Almost everyone has come across the concept of crypto-assets, or other synonyms for this phenomenon. It can be said that they have already become an integral part of everyday life in an era that is often referred to as the industrial (digital) revolution 4.0. A relatively long period has passed since the first crypto-assets were issued, and they are increasingly becoming more accessible to the general public, who do not even need to have investment experience to buy or sell them. This is also due to many other technological innovations, which are used in the competitive struggle for clients and make it possible to buy crypto-assets practically anywhere.
Nyoman Sri Subawa, Caren Angellina Mimaki, I Made Oka Mahendra, Made Srinitha Millinia Utami
Bitcoin halving is a quadrennial event that halves mining rewards and is believed to influence cryptocurrency prices and cryptocurrency market dynamics. This study examines the effect of Bitcoin halving on Cryptocurrency Prices, with Government Regulations, Market Sentiment, and Cryptocurrency Performance as mediating variables. A quantitative research approach was employed, gathering original data via survey instruments from 294 participants within the cryptocurrency community in Bali, which were analyzed using PLS-SEM. The findings indicate that Bitcoin halving exerts a favorable and statistically meaningful influence on Government Regulations, Market Sentiment, Cryptocurrency Performance, and Cryptocurrency Prices. Market Sentiment fully mediates the influence of Government Regulations and Cryptocurrency Performance on Cryptocurrency Prices, while Government Regulations and Cryptocurrency Performance partially mediate the effect of Bitcoin halving. These findings highlight that Cryptocurrency Prices are shaped by the interplay of technical, policy, and psychological factors, with strategic implications for investors, regulators, and developers.
This paper examines how the adoption of Bitcoin has affected financial inclusion, banking access, and economic activity in El Salvador, with a particular focus on small and medium-sized enterprises (SMEs) in underbanked regions. After El Salvador became the first country to recognize Bitcoin as legal tender in 2021, it created a unique opportunity to study how cryptocurrency functions outside of theory and within a real national economy. Using a mixed-methods approach, this research combines a review of academic literature, policy analysis, and media reporting with quantitative analysis of cryptocurrency market data and financial infrastructure indicators. The quantitative component includes correlation, regression, and predictive analysis of cryptocurrency price and transaction volume data, as well as an examination of Bitcoin ATM availability relative to population across major cities. These results are supported by qualitative findings that explore public adoption, SME experiences, and broader economic concerns such as volatility, infrastructure limitations, and financial stability. The findings suggest that while Bitcoin has expanded access to digital financial tools and introduced potential efficiencies in transactions, its impact on financial inclusion has been uneven, particularly in rural and underbanked areas. For SMEs, Bitcoin presents both opportunities and challenges, offering faster payments while also creating risks related to volatility, technical barriers, and implementation costs. Overall, this study highlights the mixed outcomes of cryptocurrency adoption in El Salvador and contributes to ongoing discussions about whether digital currencies can meaningfully support financial inclusion and economic development in developing economies.
Son Van Nguyen, Le Hong Ha Anh, Chu Hai Ha, Hieu M. Nguyen · 5 authors
Blockchain technology has emerged as a ground-breaking trend in recent years, with the potential to drive global economic growth by shifting business models from human-based trust to technology-based trust. The core features of Blockchain, including transparency, high security, and fraud resistance, have been widely applied across many sectors. However, one of the greatest challenges in the digital economy is the validation of ownership, protection of copyright, and monetization of digital assets. This study focuses on solving this problem by providing an in-depth analysis of Non-Fungible Tokens (NFTs)—a specialized application of Blockchain. Through synthesis and analysis, this paper proposes a strategic framework using NFTs to enable businesses and creators to digitize, authenticate, and monetize their assets, particularly through an automated royalty mechanism.
In an age where the lines between finance and technology blur into an opus of digital evolution, The VDA & Crypto Convergence: Charting the Operational Pulse of the Global Crypto Exchange Ecosystem in 2025 dissects the metamorphosis of Virtual Digital Assets (VDAs) and crypto exchanges from experimental ventures to regulated pillars of modern finance. The study unveils 2025 as a watershed year- a "regulated renaissance"- where legislation such as the U.S. GENIUS Act, EU's MiCA, and Hong Kong's Stablecoin Ordinance transformed ambiguity into architecture. It examines how hybrid exchanges-the ingenious offspring of centralized speed and decentralized autonomy- symbolize the era?s financial duality, while AI-driven intelligence and tokenization redefine market participation and asset fluidity. Through the interplay of law, technology, and trust, this paper illuminates a future where the crypto economy ceases to be an outlier and becomes the central nervous system of global finance, balancing regulation and innovation like twin sails steering the same vessel through uncharted digital waters.
In decentralized finance (DeFi), designing fixed-income lending automated market makers (AMMs) is extremely challenging due to time-related complexities. Moreover, existing protocols only support single-maturity lending. Building upon the BondMM protocol, this paper argues that its mathematical invariants are sufficiently elegant to be generalized to arbitrary maturities. This paper thus propose an improved design, BondMM-A, which supports lending activities of any maturity. By integrating fixed-income instruments of varying maturities into a single smart contract, BondMM-A offers users and liquidity providers (LPs) greater operational freedom and capital efficiency. Experimental results show that BondMM-A performs excellently in terms of interest rate stability and financial robustness.
Tuan-Dung Tran, Bao Huynh, Tra Minh Trong, Tong Thuan Nguyen · 6 authors
Permissioned blockchains using Proof-ofAuthority (PoA) deliver high throughput but face issues of predictability and centralization, while token-weighted governance risks plutocracy that undermines fairness. This paper proposes Proof-of-Merit (PoM), a consensus and governance framework that integrates PoA with Verifiable Random Functions (VRFs) and a dual-token model. PoM selects validators through a weighted combination of transferable stake (UIT-Coin) and non-transferable academic reputation (UIT-Rep), earned via verifiable onchain learning activities. Governance follows the same principle, anchoring voting rights in Sybil-resistant merit rather than pure capital. To ensure sustainability, PoM introduces reputation decay, preventing long-term power concentration and promoting continuous participation. We implement PoM on Hyperledger Besu and evaluate it with Hyperledger Caliper. Results show PoM achieves strong performance while significantly improving fairness, with a much lower Gini coefficient and higher Nakamoto coefficient compared to IBFT 2.0. Sensitivity analysis further highlights the need for dynamic reputation mechanisms to avoid saturation. These contributions establish PoM as a scalable, equitable, and sustainable foundation for Learn-to-Earn ecosystems, where influence derives from ongoing educational engagement instead of wealth accumulation.
The digital transformation of finance and accounting is accelerating with AI, blockchain, and automation, reshaping financial operations, auditing, and compliance. This study conducts a thematic analysis of academic literature (2018–2025) and industry reports from PwC, Deloitte, EY, HSBC, and central banks to examine key trends. Six themes emerged: automation and efficiency, security and fraud prevention, decentralization, financial inclusion, regulatory challenges, and adoption barriers. Findings show that AI and RPA enhance financial reporting and fraud detection, while blockchain improves transparency and security but poses scalability and regulatory challenges. Decentralized finance (DeFi) and digital currencies like JPM Coin and the Digital Yuan are transforming transactions but raise concerns over compliance and illicit activity risks. Mobile banking and blockchain-based solutions improve financial inclusion, yet digital literacy and security risks remain barriers. Using NVivo-based thematic analysis, the study identifies key trends shaping the future of financial digitalization. While AI and blockchain drive efficiency, regulatory complexities and adoption barriers must be addressed for sustainable transformation. Future research should explore scalability, AI-enhanced compliance, and blockchain’s role in financial security.
Saiful Ruchiyat Cosahan, Ahmad Yunani, Asrid Juniar, Muzdalifah Muzdalifah
This Systematic Literature Review (SLR) analyzes 38 empirical studies published between 2015 and 2025 (sourced from Scopus and Sci-ScienceDirect) to map blockchain-based funding mechanisms in the context of venture capital (VC) and entrepreneurial finance. The review addresses four research questions concerning the evolution of these mechanisms, their impact on startup performance, and associated risks and regulatory challenges. The findings establish a robust taxonomy of mechanisms, including Initial Coin Offerings (ICOs), Security Token Offerings (STOs), and Decentralized Autonomous Organizations (DAOs), each presenting unique features and regulatory profiles. Crucially, the review highlights significant gaps in long-term performance data, revealing challenges related to investor protection, fraud risk, and regulatory uncertainty. By integrating Signaling Theory and Governance Theory, the study discusses how tokenomics and team credibility function as signals instead of traditional VC due diligence, presenting a critical comparison between token-based funding and traditional-al venture capital financing. This paper offers valuable insights for academics, policymakers, and industry practitioners by providing a com-comprehensive map of the field, suggesting avenues for future empirical research, and offering focused policy implications regarding regulation and investor safety in emerging markets.
Savings and loan cooperatives play an essential role in promoting financial inclusion and supporting Indonesia's local economy by providing affordable credit and encouraging community-based savings. However, many cooperatives still depend on manual or semi-digital procedures for credit approval, resulting in inefficiencies, delayed loan processing, human errors, and limited transparency. These weaknesses often lead to mismatched capital-to-loan ratios, data inconsistencies, and reduced member trust in cooperative governance. To address these challenges, this study proposes a blockchain-based smart contract framework that automates the credit approval process through secure, rule-based decisionmaking. The research employs the Design Science Research Methodology (DSRM) to design, implement, and evaluate a prototype system developed using Solidity on the Ethereum blockchain, integrated with Web3.js and Metamask for decentralized interactions. The smart contract encodes cooperative business rules, automatically verifies member eligibility, and records transactions immutably on the blockchain ledger. A case study conducted in an Indonesian cooperative demonstrates that the proposed system reduces credit approval time from several days to a few seconds, eliminates manual verification errors, and achieves 100 % transaction success and data consistency. The findings highlight the potential of blockchain and smart contracts to enhance operational efficiency, transparency, and trust in cooperative finance, contributing to Indonesia's digital transformation and offering a scalable model for other community-based financial institutions.
This study investigates the long-run relationship between the net assets of Bitcoin spot exchange-traded funds (ETFs) and Bitcoin’s price. Using daily data from 11 January 2024 to 16 May 2025, we employ cointegration techniques—Fully Modified OLS, Dynamic OLS, and Canonical Cointegrating Regression—to test for a stable equilibrium linking these series. The empirical results indicate a strong positive association in the long run: periods of expanding Bitcoin ETF assets correspond to higher Bitcoin price levels. Cointegration is confirmed at the 10% significance level, suggesting that the ETF assets under management and the Bitcoin market price move together in a persistent equilibrium. These findings support the hypothesis that ETF-driven demand exerts a lasting influence on Bitcoin’s valuation. By highlighting a structural connection between regulated Bitcoin investment vehicles and the underlying cryptocurrency, the study provides timely evidence of how financial innovation can shape asset pricing in the digital asset market.
Blockchain and artificial intelligence (AI) are reshaping the financial landscape by improving security, operational efficiency, and intelligent automation. Blockchain&s;s decentralized and tamper-proof ledger fosters transparency and trust in financial transactions, while AI enhances decision-making through advanced data analysis, fraud detection, and risk management. Together, their convergence supports a wide range of applications, including decentralized finance (DeFi), asset tokenization, algorithmic trading, and robo-advisory services. Blockchain provides a secure infrastructure for AI-driven financial innovations by ensuring data integrity and minimizing dependence on intermediaries. In parallel, AI improves blockchain performance by automating smart contracts, refining predictive models, and streamlining compliance mechanisms. To better understand and structure this integration, the chapter introduces the Techno-Financial Synergy Framework (TFSF), which connects the technological enablers, strategic drivers, and outcomes of AI-blockchain convergence. While the synergy holds great promise, it is also accompanied by challenges such as computational overhead, scalability constraints, interoperability gaps, and evolving regulatory landscapes. However, emerging solutions such as zero-knowledge proofs, homomorphic encryption, and next-generation consensus protocols are gradually addressing these limitations. As these technologies continue to evolve, their convergence is expected to drive the next phase of digital financial transformation, fostering a smarter, more secure, and inclusive financial ecosystem.
Rosario Violeta Grijalva Salazar, Jose Antonio Caicedo-Mendoza, Arturo Jaime Zuñiga Castillo, Erikson Olivas-Valencia · 5 authors
Taxation on cryptocurrency is becoming critical in global fiscal governance as digital assets adapt to the modern reality of existing outside of traditional regulatory constructs. Theoretical and practical understanding of cryptocurrency taxation is quite new, and so a systematic review was designed to present the most recent empirical research evidence on the legal, fiscal and behavioral aspects of cryptocurrency taxation from across the globe. Using the PRISMA-2020 guidelines, a structured search was applied to the Scopus database on 21 May 2025, with the search terms “crypto-currency”, “cryptoasset” and “taxation.” The inclusion criteria consisted of original research articles published between the years of 2020 and 2025 in English or Spanish, that could be accessed via institutional library support, and that were related to taxation, legal regulation and/or compliance. Out of the original identified 224 records, 36 met the eligibility criteria after screening and verification through seven different stages of review. Socially, five themes were produced by the findings: legal ambiguity surrounding fiscal treatment, limited tax literacy and compliance issues, macroeconomic and monetary issues, application of digital technologies for fiscal tracking, and environmental repercussions from crypto mining. Many countries do not have any coherent tax frameworks to govern the risk that emerges from cryptocurrency taxation, creating uncertainty for both regulators and investors. The findings outlined in this systematic review point to the urgent need for creating a coherent approach to cryptocurrency taxation based on definitions, digital approaches to traceability, and tax literacy compliance strategies. In order to create effective cryptocurrency taxation, there must be a base balance between ensuring innovation, fiscal responsibility, transparency, equity and sustainability in the developing digital economy.
Pankaj Gugnani, Monis Khan, Spandan Barve, Debanjan Sadhya · 5 authors
Public blockchains like Ethereum generate vast amounts of transactional data, offering insight into significant economic and decentralized application activity. However, these data are often unstructured and semantically poor. Understanding the functionality of smart contracts is crucial for unlocking the potential of this data. This work presents a novel methodology to transform raw blockchain transaction logs into semantically rich representations. We first classify smart contracts by analyzing their function names and structures using N-gram profiling and embedding comparisons against known standards like ERC/EIP. This process assigns functional labels (e.g., DeFi, Exchange, Token) to the smart contracts. Subsequently, we model the framework as a heterogeneous graph of users and labeled contracts. We employ a modified Node2Vec algorithm with an enforced alternating node-type walk strategy to effectively capture the dynamics of user-contract interactions. This process yields low-dimensional vector embeddings for users and contracts, making blockchain data readily available for knowledge discovery. We demonstrate the utility of our approach through a smart contract recommendation system that suggests relevant contracts to users based on their interaction history and learned embeddings.
Purpose : Investors sometimes have difficulties in making appropriate decisions during unpredictable times such as the COVID-19 pandemic. Based on the extended theory of planned behavior (TPB), the objective of this study was to validate the psychological antecedents of willingness to invest in cryptocurrency during the outbreak of the COVID - 19 pandemic. Design/Methodology/Approach : This study was conducted by collecting primary data from 204 respondents using a structured online questionnaire, which was further analyzed using SPSS Amos 23.0. The current research explored the association between variables named “subjective norms,” “perceived self-efficacy,” and “attitude to invest.” Findings : The findings suggested that “subjective norms” and “perceived self-efficacy” are the major factors influencing investors’ attitudes toward cryptocurrency investment, directly impacting their intentions for the same. The pandemic underscored the dual nature of cryptocurrencies, demonstrating advantages such as enabling remote transactions and providing a hedge against economic instability, while simultaneously displaying difficulties, including environmental implications and market volatility. Practical Implications : The results have important reference significance for future investors who intend to invest in the crypto-assets market. The findings of the study provided important insights to investors and financial planners on which psychological factors affect whether to make a cryptocurrency investment during volatile periods, such as the COVID-19 era. Learning these key aspects will provide scientists with tools to navigate choppy waters, which will ultimately make them better decision-makers. Originality : This research enhanced the existing body of knowledge by uniquely incorporating the extended theory of planned behavior into the context of cryptocurrency investments during a global crisis. It offered an extensive comprehension of investor psychology during periods of uncertainty, essential for both scholarly study and pragmatic investment strategies.
Dan Alexandru Mitrea, Constantin Viorel Marian, Rareş Alexandru Manolescu
In many jurisdictions, property registration and transfers remain constrained by inefficient, paper-based processes that depend on multiple intermediaries and bureaucratic approvals. This paper proposes a decentralized, blockchain-based property platform designed to streamline these processes using Non-Fungible Tokens (NFTs) and artificial intelligence (AI) agents to modernize public-sector asset management. The work addresses the persistent inefficiencies of paper-based property registration and ownership transfer by embedding legal and administrative logic within smart contracts and automating compliance through an intelligent conversational interface. The system was implemented using Ethereum-based ERC-721 standards, React for the user interface, and Langfuse-powered AI integration for guided user interaction. The pilot implementation presents secure, transparent, and auditable property-transfer transactions executed entirely on-chain, while hybrid IPFS-based storage and decentralized identifiers preserve privacy and legal validity. Comparative analysis against existing national initiatives indicates that the proposed architecture delivers decentralization, citizen control, and interoperability without compromising regulatory requirements. The system reduces bureaucratic overhead, simplifies transaction workflows, and lowers user error risk, thereby strengthening accountability and public trust. Overall, the paper outlines a viable foundation for legally aligned, AI-assisted digital property registries and offers a policy-oriented roadmap for integrating blockchain-enabled systems into public-sector governance infrastructures.
The user-ownership model of Web3 commerce is widely viewed as a potential paradigm shift for the digital economy, yet its macroeconomic implications remain under-quantified within a unified, dynamic, and parameterized framework. This paper develops a tractable dynamic macroeconomic model of a “wealth flywheel” featuring two feedback channels. The income loop operates through profit-backed user rebates that raise income-equivalent purchasing capacity and stimulate consumption. The asset loop operates through consumption-driven profit and valuation growth, which expands household wealth under user ownership and feeds back into consumption via wealth effects. In a static setting, the paper derives a closed-form consumption multiplier and a corresponding stability condition. Aggregate consumption responds proportionally to an exogenous income impulse, and the system is stable if the combined strength of rebate-induced consumption feedback and wealth-effect amplification remains below unity. The static mechanism is then embedded into a global multi-period simulation framework with time-varying Web3 penetration, finite-horizon household deposit reallocation into consumption, and endogenous valuation paths. Using illustrative parameterizations, the paper simulates trajectories for global real GDP, equity market capitalization, household wealth, and inflation under neutral and aggressive adoption scenarios. The analysis further examines distributional implications when capitalization gains are directed toward user cohorts with higher marginal propensities to consume. The framework provides a parsimonious diagnostic for stability in mechanism design and contributes to macro-prudential discussions of self-reinforcing growth dynamics. Importantly, the analysis abstracts from collateralized borrowing, leverage, rehypothecation, and other financial intermediation channels. All amplification effects in the model arise from ownership structure and wealth effects rather than from credit-driven financial accelerators.
This study examines the growth trends of cryptocurrencies and their associated taxation policies, focusing on the unique technological advancements and regulatory frameworks shaping the market. Utilizing a systematic literature review methodology, this study synthesizes findings from academic and institutional sources to explore cryptocurrency growth and global taxation policies, the research investigates the adoption metrics of major cryptocurrencies and the comparative taxation policies across various jurisdictions. Findings reveal a substantial increase in cryptocurrency adoption driven by institutional investments and technological innovations. However, taxation policies vary widely, impacting investor behavior and market dynamics. This research contributes to understanding the interplay between cryptocurrency growth and taxation, providing insights for investors and policymakers.
Fintech plays an instrumental role in advancing global ESG objectives, leveraging a more inclusive, transparent, and accountable financial system. Our paper explores the occurrence of dynamic linkages between Fintech and ESG across various dimensions, examining how the strength of their interconnectedness drives the energy transition towards clean technology. Using daily data from 31st May 2018 to 1st August 2024, we apply a time-varying parameter robust Granger causality method coupled with quantile technique to provide the first attempt in the literature on the dynamic causal patterns between the strength of Fintech-ESG connection and Cleantech energy transition risk (CETR). We find asymmetry in the connectedness across different quantiles, with Fintech sectors acting primarily as shock transmitters, while most ESG indexes are receivers. The 2022 Russia-Ukraine conflict reduces the connectedness between Fintech and ESG, with minimal effects on spillover direction. Our results show a heterogeneous response to shocks in developed markets, while developing ones tend to react more homogeneously. Additionally, we find strong evidence of a time-varying causal relationship between Fintech-ESG connectedness and CETR, with the conflict exacerbating asymmetry, especially at the lower quantile. Recent trends suggest a modest resurgence in this connection, signalling a re-emergence of the Fintech-ESG connection influence on CETR. The impact of extreme events tends to taper-off over time, suggesting that the prolonged conflict-driven market environment may have stabilized sufficiently to restore Fintech's role in promoting ESG initiatives, thereby supporting the ongoing transition to clean technology. • Fintech sectors except Distributed Ledger transmit shocks, while most ESG stocks are receivers. • Developed ESG markets heterogeneously respond to shocks, unlike developing ones. • The 2022 Russia-Ukraine military conflict reduces connectedness between Fintech and ESG. • Strength of Fintech-ESG connection impacts CETR heterogeneously across the distribution. • Time-varying causality between Fintech-ESG connectedness and CETR under different market conditions.
The global insurance sector continues to be hampered by legacy systems characterized by operational inefficiencies, asymmetric information, and excessive administrative overhead. This paper presents ChainCare, a decentralized insurance platform designed to overcome these limitations by leveraging blockchain technology. Built on the Ethereum public blockchain, ChainCare employs smart contracts written in Solidity to automate insurance policy creation, claims processing, and settlements while ensuring transparency and auditability. The system integrates a React.js-based user interface with blockchain-backed transactions to deliver a secure and user-centric experience. By recording all operations on a distributed ledger, the platform minimizes fraudulent activities, reduces manual intervention, and accelerates claim resolution. Experimental validation of the prototype demonstrates that ChainCare significantly reduces administrative complexity and enhances trust through immutable, verifiable transactions. The proposed architecture establishes a practical framework for decentralized insurance, offering a scalable and transparent alternative to traditional systems.
This study examines the relationship between market efficiency and digital financial innovation in the context of global financial transformation over the past decade, when fintech, cryptocurrency, and Decentralized Finance (DeFi) have significantly altered price formation and information dissemination mechanisms. The main issue raised is whether the Efficient Market Hypothesis (EMH) theory remains relevant in the face of digital market dynamics characterized by high volatility, speculative behavior, and regulatory uncertainty. The objective of this study is to assess the impact of digital innovation on information efficiency, price transparency, and the stability of modern financial markets. The study used the Systematic Literature Review (SLR) method, examining 15 scientific articles published between 2015 and 2025 from various academic databases. The findings indicate that digital technology increases access and speed of information distribution, but does not always result in consistently efficient markets. Crypto and DeFi markets have been shown to exhibit fluctuating efficiency due to price anomalies, information asymmetry, and weak regulation. Overall, the literature synthesis confirms that market efficiency in the digital era is dynamic and influenced by the interaction between technology, investor behavior, and governance quality. This study concludes that the EMH remains relevant as a basic framework, but needs reinterpretation to suit the complex and rapidly changing characteristics of digital markets.
M. Ganesan Alias Kanagaraj, K. Sathiyamurthi, K.K. Karthick, V. Vimalnath · 6 authors
The complexities and inefficiencies that are ever increasing in the payment of insurance claims usually lead to delays, frauds, and disputes, and thus shows the need to allow more transparency and trust to the process. The paper presents a new blockchain-based smart contract platform that automates and simplifies insurance claim settlements through the combination of non-mutable distributed ledger technology and self-executable digital contracts. The presented approach will guarantee transparency since all events associated with claims will be recorded in the blockchain, thereby serving auditable and tamper-proof information which can be accessed by all stakeholders. Smart contracts are coded to ensure that claim conditions are met, triggered automated compensation on meeting policy criteria and the removal of human interaction in the process of decision making, so fraudulent practices and operational expenses are reduced to a minimum. Moreover, this strategy builds customer trust by providing real-time information and decentralized management. The efficiency of the system is measured in terms of transaction speed, cost effectiveness and reduction of fraud and this proves to be much better than the traditional conventional models that are centralized. In this study, the author has identified the revolutionary nature of blockchain to bring change in the insurance industry, a situation where claims can be settled through secure, transparent, and efficient methods.
This article analyzes the prospects and limitations of implementing blockchain technologies in the insurance industry, with a particular focus on the Russian market. The relevance of the study is driven by the sector's conservatism, rising fraud, pressure from digitalization, and demand for transparency. Despite blockchain's potential, its widespread adoption faces barriers: regulatory uncertainty, high costs, and mistrust among market participants. Therefore, the authors identify and categorize the technological, regulatory, and organizational limitations to the large-scale use of distributed ledgers in insurance. Particular attention is paid to assessing the prospects for adapting blockchain technologies to the Russian insurance market, taking into account its specific characteristics.
Sharmila Mary Joseph, Baseera A, Mayank Sharma, Prajal Mishra · 6 authors
This study presents an innovative framework integrating machine learning algorithms to enhance the operational efficacy of blockchain-based decentralized autonomous organizations (DAOs). By leveraging reinforcement learning, deep Q-networks, natural language processing (NLP), and genetic algorithms, the framework addresses core challenges in governance automation, decision optimization, and adaptive resource management within DAOs. The proposed method demonstrates superior performance across critical metrics such as accuracy, scalability, convergence speed, and energy efficiency. Additionally, domain-specific visualizations, such as real-time Q-value convergence and NLP-enhanced proposal analysis, are introduced to ensure interpretability and transparency. This multidisciplinary approach not only overcomes inherent limitations in traditional DAO structures but also introduces a scalable, intelligent, and fair governance model capable of dynamic adaptation in decentralized environments.