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Journal articles on the topic 'Automated monitoring of financial transactions'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Lyeonov, S., O. Kuzmenko, V. Koibichuk, and O. Kushnerov. "DEVELOPMENT OF A BUSINESS PROCESS MODEL FOR AUTOMATED MONITORING OF FINANCIAL OPERATIONS BY THE BANK TO COUNTER LEGALIZATION OF CRIMINAL INCOME." Vìsnik Sumsʹkogo deržavnogo unìversitetu 2021, no. 1 (2021): 9–16. http://dx.doi.org/10.21272/1817-9215.2021.1-1.

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The general architecture of the automated information system of financial monitoring consisting of 4 levels is developed in the article: internal financial monitoring of economic agents (level 1), bank financial monitoring (Client-bank - level 2), state financial monitoring ( level 3), law enforcement and intelligence organs (level 4). The model was developed using the Bizagi Studio software product and modern BPMN 2.0 notation for automated monitoring of the business process of financial transactions through the "Client-Bank" system, which reveals the purpose and subject of the study. Relevan

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Lyeonov, S., H. Yarovenko, V. Koibichuk, A. Boyko, and Yu Kravchyk. "CREATION OF USERS’ SCREEN FORMS OF THE FINANCIAL MONITORING AUTOMATED INFORMATION SYSTEM FOR ECONOMIC DEVELOPMENT AND ECONOMIC GROWTH." Financial and credit activity problems of theory and practice 6, no. 41 (2022): 212–22. http://dx.doi.org/10.18371/fcaptp.v6i41.251441.

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Abstract. The processes of intellectualization and informatization of society have necessitated the development and application of screen forms of automated information systems in various fields by the subjects of the national economy for sustainable growth and economic development. The article is devoted to the development of screen forms, which are designed to organize interaction between users of automated financial monitoring systems and relevant modules for verifying financial transactions, entering regulatory information, working with variable-intermediate and variable effective, serve a

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Leonov, Serhiy, Hanna Yarovenko, Anton Boiko, and Tetiana Dotsenko. "Prototyping of information system for monitoring banking transactions related to money laundering." SHS Web of Conferences 65 (2019): 04013. http://dx.doi.org/10.1051/shsconf/20196504013.

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The article deals with the prototyping of an information system for intrabank monitoring of transactions related to money laundering. It has been proven that the automation of financial monitoring system would increase the bank’s efficiency due to examining all bank transactions without exception, leveling the human factor, maximizing the speed of identifying suspicious transactions, which will provide the bank management with the possibility to reduce reputational risk and minimize losses related to paying penalties imposed by regulatory agencies. It has been established that the prototype of

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Riazanova, Nataliia. "ENSURING FINANCIAL AND ECONOMIC SECURITY IN THE CONDITIONS OF SHADOW BANKING." Proceedings of Scientific Works of Cherkasy State Technological University Series Economic Sciences, no. 61 (June 28, 2021): 65–74. http://dx.doi.org/10.24025/2306-4420.61.2021.234596.

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A scientific approach to financial and economic security based on the use of digital financial monitoring technologies in the growth of financial operations of shadow banking, which allows in the transition to a digital economy to reduce threats to financial and economic security by reducing the possibility of anonymous capital management using impersonal electronic transactions , including remote cross-border management of financial assets in offshore areas and low-tax jurisdictions that hide real participants and beneficiaries of financial transactions from state control. It is substantiated

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D Priyadarshana, T Ramachandra Rao, and M Sambasiva Rao. "AI and blockchain technology for secure and transparent financial transactions." International Journal of Science and Research Archive 13, no. 1 (2024): 2013–19. http://dx.doi.org/10.30574/ijsra.2024.13.1.1845.

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The integration of Artificial Intelligence (AI) and blockchain technology presents a transformative approach to enhancing the security and transparency of financial transactions. Blockchain’s decentralized and immutable ledger system ensures that transaction records are tamper-proof and transparent, significantly reducing the risk of fraud and errors. AI, with its advanced data analytics and machine learning capabilities, further augments this ecosystem by providing real-time monitoring, predictive analytics, and automated decision-making processes. Together, these technologies enable more eff

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Rakesh Kumar Jha. "AI-driven transformation in general ledger systems: A technical deep dive." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 2363–71. https://doi.org/10.30574/wjaets.2025.15.3.1132.

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Integrating Artificial Intelligence into General Ledger (GL) systems marks a revolutionary transformation in financial operations, particularly within the insurance sector. This technological advancement enables real-time transaction processing, automated reconciliation, and enhanced anomaly detection capabilities. Implementing AI-driven systems has significantly improved operational efficiency, reduced manual intervention, and strengthened regulatory compliance. Through sophisticated machine learning pipelines, advanced data processing architectures, and intelligent automation, these systems

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Wild, Katherine, Jennifer Marcoe, Nicole Sharma, et al. "Aging and Financial Capacity: Cognitive Correlates of an Early Indicator of Functional Decline." Innovation in Aging 4, Supplement_1 (2020): 467–68. http://dx.doi.org/10.1093/geroni/igaa057.1514.

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Abstract Financial capacity describes the ability to make and carry out sound financial decisions sufficient to meet an individual’s needs for health and well-being. Impairments in financial capacity have been shown to be one of the earliest functional changes in patients with mild cognitive impairment (MCI), the precursor to Alzheimer’s disease and related dementias. Recent developments using online automated monitoring of financial transactions promise a new way to identify the earliest signs of cognitive decline. We examine the feasibility of using secure online technology to link ongoing f

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Vemulapalli, Vamsi Krishna. "Revolutionizing Bookkeeping: Retrieval-Augmented AI Agents for Modern Accounting." European Journal of Computer Science and Information Technology 13, no. 31 (2025): 36–48. https://doi.org/10.37745/ejcsit.2013/vol13n313648.

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Retrieval-augmented generation (RAG) technology represents a transformative advancement in accounting automation, addressing longstanding challenges in financial data processing. This article explores how platform-agnostic RAG agents revolutionize bookkeeping workflows through enhanced semantic understanding of transactions and documents. Traditional accounting systems rely on rigid rule-based categorization that struggles with ambiguous vendor descriptions, cross-category transactions, and varied document formats. In contrast, RAG-powered systems leverage vector databases, sophisticated docum

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Sai Krishna Gurram. "Revolutionizing Financial Infrastructure: The Convergence of Blockchain and Cloud in Next-Generation Payment Networks." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 607–18. https://doi.org/10.32996/jcsts.2025.7.4.71.

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The convergence of blockchain technology and cloud computing has fundamentally transformed traditional payment networks, establishing new paradigms in financial infrastructure. This transformation encompasses enhanced security frameworks, automated smart contract implementations, and sophisticated scaling mechanisms that have revolutionized transaction processing across global financial systems. The integration of these technologies has resulted in dramatic improvements in operational efficiency, cost reduction, and security enhancement while maintaining robust regulatory compliance. Through d

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Balanova, Maria V., and Lyubov V. Gusarova. "NEW DIRECTIONS FOR THE DEVELOPMENT OF AUTOMATED TOOLS IN THE SYSTEM OF INTERNAL STATE FINANCIAL CONTROL." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 5/4, no. 137 (2023): 77–83. http://dx.doi.org/10.36871/ek.up.p.r.2023.05.04.010.

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The article is devoted to the development of methods of internal state financial control based on transactional monitoring of operations of participants in the treasury payment system. In 2021, the transition to treasury servicing of the budgets of the budget system of the Russian Federation and the introduction of a treasury payments system were implemented, which led to a modification of the functionality of the Federal Treasury. The status of the Federal Treasury as the chief cashier of budgetary funds was supplemented by the status of a quasi-bank of the budget of the Russian Federation, a

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Nwangele, Chigozie Regina, Ademola Adewuyi, Omoniyi Onifade, and Ayodeji Ajuwon. "AI-Driven Financial Automation Models: Enhancing Credit Underwriting and Payment Systems in SMEs." International Journal of Social Science Exceptional Research 1, no. 2 (2022): 131–42. https://doi.org/10.54660/ijsser.2022.1.2.131-142.

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Small and Medium-sized Enterprises (SMEs) are critical drivers of economic growth and job creation globally but often face significant barriers in accessing timely credit and efficient payment systems. Traditional credit underwriting processes are typically manual, time-consuming, and reliant on limited financial data, resulting in inefficiencies, higher default risks, and exclusion of many SMEs from formal financial services. Similarly, SME payment systems encounter challenges such as transaction delays, fraud risks, and cumbersome reconciliation processes, which hinder smooth cash flow manag

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Vegesna, Rohith Varma. "Automated Reporting Software for Fuel Usage and Dispenser Activity." International Journal of Multidisciplinary Research and Growth Evaluation. 4, no. 5 (2023): 1132–34. https://doi.org/10.54660/.ijmrge.2023.4.5.1132-1134.

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Fuel station operators require accurate and efficient reporting mechanisms to track fuel usage and dispenser activity in real time. The traditional manual reconciliation process is not only prone to human error but also introduces inefficiencies that lead to financial discrepancies, regulatory non-compliance, and operational delays. These challenges make automation a necessity for modern fuel management systems. This paper presents a software-driven approach to automating fuel usage reconciliation by leveraging Automated Tank Gauge (ATG) systems and dispenser transaction data. The proposed sys

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Pradeepkumar Palanisamy. "Large-Scale Financial Automation: Lessons from Enterprise-Level Stock Plan Testing." Journal of Computer Science and Technology Studies 7, no. 2 (2025): 585–90. https://doi.org/10.32996/jcsts.2025.7.2.62.

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The rapid evolution of financial technology has transformed stock trading and equity compensation platforms, necessitating sophisticated automation frameworks for managing complex transactions. This document presents insights from implementing an AI-enhanced automation framework for stock plan services, focusing on transaction validation, reconciliation testing, and regulatory compliance. The implementation demonstrates significant improvements in system reliability, error reduction, and operational efficiency while maintaining strict regulatory compliance across global markets. The framework

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Adekunle, Bolaji Iyanu, Ezinne C. Chukwuma-Eke, Emmanuel Damilare Balogun, and Kolade Olusola Ogunsola. "Optimizing Internal Control Systems through Blockchain-Based Financial Reporting: Opportunities and Risks." International Journal of Management and Organizational Research 3, no. 1 (2024): 213–22. https://doi.org/10.54660/ijmor.2024.3.1.213-222.

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The integration of blockchain technology into financial reporting systems has the potential to revolutionize internal control processes and risk management frameworks within organizations. This explores the opportunities and risks associated with optimizing internal control systems through blockchain-based financial reporting. Blockchain offers a decentralized, transparent, and immutable ledger that ensures the accuracy, security, and traceability of financial transactions. These features provide a unique opportunity to enhance internal controls by reducing fraud, errors, and operational ineff

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Mrs., Ashwini J. Shinde. "Artificial Intelligence and Machine Learning: Pioneering Change in Banking." International Journal of Advance and Applied Research S6, no. 22 (2025): 436–43. https://doi.org/10.5281/zenodo.15502042.

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<em>Financial institutions are organizations that facilitate the flow of money within the economy by providing various financial services. They play a crucial role in managing funds, allowing individuals and businesses in financial transactions. Financial institutions provides security to the personal and financial information of clients. Detects the fraudulent activities that could results in significant loss. Financial institutes have ability to protect customer’s assets which ensures the confidence of the customers. It contributing to the overall stability of the financial system. Fin

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Oleh, Kolodiziev, Mints Aleksey, Sidelov Pavlo, Pleskun Inna, and Lozynska Olha. "AUTOMATIC MACHINE LEARNING ALGORITHMS FOR FRAUD DETECTION IN DIGITAL PAYMENT SYSTEMS." Eastern-European Journal of Enterprise Technologies 5, no. 9 (107) (2020): 14–26. https://doi.org/10.15587/1729-4061.2020.212830.

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Data on global financial statistics demonstrate that total losses from fraudulent transactions around the world are constantly growing. The issue of payment fraud will be exacerbated by the digitalization of economic relations, in particular the introduction by banks of the concept of "Bank-as-a-Service", which will increase the burden on payment services. The aim of this study is to synthesize effective models for detecting fraud in digital payment systems using automated machine learning and Big Data analysis algorithms. Approaches to expanding the information base to detect fraudu

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Intisari Haryanti, Ita Purnama, Feni Aryani, Wulan Arlin, and Naurah Islami Pasha. "Level Up Bisnis Tahu & Tempe: Optimalisasi Usaha dengan Aplikasi Credibook." Jejak digital: Jurnal Ilmiah Multidisiplin 1, no. 4b (2025): 1686–93. https://doi.org/10.63822/aap8v285.

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Training on the use of digital technology based on the Credibook application was carried out to improve the financial management capacity of Micro, Small, and Medium Enterprises (MSMEs) tofu and tempeh factories UD. Sumber Hidup in Bima City. The main problem faced is the absence of an adequate bookkeeping system, which has an impact on the unclear cash flow, business planning, and access to formal financing. The training aims to provide a comprehensive understanding of how to utilize the main features of the application such as transaction recording, stock management, monitoring receivables a

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Karri, Vidya Sagar. "Real-Time Compliance Monitoring: Transforming Audit Processes Through MuleSoft and Salesforce Integration." European Journal of Computer Science and Information Technology 13, no. 49 (2025): 44–56. https://doi.org/10.37745/ejcsit.2013/vol13n494456.

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This article explores the evolution of financial auditing through the integration of MuleSoft and Salesforce Data Cloud technologies. Traditional audit processes operate as periodic, resource-intensive assessments that create significant blind spots between review cycles, leaving organizations vulnerable to undetected compliance issues. By implementing a continuous compliance monitoring framework, enterprises can enhance their risk management capabilities, achieve operational efficiencies, and gain a strategic advantage. The technological architecture combines MuleSoft's API-led connectivity f

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Gozman, Daniel, and Wendy Currie. "The Role of Investment Management Systems in Regulatory Compliance: A Post-Financial Crisis Study of Displacement Mechanisms." Journal of Information Technology 29, no. 1 (2014): 44–58. http://dx.doi.org/10.1057/jit.2013.16.

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The financial crisis of 2007-2009 and the resultant pressures exerted on policymakers to prevent future crises have precipitated coordinated regulatory responses globally. A key focus of the new wave of regulation is to ensure the removal of practices now deemed problematic with new controls for conducting transactions and maintaining holdings. There is increasing pressure on organizations to retire manual processes and adopt core systems, such as Investment Management Systems (IMS). These systems facilitate trading and ensure transactions are compliant by transcribing regulatory requirements

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Tiwari, Shivam. "Enhancing Financial Crime Detection through Data Science-Driven Transaction Monitoring: A Comprehensive Framework for Modern Financial Institutions." International Journal of Computing and Engineering 7, no. 13 (2025): 53–63. https://doi.org/10.47941/ijce.3001.

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Financial institutions face mounting challenges in detecting money laundering, terrorist financing, and fraudulent activities within increasingly complex global payment ecosystems. Traditional transaction monitoring systems rely heavily on static rule-based approaches that generate excessive false-positive alerts while failing to adapt to evolving criminal methodologies. The integration of advanced data science techniques, including machine learning algorithms, behavioral profiling, and network analytics, offers transformative potential for enhancing detection capabilities while improving oper

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Utkina, Maryna. "DIGITAL IDENTIFICATION AND FINANCIAL MONITORING: NEW TECHNOLOGIES IN THE FIGHT AGAINST CRIME." Scientific Journal of Polonia University 58, no. 3 (2023): 303–8. http://dx.doi.org/10.23856/5842.

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The purpose of the research is to explore the role of emerging technologies in combating criminal activities, particularly in digital identification and financial monitoring. The article aims to highlight how these new technologies can enhance the effectiveness of law enforcement agencies and financial institutions in detecting and preventing crime. Methods. The methodological basis of the research was a set of methods of scientific knowledge. In particular, the phenomenological method allowed the author to analyse national, international, and foreign law legal sources. The analytical method w

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Bykovets, Anton. "Use of advanced technologies in financial monitoring." Economic Analysis, no. 34(3) (2024): 238–45. https://doi.org/10.35774/econa2024.03.238.

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Introduction. The modern financial sector is on the verge of significant transformations due to the integration of advanced technologies, such as artificial intelligence (AI), blockchain, and big data. These innovations not only enhance the efficiency of financial processes but also open new horizons for risk monitoring and management. The systematic and widespread adoption of these technologies each year reshapes traditional approaches to financial monitoring and strengthens protection against financial crimes. AI is actively used to automate the analysis of large datasets, detect fraud, and

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Belyakov, S. L., and S. М. Karpov. "IDENTIFY OF FRAUDULENT FINANCIAL OPERATIONS USING THE MACHINE LEARNING ALGORITHM." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 188 (2020): 23–31. http://dx.doi.org/10.14489/vkit.2020.02.pp.023-031.

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Current work is devoted to the problem of automatic detection of fraudulent financial transactions. The article describes the causes of fraudulent transactions their typical attributes, as well as the basic principle of detection. The concepts of fraudulent and honest transactions are defined. Examples of algorithms for determining suspicious financial transactions in antifraud systems are given. Modern approaches to monitoring and detecting cases of fraud in remote banking systems are considered. The positive and negative aspects of each approach are described. Particular attention is paid to

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Vankudoth, Suman, Vamshi Teega, Meera Alphy Dr., and Shirisha K. "EXPENSE TRACKER." Recent Trends in Cloud Computing and Web Engineering 6, no. 3 (2024): 22–28. https://doi.org/10.5281/zenodo.13304555.

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<em>The abstract proposes the development of an Expense Tracker to address the challenges of managing expenses in a rapidly changing economic environment. As financial landscapes evolve, individuals encounter increasing complexity in tracking and managing their expenditures. The proposed system leverages advanced technologies such as machine learning, artificial intelligence, and data analytics to provide a sophisticated, user- centric platform for monitoring, analyzing, and optimizing personal spending habits. One of the core features of the Expense Tracker is real-time transaction tracking.

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Halima Oluwabunmi Bello, Courage Idemudia, and Toluwalase Vanessa Iyelolu. "Integrating machine learning and blockchain: Conceptual frameworks for real-time fraud detection and prevention." World Journal of Advanced Research and Reviews 23, no. 1 (2024): 056–68. http://dx.doi.org/10.30574/wjarr.2024.23.1.1985.

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Integrating machine learning (ML) and blockchain technologies presents a groundbreaking approach to real-time fraud detection and prevention, addressing the growing complexity and sophistication of financial fraud schemes. This integration leverages the strengths of both technologies: the predictive power of ML algorithms and the transparency, security, and immutability of blockchain. Machine learning algorithms are proficient at analyzing large datasets, detecting patterns, and identifying anomalies that signify potential fraud. By employing supervised learning models such as logistic regress

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Halima, Oluwabunmi Bello, Idemudia Courage, and Vanessa Iyelolu Toluwalase. "Integrating machine learning and blockchain: Conceptual frameworks for real-time fraud detection and prevention." World Journal of Advanced Research and Reviews 23, no. 1 (2024): 056–68. https://doi.org/10.5281/zenodo.14777016.

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Integrating machine learning (ML) and blockchain technologies presents a groundbreaking approach to real-time fraud detection and prevention, addressing the growing complexity and sophistication of financial fraud schemes. This integration leverages the strengths of both technologies: the predictive power of ML algorithms and the transparency, security, and immutability of blockchain. Machine learning algorithms are proficient at analyzing large datasets, detecting patterns, and identifying anomalies that signify potential fraud. By employing supervised learning models such as logistic regress

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Jolaiya, Olatubosun Felix. "Effect of Electronic Fraud on the Financial Performance of Banks in Nigeria." Asian Journal of Economics, Business and Accounting 24, no. 4 (2024): 80–92. http://dx.doi.org/10.9734/ajeba/2024/v24i41266.

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The study investigated the effect of electronic fraud on the financial performance of banks in Nigeria. The specific objectives were to investigate the effect of electronic fraud through online web transactions, evaluate the effect of electronic fraud through automated teller machine, to determine the effect of fraud through point of sale machine, and to investigate the effect of fraud through mobile phone USSD transactions on the financial performance of selected deposit money banks in Nigeria. Panel Generalized method of moments (GMM) was used to analyze the panel series of the model. The Ha

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Putra, Ardiansyah, and Muhamad Alda. "Financial Management Information System Design with Business Intelligence Approach." Journal of Dinda : Data Science, Information Technology, and Data Analytics 5, no. 1 (2025): 122–27. https://doi.org/10.20895/dinda.v5i1.1796.

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This research aims to design and develop a web-based financial management application for Pabrik Opak Sun Jaya Mandiri, focusing on financial management. Prior to the application’s development, the business used a manual financial management system, which led to various issues, such as unstructured transaction records, difficulties in monitoring cash flow in real-time, and slow financial reporting prone to human errors. These problems could hinder the business owner from making accurate financial and operational decisions.To address these issues, the application was developed using the PHP pro

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Oluwatosin Abdul-Azeez, Alexsandra Ogadimma Ihechere, and Courage Idemudia. "Promoting financial inclusion for SMEs: Leveraging AI and data analytics in the banking sector." International Journal of Multidisciplinary Research Updates 8, no. 1 (2024): 001–14. http://dx.doi.org/10.53430/ijmru.2024.8.1.0037.

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Financial inclusion is crucial for the growth and sustainability of small and medium-sized enterprises (SMEs), which are significant contributors to economic development and job creation. However, traditional banking models often fall short in serving the unique needs of SMEs due to perceived high risks and insufficient credit history. Leveraging artificial intelligence (AI) and data analytics, the banking sector can transform its approach to financial inclusion, offering tailored financial products and services that cater specifically to SMEs. AI and data analytics enable banks to analyze vas

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Eseoghene Kokogho, Obianuju Clement Onwuzulike, Bamidele Michael Omowole, Chikezie Paul-Mikki Ewim, and Mary Oyenike Adeyanju. "Blockchain technology and real-time auditing: Transforming financial transparency and fraud detection in the Fintech industry." Gulf Journal of Advance Business Research 3, no. 2 (2025): 348–79. https://doi.org/10.51594/gjabr.v3i2.88.

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Blockchain technology has emerged as a transformative tool in the fintech industry, offering unprecedented opportunities to enhance real-time auditing processes, financial transparency, and fraud detection. This study explores how the integration of blockchain with advanced analytics can revolutionize traditional auditing practices, addressing critical challenges such as data tampering, inefficiencies, and lack of transparency. By leveraging blockchain’s immutable ledger and decentralized architecture, real-time auditing becomes more accurate, secure, and efficient, enabling continuous monitor

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Gupta, Prashant, and Vinay Singh. "Enhancing Tax Technology with AI/ML: Monitoring ERP Transactions for Real-Time Compliance and Efficiency." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 1317–21. https://doi.org/10.22214/ijraset.2025.70477.

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In the complex tax environment of today, companies face more stringent legal scrutiny, more data, and evolving compliance criteria. Though they are essential for managing financial transactions for global businesses, Enterprise Resource Planning (ERP) systems sometimes struggle with the complexity and dynamic character of present tax responsibilities. This study looks at how Machine Learning (ML) and Artificial Intelligence (AI), including advanced approaches like deep learning and reinforcement learning, can transform tax compliance systems. Embedding AI/ML within ERP systems lets businesses

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Ogunyankinnu, Tunde, Erumusele Francis Onotole, Akintunde Akinyele Osunkanmibi, Yetunde Adeoye, and ,. Godwin Aipoh. "Blockchain and AI synergies for effective supply chain management." International Journal of Multidisciplinary Research and Growth Evaluation 3, no. 1 (2022): 626–37. https://doi.org/10.54660/.ijmrge.2022.3.1-626-637.

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In supply chain management, the combination of Blockchain and Artificial Intelligence (AI) offers innovative solutions to address critical challenges, particularly in safeguarding financial transactions and reducing fraud. Blockchain’s decentralized and immutable nature, coupled with AI’s ability to analyze vast data sets and detect patterns, can create tamper-proof financial records and enhance trust in supply chain operations. Blockchain-backed smart contracts can automate processes, ensuring transparency, accountability, and efficiency in trade finance. These smart contracts execute predefi

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Ogunyankinnu, Tunde, Erumusele Francis Onotole, Akintunde Akinyele Osunkanmibi, Yetunde Adeoye, Godwin Aipoh, and Joseph Egbemhenghe. "Blockchain and AI synergies for effective supply chain management." International Journal of Multidisciplinary Research and Growth Evaluation 3, no. 4 (2022): 569–80. https://doi.org/10.54660/.ijmrge.2021.2.4-873-876.

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In supply chain management, the combination of Blockchain and Artificial Intelligence (AI) offers innovative solutions to address critical challenges, particularly in safeguarding financial transactions and reducing fraud. Blockchain’s decentralized and immutable nature, coupled with AI’s ability to analyze vast data sets and detect patterns, can create tamper-proof financial records and enhance trust in supply chain operations. Blockchain-backed smart contracts can automate processes, ensuring transparency, accountability, and efficiency in trade finance. These smart contracts execute predefi

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Andronie, Mihai, Roman Blažek, Mariana Iatagan, et al. "Generative artificial intelligence algorithms in Internet of Things blockchain-based fintech management." Oeconomia Copernicana 15, no. 4 (2024): 1349–81. https://doi.org/10.24136/oc.3283.

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Research background: Big data-driven artificial Internet of Things (IoT) fintech algorithms can provide real-time personalized financial service access, strengthen risk management, and manage, monitor, and mitigate transaction operational risks by operational credit risk management, suspicious financial transaction abnormal pattern detection, and synthetic financial data-based fraud simulation. Blockchain technologies, automated financial planning and investment advice services, and risk scoring and fraud detection tools can be leveraged in financial trading forecasting and planning, cryptocur

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Sharenko, M. S., and V. V. Chumachenko. "The role of international financial law in combating money laundering." Uzhhorod National University Herald. Series: Law 4, no. 86 (2025): 163–67. https://doi.org/10.24144/2307-3322.2024.86.1.4.26.

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The article examines the role of international financial law in combating money laundering on a global scale. Money laundering, which involves the legalization of proceeds obtained through criminal means, is one of the main threats to modern financial stability and security. This issue has a cross-border nature, as financial crimes often span multiple jurisdictions, significantly complicating their detection and suppression. The absence of unified standards or coordinated actions between countries creates favorable conditions for illegal activities, including the use of offshore zones and comp

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Premnath, J. Felix. "Perennial Expense Tracker." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42216.

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The Personal Expenses Tracker is an intuitive and efficient financial management application designed to help users track and analyze their spending habits. This system enables users to record daily expenses, categorize them, and generate insightful reports. By understanding their spending patterns, users can make informed financial decisions, set realistic budgets, and control unnecessary expenditures. The application provides interactive charts and graphs for better visualization of financial trends. Users can also set financial goals and monitor their progress over time. With features like

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Pradeepkumar Palanisamy. "Cloud-native test automation: The future of scalable financial software quality engineering." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 2371–79. https://doi.org/10.30574/wjaets.2025.15.1.0461.

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Cloud-native test automation is revolutionizing quality engineering for financial software by addressing the challenges traditional testing methodologies face with distributed systems, containerized applications, and microservices architectures. This article explores how financial institutions leverage containerization technologies, serverless execution platforms, and AI-driven test orchestration to maintain rigorous quality standards while accelerating delivery pipelines. The transformative impact of self-healing automation powered by artificial intelligence enables systems to learn from hist

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Oluwafunmike O. Elumilade, Ibidapo Abiodun Ogundeji, Godwin Ozoemenam Achumie, and Hope Ehiaghe Omokhoa. "Leveraging financial data analytics for business growth, fraud prevention, and risk mitigation in markets." Gulf Journal of Advance Business Research 3, no. 3 (2025): 906–22. https://doi.org/10.51594/gjabr.v3i3.119.

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Financial data analytics has become a critical tool for businesses seeking to drive growth, enhance fraud prevention, and mitigate risks in dynamic markets. By leveraging large datasets, advanced algorithms, and real-time analytics, organizations can make more informed financial decisions, improve operational efficiency, and enhance compliance with regulatory frameworks. This review explores how financial data analytics contributes to business growth by improving revenue forecasting, identifying market trends, and optimizing financial planning. Companies can leverage predictive models and arti

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Chukwuma-Eke, Ezinne C., Olakojo Yusuff Ogunsola, and Ngozi Joan Isibor. "Conceptualizing Digital Financial Tools and Strategies for Effective Budget Management in the Oil and Gas Sector." International Journal of Management and Organizational Research 2, no. 1 (2023): 230–46. https://doi.org/10.54660/ijmor.2023.2.1.230-246.

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The oil and gas sector operates in a dynamic financial environment characterized by volatile commodity prices, high capital expenditure, and complex regulatory frameworks. Effective budget management is crucial to ensuring financial sustainability, cost efficiency, and operational resilience. This study proposes a conceptual framework for integrating digital financial tools and advanced budget management strategies to optimize financial planning, mitigate risks, and enhance cost control in the oil and gas industry. The framework comprises three core components: data-driven financial forecastin

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Behera, Trupti Ranjan, and Asst Prof Mohapatra Girashree Sahu. "Financial Fraud Detection Using Machine Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51292.

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Financial fraud poses a significant threat to global economic stability, affecting individuals, institutions, and governments. Traditional fraud detection systems, which often rely on predefined rules and manual inspections, struggle to adapt to evolving fraudulent tactics. In this study, we explore the application of machine learning (ML) techniques to detect and prevent financial fraud with greater accuracy and efficiency. By leveraging supervised and unsupervised learning algorithms, the system can identify complex patterns and anomalies in large volumes of transactional data. We utilize a

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Merrad, Yaçine, Mohamed Hadi Habaebi, Md Rafiqul Islam, Teddy Surya Gunawan, and Mokhtaria Mesri. "Robust Decentralized Proof of Location for Blockchain Energy Applications Using Game Theory and Random Selection." Sustainability 14, no. 10 (2022): 6123. http://dx.doi.org/10.3390/su14106123.

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To combat the problem of illegal access to a service, several location proof strategies have been proposed in the literature. In blockchain-based decentralized applications, transactions can be issued by IoT nodes or other automated smart devices. Key pair encryption and private key signing have been defined mainly for human identification in blockchain applications, where users are personally and responsibly concerned about the confidentiality of their private key. These methods are not suitable for computing nodes whose private key is implemented in the software they run. Ensuring that trans

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Ikponmwoba, Sandra Orobosa, Onyeka Kelvin Chima, Onyinye Jacqueline Ezeilo, Benjamin Monday Ojonugwa, Akoche Ochefu, and Michael Olumuyiwa Adesuyi. "Conceptual Framework for Improving Bank Reconciliation Accuracy Using Intelligent Audit Controls." Journal of Frontiers in Multidisciplinary Research 1, no. 1 (2020): 57–70. https://doi.org/10.54660/.ijfmr.2020.1.1.57-70.

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Bank reconciliation is a critical financial process that ensures the accuracy of a company’s financial records by matching internal transactions with external bank statements. Traditionally, this process has been manually intensive, prone to errors, and time-consuming, which can lead to inaccuracies in financial reporting. The integration of intelligent audit controls leveraging technologies such as artificial intelligence (AI), machine learning (ML), and data analytics offers a transformative solution to improve the accuracy and efficiency of bank reconciliation. This conceptual framework pro

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Kushwah, Lokendra Singh. "Enterprise Platform Modernization: Migrating Legacy Payment Systems to Cloud-Native Architectures." European Journal of Computer Science and Information Technology 13, no. 7 (2025): 19–35. https://doi.org/10.37745/ejcsit.2013/vol13n71935.

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Financial institutions worldwide are undergoing a fundamental transformation as they migrate legacy payment systems to cloud-native architectures. The modernization of legacy payment systems to cloud-native architectures is a critical transformation for financial institutions aiming to enhance scalability, reduce costs, and meet evolving regulatory requirements. Traditional monolithic payment infrastructures suffer from limited scalability, high maintenance costs, and slow integration cycles, consuming a significant portion of IT budgets. Cloud-native architectures, powered by microservices, e

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Kuzmenko, Olha V., Serhii V. Mynenko, Serhii V. Lyeonov, and Aleksy S. Kwilinski. "Business Process Model for Monitoring the Automatic Payments in the "Client-Bank" System." Mechanism of an Economic Regulation, no. 1 (2021): 18–28. http://dx.doi.org/10.21272/mer.2021.91.02.

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The innovative development of banking presupposes modernization in the approaches to anti-money laundering. The article considers the issue of financial monitoring of banking operations without bank employees’ participation through the "Client-Bank" system. Two models for monitoring the automatic payments in the "Client-Bank" system are identified. The list of functions performed by the "Client-Bank" system in terms of types of clients: individuals and legal entities (including individuals-entrepreneurs) was determined. The first model describes general indicators of transactions that have the

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Meitova, Anna N., and Lyudmila G. Ripoll-Saragosi. "DIGITAL PLATFORMS AND SERVICES IN TAX CONTROL AS EFFECTIVE TOOLS FOR ENSURING ECONOMIC SECURITY." Ekonomika i upravlenie: problemy, resheniya 6/6, no. 159 (2025): 174–81. https://doi.org/10.36871/ek.up.p.r.2025.06.06.021.

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The scientific article is aimed at studying the features of tax control, its leading role as a tool for ensuring economic security. The authors substantiate that tax control as an effective tool is aimed at identifying all sorts of illegal taxation schemes, various forms of financial manipulation, which undermines the financial and tax system and the stability of economic security, which is especially relevant in the current conditions. Tax control plays a key role in monitoring controlled transactions of taxpayers, tracks “migrating” taxpayers, controls financial flows and provides informatio

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Achebe, Victor Chinedu, Oluwatosin Ilori, and Ngozi Joan Isibor. "Next-Generation AML Compliance: Leveraging Blockchain Innovations to Disrupt Money Laundering Networks." International Journal of Multidisciplinary Research and Growth Evaluation 4, no. 2 (2023): 741–53. https://doi.org/10.54660/.ijmrge.2023.4.2.741-753.

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The fight against money laundering (ML) remains a significant challenge for global financial systems. Traditional anti-money laundering (AML) measures often struggle with inefficiencies, high compliance costs, data fragmentation, and the increasing complexity of illicit financial activities. Blockchain technology, with its unique features of decentralization, transparency, and immutability, presents a next-generation solution to transform AML compliance and disrupt money laundering networks. By providing real-time transaction monitoring, transparent audit trails, and secure data sharing, block

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Researcher. "TRANSFORMING FINANCIAL SYSTEMS: THE ROLE OF DATA ENGINEERING IN FRAUD DETECTION, RISK MANAGEMENT, AND OPERATIONAL EFFICIENCY." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 7, no. 2 (2024): 2095–105. https://doi.org/10.5281/zenodo.14334195.

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This comprehensive article explores the transformative impact of data engineering on modern financial systems, focusing on critical areas, including fraud detection, risk management, and operational efficiency. The article delves into the evolution of financial technology infrastructure, highlighting how advanced data processing capabilities, machine learning implementations, and robust security frameworks have revolutionized the banking sector. The study investigates key technological advancements in real-time transaction processing, data warehousing solutions, and automated monitoring system

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Chepkutwo, Lawrence Kipchumba, and Nasieku Tabitha Nasieku. "Impact of Electronic Banking Transactions on the Volume of Trade of Commercial Banks in Kenya." International Journal of Finance 7, no. 5 (2022): 41–52. http://dx.doi.org/10.47941/ijf.1074.

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Purpose: Electronic banking is a mechanism that enables a financial institution's clients to conduct a number of financial transactions via an electronic device such as a cell phone or a personal digital assistant. Electronic banking refers to the provision of banking and financial services through electronic devices over a network. Commercial banks have been at the forefront of embracing and assimilating electronic fund transfer technology into their core tasks in order to achieve competitive advantages and manage their overhead operating costs. The purpose of this study was to determine the

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Manigonda, Srujana. "BLOCKCHAIN AND DATA GOVERNANCE IN FINANCIAL PIPELINES ENHANCING TRANSPARENCY AND SECURITY." BLOCKCHAIN AND DATA GOVERNANCE IN FINANCIAL PIPELINES ENHANCING TRANSPARENCY AND SECURITY 6, no. 12 (2021): 455–61. https://doi.org/10.5281/zenodo.14709441.

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Blockchain technology has emerged as a powerful tool for enhancing data governance in financialpipelines by ensuring transparency, security, and data integrity. This paper examines howblockchain’s decentralized and immutable ledger can address key challenges such as databreaches, compliance failures, and inefficient audit processes in the financial sector. It highlightsblockchain’s ability to enable real-time data monitoring, automated compliance checks throughsmart contracts, and secure transaction histories. By integrating blockchain into data governanceframeworks, financial inst

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Dzhikiya, К. А., N. D. Khabarova, and F. V. Мizyurev. "Application of ML-technologies for automation of financial monitoring and effective detection of anomalies in accounting." Buhuchet v sel'skom hozjajstve (Accounting in Agriculture), no. 5 (April 17, 2025): 340–49. https://doi.org/10.33920/sel-11-2505-04.

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The article discusses the use of machine learning methods to prevent fraud and identify anomalies in accounting. Modern organizations face the need to process large amounts of data, which makes it more difficult to detect errors and fraud in traditional ways. Machine learning, in particular, the methods of the nearest neighbor (KNN) and isolation forests, make it possible to automate the process of data analysis and effectively detect suspicious transactions. Practical examples of the use of these methods in large companies are given, and the prospects and challenges of introducing machine lea

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