, ScamDetect will evolve in two stages: first, by tackling obfuscated Ethereum Virtual Machine (EVM) bytecode through graph neural network (GNN) analysis of control flow graphs (CFGs), leveraging GNNs' ability to capture complex structural patterns beyond opcode sequences; and second, by generalizing detection capabilities to emerging runtimes such as WASM. ScamDetect aims to enable proactive, scalable security for the future of decentralized ecosystems.
It is stated that the Decentralized Finance (DeFi) is transforming the financial industry because it provides its users with such services as lending, borrowing, trading, and insurance on decentralized terms using blockchain technology. DeFi is cheaper, transparent, and secure because it is developed on decentralized platforms, including Ethereum. But it is also encircled by such threats as regulatory risk, security risk and market risk. In this paper, the comparison of the DeFi and traditional financial systems will be presented involving such central capabilities of the DeFi as decentralized exchanges, liquidity pools, and lending platforms. It also mentions the discrepancies in rules, the positives of financial inclusions and the DeFi negatives such as volatility and absence of consumer protections. The paper gives a concluding look at what traditional institutions and regulators can do to react and cooperate with DeFi.
Pasquale De Rosa, Simon Queyrut, Yérom-David Bromberg, Pascal Felber · 5 authors
The Ethereum Virtual Machine (EVM) is a decentralized computing engine. It enables the Ethereum blockchain to execute smart contracts and decentralized applications (dApps). The increasing adoption of Ethereum sparked the rise of phishing activities. Phishing attacks often target users through deceptive means, e.g., fake websites, wallet scams, or malicious smart contracts, aiming to steal sensitive information or funds. A timely detection of phishing activities in the EVM is therefore crucial to preserve the user trust and network integrity. Some state-of-the art approaches to phishing detection in smart contracts rely on the online analysis of transactions and their traces. However, replaying transactions often exposes sensitive user data and interactions, with several security concerns. In this work, we present PhishingHook, a framework that applies machine learning techniques to detect phishing activities in smart contracts by directly analyzing the contract’s bytecode and its constituent opcodes. We evaluate the efficacy of such techniques in identifying malicious patterns, suspicious function calls, or anomalous behaviors within the contract’s code itself before it is deployed or interacted with. We experimentally compare 16 techniques, belonging to four main categories (Histogram Similarity Classifiers, Vision Models, Language Models and Vulnerability Detection Models), using 7,000 real-world malware smart contracts. Our results demonstrate the efficiency of PhishingHook in performing phishing classification systems, with about 90% average accuracy among all the models. We support experimental reproducibility, and we release our code and datasets to the research community.
Lei Yu, Zhirong Huang, Hang Yuan, Shiqi Cheng · 11 authors
Smart contract vulnerability detection is a critical challenge in the rapidly evolving blockchain landscape. Existing vulnerability detection methods face two main issues: (1) Existing datasets lack comprehensiveness and sufficient quality, with limited vulnerability type coverage and insufficient distinction between high-quality and low-quality explanations for preference learning. (2) Large language models (LLMs) often struggle with accurately interpreting specific concepts in smart contract security. Through our empirical analysis, we found that even after continual pre-training and supervised fine-tuning, LLMs still exhibit limitations in precisely understanding the execution order of state changes in smart contracts, which can lead to incorrect vulnerability explanations despite making correct detection decisions. These limitations result in poor detection performance, leading to potentially severe financial losses. To address these challenges, we propose Smart-LLaMA-DPO, an advanced detection method based on the LLaMA-3.1-8B. First, we construct a comprehensive dataset covering four vulnerability types and machine-unauditable vulnerabilities, containing labels, detailed explanations, and precise vulnerability locations for Supervised Fine-Tuning (SFT), as well as paired high-quality and low-quality outputs for Direct Preference Optimization (DPO). Second, we perform continual pre-training using large-scale smart contract code to enhance the LLM's understanding of specific security practices in smart contracts. Futhermore, we conduct supervised fine-tuning with our comprehensive dataset. Finally, we apply DPO, which leverages human feedback to improve the quality of generated explanations. Smart-LLaMA-DPO utilizes a specially designed loss function that encourages the LLM to increase the probability of preferred outputs while decreasing the probability of non-preferred outputs, thereby enhancing the LLM's ability to generate high-quality explanations. We evaluate Smart-LLaMA-DPO on four major vulnerability types: reentrancy, timestamp dependence, integer overflow/underflow, and delegatecall, as well as machine-unauditable vulnerabilities. Our method significantly outperforms state-of-the-art baselines, with average improvements of 10.43% in F1 score and 7.87% in accuracy. Moreover, both LLM evaluation and human evaluation demonstrate the superior quality of explanations generated by Smart-LLaMA-DPO in terms of correctness, thoroughness, and clarity.
The emergence of Decentralized Autonomous Organizations (DAOs) presents a fundamental challenge to the traditional corporate form, which has dominated economic organization for over a century. Built on blockchain technology, DAOs propose a new model for coordinating economic activity. This study addressed the critical question of institutional efficiency by applying the lens of Transaction Cost Economics (TCE) to compare DAOs and traditional corporations. A comparative institutional analysis was conducted using a mixed-methods approach. We employed a multiple case study design, analyzing two representative DAOs and two analogous traditional corporations from Q1 2023 to Q4 2024. Data collection involved the systematic analysis of archival records, including 215 DAO governance proposals and corporate filings, and 32 semi-structured interviews with key participants. A novel analytical framework was developed to categorize transaction costs into ex ante (search, bargaining) and ex post (monitoring, enforcement), further distinguishing between 'on-chain' and 'off-chain' costs. The study revealed significant trade-offs between the two organizational forms. Traditional corporations exhibited high ex ante bargaining costs (legal, negotiation) and ex post monitoring costs (managerial overhead), but benefited from established legal frameworks that reduced enforcement uncertainty. Conversely, DAOs significantly lowered specific transaction costs through automation via smart contracts, particularly in on-chain bargaining and enforcement for codified tasks. However, DAOs incurred substantial, often hidden, new transaction costs related to off-chain social coordination, governance participation, and navigating legal ambiguity. This was termed the 'Governance Overhead Paradox'. In conclusion, DAOs do not represent a universally superior organizational form but rather a new point on an institutional possibility frontier. They are highly efficient for tasks that are global, permissionless, and computationally verifiable. Traditional firms retain advantages in contexts requiring complex, subjective decision-making and legal certainty. The future of the firm is likely not a replacement of one form by the other, but a pluralistic ecosystem where hybrid models emerge.
Vladislav V. Fomin, Ugnius Kerulis, Rihards Grāmatiņš, Tan Gürpinar
Background: Despite the financial technology (Fintech) industry being marked as a strategic development direction in many countries, cryptocurrency products show low adoption rates. Purpose: This study investigated factors affecting consumer trust in cryptocurrency products, particularly exchanges and crypto wallets. Methods: A three-stage multi-method approach was adopted: two non-probability convenience surveys and a systematic literature review. The initial survey (N=45) was followed by literature review (N=16) and a follow-up survey (N=95). Qualitative and quantitative analysis techniques were used. Findings: Trust must be understood as a versatile concept, with consumers perceiving different factors differently when choosing cryptocurrency products. Two key findings emerged: convenience, rather than trust, is the biggest factor attributed to cryptocurrency product popularity and adoption. Second, an inverse relationship exists between trustworthiness and popularity of information sources about cryptocurrency products, with less popular sources being more trusted. Consumers rely on convenience-based attributes like the ease of use and accessibility, which indirectly influence trust perception. Conclusions: Trust degree is not bound to specific products or services but depends on consumer intentions and knowledge, among other factors. Research implications: The authors suggest policy and innovation development directions to increase consumer trust in cryptocurrency products.
Marvin Hanisch, Curtis Goldsby, Mélissa Fortin, Michael Rogerson
ABSTRACT Blockchain‐based platforms can facilitate data sharing and coordination in interorganizational ecosystems by enabling secure, tamper‐evident recordkeeping and streamlined, trust‐minimized transactions across organizational boundaries. However, their decentralized architecture may conflict with the centralized control exercised by platform sponsors, giving rise to a centralization–decentralization paradox. This study explores how this paradox unfolds in a large, blockchain‐based logistics platform that was ultimately discontinued. Through an in‐depth, longitudinal case study, we identify three interrelated governance contradictions—regarding ownership, trust, and growth—that triggered destabilizing oscillations between centralized and decentralized governance modes. We introduce the concept of semirigid limits to capture the bounded flexibility within which governance can be made and adapted under such paradoxical conditions. Our findings show that the centralization–decentralization paradox is especially difficult to navigate when strategic boundary conditions—here, industry competition, fragmented coordination, and high interdependencies—are present. Our study contributes to the paradox and governance literature by theorizing how governance contradictions emerge and persist and by identifying the mechanisms that constrain alignment and adaptation. We also offer guidance for managers in regard to addressing the competing demands of centralization and decentralization in interorganizational platforms.
Sharia fintech is a digital financial innovation that integrates technology with sharia principles, one of which is through a Peer To Peer (P2P) lending platform. However, in practice, various sharia compliance issues are still found, such as the potential for usury, gharar, and non compliance with contracts. This is due to limited manual supervision and the complexity of digital transactions. This study aims to analyze the potential for implementing smart contract technology to improve sharia compliance on P2P lending platforms. Using a qualitative approach through literature studies, this article examines how smart contract characteristics such as transparency, automation, auditability, and resistance to manipulation can support the implementation of sharia contracts such as murabahah, mudharabah, and musyarakah. The results of the study show that smart contracts enable the automatic implementation of sharia compliant transactions, reject unauthorized processes, and provide an immutable blockchain based monitoring and reporting system. This potential makes it a strategic tool in building a more accountable, efficient, and trusted sharia fintech ecosystem. However, the implementation of this technology still faces challenges, such as limited regulations, the need for multidisciplinary human resources, and low digital sharia literacy. Therefore, collaboration between scholars, regulators, and technology developers is needed to ensure that the implementation of smart contracts is not only technically superior, but also in accordance with the maqashid sharia. This study recommends the development of prototypes and further empirical research as concrete steps for implementation.
Based on the document content, I'll create a comprehensive abstract that captures the key aspects of the research. The research investigates the performance and efficiency of various consumer banking platforms using Grey Relational Analysis (GRA). The study analyzed five distinct banking platforms—Online Banks (Nedbank's), Credit Unions, Peer-to-Peer (P2P) Lending, Fintech Solutions, and Cryptocurrency/Decentralized Finance (Deify)—across four critical dimensions: Customer Satisfaction, Digital Banking and Technology, Financial Products and Services, and Customer Support. The analysis employed normalized data, deviation sequences, and grey relation coefficients to establish comprehensive performance metrics. The findings reveal significant variations in platform effectiveness, with Fintech solutions achieving the highest Grey Relationship Grade (GRG: 0.7387), followed closely by P2P lending (GRG: 0.7064). Traditional platforms like Credit Unions maintained moderate performance (GRG: 0.5674), while Cryptocurrency/Deify (GRG: 0.5117) and Online Banks (GRG: 0.5115) showed considerable room for improvement. The research demonstrates that success in modern banking requires a balanced integration of technological innovation with customer-centric services, rather than excellence in isolated areas. These results hold significant importance for shaping the strategic growth of banking services and guiding the future advancement of financial technology platforms.
Jundullah Rifqi Prasmanto, Anang Ma’ruf, Muhammad Fathurrahman Assidiq, Muhammad Faiz Diyaulhaq
This study examines the status of Bitcoin and its underlying blockchain technology from the perspective of Islamic law. The research utilizes a qualitative library-based method, analyzing primary sources of Islamic jurisprudence alongside recent academic studies. It explores key Shariah principles such as mal mutaqawwam, maysir, gharar, and riba, in assessing Bitcoin's permissibility. The findings reveal that while Bitcoin's volatility, speculation, and lack of intrinsic value raise concerns under Islamic finance, the asset does not inherently involve interest (riba). Furthermore, the research distinguishes between the controversial nature of Bitcoin and the positive potential of blockchain technology, which aligns with the objectives of maqasid al-shariah, particularly in promoting transparency, financial inclusion, and ethical conduct. The study concludes that while Bitcoin may remain contentious, blockchain offers significant opportunities for Shariah-compliant financial innovation when supported by appropriate regulation and ethical oversight.
Abdulrahman Alzahrani, Amin Y. Noaman, Ahmed A. A. Gad-Elrab, Fathy Eassa · 7 authors
Interoperability among heterogeneous blockchain platforms remains a significant challenge in decentralized ecosystems, especially with the growing adoption of blockchain across various industries. This research introduces the Data Standardization Module (DSM). This framework facilitates seamless communication between platforms like Ethereum and Hyperledger Fabric using a unified schema for data transformation and exchange. DSM leverages Concise Binary Object Representation (CBOR) encoding, which reduces data size by 60 % and achieves a compression ratio (CR) of 2.5. This outperforms conventional JSON-based methods, typically achieving only 20–30 % compression with lower CR values. The system ensures data security and integrity through end-to-end encryption, access control, and validation mechanisms. Performance evaluations show that DSM supports an average throughput of 250 transactions per second (TPS). In comparison, interoperability frameworks like Cosmos and Polkadot typically achieve 100–150 TPS, while early implementations of Hyperledger Fabric reported TPS as low as 300. However, optimized settings of Hyperledger Fabric now achieve over 100,000 TPS. DSM strikes a balance by providing high throughput with minimal resource overhead, making it suitable for real-world applications. This work advances blockchain interoperability by offering a lightweight, secure, and scalable framework, ideal for high-frequency use cases in healthcare, finance, and supply chains.
T. C. Jermin Jeaunita, Thiyagarajan Ramesh, C. V. Manjushree, P. T. Shantala
Crowdfunding has become essential for financing entrepreneurial projects, innovative projects, and social initiatives.However, existing platforms face critical challenges, including a lack of transparency, low user engagement, data privacy concerns, and ineffective personalization of user experiences.To address these limitations, this study introduces a novel decentralized crowdfunding framework that integrates Federated Learning (FL), blockchain technology, and Q-learning to enhance security, transparency, and user engagement.The framework leverages FL to collaboratively train models across distributed datasets while ensuring privacy preservation by eliminating the need to share raw user data.Blockchain technology is utilized to ensure tamper-proof transaction records and automate trustless interactions through smart contracts, effectively preventing fraud while increasing transparency.Additionally, a Q-learning-based incentive mechanism is incorporated to predict and stimulate user engagement, ensuring dynamic long-term engagement.The experimental evaluation illustrates that the designed framework attains state-of-the-art performance with an accuracy rate of 99.39%, surpassing existing methodologies.The results demonstrate the effectiveness of the framework in providing a secure, decentralized, and highly personalized crowdfunding system, raising trust and engagement among stakeholders and resolving long-standing issues in crowdfunding platforms.
The complexity of financial decision-making has intensified in the digital era due to data saturation, market volatility, and the inability of conventional models to respond to real-time and non-linear dynamics. Addressing these challenges requires the integration of intelligent systems capable of adapting to evolving financial environments. Smart finance, which combines artificial intelligence, machine learning, big data analytics, blockchain, and automation, offers transformative potential across financial services. This study synthesizes scholarly findings from 2019 to 2024 across five domains: AI-based modeling, robo-advisory applications, behavioral finance integration, decentralized finance (DeFi), and real-time risk analytics. Results indicate substantial gains in efficiency, accuracy, and personalization, yet also reveal persistent challenges, including algorithmic opacity, ethical concerns in data use, and regulatory ambiguity. Advancing smart finance demands development in explainable AI, hybrid advisory systems, and inclusive, adaptive regulation for decentralized infrastructures. The scope of the analysis is limited to peer-reviewed academic literature published in English, excluding industry reports and grey literature.
Abstract Blockchain technology has emerged as a transformative force in the financial sector, offering decentralization, transparency, security, and cost-efficiency. Originally developed for cryptocurrencies, Blockchain now extends into banking, remittances, trade finance, and securities settlement. This study investigates Blockchain potential to revolutionize financial transactions by exploring real-world applications, implementation challenges, and stakeholder perceptions. Using a mixed-methods approach of surveys and expert interviews, the research provides empirical evidence of Blockchain benefits and limitations, contributing to the discourse on its role in reshaping financial ecosystems.
Virtual currencies in general, and Bitcoin in particular, are currently the most used and famous compared to other circulated cryptocurrencies. Bitcoin is considered one of the currencies that has been fully implemented. A cryptocurrency is a decentralized peer-to-peer virtual currency. Exchange operations between users are conducted without resorting to a bank to manage the transactions. This explains one of the major advantages offered by this system: low costs or low transaction fees, which are much lower than those provided by banks in terms of modern and traditional payment methods. To ensure the validity of transactions and the dissemination of this type of money, encryption technology is used.
M Y Khan, Shaik Rehan, Mohammed Abdullah, Marwan Ali
In the rapidly evolving world of digital finance,there remains a growing need to bridge the gapbetween decentralized crypto assets and traditionalfiat currency systems. RupXpay is a robust andsecure payment application designed to meet thisdemand by enabling users to convert their cryptocurrency into Indian Rupees (INR) and alsoperform direct INR transfers through their bankaccounts. The app begins by allowing users toconnect any Web3 wallet of their choice (such asMeta Mask, Trust Wallet, etc.). Upon successfulconnection, RupXpay displays the user’s real-timewallet balance, providing full visibility andtransparency. When a user wants to convert theircrypto holdings into INR, they simply enter thedesired amount, select the block chain network,choose the crypto currency, and the preferredpayment method. To initiate the transaction, theuser must provide a digital wallet signature, whichnot only authorizes the transaction but alsotriggers a temporary wallet lock for five minutes.This lock mechanism ensures the transaction dataremains secure and unaltered during theverification process, significantly reducing the riskof fraud. The system calculates applicable gas feesbased on the selected network and applies a fixed1% fee for network processing and a 2% service feecharged by RupXpay for conversion services. Onceverified, the INR amount is credited to the user’slinked bank account. In addition to crypto-basedconversions, RupXpay supports traditional bankto-bank INR transfers. By linking their bankaccount within the app, users can send moneydirectly to other users without involving cryptocurrency, making RupXpay a complete, dual-modepayment solution. By combiningblock chain technology with traditional financialinfrastructure, RupXpay provides users with areliable, efficient, and secure platform to makecrypto spendable in everyday life. It is a futurereadyfinancial tool that redefines how digitalassets are used in the real economy.
Title: Systemic Risk Analysis of Synthetic Asset Issuance Protocols in Decentralized Finance (DeFi) Networks Based on Network Analysis and On-Chain Data DBA Candidate, University of Tehran Abstract: This study aims to analyze the systemic risk of synthetic asset issuance protocols within Iranian Decentralized Finance (DeFi) networks. To this end, a network analysis and on-chain data approach was employed to investigate financial interdependencies among key domestic cryptocurrency platforms, including Ramzinex, Nobitex, Bit24, Phintra, and IranExChain. Real-world data from 382,747 transactions spanning from March to December 2024 (Farvardin to Azar 1403 SH) were extracted and modeled as a cross-platform transaction matrix. Network analysis results indicate that the structure of Iran’s decentralized financial ecosystem is scale-free and heterogeneous, and liquidity concentration in two primary nodes (Ramzinex = 0.62, Nobitex = 0.51) significantly increases the probability of financial contagion among protocols. The network propagation model, with transmission coefficients β=0.16\beta = 0.16β=0.16 and γ=0.09\gamma = 0.09γ=0.09, demonstrates that under a scenario of a 30% drop in collateral value, the ratio of infected nodes to the entire network increases. The composite Network Stability Index (NSI), valued at 0.74 under normal conditions and 0.46 under severe shocks, confirms the transition of the system into a fragility phase. Sensitivity and bootstrap analyses recorded an error of 0.038, validating the robustness of the model. Furthermore, results show that the introduction of the digital Rial (Rial Digital Currency) in June 2024 led to a 12% reduction in average systemic risk and enhanced cross-platform stability. Based on the findings, three strategies are proposed to mitigate systemic risk in Iran’s DeFi ecosystem: improving on-chain data transparency, regulating Rial-based collateralization policies, and designing an early warning system based on the SIR model. By combining local on-chain data with international network metrics, this study presents the first comprehensive analytical framework for assessing financial resilience in Iranian synthetic asset protocols. Keywords: Systemic Risk, Synthetic Assets, Decentralized Finance (DeFi), Network Analysis, On-Chain Data, Stability Index, Rial Digital Currency, SIR Model.
The advent of cryptocurrency has unleashed a tsunami in the global financial system, and the impact on traditional banking systems, particularly in India, has been nothing short of revolutionary. Effect of cryptocurrency on traditional banking in relation to India(04) Cryptocurrency comprises of non-regulated digital or virtual currency systems that use cryptography as a security process to verify and secure transactions along with the creation of additional units of the currency. Cryptocurrencies are based on the blockchain and are decentralized, serving as an alternative to traditional banking systems due to how it allows for faster, cheaper, and borderless transactions. This threatens traditional banking services, such as remittances, payments and lending. Speculation Points to Continued Growth in the Indian cryptocurrency industry floundered in the face of regulatory uncertainty, but it has still grown exponentially, as tech-savvy people and businesses adopt cryptocurrencies. Within this context, the study analyzes responses of traditional banks, which range from adopting blockchain technology and enhancing digital offerings to address competition from fintech companies. It also examines any regulatory policies implemented by the Reserve Bank of India (RBI) and the repercussions those policies have on the peaceful coexistence of cryptocurrency and traditional banking. The paper seeks to delve into potential collaboration and integrate between cryptos and conventional banking in India via a combination of qualitative and quantitative research methods while underlining the necessity of balanced regulation that encourages innovation, all while upholding financial stability. And the research ends with policy recommendations that would allow India’s banking sector adapt to digital currency as it evolves. Keywords: Cryptocurrency, Traditional Banking, Financial Innovation
Purpose: The paper discusses the intersection of financial literacy and digital asset education as an inherent determinant of the emergence of a new wave of self-made millionaires in America. As conventional means to wealth creation become ever more tenuous, especially for Millennials and Gen Z, advances in digital technology, including cryptocurrency, decentralized finance (DeFi), non-fungible tokens (NFTs), and e-business present unparalleled opportunities. The article investigates the key role played by financial literacy in empowering individuals to access these new avenues. Materials and Methods: A mixed-method research design was employed in this study. The paper employs current data published by Pew Research, Chainalysis, Fidelity, and the Global Financial Literacy Excellence Center. The research also employs qualitative interviews and public case profiles of investors and digital entrepreneurs. Findings: The most successful lasting success factor among the new digital millionaires is not inherited wealth or high income, but rather high financial and digital literacy levels. Case studies of individuals who have utilized cryptocurrency investing, digital enterprises, and online learning to attain prosperity prove the trend. Furthermore, this paper presents a comparative review of traditional and digital wealth creation models. Implications to Theory, Practice, and Policy: The study proposes a redefinition of financial literacy to include blockchain, tokenomics, and platform-based earnings. Practically, it summons schools, governments, and financial institutions to incorporate digital financial literacy into education and advisory services. Policy implications are public funding for Web3 education, support for digital entrepreneurship, and the decentralization of access to wealth-building.
The digital transformation of traditional finance is enabled through intelligent automation and cloud platforms. With these technologies, traditional banks and financial institutions can digitalize their products and services, transforming the banking and finance value chain along the way. Digital transformation goes beyond mere product digitization. As traditional financial institutions journey through the transformation process, they start to share their data and enable integration of back-end processes with other players in the finance ecosystem. Digital transformation leads to opening of traditional financial products through partnerships with fintech enabling easier access to financial services by suppliers, with embedded finance options. Traditional financial services such as lending and insurance underwriting become easier for customers to access through any supplier's front-end interface with integration to bank backends. Data sharing on transaction-based open finance and creditworthiness on decentralized identity with digital wallets, backed by blockchain privacy models enhances financial access for the unbanked and under-banked customers. Products are tailored to the needs of end-users through data analytics techniques and fintech partnerships.