This paper proposes a sociotechnical framework to address these issues by integrating fairness metrics, explainable AI (XAI), and game-theoretic models. We adapt statistical fairness criteria (demographic parity, equal opportunity) to audit bias, extend SHAP values to blockchain data for transparency in DeFi, and simulate stakeholder dynamics using agent-based models. Novel contributions include a governance-aware fairness metric that combines technical parity with stakeholder trust scores and a multi-layer agent model linking AI behavior to decentralized governance. Our findings reveal that DeFi systems exhibit narrower bias gaps than traditional systems but introduce new risks (e.g., collateral volatility), while profit-driven DAO governance often prioritizes short-term gains over systemic stability. This work advances interdisciplinary approaches to AI governance, emphasizing the need to reconcile technical robustness with social accountability.
This article examines the integration of blockchain technology and smart contracts within financial regulatory systems and their potential to transform traditional compliance frameworks. The distributed and immutable nature of blockchain presents unique opportunities for enhancing regulatory reporting, fraud detection, and compliance monitoring in financial institutions. Through analysis of implementation cases and theoretical frameworks, this article identifies key applications in automated reconciliation, real-time monitoring, and cross-border regulatory coordination. Despite promising benefits in transparency and automation, significant challenges persist in scalability, legacy system integration, and regulatory uncertainty. This article contributes to the growing body of literature on regulatory technology by providing a comprehensive examination of blockchain applications in financial oversight, offering insights for both regulatory bodies and financial institutions navigating this technological transition. The articles suggest that while blockchain implementation requires substantial infrastructure adaptation, its potential to create more efficient, transparent, and secure regulatory systems warrants continued exploration and development.
Paula Ungureanu, Francesca Bellesia, Carlotta Cochis
This study investigates an emblematic case of innovation failure in blockchains as to understand how turbulent episodes of innovation failure shape the socio-technical organization of digital ecosystems. The Decentralized Autonomous Organization ( The DAO ) was an alternative model of organizational governance based on the Ethereum blockchain which registered one of the biggest successes in crowdfunding history and fell victim to one of the biggest hacks of the crypto world. Our empirical qualitative study combines interviews, archival and social media data to develop a grounded theory on how innovation failure was framed and dealt with in the Ethereum ecosystem. Our findings highlight the key role of blaming processes following innovation failures in digital ecosystems. Building on blame theory, we theorize about the interplay between human and technological blaming, and document a process called multi-distributed blaming whereby actors circle between multiple blames to an ecosystem's human and technological components, with multi-level (i.e., organizational and technological) consequences for the ecosystem. By adopting a socio-technical perspective, our findings contribute to blame theories, to the literature on digital ecosystems and to the scant research on blockchain organization. • We study The DAO blockchain experiment as a case of failure in digital ecosystems • We show the interplay between organizational and technological ecosystems’ elements • We introduce a multi-distributed blaming process in complex digital ecosystems • We show how blaming processes shape the consequences of an innovation failure • We show the consequences for the ecosystem’s organizational and technological players
“Law is code” is pivotal for advancing the intelligent judiciary. This article proposes a business process modeling notation-large language model (BPMN-LLM), which transforms BPMN models of legal contracts (LCs) into smart contracts (SCs) using LLMs in a user-friendly and cost-effective manner.
“Değiştirilemez ve benzersiz varlıklar” şeklinde ifade edilen NFT’ler (Non-Fungible Token), kripto para teknolojisinin bir uzantısı olarak doğmuş olmasına rağmen kısa süre içerisinde sanat ve estetik konularıyla iç içe geçmiştir. Dijital sanatın bir göstergesi olan NFT’ler, sadece estetik ve etik açıdan değil, aynı zamanda orijinallik, koleksiyonerlik ve ticarileşme gibi pek çok açıdan incelenmeye değer bir konudur. Yapay zekâ destekli algoritmaların etken bir faktör olarak NFT’lerde yer alması, sanatçının rolünü birçok açıdan dönüştürmüştür. Bunun yanı sıra sanat eserlerinin mülkiyetinin dijitalleşmesi, eserden beklentilerin de değişmesine sebep olmuştur. Bu değişimde NFT’ler üzerinden sanatın ticarî bir meta hâline getirilmesinin büyük bir etkisi bulunmaktadır. Yapay zekâ desteğiyle üretilen sanat eserlerinin, yine yapay zekâ tarafından manipüle edilerek para piyasalarını kontrol altına alabilmesi pek çok spekülasyona yol açsa da Refik Anadol, Murat Pak, Selçuk Erdem, Cem Yılmaz gibi bazı öncü Türk NFT sanatçıları küresel ölçekte yeni bir sanat zemini oluşturmuştur. Bu çalışmada yapay zekâ ile desteklenen NFT’lerin sanat dünyasındaki yeri, Türk NFT sanatçıları örnekleminde değerlendirilecektir. Aynı zamanda sanatın doğuşundan kitlelere uzanan yolda yapay zekânın etkisi ve önemi ile yaratıcılık ve orijinallik kavramlarının nasıl değişime uğradığı tartışılacak, NFT’lerin sanatı yayma gücü ve potansiyeli irdelenirken, dijital teknolojilerin sanatçı ve sanatın alımlayıcısı arasındaki yeni ve doğrudan ilişkiyi nasıl dönüştürdüğü üzerinde de durulacaktır.
Javier Parra-Domínguez, Laura Sanz Martín, Germán López‐Pérez, José Luis Zafra Gómez
Purpose The purpose of this study is to explore the disruptive potential of blockchain technology in the field of accounting. By conducting a systematic review and bibliometric analysis, the research aims to identify key clusters and trends that illustrate how blockchain can transform traditional accounting practices. This includes improving transparency, enhancing data security, automating processes and integrating emerging technologies such as artificial intelligence. This study also seeks to highlight current research gaps, challenges in practical implementation and the future impact of blockchain on governance and financial systems. Design/methodology/approach This study uses two main methodologies: a systematic literature review and bibliometric analysis. The systematic review follows the PRISMA 2020 guidelines to identify and analyze relevant articles from Scopus, Web of Science and EBSCO databases, using specific search equations related to blockchain and accounting. A bibliometric analysis was conducted using VOSviewer to identify key clusters and trends within the collected literature. Clustering techniques, such as exploratory factor analysis, were applied to explore the relationships among documents, keywords and authors, providing insights into the evolution of blockchain’s impact on accounting practices. Findings The results of this study reveal four primary clusters in the intersection of blockchain and accounting: CryptoLedger Accounting Network, TransparentChain Trust Framework, IntelliLedger Accounting Tech and DigiGov Ledger Insights. These clusters highlight key areas where blockchain technology is transforming accounting practices, such as enhancing transparency and trust in supply chains, integrating artificial intelligence for accounting automation and improving data security. The bibliometric analysis also identified emerging trends, including the increasing relevance of smart contracts, the challenges of integrating blockchain with existing systems and the need for updated regulatory frameworks. Practical implications In this sense, this paper presents several theoretical and practical implications, as well as identifying possible limitations and gaps in current knowledge, providing new opportunities for the establishment of future lines of research, such as robust regulatory frameworks, privacy and security considerations, and the practical implementation of blockchain solutions in real-world accounting scenarios. Originality/value This study provides a unique contribution by synthesizing the disruptive impact of blockchain technology on accounting through a combination of systematic literature review and bibliometric analysis. By identifying four distinct research clusters, this paper offers fresh insights into how blockchain integrates with accounting practices, particularly in transparency, automation and security. It also highlights emerging challenges and research gaps, such as regulatory frameworks and practical implementation. The originality lies in the comprehensive exploration of blockchain’s multifaceted role in modernizing accounting, offering valuable guidance for both academics and practitioners navigating this evolving field.
The decentralized finance (DeFi) ecosystem continues to evolve, allowing crypto holders greater control over their assets. This research examines key aspects of token accessibility, liquidity provisioning, and holder distribution. The study focuses on evaluating whether holders can check their ranking and percentage ownership, the availability of the token on decentralized exchanges (DEXs), the feasibility of liquidity pool creation, and opportunities for holders to acquire at least 0.1% of the total supply. In present paper, Coredaovip token has been considered as example to evaluate the crypto holder accessibility, liquidity and participation in decentralized ecosystem.
Embedded finance represents a transformative shift in how financial services integrate within non-financial platforms, creating seamless user experiences that eliminate traditional friction points. This comprehensive article explores how companies have leveraged embedded payment infrastructures to create extensive ecosystems that transcend their original business models. The technical infrastructure powering these innovations—including API-first banking, regulatory technology, and microservices architecture—enables real-time processing at scale while maintaining security and compliance. The evolution toward Super Apps demonstrates how financial transactions can become invisible utilities within broader digital experiences, while artificial intelligence enhances these platforms through predictive analytics and conversational interfaces. Despite technical challenges related to data security, scalability, and cross-border complexity, emerging trends including decentralized finance integration, context-aware services, and embedded insurance promise continued innovation in this rapidly developing field
Purpose This study aims to examine the relation between the audit risk and the audit report lag (ARL), in the context of popularity of blockchain-based cryptocurrency used as a financial asset by the firms. Design/methodology/approach This study uses a quantitative research approach, using pooled ordinary least squares regression and quantile regression methodologies to analyse the impact of blockchain-based cryptocurrency (Bitcoin trading volume) on audit report lag (ARL). A sample of 84 country-year observations from 12 European countries, where crypto asset trading is legally allowed, is analysed for the years 2013–2019. Audit report lag data is sourced from the Audit Analytics database, while country-level control variables are obtained from the World Bank database. The robustness of the results is further tested to ensure consistency and reliability. Findings The findings indicate that this paper will observe an increase in the engagement of the firm’s stakeholders because of timely audited information. Policymakers will get a better understanding about how to use disruptive technology to reduce the adverse consequences related to ARL. Research limitations/implications The findings of this study will assist audit firms to find how to generate timely report, which will help their client firms to enhance trust among their stakeholders in their quality financial reports. In addition, the theoretical models supporting the findings will help the firms to understand when to adapt the recent technology and how their choice of adaptation of technology could assist their audit firms to produce timely reports. Originality/value The findings will help the audit firms to understand the significance of the use of blockchain technology to efficiently assess the main audit risks and how to produce quality audit reports on time.
Khoirul Hidayah, Muhammad In’am Esha, Dwi Hidayatul Firdaus, Ramadhita Ramadhita
The Non-Fungible Token (NFT) is one form of trade utilising crypto assets as a medium of exchange. This system has proven effective in assisting creators in protecting both their economic and moral rights. However, the existence of Regulation of the Minister of Finance No. 68/PMK.03/2022 concerning Value Added Tax and Income Tax on Cryptocurrency Trading does not adequately address the phenomenon of NFT trading. This raises an intriguing issue regarding the formulation of tax collection for NFTs as digital assets that can be traded and serve as a source of state revenue. This study employs a socio-legal approach with qualitative methods. Based on an analysis of legislation, the theory of justice, and tax collection theory, three alternative models for regulating income tax and VAT on NFTs in Indonesia are proposed. The first model suggests specific regulation in the form of a Minister of Finance Regulation. The second model recommends classifying NFT trading platforms as Permanent Establishments (PE). The third model advocates for the application of tax treaties to prevent double taxation. This study is expected to contribute to the development of NFT taxation regulations in Indonesia.
This comprehensive article explores the rapid advancement of financial technologies (FinTech), highlighting their transformative role in enhancing transaction efficiency and security across global financial markets. The integration of artificial intelligence and machine learning in financial services has revolutionized fraud detection, credit assessment, and customer service delivery while presenting new implementation challenges. As digital payment systems and banking platforms continue to evolve from early electronic transfers to sophisticated mobile applications and neobanks, they reshape traditional financial models and expand access to previously underserved populations. The interplay between emerging technologies like distributed ledger systems, cloud computing, and biometric authentication creates a dynamic ecosystem where established institutions and innovative startups both compete and collaborate. Regulatory frameworks worldwide adapt to balance innovation facilitation against consumer protection, while specialized compliance technologies address increasingly complex requirements. Despite cybersecurity threats including data breaches and ransomware attacks, advanced security measures provide essential protection for the digital financial landscape.
The banking industry is experiencing a swift transformation fueled by technological advancements, including artificial intelligence (AI), blockchain, and automation, which are redefining financial services. The rise of the metaverse offers banks new avenues to boost customer engagement, provide immersive financial experiences, and create innovative digital products. This paper delves into the effects of technological innovation on banking, focusing on how the metaverse can be integrated into banking business models. It looks at the advantages of virtual banking branches, decentralized finance (DeFi), and tailored financial services, while also tackling significant challenges like cybersecurity threats, regulatory issues, and obstacles to consumer adoption. By analyzing existing literature and industry trends, this study underscores the metaverse's potential to transform banking, while stressing the importance of strong security measures and regulatory frameworks. The findings indicate that banks need to embrace a hybrid strategy that balances innovation with compliance and risk management to effectively navigate the changing digital landscape.
Marko Štaka, Miroslav Stefanović, Darko Stefanović, Đorđe Pržulj · 5 authors
Information systems in the healthcare sector face significant challenges regarding the protection of user data. These systems process highly sensitive data, including medical and private information of patients. Unauthorized access and breaches of data security are among the most commonly identified issues in data protection. Inadequate security of information systems negatively impacts the integrity of healthcare systems and jeopardizes the safety of citizens who use these services. To address these problems, the implementation of smart contracts is proposed, which would regulate access rights to important data. Leveraging the potential of smart contracts can contribute to reducing security risks and enhancing system security. This paper discusses the technical, legal, and ethical issues related to the implementation of smart contracts in healthcare systems, along with their benefits and challenges.
Temitope Ezekiel Ajibola, Opeyemi Adeniran, Peter Taiwo
This study introduces SmartPattern, a novel machine learning-based framework to detect reentrancy attacks in smart contracts, a critical threat to blockchain security. Analyzing 40,000 smart contract, SmartPattern achieves 94% detection accuracy with Random Forest and Support Vector Classifier, outperforming Bidirectional Encoder Representations Transformers embeddings, which produced inconsistent accuracies of 84% and 78% Random Forest and Support Vector Classifier, respectively. Unlike traditional tools like Slither, which rely on static analysis and predefined heuristics, SmartPattern overcomes limitations related to dynamic invocation patterns and non-linear state changes. By leveraging machine learning models and targeted pattern recognition, SmartPattern effectively detects obfuscated attack patterns and generalizes to unseen vulnerabilities. This scalable, automated framework significantly enhances blockchain security by safeguarding billions of dollars in digital assets and promoting trust in decentralized ecosystems. The results demonstrate that SmartPattern is a viable alternative to state-of-the-art models, including those using Graph Convolutional Networks, and provides a comprehensive solution for fortifying smart contract ecosystems against reentrancy attacks.
This study explores the transformative potential of blockchain technology in revolutionizing cross-border payment systems. Traditional methods are hindered by inefficiencies such as high transaction fees, prolonged processing times, and opaque operations, which impede seamless global financial interactions. Blockchain, with its decentralized and immutable ledger, offers a secure and transparent alternative that can significantly streamline payment processes. This paper examines how blockchain can facilitate real-time settlements, eliminate intermediaries, and enhance data integrity, thereby reducing costs and improving efficiency. Further, it addresses the practical applications and regulatory challenges associated with integrating blockchain into existing payment infrastructures. Ultimately, this research aims to provide actionable insights for developing a more efficient, transparent, and cost-effective cross-border payment ecosystem.
It is quite challenging to properly address the issues of digital assets and online identities by conventional estate rules in the era of digital technologies. Rising social media platforms, cryptocurrencies, non-fungible tokens (NFTs), and other virtual assets have made digital legacy complex. Current research highlights the constraints of existing estate laws for the administration of digital assets after death and the legal obstacles resulting from digital platform contractual limitations. The key challenges identified are assets classification, protection of privacy rights, and enforcement of policies on a wider scale. By comparing the global legal approaches and evolving trends in digital inheritance, a comprehensive framework including digital assets into estate planning has been proposed. A balanced legal framework ensuring fair distribution, protecting heirs' rights and building trust in the digital economy is the solution.
Smart contracts on the blockchain play an important role in decentralised systems by automating and executing agreements without the need for intermediaries. As these contracts become integral to various domains, ensuring users’ understanding of their functioning is paramount. This article investigates the need for explanations in smart contracts, drawing inspiration from contract law principles and established practices in Explainable AI (XAI). It introduces key purposes—justification, clarification, compliance and consent to design explainability. Additionally, the study proposes a novel assessment framework informed by the Metacognitive Explanation-Based (MEB) theory to systematically evaluate surprise potential in smart contracts lacking explanations. We use surprise as a guiding factor to systematically identify areas requiring improvement in terms of justification, clarification, compliance and consent. To demonstrate the utility of the assessment approach, we evaluate two decentralised lending projects, uncovering potential surprises. One of the key observations is the lack of setting information, especially concerning compliance, consent and decision justification. This absence of information has heightened the potential for surprises. In the process of validating the explanation purposes, we implement techniques to improve the design of the assessed smart contracts. Further, the research explores the tradeoffs involved in integrating explanations, providing nuanced insights into economic implications such as increased deployment and execution costs. This work contributes to the broader comprehension of smart contract explainability requirements and lays out a theoretical foundation for a generic evaluation method. It aims to facilitate the development of more human-centric and comprehensible smart contracts.
Recent advancements in large language models (LLMs) have demonstrated their potential to significantly impact finance trading, particularly through sentiment analysis. The cryptocurrency market, known for its volatility and unpredictability, often renders price-based trading approaches inadequate. This necessitates the adoption of more sophisticated techniques such as market sentiment analysis, which can benefit from the insights provided by LLMs. This study introduces an innovative method that integrates sentiment analysis derived from five distinct LLMs with deep reinforcement learning to devise a cryptocurrency trading strategy. Recognizing that LLM outputs cannot be guaranteed to be infallibly accurate, which contributing to the LLM hallucinations, this paper details the implementation of a stringent outlier detection and removal process. By adopting a “Trust-The-Majority” strategy, the research aims to ensure that trading decisions are informed by reliable sentiment data. In addition, sentiment scores are traditionally timestamped to the publication of news or social media posts. To more accurately reflect the actual impact of such information on market sentiment, this study applies the Ebbinghaus Forgetting Curve to model the waning influence of information over time. This allows for a more nuanced understanding of how news affects market dynamics. The enhanced sentiment scores, in conjunction with traditional market data such as OHLCV (Open, High, Low, Close, Volume), are utilized by a deep reinforcement learning model to make trading decisions. Experimental results demonstrate that the proposed multi-LLM sentiment-driven framework improves trading performance in the fast-paced cryptocurrency market. The methodology outlined in this paper offers a solid foundation for incorporating real-time market sentiment analysis into financial applications.
Damiano Di Francesco Maesa, Francesco Donini, Paolo Mori, Laura Ricci
Distributed Ledger Technology can be a key component in improving the interoperability, security, and privacy of many application scenarios, including cyber-physical systems. Moreover, smart contracts integration could unlock novel capabilities and use cases impossible in a traditional system. However, this integration should not degrade the overall system scalability. This is why it is important to have sound tools and methodologies to properly evaluate the sustainability of smart contract based applications deployed on Distributed Ledgers. This is why, in this paper we present a simulation engine able to estimate the cost over time of a smart contracts based application. Our proposal leverages a parametrized simulation environment to track a system evolution for long periods of time depending and on the involved entities behaviour. To validate our proposal we have applied it to a novel mutable Non-Fungible-Tokens proposal and evaluated its sustainability in three different scenarios.
This chapter explores the transformative impact of AI and blockchain on the FinTech industry, highlighting their roles in enhancing efficiency, security, and customer experience. AI's ability to analyze vast datasets in real time enables personalized services, optimized risk management, and streamlined operations, while blockchain's secure, transparent ledger fosters trust and innovation. The integration of these technologies is reshaping sectors like banking, insurance, and investment management, promoting financial inclusion and economic growth. However, challenges such as data privacy, regulatory compliance, and job displacement require careful management. The chapter also offers recommendations for stakeholders to leverage AI and blockchain effectively, ensuring sustained growth and a more inclusive financial ecosystem.
The evolution of SME financing is being reshaped by disruptive technologies such as blockchain, artificial intelligence, big data, and the Internet of Things. These innovations enhance financial accessibility, streamline credit assessment, and enable decentralized finance solutions. However, challenges such as regulatory uncertainties, cybersecurity risks, and algorithmic biases persist. This research explores the transformative impact of these technologies, addressing both opportunities and risks while proposing policy recommendations to ensure secure, inclusive, and efficient SME financing in an increasingly digital economy.