This paper develops computational methods for optimizing revenue recognition in machine learning platforms operating on cloud computing infrastructure. We analyze how Artificial Intelligence as a Service (AIaaS) platforms leverage distributed computing architectures, containerization technologies (Docker, Kubernetes), and microservices patterns to deliver AI capabilities, creating complex revenue recognition challenges under IFRS 15. Our research employs algorithmic analysis to examine five critical technical challenges: (1) computational resource allocation tracking across multi-tenant cloud environments, (2) real-time transaction price determination using usage metering APIs and consumption-based billing algorithms, (3) automated revenue allocation across platform components using distributed ledger technologies, (4) temporal revenue recognition optimization through event-driven architectures and streaming data processing, and (5) network effect quantification using graph algorithms and data analytics.
The phenomenon of increasing public interest in investing in crypto assets, especially Bitcoin, has raised major questions about its feasibility and profitability compared to conventional investment instruments such as mutual funds. This study aims to compare the profitability and risk levels between Bitcoin as a cryptocurrency asset and mutual funds as traditional financial instruments. Although Bitcoin has gained increasing popularity as an alternative investment, there remains a lack of empirical research directly comparing its performance with mutual funds over an equivalent time horizon. Using a quantitative approach, this study analyzes historical monthly data from 2015 to 2024. Metrics such as cumulative return, average monthly return, CAGR, Sharpe Ratio, and maximum drawdown were employed to evaluate the performance of both instruments. Positioned within the existing literature on asset comparison, this study offers a novel empirical contribution by directly contrasting Bitcoin and mutual funds through risk-return analysis. The findings reveal that while Bitcoin offers significantly higher returns, it also carries much greater volatility and drawdown risk. These insights serve as a practical foundation for designing investment strategies aligned with different investor risk profiles. The research contributes to the body of knowledge in portfolio management and data-driven investment decision-making. Keywords: Bitcoin, mutual funds, risk-return, volatility, investment performance, portfolio management
This study aims to analyze the role of autonomous agent-based Information Systems in Accounting (ISA) in managing the decentralized accounting cycle using a socio-technical systems approach in the private sector. The background of this research lies in the increasing demand for speed, accuracy, and transparency in financial reporting within the competitive digital business ecosystem. This study adopts a qualitative method through in-depth interviews and document analysis, supported by thematic analysis for data interpretation. The findings reveal that autonomous agent-based ISA enhances transaction-processing efficiency, reduces recording errors, strengthens internal control, and provides real-time financial information for strategic decision-making. However, its effectiveness depends on the alignment between technological and social dimensions of organizations, including digital competence readiness, employee acceptance of automation, and role restructuring. This research concludes that agent-based accounting systems are not merely digital tools, but strategic infrastructures that shape long-term competitive advantage for private-sector firms
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.
A digital or virtual currency that is virtually impossible to counterfeit or double-spend is called cryptocurrency. It is protected by cryptography. The majority of cryptocurrencies are maintained on decentralized networks through the use of blockchain technology, which is a distributed ledger maintained by various computer networks. This study aims to determine the degree of investor awareness of cryptocurrencies, as well as the preferences of investors across age and income brackets. Additionally, it will examine investor behaviour about crypto currencies and the awareness of various cryptocurrencies.
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.
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 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.
YASH RAJPUT, Chaitanya Kale -, Santosh Kumar -, Asam Bhanu Prakash - · 5 authors
Know Your Customer (KYC) verification is an essential regulatory procedure in financial services to prevent fraud, money laundering and other financial crimes. Conventional approaches are centralized, redundant across institutions, and prone to data breaches. This paper presents a decentralized framework that combines blockchain smart contracts and InterPlanetary File System (IPFS) for immutably recording KYC document fingerprints while storing actual documents off-chain. We describe the system architecture, implementation choices, security and privacy considerations, and evaluation metrics. The paper includes a comparison between traditional and blockchainenabled KYC systems and discusses future directions such as Decentralized Identifiers (DIDs) and Zero-Knowledge Proofs(ZKPs).
Abstract : The purpose of this paper is to examine the issues regarding accounting for cryptocurrency. An in-depth study of accounting standards is performed to scrutinise their appropriateness for the accounting of cryptocurrency. This research paper focuses on significant accounting aspects which are relevant for crypto accounting. The title of this paper is pointing toward the issues related to accounting for cryptocurrency which requires clarification. This paper will help in understanding the characteristics of cryptocurrency having relevance to business for accounting for them correctly as cryptocurrency has characteristics of currency as well as assets and can act as inventory for some businesses. This paper will analyse the accounting standards and accounting of cryptocurrencies in the financial statement of a company. This paper will also examine the requirement of making amendments to existing accounting standards or having a new accounting standard for the financial reporting of cryptocurrency. The qualitative approach is used in this research. Secondary data is used for this study as previous literature regarding the topic is used for collecting the data through published resources including journals and books. This study finds that cryptocurrency cannot be considered as a currency because of some of its characteristics but can be considered as inventory or intangible assets on the basis of the business model as it has a quasi-currency and quasi-asset nature. The accounting for cryptocurrency needs stand-alone standards to simplify its reporting in the books of accounts to compare financial statements and to maintain consistency in the financial reporting of cryptocurrency. This research area has a lot of potential regarding clarification and guidance of experts for avoiding future issues regarding the accounting of cryptocurrency.
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Innovations and Analysis in Business and Education
This comprehensive review examines the evolutionary trajectory of financial information systems from the 1670s to the present day, analyzing how technological innovations have fundamentally transformed financial reporting, auditing practices, and information accessibility. Through a bibliometric and conceptual analysis of seminal literature, this study identifies key technological inflection points including the emergence of structured bookkeeping systems, the institutionalization of financial publicity through the 1867 law, the development of sophisticated financial communication tools, and the recent integration of blockchain technology and data analysis capabilities. The review demonstrates that each technological wave has progressively enhanced data accuracy, real-time reporting capabilities, and audit efficiency while simultaneously introducing new challenges related to data security, regulatory compliance, and technological adoption barriers. Contemporary developments in distributed ledger technology and advanced analytics represent a paradigm shift toward autonomous financial reporting systems with unprecedented transparency and verification capabilities. The findings suggest that future financial information systems will be characterized by increased automation, enhanced predictive analytics, and seamless integration of blockchain-based audit trails. This evolution has profound implications for accounting professionals, regulatory frameworks, and corporate governance structures, necessitating adaptive strategies for stakeholder education and regulatory modernization.
Xiang, Yuexin, Yang Lei, Yuanzhe Zhang, Qin Wang · 7 authors
Stablecoins such as USDT and USDC aspire to peg stability by coupling issuance controls with reserve attestations. In practice, however, transparency remains fragmented across heterogeneous data sources, with key evidence about circulation, reserves, and disclosure dispersed across records that are difficult to connect and interpret jointly. We introduce a large language model (LLM)-based automated framework for bridging cross-domain transparency in stablecoins by aligning issuer disclosures with observable circulation evidence. First, we propose an integrative framework using LLMs to parse documents, extract salient financial indicators, and semantically align reported statements with corresponding market and issuance metrics. Second, we integrate multi-chain issuance records and disclosure documents within a model context protocol (MCP) framework that standardizes LLM access to both quantitative market data and qualitative disclosure narratives. This framework enables unified retrieval and contextual alignment across heterogeneous stablecoin information sources and facilitates consistent analysis. Third, we demonstrate the capability of LLMs to operate across heterogeneous data domains in blockchain analytics, quantifying discrepancies between reported and observed circulation and examining their implications for transparency and price dynamics. Our findings reveal systematic gaps between disclosed and verifiable data, showing that LLM-assisted analysis enhances cross-domain transparency and supports automated, data-driven auditing in decentralized finance (DeFi).
In the context of economic globalization and rapid internet development, emerging digital technologies such as cloud computing, big data, and AI are revolutionizing industry production and sales. Smart Contracts, particularly empowered by blockchain advancements, present promising prospects. However, traditional contracts remain dominant in economic activities, especially in China’s vast SME market, where risks of real world transaction instability hinder smart contract adoption. Technical vulnerabilities and ecological security issues in smart contract platforms pose challenges in translating legal language into code. Despite progress in natural language processing, translating legal documents accurately remains difficult, burdening judges and programmers with time costs. Therefore, research on smart contract architecture and legal applications, along with practical solutions, is imperative for both theoretical and practical advancements.
This study examines the emerging convergence of triple-entry accounting, blockchain technology, and machine learning as a transformative framework for enhancing financial transparency. Using a bibliometric analysis of Scopus-indexed publications from 2000 to 2025, the research identifies key intellectual structures, thematic clusters, and temporal trends that shape this field. The results show that blockchain serves as the foundational infrastructure enabling immutable, verifiable accounting records, while machine learning functions as an analytical layer that strengthens anomaly detection, continuous auditing, and fraud prevention. Triple-entry accounting is found to be evolving from a conceptual innovation into a practical accounting architecture supported by cryptographic verification and distributed ledger systems. The study highlights significant implications for auditors, regulators, and organizations seeking to modernize financial reporting through automation and secure digital ecosystems. Although promising, the research also notes limitations related to data scope, conceptual depth, and the need for empirical validation. Overall, the findings underscore the potential of technologically integrated accounting systems to redefine trust, accountability, and transparency in modern financial environments.
A blockchain-and-smart-contracts architecture, which is suggested in the present research, can make public administration become more transparent, efficient, and trustworthy. The old-fashioned integrated systems of administration have the disadvantage of tampering with data, slow auditing and lack of trust of the population. To achieve these problems we develop a multi-layered solution that consists of: a user-facing application layer; a governance-rule automation layer driven by smart contracts; a Proof-of-Authority consensus layer that is fast with permissioned agreement; and a storage layer that integrates off-chain storage with immutable distributed ledger. To support the performance assessment, we establish mathematical models that are used to validate transactions, latency, cost, and transparency. The framework runs on a decentralized Hyperledger Fabric network with permissioned validator nodes and is tested on a real-world data sample of approximately 8, 000 government procurement records. Our experiments demonstrate significant improvements over conventional ERP-based systems: 2.8x increase in throughput, 65 percent decrease in average latency, an increase in a transparency index by 38 percent, 22 percent better data integrity, as much as 35 percent better fraud-detection effectiveness, and reduced operating cost per transaction by 39 percent. Through the introduction of read-only nodes, tamper-proof record and real-time audits, the suggested infrastructure enhances accountability and exemplifies how the blockchain-enabled governance can make the processes of the public sector more rapid, more secure, and people-focused.
Purpose –this paper aims to examine the impact of the integration between Extensible Business Reporting Language (XBRL) and Smart Contracts, which represent the second generation of the decentralized ledger Blockchain, on the transition from continuous auditing to Real-time Auditing. Design/methodology/approach – Using Exploratory Study , this study examines the impact of the integration between XBRLand Smart Contracts on the transformation from continuous Auditing to Real-time Auditing. Findings – This paper finds that the XBRL- Smart Contracts is a good way to activate real-time Auditing because of the characteristics of XBRL and Smart contracts based on blockchain that can support real-time Auditing, including transparency, privacy, decentralization, and pre-validation of operations at the same time as they occur with no possibility of modification or fraud. Therefore, Smart Contracts is not a substitute for XBRL, as the Blockchain is a ledger through which transactions can be conducted, and XBRL is the standard that can standardize the terms and standards for the items that are exchanged in accounting in those transactions, which means that XBRL supports Smart contracts based on blockchain in transparency and trust in transactions. There for, this paper finds that the XBRL- Smart contracts based on blockchain integration affects significatively to transfer from continuous auditing to real time auditing. Originality/value – This paper contributes to the literature on Provide a proposed A Prospective framework for the integration between XBRL and Smart Contract to transfer from continuous Auditing to Real time Auditing.
Decentralized finance (DeFi) lending platforms have rapidly evolved within financial markets, with stablecoins playing a pivotal role in these ecosystems by providing price stability and enhancing capital efficiency. However, DeFi lending platforms still face challenges including market volatility, smart contract security, regulatory uncertainty, and liquidity constraints. This paper analyzes the function of stablecoins within DeFi lending platforms, explores their advantages and challenges, and forecasts future development trends. The article first introduces the fundamental concepts and classifications of stablecoins, then analyzes their advantages and challenges within lending markets, and finally looks ahead to innovations and future developments for stablecoins. Through this analysis, the paper provides in-depth insights for researching stablecoin applications in DeFi lending.
We explore the role of auditor reputation in driving the value of smart contract audits (SCAs) within the decentralized finance (DeFi) ecosystem. Given the lack of regulatory oversight and the risk of cybersecurity breaches against the protocols comprising the DeFi ecosystem, a marketplace has emerged for voluntary on-demand assurance to identify vulnerabilities in smart contracts’ coded logic. After documenting that market participants value SCAs and exploring the protocol attributes associated with the demand for smart contract audits, we show that auditor reputation can be established through both advertising (i.e., engagement on Twitter) and the delivery of a high-quality audit, which significantly shape the extent to which an SCA is valued. Additional analyses suggest that the value of an SCA is maximized when both high advertising and high audit quality are present, highlighting the complementary role of these two factors in enhancing auditor reputation. Furthermore, we find that events conceivably damaging the reputation of the auditor (i.e., breaches of protocols recently audited) generate a negative spillover to the auditor’s other recent clients. Overall, our study provides novel insights about the role of auditor reputation in emerging audit markets. This paper was accepted by Suraj Srinivasan, accounting. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.02245 .
With the rapid digitalization of financial services-spanning mobile wallets, peer-to-peer lending, central bank digital currencies (CBDCs), and decentralized finance (DeFi)-security architectures must evolve to counter diverse and emerging threats. Building on our earlier FinTechSec++ design for FinTechs and CBDCs, this paper reconceives the framework as a [Simplified] foundational platform for wider financial ecosystems. The framework introduces: (i) modular cryptographic plugins tailored to domain-specific data, (ii) a policy orchestration engine for reconciling multi-jurisdictional rules, (iii) audit logs optimized for external analytics tools, and (iv) automated retraining pipelines for anomaly detection. [Simplified long sentence] Benchmarks on three prototypes (Micro Payment App, CBDC Sandbox, and DeFi DEX) demonstrate threat detection rates of 94-97%, encryption throughput gains of 1.7x-1.9x, and policy enforcement latencies below 60 ms. These findings establish FinTechSec++ as a practical foundation for future financial data security solutions.
The recent blockchain policy pronouncement in Nigeria gave rise to examine the effect on digital currency market performance. Knowing that policy statements played a dynamic role on market performances, and for the fact that digital currency is link to market volatility, this work analyzed the impact of Nigerian blockchain policy on digital currency market performance during the short-term periods. Based on the exigencies, the research covered a period of 23 weeks using a-weekly data between May 3, 2023 and October 4, 2023. The study employed selected top-five digital currencies including Bitcoin, Ethereum, Tether, BNB, and XRP of their market performances extracted from crypto database. The generalized autoregressive conditional heteroskedasticity (GARCH) least squares analytical tool was applied to ascertain how Bitcoin, Ethereum, Tether, BNB, and XRP digital currencies market performance responded to Nigerian blockchain policy in the short-term. The findings showed that Nigerian blockchain policy impacted negatively on Bitcoin, XRP, and BNB market performance in the short-term. However, Nigerian blockchain policy impacted positively on Tether, and Ethereum market performance in the short-term. The research further revealed Ethereum, and BNB digital currencies constituted significant variables of study. Finally, Nigerian blockchain policymakers were recommended to revised and address the diverse impacts on digital currencies with tailored regulations to enhance investors protection, and support the positive trends for a balance-support of the digital currency market.