Financial technology (FinTech) has emerged as a key driver of financial inclusion, transforming access to payments, credit, savings, and insurance for households, small businesses, and underserved populations worldwide. This study synthesizes a decade of Scopus-indexed bibliometric and systematic-review research on FinTech and financial inclusion published between 2015 and 2025. Rather than conducting a new bibliometric extraction, it provides a comparative synthesis of major peer-reviewed review studies, consolidating evidence on publication trends, intellectual structure, geographic distribution, and emerging research themes. The findings reveal rapid growth in scholarly output since 2016, led by China, India, the United States, and the United Kingdom. Dominant themes include digital payments, mobile money, regulatory technology, artificial intelligence, decentralized finance, financial literacy, SME finance, and sustainability-oriented digital finance. The review identifies persistent gaps in low-income regions and limited integration of AI and ESG perspectives. It offers a consolidated evidence base and proposes directions for future research, policy formulation, and practice.
ABSTRACT In the rapidly evolving field of information technology (IT), blockchain‐based smart contracts have emerged as a transformative force, redefining the mechanisms of digital agreements and transactions. These self‐executing contracts, with terms directly written into code on a blockchain, promise to enhance the automation, transparency and security of business processes. The integration of smart contracts into IT businesses stands as a critical innovation, aiming to streamline operations and foster trust in digital interactions. This paper aims to identify and prioritize the key variables influencing the adoption of blockchain‐based smart contracts within IT businesses. To achieve the stated objective, initially, a systematic literature review (SLR) was conducted to identify the variables of blockchain‐based smart contracts in IT businesses. Secondly, questionnaire‐based survey was conducted with IT professionals and experts, to get the experts perceptions on identified variables. The study further applied the fuzzy analytic hierarchy process (AHP) to evaluate and prioritize the identified variables based on their significance and impact on the adoption process. The research successfully identified 16 critical variables that significantly influence the adoption of blockchain‐based smart contracts in IT businesses. These variables were categorized and analyzed to understand their roles and interdependencies in the adoption process. The fuzzy AHP results revealed a hierarchical ranking of these variables, highlighting those with the most substantial impact on successful adoption, such as “security and privacy concerns,” “technical complexity,” and “regulatory and legal challenges.” The integration of blockchain‐based smart contracts presents both opportunities and challenges for IT businesses. The identified variables and their prioritization offer a roadmap for organizations to navigate the complexities of adopting this technology.
The growing demand for secure, transparent, and efficient financial systems has accelerated interest in blockchain technology within the financial sector. This study investigates the determinants and outcomes of financial blockchain adoption by proposing an integrated research model that links core blockchain characteristics security and transparency, smart contracts, and decentralization to financial blockchain adoption and its subsequent effects on fraud reduction, risk management, and cost efficiency. Using data collected from financial institutions operating in Jordan, the study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to empirically test the proposed hypotheses. The findings demonstrate that security and transparency, smart contracts, and decentralization significantly and positively influence financial blockchain adoption. Moreover, the results confirm that financial blockchain adoption has a strong positive impact on fraud reduction, risk management effectiveness, and operational cost efficiency. By conceptualizing blockchain adoption as a strategic organizational capability rather than a purely technological choice, this study extends existing blockchain and fintech literature. The findings provide valuable theoretical insights into how blockchain characteristics translate into tangible financial outcomes and offer practical guidance for financial institutions and policymakers seeking to enhance trust, governance, and efficiency through blockchain-based financial systems.
Shahinaz Hanem Abdellatif, Marwan Kobtan, Mostafa Zeinelabdein, Ramina Pashaee
The study examines the role of development finance theory, stakeholders’ theory, creating shared value (CSV), and the triple bottom line (TBL) framework to advance the Sustainable Development Goals (SDGs). Most studies focus on sustainable Business Models (SBMs) from the perspective of developed countries and often overlook the interdisciplinary nature and peculiarities of emerging economies, in terms of technology opportunities, financing constraints, and governance challenges, in the Global South. This study proposes a multi-layered framework to advance economic sustainability in emerging economies by integrating blended green finance, public-private partnerships (PPP), and fintech-enabled SBMs. The multi-layered framework redefines traditional PPP as a collaborative delivery and governance mechanism involving public, private, and development multilateral organizations to implement Economic, Social, Governance (ESG), and climate-aligned infrastructure. It also reshapes the role of blended finance strategies and emphasizes the often-overlooked role of non-banking financial institutions (NBFIs); particularly leasing companies, small and microfinance institutions, alongside banks in enabling inclusive green finance, and incorporates financial technology (FinTech) innovations, including decentralized finance (DeFi), blockchain, and digital crowdfunding, to improve access to capital, and financial inclusion. Tailored to the context of MENA economies, like Egypt's Vision 2030, the framework offers policy insights and a smooth transition toward sustainable development. Keywords: Economic Sustainability, Green Finance, Blended Finance, Public-Private Partnerships (PPP), Fintech-Enabled Sustainable Business Models, Economic, Social, Governance (ESG), Egypt Vision 2030
Decentralized Finance (DeFi) represents an emerging financial ecosystem that offers services such as lending, investing, and trading without traditional intermediaries like banks or financial institutions. Unlike conventional financial systems, users interact directly with software programs called smart contracts that encode financial logic and automate service delivery. This novel ecosystem promises transparency through public blockchain ledgers that make all transactions visible and inclusion through open access that eliminates traditional barriers to financial participation. Additionally, DeFi enables decentralized governance where users participate in protocol decision-making, and smart contracts facilitate advanced financial engineering through compositional service integration. However, despite these technical innovations, DeFi introduces significant challenges related to transaction complexity, governance concentration, and cybersecurity vulnerabilities that undermine its foundational promises. This thesis develops computational methods to systematically investigate these challenges in Decentralized Finance through empirical analysis of blockchain data. First, to address the complexity of DeFi compositions, we developed an algorithm that extracts fundamental building blocks from individual transactions, revealing recurring patterns and hidden interdependencies between financial services and assets that manual analysis cannot capture at scale. Second, we applied network analysis techniques and introduced novel measurements to examine the governance structures of decentralized applications, focusing on contributors with development and administrative roles. Our analysis revealed common voting patterns and centralized decision-making that contradict claims of decentralized governance. Third, we adapted a difference-in-differences statistical framework to quantify the economic impact of cybercrime on governance tokens, demonstrating that indirect effects on prices and trading volumes significantly exceed the direct losses suffered by immediate victims. These computational methods collectively provide the first systematic, large-scale analytical framework for empirically investigating DeFi ecosystems, revealing fundamental gaps between theoretical promises of transparency and inclusion and practical realities. The findings have significant implications for researchers, policymakers, and practitioners by establishing evidence-based approaches to measuring decentralization claims and systemic risks in blockchain-based financial systems.
Ahmad Ahmad, Muhammad Said, Abdillah Abdillah, Abdulloh Munir
The rapid expansion of Decentralized Finance (DeFi), powered by blockchain technology, has transformed global financial systems by offering peer-to-peer, intermediary-free services. However, its compatibility with Islamic economic law (hukum ekonomi syariah) remains uncertain due to potential violations of Sharia principles such as the prohibition of riba (usury), gharar (excessive uncertainty), and maysir (speculation). This study addresses this gap by employing a qualitative maqāṣid al-sharī‘ah-based analysis to assess the alignment of DeFi mechanisms decentralized exchanges, lending protocols, and smart contracts with Islamic ethical and legal values. Data were collected through literature review and document analysis from classical Islamic sources, fatwas, and current DeFi documentation. The findings show that while many DeFi practices contain non-compliant elements, their underlying technology particularly smart contracts and decentralized governance holds significant potential for adaptation. When structured using Sharia-compliant contracts such as murābaḥah, mushārakah, or wakālah, and guided by maqāṣid objectives like ḥifẓ al-māl (preservation of wealth) and ḥifẓ al-dīn (preservation of faith), DeFi can support financial inclusion, transparency, and justice in accordance with Islamic law. This study proposes a normative framework for building Sharia-compliant DeFi platforms, integrating technical innovations with ethical governance, thereby offering a transformative model for Islamic finance in the digital era.
Decentralized Finance (DeFi) has introduced new security challenges due to its open, permissionless, and pseudonymous nature, which has increased the risk of fraud and phishing activities. This thesis first presents a comprehensive study of 284 DeFi platforms to examine their architectural, functional, and security-related characteristics. Building on this ecosystem-level analysis, the thesis develops a behavior-centric multiclass detection framework using Ethereum transaction data. The framework integrates legitimate, fraud, and phishing activities into a unified dataset and evaluates several traditional and deep tabular learning models, including TabNet, GANDALF, and NODE. The results show that deep tabular models outperform conventional baselines, with NODE achieving the strongest overall performance. Feature importance analysis highlights gas usage, nonce behavior, transaction frequency, and wallet activity as key indicators of malicious behavior. Overall, this thesis demonstrates that behavior-based Ethereum transaction features combined with deep tabular learning can support more effective and scalable DeFi threat detection.
This study aims to examine the effect of Bitcoin risk perception on stock investment decisions by considering the mediating roles of financial literacy and investor trust. The rapid development of digital financial technology, particularly cryptocurrencies, has introduced new dimensions of risk that influence investor behavior across financial instruments. This research adopts a quantitative approach with an explanatory design, involving 120 respondents selected through purposive sampling. Data were collected using structured questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that Bitcoin risk perception has a positive and significant effect on financial literacy, investor trust, and stock investment decisions. Furthermore, financial literacy and investor trust significantly influence stock investment decisions and serve as partial mediators in the relationship between Bitcoin risk perception and investment decisions. These findings suggest that higher awareness of cryptocurrency risk encourages individuals to enhance their financial understanding and develop rational trust, ultimately leading to more informed investment decisions in the stock market. This study contributes to the integration of behavioral finance and financial technology by highlighting the indirect mechanisms through which risk perception shapes investment behavior. Practically, the results emphasize the importance of financial education and transparent information in improving investor decision-making in the digital era.
This study presents a comprehensive bibliometric analysis of 1,567 scholarly publications to map the evolution of Fintech from 2005 to 2025. Leveraging the SPAR4SLR framework and advanced tools like Biblioshiny, three critical paradigm shifts are identified: the transition from foundational digital banking (2005–2014) to AI-driven financial systems (2015–2019), pandemic-accelerated digitization (2020–2022), and the current era of ethical AI and decentralized finance (2023–2025). The analysis reveals that post-2020 research predominantly focuses on technological innovations such as blockchain and algorithmic trading, while ethical implications remain underrepresented—highlighting a significant governance gap. Geographical disparities are also evident, with most publications originating from North America and Europe, despite Sub-Saharan Africa and South Asia emerging as key regions for fintech adoption. This research provides actionable policy recommendations to bridge these gaps, including a framework for AI ethics in credit scoring and strategies for fintech integration.
Zokir Mamadiyarov, R. N. Ravikumar, S. Aarthi, E. Padma · 5 authors
The integration of ESG (Environmental, Social, and Governance) principles with FinTech is reshaping modern finance through technologies like blockchain, digital wallets, robo-advisors, and DeFi. This work explores how computational tools such as machine learning, data analytics, and simulation modelling enhance ESG risk management in digital finance. It addresses cybersecurity, regulatory compliance, AI ethics, and financial resilience, linking ESG issues to practical risk control strategies. Real-time tracking of ESG indicators and transparent reporting via blockchain are emphasized. Techniques like ESG scoring models, heatmaps, and dashboards assist in monitoring sustainability and performance. It also examines emerging risks such as greenwashing, data ethics, and decentralized finance vulnerabilities. The focus is on combining innovation, ethics, and sustainability to build a robust, risk-aware financial ecosystem. This approach is essential for aligning FinTech growth with responsible, long-term ESG goals.
Risk management along with sustainable wealth generation are being revolutionized by the combination of Fintech with Environmental, Social, and Governance (ESG) standards. Fintech platforms enable financial institutions to detect and reduce ESG risks, improve transparency, and avoid greenwashing by utilizing blockchain, big-data analytics, artificial intelligence (AI), and decentralized finance (DeFi). Risk assessment techniques are improved by blockchain-enabled ethically finance protocols as well as AI-driven ESG evaluations, which support regulatory oversight and transparency. Research indicates that companies that include ESG factors into Fintech products see improved financial outcomes and attract impact-oriented funding. But there are still a lot of barriers, like disjointed legal regimes, difficulties harmonizing data, and high compliance costs.
The realms of metaverse and finance have been completely revolutionized through the application of blockchain technology. This technology offers convenience, transparency, security, and decentralization to the virtual world while overcoming the inefficiencies of the traditional financial landscape. The present chapter highlights the various services offered by blockchain technology in the metaverse, such as security, interoperability, and ownership status, especially in the area of finance. A digital landscape with a large number of users sharing information from various geographical locations using an internet connection is called the metaverse. Blockchain technology ensures transparency and security in the metaverse by building trust among users. The users get complete authority over their digital assets, thereby enhancing their participation in the digital realm. In the financial sector, the traditional financial system is transformed through the introduction of blockchain technology, such as cryptocurrencies like Bitcoin and Ethereum, decentralized finance (DeFi), smart contracts, and asset tokenization. Cryptocurrencies, like Bitcoin 506 and Ethereum, provided by blockchain technology, are digital currencies that ensure secure transactions and do not need any authority to act as a middleman. Decentralized finance (DeFi), based on decentralization, facilitates peer-to-peer financial transactions. Smart contracts are automatically executed agreements or contracts made using blockchain technology, which makes the process of transactions easier. Asset tokenization is a representation of the value of assets as digital tokens. However, blockchain technology also presents challenges in various services, necessitating the need to address them to improve opportunities.
In the current conditions of digitalization of the economy, the financial sector is undergoing significant transformations under the influence of innovative technologies and FinTech solutions. At the same time, digitalization is accompanied by new challenges, such as cyber risks, the need to adapt the regulatory environment, and ensuring financial stability. Therefore, the study of trends in the financial and digital space is relevant for assessing the state of the FinTech sector, identifying dominant technologies and directions for the development of the digital financial ecosystem. The purpose of the study is to analyze current trends in the development of the financial and digital space and determine the structure of its main segments in order to assess the role of financial technologies in the transformation of the financial sector and the formation of a digital financial ecosystem. A set of general scientific and special methods was used: theoretical generalization and systematization, analysis and synthesis, statistical and comparative analysis, as well as the graphical method. The empirical basis is the NBU's statistical data on the dynamics of the payment infrastructure for 2021–2025 and analytical materials of the Ukrainian FinTech Association and innovative companies on the structure of the FinTech market. As a result, it was found that in 2021–2025, the payment infrastructure of Ukraine demonstrates a steady recovery after the shocks of 2022: the number of POS terminals increased from 368 thousand units (2022) to 605 thousand units (2025), active payment cards - from 46.3 million units to 65.4 million units, and the volume of transactions through POS terminals - from UAH 106 billion to UAH 210 billion. The structure of the Ukrainian FinTech market in 2025 is characterized by the dominance of technological infrastructure (28%), payments and transfers (18%), and personal/consumer lending (10%); smaller shares are accounted for by RegTech (8%), digital banks (7%), and personal finance management (7%). Among the technologies used by FinTech companies, API (71%), artificial intelligence (43%), chatbots (42%), and cloud technologies (39%) are leading, while blockchain (9%), DeFi (4%), and NFT (2%) are in the initial stages of implementation. The results confirm that the key trends in the financial and digital space are the integration of financial services, process automation, and the active use of artificial intelligence, which form the basis of the digital financial ecosystem. At the same time, the modern FinTech market of Ukraine is in the process of formation, and the latest technologies, such as blockchain and decentralized finance, have not yet become widespread.
This study examines the drivers of decentralized finance (DeFi) token returns, focusing on protocol metrics and broader market trends. While previous research has primarily analyzed a limited set of factors, this study incorporates additional indicators, including such groups of metrics as protocol activity indicators, income statement metrics, treasury balances, market efficiency metrics, and valuation multiples. Using weekly data from January 2021 to March 2025 for three major DeFi tokens (COMP, AAVE, CRV), we apply linear regression to test the relationship between token returns and internal protocol metrics. Our findings show that COMP and AAVE exhibit strong associations, mainly with Ether price movements, whereas CRV is also linked to financial metrics such as net treasury and Total Value Locked (TVL). These results suggest that DeFi token returns are shaped both by market-wide conditions and by protocol-specific characteristics, with the relative importance of these factors varying across different token types. This study contributes to the decentralized finance literature in three key ways: (1) we conduct the first comprehensive analysis linking governance token performance to five distinct categories of protocol-specific metrics, (2) we demonstrate significant variation in valuation drivers between different protocol types (lending versus DEX), and (3) we challenge the assumption that DeFi tokens simply track Ether’s price movements. Our results establish that protocol-specific factors must be accounted for in any comprehensive valuation model of DeFi assets.
Purpose This paper aims to examine decentralized finance (DeFi) as a Web 3.0 information system, not solely as a financial innovation. It synthesizes how DeFi mechanisms are structured across architectural, functional and governance dimensions and clarifies how they reshape trust, coordination, transparency and accountability in decentralized digital environments. Design/methodology/approach The study adopts a state-of-the-art survey based on a structured review of academic, industry and regulatory literature. The reviewed sources are analyzed to identify major system components, including decentralized applications, smart contracts, blockchain-based execution layers, oracle-based data integration, governance protocols and interoperability mechanisms. Expert interviews provide supplementary interpretive context on adoption barriers and governance tensions. Findings DeFi operates as a web-native information system composed of interconnected service layers supporting exchange, lending, payments, insurance, asset management and protocol governance. These mechanisms increase programmability, automation and accessibility while introducing persistent challenges related to governance concentration, security vulnerabilities, scalability constraints, usability barriers, oracle dependence and regulatory fragmentation. Originality/value While prior DeFi surveys have characterized mechanisms, business models or regulatory arrangements, this paper is the first to read DeFi as a layered Web 3.0 information system, integrating distributed execution, data coordination, service composition and decentralized governance. It offers a structured synthesis and a system-oriented perspective relevant to researchers and practitioners interested in decentralized applications, blockchain-based web services and digital financial infrastructure design.
Inseong Jeon, Sundeuk Kim, Hyunwoo Kim, Hoh Peter In
<title>Abstract</title> As Solidity becomes the dominant language for blockchain smart contracts, efficient debugging grows increasingly critical. However, current Solidity debugging remains inefficient: developers must compile, deploy, set up transactions, and step through execution line-by-line to examine each variable. This process is too slow for practical use. To address this challenge, this paper presented SolQDebug, the first interactive source-level debugger for Solidity that delivered millisecond feedback directly on source code. Developers specify input value ranges through annotations and compare them against abstract interpretation results, thereby enabling exploration of contract behavior across multiple execution paths. SolQDebug was evaluated on 30 real-world functions from DAppSCAN, achieving 350$\times$ faster debugging (0.15s vs. 53s per function) than Remix IDE. The evaluation provided debugging insights: overlapping annotation patterns improved precision in most Solidity debugging scenarios, while analysis of diverse loop patterns demonstrated improved convergence while preserving soundness guarantees. These results demonstrated that SolQDebug enabled interactive debugging for Solidity development.
Zishan Ashraf Mohammad, Nick Harkiolakis, Saman Sarbazvatan
Although there has been a massive increase in the size and complexity of the cryptocurrency ecosystem, most of the academic research into the relationship between token design parameters and the long-term value of a given token is still very much in its infancy. Most of the research in tokenomics is theoretical in nature, based upon frameworks for understanding, or is focused solely on observing a specific time frame. The authors of this paper address the above mentioned void by studying the statistically significant relationships between five on-chain tokenomic variables--transaction gas fees, total value locked (TVL), token unlocks, tokens burned, and governance concentration (as measured using the Gini coefficient) -- and the market price of Ether (ETH) during a 52 months observation window that began in August 2021 and ended in September 2025. The data for the study consisted of bi-weekly observations (n = 108) which allowed researchers to use three different analytical methods--Spearman correlation analysis, log-linear multiple regression analysis, and an error correction model (ECM) after conducting Johansen cointegration and unit root tests. A cointegrating equation among the variables was established through Johansen Trace Testing, indicating that all of these variables do indeed exhibit a long-run equilibrium relationship. The ECM revealed that the total amount of funds “locked” into smart contracts (“total value locked”) was the strongest single predictor of the price of Ether in both the long run (beta = 0.8, p &lt; 0.001) and short run (beta = 1.18, p &lt; 0.001) specifications. Additionally, it was found that token unlocks have a negative relationship with price (beta = −0.22, p &lt; 0.001). Gas Fees (beta = 0.2, p = 0.021) and tokens burned (beta = 0.15, p = 0.039) had positive coefficients at the 0.01 level in the long-run specification; however, both exhibited extremely high levels of multicolinearity (Variance Inflation Factor&gt;28,000), likely due to their technical/operational linkages under EIP-1559. Voting power did not demonstrate a statistically significant relationship to price (rho =0.143, p &gt; 0.05).
India's asset management systems, especially land records, property registries and ownership documents, face major challenges such as fraud, ownership disputes, slow manual verification and fragmented documentation. These issues affect citizens, government departments, financial institutions and real-estate stakeholders. Blockchain technology provides an opportunity to improve asset management by creating tamper-resistant records, transparent transaction history and automated workflows through smart contracts. This paper studies the use of blockchain platforms for asset management in India with a comparative focus on Hyperledger Fabric and Ethereum. The study analyzes technical architecture, performance, privacy, cost, scalability and implementation barriers. It also considers Indian use cases such as Telangana land parcel initiatives, Karnataka Bhoomi-related digital land record modernization and national-level blockchain adoption efforts. The findings show that Hyperledger Fabric is more suitable for regulated government asset systems because it provides permissioned access, privacy channels, higher transaction throughput and lower operational cost. Ethereum is useful for public transparency and open applications, but its public-chain gas cost, lower throughput and regulatory challenges reduce suitability for high-volume government asset records. The paper concludes that a permissioned blockchain model with proper standards, legacy-system integration, legal recognition and rural digital infrastructure can support scalable blockchain-based asset management in India.
The rapid expansion of decentralized financial applications has increased the importance of understanding user trust in crypto wallet platforms. This study examines trust expressions in multilingual Phantom Wallet reviews using a hybrid classification framework that integrates BERT-based contextual embeddings with an XGBoost model. A total of 12,422 English and Indonesian reviews were collected and processed to construct a multilingual dataset for trust analysis. Exploratory findings reveal a highly polarized distribution of user ratings, indicating that trust in crypto wallets is strongly influenced by clear satisfaction or dissatisfaction rather than moderate evaluations. Cross-linguistic analysis indicates that Indonesian users express a higher proportion of low-trust reviews compared to English users, suggesting greater sensitivity to transaction errors and perceived asset safety concerns. Lexical patterns demonstrate that positive trust is associated with usability and performance stability, while negative trust is primarily driven by system failures, delays, and missing balance incidents. The results confirm that the BERT–XGBoost hybrid model is well-suited for decoding trust-related signals by combining contextual semantic understanding with structured metadata. This study contributes to the broader discourse on digital trust within Web3 environments by demonstrating an effective multilingual machine learning approach for analysing user perceptions in decentralized financial technologies.
The rapid expansion of Decentralized Finance (DeFi) has enabled open and permissionless token trading, but it has also led to a surge in fraudulent activities such as rug pulls, wash trading, and pump-and-dump schemes. This paper presents a novel fraud detection approach based on correlation analysis between token price and liquidity, leveraging the inherent relationship between these two market variables. In legitimate markets, price movements are typically supported by corresponding changes in liquidity, whereas fraudulent tokens often exhibit abnormal or decoupled behavior due to artificial price manipulation. To investigate this, we analyze time-series data of token price and liquidity across multiple decentralized exchanges and compute statistical correlation metrics alongside liquidity variation patterns. Experimental results show that legitimate tokens maintain strong positive correlations (r > 0.7) between price and liquidity, while fraudulent tokens exhibit weak or unstable correlations (r < 0.3), often accompanied by sudden liquidity withdrawals or artificial volume spikes. The proposed framework achieves high detection performance with an accuracy of 92.4%, precision of 90.1%, recall of 93.6%, and F1-score of 91.8%, demonstrating its effectiveness in identifying suspicious tokens at early stages. The findings confirm that deviations in price–liquidity correlation serve as a reliable and computationally efficient indicator for fraud detection in DeFi ecosystems. This approach can be integrated with existing blockchain analytics tools to enhance real-time monitoring and improve investor protection.
This conceptual paper explores the profound impact and pivotal role of information systems (IS) within the rapidly evolving landscape of Decentralized Finance (DeFi). Emerging from the advancements in blockchain technology, DeFi represents a paradigm shift in financial management, offering an ecosystem that is more inclusive, transparent, and efficient by removing centralized intermediaries through smart contracts. This paper analyzes how IS principles are fundamental to the design, management, and security of DeFi protocols, contrasting them with traditional financial systems. It delves into core DeFi applications such as Decentralized Exchanges (DEXs), lending/borrowing protocols, stablecoins, and yield farming, emphasizing their underlying IS architectures and the challenges related to user experience (UX/UI). Furthermore, the paper discusses critical IS aspects in DeFi, including security management, automation via smart contracts, blockchain-based analytics for risk management and anomaly detection, and the unique governance mechanisms through Decentralized Autonomous Organizations (DAOs). Finally, it outlines the future trajectory of DeFi, considering its integration with emerging technologies like Artificial Intelligence (AI) and Web3, and its evolving relationship with global financial systems and regulations. This work contributes to understanding the complex interplay between technology and finance, highlighting how robust information systems are indispensable for DeFi's sustained growth and its potential to reshape the digital financial ecosystem.