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Journal articles on the topic 'Real-time financial insights'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Ajala, A.M, Ajala, A. M., Omotoso L.T, and Rotipin M.M. "Effect of Real-Time Financial Insights from Cloud Accounting on Managerial DecisionMaking in Organizations." International Journal of Advances in Engineering and Management 7, no. 2 (2025): 360–67. https://doi.org/10.35629/5252-0702360367.

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This paper examine the effect of real-time financial insight from cloud-based accounting on management decision making system of organisations. The ability of cloud accounting to provide real-time financial insights allows managers to make informed decisions quickly. This advantage improves cash flow management and capital allocation, leading to better financial performance. Respondent demographics indicate a majority of female participants (57.1%) and those aged 31– 44 years (52.6%). Educational qualifications showed 51.8% held a B.Sc, with MBA/M.Sc holders at 36.8%. The findings reveal that

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Singh, Manish, Qingyang Xu, Sarah J. Wang, Tinah Hong, Mohammad M. Ghassemi, and Andrew W. Lo. "Real-time extended psychophysiological analysis of financial risk processing." PLOS ONE 17, no. 7 (2022): e0269752. http://dx.doi.org/10.1371/journal.pone.0269752.

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We study the relationships between the real-time psychophysiological activity of professional traders, their financial transactions, and market fluctuations. We collected multiple physiological signals such as heart rate, blood volume pulse, and electrodermal activity of 55 traders at a leading global financial institution during their normal working hours over a five-day period. Using their physiological measurements, we implemented a novel metric of trader’s “psychophysiological activation” to capture affect such as excitement, stress and irritation. We find statistically significant relatio

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Celestin, M., S. Mishra, and A. K. Mishra. "Real-Time Financial Reporting in the Digital Age: How Companies Are Adapting to the Growing Demand for Instantaneous Financial Insights." Insight Journal of National Open College 2, no. 1 (2025): 96–117. https://doi.org/10.5281/zenodo.15366124.

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The digital transformation of financial reporting has led to the increasing adoption of real-time financial reporting (RTFR), driven by advancements in artificial intelligence (AI), blockchain, and cloud computing. This study examines how companies are adapting to the demand for real-time financial insights, with a focus on technological advancements, challenges, and financial implications. Using a mixed-methods approach, data were collected from financial reports, regulatory filings, and expert interviews from 2020 to 2024. Empirical findings reveal a strong positive correlation (r = 0.9878)

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Chundi, Venkata Ramachandra Karthik. "AI-Enhanced Financial Management: Real-Time Monitoring and Human-AI Collaboration in Modern ERP Systems." European Journal of Computer Science and Information Technology 13, no. 43 (2025): 83–92. https://doi.org/10.37745/ejcsit.2013/vol13n438392.

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In the fast-paced business world, real-time financial monitoring and decision support are crucial to maintaining competitiveness. Traditional financial systems struggle to provide timely insights, often relying on batch processing or historical data, leading to delayed reactions and missed opportunities. Modern cloud-based ERP systems with advanced AI capabilities offer solutions by delivering real-time financial analytics. This integration empowers financial leaders to continuously monitor financial health, detect anomalies, and make decisions quickly. AI technologies excel at pattern recogni

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Kumar, Sudhir. "Real-Time Data Streaming: Transforming FinTech Through Modern Data Architectures." European Journal of Computer Science and Information Technology 13, no. 18 (2025): 49–64. https://doi.org/10.37745/ejcsit.2013/vol13n184964.

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This comprehensive article explores the transformative impact of real-time data streaming technologies in the financial services sector through four detailed case studies. It examines how leading financial institutions have leveraged modern data architectures, including Apache Kafka, Spark Streaming, AWS Kinesis, and cloud computing platforms, to address critical business challenges. The article demonstrates how these technologies enable instantaneous fraud detection, enhanced customer experience through personalized offerings, streamlined regulatory reporting, and optimized customer acquisiti

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Dr., Mrs. Swapna Bhavsar, Bajare Arjun, Jadhav Vaidehi, Marathe Gaurav, and Nikam Aishwarya. "A Survey on Real-Time Market Dynamics Through Visual Dashboards." International Journal of Engineering and Management Research 14, no. 1 (2024): 52–57. https://doi.org/10.5281/zenodo.10656991.

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This paper presents a web-based dashboard for real-time data visualization, primarily focusing on financial markets and cryptocurrencies. Data visualization serves as an effective means to convey intricate data clearly and concisely. Utilizing React for the front end, Flask for the backend API, and incorporating data visualization libraries such as Chart.js, our dashboard offers dynamic and interactive data representations. Comprehensive overview of dashboard design, architecture, and functionality, highlighting its importance in monitoring and analyzing financial information in real-time. Fur

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Ahuja, Dharmendra. "Platform Engineering for Financial Services: Enabling Real-Time Transaction Processing." European Journal of Computer Science and Information Technology 13, no. 9 (2025): 81–91. https://doi.org/10.37745/ejcsit.2013/vol13n98191.

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This article examines key emerging technologies transforming financial platform engineering. Platform engineering plays a pivotal role in building these systems by leveraging microservices architecture, event-driven systems, and cloud-native technologies. This article explores how modern platform engineering practices ensure low latency, high throughput, security, and regulatory compliance while integrating cutting-edge technologies like machine learning and blockchain. Machine learning has revolutionized fraud detection by enabling the analysis of vast transactional datasets to identify patte

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Sai Venkata Kondapalli. "Real-time analytics with cloud-native database technologies." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 3689–99. https://doi.org/10.30574/wjarr.2025.26.1.1503.

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Cloud-native database technologies are revolutionizing real time analytics capabilities across industries by enabling enterprises to extract actionable insights from massive datasets with minimal latency. This article explores the evolution of these technologies through their core technical components: columnar storage optimization, in-memory processing, and streaming data capabilities. Further the article examines architectural patterns, including Lambda, Kappa, and HTAP approaches that support sub-second query responses at scale. The business value of real-time analytics is demonstrated thro

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Mula, Krishna. "Real-Time Revolution: The Evolution of Financial Transaction Processing Systems." European Journal of Computer Science and Information Technology 13, no. 10 (2025): 86–100. https://doi.org/10.37745/ejcsit.2013/vol13n1086100.

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This article examines the transformative evolution of transaction processing systems from traditional batch processing to real-time payment mechanisms. The historical progression and architectural distinctions between these paradigms while analyzing the critical transition factors that facilitated this evolution. The discussion encompasses the enabling technologies—including API-driven banking, distributed ledger solutions, and cloud computing infrastructure—that have revolutionized payment processing capabilities. Through the demonstration of current implementation cases across peer-to-peer t

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Hussain, Jawad, and Badaruddin Kalhoro. "Navigating Financial Complexity: Language Processing Insights for Modern Businesses." SciWaveBulletin 01, no. 04 (2023): 24–31. http://dx.doi.org/10.61925/swb.2023.1404.

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Complex financial markets generate massive volumes of unstructured text data from news, publications, social media, and analyst comments. NLP can assist investors and traders make real-time judgments using this data. Analysis of markets This article reviews NLP advancements in three main areas. Generally favorable, negative, or neutral opinions toward companies, industries, or markets. Conversational tone predicts market and investor confidence using machine learning and sentiment lexicons. Finance conversation topic discovery. NLP algorithms may find hidden patterns and investment possibiliti

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Sai Kiran Karumuri. "Cloud Computing: Revolutionizing Enterprise Data with Integration and Real-time Insights." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 11–20. https://doi.org/10.32628/cseit251112359.

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This article examines the transformative impact of cloud computing on enterprise data management, focusing on how organizations are leveraging cloud-native technologies to overcome traditional data silos and enhance operational efficiency. The article explores key benefits including improved scalability, enhanced data integration capabilities, and real-time analytics, supported by case studies from manufacturing and financial sectors. Through comprehensive analysis of security frameworks, change management strategies, and implementation best practices, the article demonstrates how cloud comput

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Priyanka, Prajapati, K. Sreekala Dr., and Sultana Ms.N.Musrat. "RetailSphere: Real-Time Retail House Management Software." Journal of Network Security and Data Mining 7, no. 3 (2024): 20–30. https://doi.org/10.5281/zenodo.12526844.

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<em>This abstract introduces a Rental House Management System, designed to streamline the process of managing rental properties for landlords and property managers. The system aims to automate various tasks involved in property management, enhancing efficiency, accuracy, and overall tenant satisfaction. </em><em>The Rental House Management System offers a comprehensive suite of features including property listing management, tenant management, rent collection, maintenance tracking, and financial reporting. Landlords and property managers can easily add new properties to the system, upload prop

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Konakalla, Kiran. "Integrating ChatGPT with Salesforce for Real-Time Market Insights on Accounts." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 10 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem37483.

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This paper explores the integration of ChatGPT, an AI-driven natural language processing model, with Salesforce to enhance sales teams' access to real-time market information about specific accounts. By integrating ChatGPT with Salesforce through API calls, users can fetch the latest market trends, news articles, stock prices, financial data, legal filings, and acquisitions related to specific accounts directly on the Account detail page. This integration not only improves decision-making and customer engagement but also offers a scalable, automated solution that saves time and enhances data a

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Anju Santosh Yedatkar. "Real-time data analytics in distributed systems." International Journal of Scientific Research in Modern Science and Technology 3, no. 6 (2024): 09–16. http://dx.doi.org/10.59828/ijsrmst.v3i6.215.

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Real-time data analytics involves the processing and analysis of data as it arrives, delivering immediate insights that are crucial for time-sensitive applications. This research explores the platforms and techniques necessary for supporting real-time analytics, extending beyond traditional Event Processing Systems (EPS) to include broader big data contexts that integrate both 'data at rest' and 'data in motion' solutions. A detailed case study is presented, showcasing the application of the Event Swarm complex event processing engine in addressing financial analytics challenges. The study ide

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Tasan, Mehmet, Yusuf Ozkan, Ahmet Omer Ozgur, and Alper Ozpinar. "Data Plateau: A Unified Analytics Platform with Intuitive Interfaces for Real-Time and ML-Driven Insights." Orclever Proceedings of Research and Development 4, no. 1 (2024): 73–89. http://dx.doi.org/10.56038/oprd.v4i1.457.

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Recent advances in artificial intelligence, particularly generative AI, have significantly transformed the financial technology (fintech) industry. This paper explores the development and application of Data Plateau, an integrated data analytics platform designed to simplify complex data manipulation and analysis tasks within the fintech domain. Data Plateau empowers users with intuitive, drag-and-drop interfaces, making advanced analytics accessible to a broader range of professionals. The research aims to accomplish three main objectives. Firstly, it investigates how user-centric interfaces

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Researcher. "OPTIMIZING REAL-TIME DATA PIPELINES FOR FINANCIAL FRAUD DETECTION: A SYSTEMATIC ANALYSIS OF PERFORMANCE, SCALABILITY, AND COST EFFICIENCY IN BANKING SYSTEMS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 878–94. https://doi.org/10.5281/zenodo.14264978.

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The proliferation of digital financial transactions has intensified the need for sophisticated real-time fraud detection systems within banking institutions. This article presents a systematic analysis of real-time data pipeline optimization strategies for financial fraud detection, addressing critical challenges in performance, scalability, and cost efficiency. Through a comprehensive examination of stream processing architectures, we evaluate various optimization techniques across the data pipeline lifecycle, from ingestion to analytical processing. The article methodology combines theo

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Khrais, Laith. "Bridging gaps in InsurTech and e-commerce integration: Insights from Saudi Arabia." Insurance Markets and Companies 16, no. 1 (2025): 64–73. https://doi.org/10.21511/ins.16(1).2025.06.

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The integration of insurance technology with e-commerce in Saudi Arabia is a key driver of financial and technological advancement, aligning with Vision 2030, the national strategy for economic diversification and digital transformation. This study examines the technological factors influencing this integration, assessing both enablers and barriers, including application programming interfaces, artificial intelligence, real-time risk assessment, cybersecurity, outdated infrastructure, and regulatory alignment. A quantitative approach was employed, gathering data from 253 professionals in Saudi

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Azhar Shaikh, Mohammad Aqdas. "AI-Driven Real-Time Phishing Detection System." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04419.

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ABSTRACT: The escalating threat of phishing attacks poses significant risks to individuals and organizations, compromising sensitive data and financial security. Traditional phishing detection methods, reliant on manual analysis and static rules, struggle to keep pace with the sophistication and volume of modern attacks. This study proposes an innovative artificial intelligence (AI)-driven system for real-time phishing detection, integrating machine learning algorithms with a dynamic network of data sources, including email metadata, URL features, and user behavior analytics. By leveraging adv

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Researcher. "REAL-TIME FRAUD DETECTION: A BANKING INDUSTRY CASE STUDY." International Journal of Research In Computer Applications and Information Technology (IJRCAIT) 15, no. 6 (2024): 1232–45. https://doi.org/10.5281/zenodo.14360088.

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This comprehensive article examines the implementation and evolution of real-time fraud detection systems in modern banking environments. The article explores the transformation of digital payment landscapes, focusing on the architectural frameworks, implementation strategies, and performance metrics of advanced fraud detection systems. The article demonstrates how financial institutions can effectively combat sophisticated fraud patterns while maintaining operational efficiency through detailed analysis of system components, stream processing, machine learning models, and data management stra

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20

Bagam, Naveen. "Advanced Techniques in Predictive Analytics for Financial Services." Integrated Journal for Research in Arts and Humanities 1, no. 1 (2021): 117–26. http://dx.doi.org/10.55544/ijrah.1.1.16.

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Predictive analytics in financial services is rapidly evolving with advancements in machine learning, time series modeling, and big data analytics. This paper explores state-of-the-art techniques, emphasizing methods such as deep learning, NLP, and real-time analytics. It further examines ethical and regulatory implications, challenges, and emerging trends, aiming to provide insights for industry professionals and researchers.

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Shatrughna Upadhyay. "Next-Generation Payment Protocols: Architecting Secure, Scalable, and Real-Time Transaction Systems." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2322–32. https://doi.org/10.32628/cseit251112275.

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The evolution of digital payment systems represents a critical transformation in global financial infrastructure, driven by increasing demands for faster, more secure, and scalable transaction processing. This comprehensive article examines the architecture, implementation, and future directions of next-generation payment protocols, focusing on three fundamental pillars: ISO 20022 messaging standards, Layer 2 scaling solutions, and real-time settlement networks. The article analyzes how these components work in concert to address current limitations in traditional payment systems while enablin

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PAVAN KUMAR REDDY, ALURU. "Dashboard Real-Time Monitoring of Construction Projects." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47451.

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Abstract: The complexity of managing large-scale construction projects necessitates efficient real-time monitoring systems to ensure timely completion, cost control, and streamlined resource management. Traditional monitoring methods often rely on manual data collection, periodic updates, and fragmented communication, leading to inefficiencies and delays. This research presents a software-based real-time dashboard that enables automated tracking, visualization, and management of construction projects using modern web technologies and data analytics. The proposed system is developed using Next.

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Himanshu Adhwaryu. "Real-Time AI: Building Intelligent Stream Processing Pipelines." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 3042–50. https://doi.org/10.32628/cseit251112313.

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This comprehensive technical article explores the evolution and implementation of real-time AI systems through stream processing pipelines. It explores the transformation from traditional batch processing to dynamic, real-time intelligence, highlighting the architectural components, implementation patterns, and industry applications. The article discusses critical aspects of stream processing foundations, AI/ML integration layers, and real-time inference engines while addressing challenges in feature engineering, model deployment, and system monitoring. Through detailed analysis of application

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Alam, Md Ashraful, Ashrafur Rahman Nabil, Abdul Awal Mintoo, and Ashraful Islam. "Real-Time Analytics In Streaming Big Data: Techniques And Applications." Non human journal 1, no. 01 (2024): 104–22. https://doi.org/10.70008/jeser.v1i01.56.

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The increasing prevalence of streaming big data has revolutionized how organizations approach real-time analytics, providing a competitive edge by enabling immediate, actionable insights from continuously generated data streams. This review systematically examines real-time analytics techniques and their applications in streaming big data using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. The methodology involves identifying, screening, and synthesizing relevant studies to provide a comprehensive overview of state-of-the-art techniques, including d

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Frank, Pascal, and Markus Rudolf. "Is the Metaverse Dead? Insights from Financial Bubble Analysis." FinTech 3, no. 2 (2024): 302–23. http://dx.doi.org/10.3390/fintech3020017.

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This paper explores the economic trends and identifies speculative bubbles within the emerging metaverse, based on the specific example of Decentraland, which is represented by its underlying native token MANA.For comparability, we consider three further tokens: SAND, ETH, and BTC.The study shows price prediction and provides further insight into bubble behavior to provide a deeper insight into the real trend and situation of the metaverse. When comparing all considered tokens, evidence of comovement and positive as well as negative bubbles is identified. This paper makes use of proven modelin

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Bhagavathi Sathya Satish Kadiyala. "Implementing Conversational AI in ERP Systems: A Technical Framework for Real-Time Financial Operations." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 3583–93. https://doi.org/10.32628/cseit251112383.

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This article presents a comprehensive technical framework for implementing conversational AI interfaces within Enterprise Resource Planning (ERP) systems, focusing on real-time financial operations. The article examines how Natural Language Processing (NLP) technologies can transform traditional ERP interfaces into intuitive, conversation-driven systems that enhance user accessibility and operational efficiency. The article details the technical architecture, core capabilities, implementation methodologies, and business impact of integrating NLP-enhanced interfaces in enterprise environments.

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Swathi, Suddala. "Harnessing Cloud Technology for Real-Time Machine Learning in Fraud Detection." European Journal of Advances in Engineering and Technology 10, no. 5 (2023): 118–23. https://doi.org/10.5281/zenodo.14274583.

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Fraud detection in financial services is a vital function that demands real-time analysis to minimize losses and safeguard customer accounts. This research investigates how cloud-based machine learning (ML) can implement a real-time fraud detection system. We developed a scalable and responsive fraud detection pipeline by integrating cloud infrastructure with advanced ml algorithms. This architecture leverages cloud resources for high-throughput processing and efficient model training, enabling it to adapt smoothly to changing transaction volumes. Our approach encompasses feature engineering,

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Samuel Tatipamula. "Real-Time vs. Batch Data Processing: When speed matters." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 1612–31. https://doi.org/10.30574/wjarr.2025.26.1.1213.

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Organizations today face critical decisions between batch and real-time data processing architectures. While batch systems have powered data operations for decades with their efficiency and thoroughness, the growing demand for low-latency decision-making is driving industries toward real-time architectures that emphasize immediacy and responsiveness. This article explores the fundamental differences between these two paradigms, examining their inherent trade-offs in efficiency versus speed, cost versus complexity, scalability versus immediacy, and data completeness versus timeliness. Through c

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Heo, Wookjae, Yi Liu, and Jae-min Lee. "Improving Communication with Financial Consumers: Insights from a Study of Phone Call Phobia." Financial Services Review 32, no. 4 (2024): 78–102. https://doi.org/10.61190/fsr.v32i4.4041.

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A phone call phobia is a symptom of avoiding real-time communication that ranges from mild nervousness to a debilitating fear of making or receiving phone calls. The situation of avoidance of real-time communication, including phone call phobia, can potentially influence personal finance, particularly if it limits an individual's ability to communicate effectively with not only family, friends, and employers but also financial service providers. As the COVID-19 pandemic has affected ways of socializing and communicating, it is important to understand the situation and related factors of phone

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Ashiedu, Benedict Ifechukwude, Ejielo Ogbuefi, Uloma Stella Nwabekee, Jeffrey Chidera Ogeawuchi, and Abraham Ayodeji Abayomi. "Designing Financial Intelligence Systems for Real-Time Decision-Making in African Corporates." Journal of Frontiers in Multidisciplinary Research 4, no. 2 (2023): 68–81. https://doi.org/10.54660/.jfmr.2023.4.2.68-81.

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In the rapidly evolving business landscape of Africa, corporates face increasing pressure to make swift, data-driven decisions in order to remain competitive and agile. Traditional financial management systems, often siloed and reactive, struggle to meet the demands for real-time, informed decision-making. This explores the design and implementation of financial intelligence systems (FIS) tailored for African corporates, drawing from a systems thinking approach that integrates finance, planning, and infrastructure divisions. By adopting a holistic perspective, these systems enable organization

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S, Shanthi. "Integrating Expense Tracking with AI-Driven Investment Recommendations." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40779.

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The Expense Tracker is a comprehensive financial management application developed using the MERN stack—MongoDB, Express.js, React, and Node.js—to simplify expense tracking, budgeting, and investment decision-making. The application features a secure backend powered by Node.js and Express.js, utilizing RESTful APIs for efficient data handling, while MongoDB ensures flexible and scalable data storage. The React-based front end provides a responsive and intuitive interface, enabling users to seamlessly input, categorize, and visualize their expenses. Core functionalities include user authenticati

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Kadiyala, Bhagavathi Sathya Satish. "AI-ENHANCED FINANCIAL INTELLIGENCE SUITE: REAL-TIME ERP MODULE FOR FORECASTING, ANOMALY DETECTION, AND STRATEGIC INSIGHTS." INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY 16, no. 1 (2025): 673–86. https://doi.org/10.34218/ijaret_16_01_047.

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Kotte, Kulasekhara Reddy. "Integrating Cybersecurity and Real-Time Analytics in Treasury Management: Enhancing Liquidity, Optimizing Working Capital, and Mitigating Financial Risks." International Journal of Professional Studies 16, no. 1 (2023): 61–69. https://doi.org/10.37648/ijps.v16i01.006.

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Treasury management plays a pivotal role in maintaining an organization’s financial stability, ensuring optimal liquidity, working capital efficiency, and comprehensive risk mitigation. As businesses navigate an era marked by digital transformation, integrating robust cybersecurity measures and leveraging real-time analytics has emerged as a strategic necessity. Cybersecurity fortifies treasury functions against escalating cyber threats, safeguarding sensitive financial data and operational integrity. Concurrently, real-time analytics enables treasury professionals to access actionable insight

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Ajala, A.M, O.L Oluwagbuyi, and A.R Olaniyi. "Overall Effect of Cloud-Based Accounting on Financial Information Quality of Organizations." Global Journal of Economic and Finance Research 02, no. 02 (2025): 91–96. https://doi.org/10.5281/zenodo.14903910.

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<strong>ABSTRACT: </strong>This paper explores the overall effect of cloud-based accounting in enhancing financial information quality of organizations. Respondent demographics indicate a majority of female participants (57.1%) and those aged 3144 years (52.6%). Educational qualifications showed 51.8% held a B.Sc, with MBA/M.Sc holders at 36.8%. The findings reveal that 63.9% of respondents agree on the benefits of cloud-based accounting for financial information quality, and 67.7% affirm its potential in reducing operational costs and increasing profitability in SMEs. Conversely, 62.4% of res

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Dileep Kumar Siripurapu. "Real-Time Data Analytics Integration: A Technical Deep Dive." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2484–92. https://doi.org/10.32628/cseit251112253.

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Real-time data analytics integration represents a transformative approach to processing and utilizing data in modern organizations. This comprehensive article of real-time analytics systems explores the architectural foundations, implementation considerations, and industry applications that define successful deployments. The content delves into event-driven architectures, core components, and best practices that enable organizations to harness immediate insights from their data streams. The discussion encompasses performance optimization strategies, data quality frameworks, and fault tolerance

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Famoti, Oluwakemi, Bamidele Michael Omowole, Okiomah Eloho, et al. "Enhancing Customer Satisfaction in Financial Services through Advanced BI Techniques." International Journal of Multidisciplinary Research and Growth Evaluation 5, no. 6 (2024): 1258–66. https://doi.org/10.54660/.ijmrge.2024.5.6.1258-1266.

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In the fast-paced and competitive realm of financial services, maintaining high levels of customer satisfaction is not just a goal but a critical imperative. This review delves into the pivotal role that advanced Business Intelligence (BI) techniques play in elevating customer satisfaction within the financial sector. By harnessing sophisticated analytics tools and methodologies, financial institutions can glean invaluable insights into customer behavior, preferences, and feedback, thereby empowering them to deliver tailored and proactive services. The review begins by elucidating the signific

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Kıralioğlu, Tuna. "Developing Models for Analyzing Financial Time Series Data for Investment Strategies." Human Computer Interaction 8, no. 1 (2024): 33. http://dx.doi.org/10.62802/w0n1y007.

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Financial time series data is a cornerstone of investment strategy development, providing critical insights into market trends, asset performance, and risk assessment. This research explores the application of advanced statistical and machine learning models for analyzing financial time series data to optimize investment strategies. The study examines various techniques, including autoregressive integrated moving average (ARIMA), GARCH models for volatility forecasting, and recurrent neural networks (RNNs) for capturing temporal dependencies in financial data. By leveraging these models, the r

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Deepika Annam. "Advancements in latency reduction for real-time data processing in the cloud." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 1370–76. https://doi.org/10.30574/wjaets.2025.15.2.0673.

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Latency reduction in real-time data processing represents a critical competitive differentiator in contemporary enterprise environments. This comprehensive technical article examines cutting-edge techniques for minimizing processing delays and optimizing performance in cloud-based systems. The digital transformation journey demands instantaneous insights for decision-making, creating unprecedented challenges as data volumes continue to expand exponentially across sectors. Financial services, healthcare, telecommunications, and manufacturing all demonstrate compelling advantages when implementi

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Qi, Jiaxuan, and John Cao. "A Study on Big Data Adoption in Financial Accounting and Its Implications for Financial Statement Accuracy." Journal of Applied Economics and Policy Studies 18, no. 2 (2025): 13–20. https://doi.org/10.54254/2977-5701/2025.21866.

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Financial accounting has been changed by using vast datas to increase the accuracy of financial statements with big data. In this paper, big data in financial accounting adoption process, insights from data driven and real world cases are studied and its implication for accuracy of financial statements is also investigated. It investigates how these set of characteristics or paradigms of big data (volume, veracity, velocity and variety) facilitate real time transaction analysis and help to minimize the errors there are in periodic reporting which are prone to errors. The study also demonstrate

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Ravi Kiran Puvvada. "The Impact of SAP S/4HANA Finance on Modern Business Processes: A Comprehensive Analysis." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 817–25. https://doi.org/10.32628/cseit25112413.

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This article provides a comprehensive analysis of SAP S/4HANA Finance, a cutting-edge financial management system that is revolutionizing how organizations handle their financial processes. The article explores the key features of SAP S/4HANA Finance, including its predictive analytics capabilities, advanced real-time reporting through SAP Analytics Cloud, and seamless integration with other SAP solutions. It delves into the transformative concept of Event-Based Accounting, examining how this approach leverages automation and real-time data processing to enhance financial accuracy and efficien

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Ugbaja, Unomah Success, Uloma Stella Nwabekee, Wilfred Oseremen Owobu, and Olumese Anthony Abieba. "Machine Learning-Powered Chatbots for Real-Time Business Intelligence and Analytics." International Journal of Management and Organizational Research 2, no. 1 (2023): 328–35. https://doi.org/10.54660/ijmor.2023.2.1.328-335.

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Machine learning-powered chatbots have revolutionized real-time business intelligence (BI) and analytics by enabling instant data retrieval, automated reporting, and predictive decision-making. These AI-driven systems leverage natural language processing (NLP), deep learning, and predictive analytics to interact with users, process vast datasets, and generate actionable insights. By integrating with business intelligence platforms, chatbots facilitate seamless access to key performance indicators (KPIs), financial metrics, and customer analytics, enhancing operational efficiency and strategic

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Sasibhushan Rao Chanthati. "Training LLMs for querying financial data with natural language prompts." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 025–32. https://doi.org/10.30574/wjaets.2025.15.1.0190.

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The abstract introduces the motivation behind this research: the rapid expansion of financial investment data and the need for Artificial Intelligence-driven solutions for accurate and real-time analysis. The research presents an open-source Large Language Model (LLM) fine-tuned on financial datasets to provide precise investment insights. The LLM integrates MongoDB Atlas Vector Search to store and retrieve vector embeddings efficiently. This allows natural language querying of financial data. The implementation leverages Hugging Face Transformers, Sentence-Transformers, and FastAPI, enabling

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Chukwuma-Eke, Ezinne C., Olakojo Yusuff Ogunsola, and Ngozi Joan Isibor. "Developing an Integrated Framework for SAP-Based Cost Control and Financial Reporting in Energy Companies." International Journal of Multidisciplinary Research and Growth Evaluation. 3, no. 1 (2022): 805–18. https://doi.org/10.54660/.ijmrge.2022.3.1.805-818.

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The energy sector faces increasing challenges in cost management and financial reporting due to fluctuating market conditions, regulatory requirements, and operational complexities. Effective cost control and financial transparency are critical for energy companies to maintain profitability and compliance. This study proposes an integrated framework leveraging SAP-based solutions to optimize cost control and financial reporting. By integrating SAP’s advanced financial management modules, the framework aims to enhance real-time cost tracking, budget forecasting, and regulatory compliance. The p

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Amos Nyombi, Jimmy Ampe, Babrah Happy, Mark Sekinobe, Wycliff Nagalila, and Benon Masaba. "Leveraging big data for real-time financial oversight in non-profit and government accounting: A framework to empower accountants and improve transparency." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 2544–54. https://doi.org/10.30574/wjarr.2025.26.2.1937.

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The evolving landscape of the accounting profession is increasingly shaped by the integration of big data and advanced analytics, enabling professionals to derive actionable insights, enhance decision-making, and optimize financial oversight (Appelbaum et al., 2017; Vasarhelyi et al., 2015). This study explores how these innovations are transforming financial operations, particularly within non-profit and government organizations, by supporting real-time data processing and improving transparency and accountability (Warren et al., 2015; Smith, 2023). The research highlights how big data techno

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Researcher. "THE CONVERGENCE OF FINANCE AND HIGH-PERFORMANCE COMPUTING: IMPLICATIONS FOR MODELING ACCURACY AND RISK MITIGATION." International Journal of Engineering and Technology Research (IJETR) 9, no. 2 (2024): 54–63. https://doi.org/10.5281/zenodo.13646458.

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This article investigates the transformative impact of High-Performance Computing (HPC) on financial modeling and risk assessment through a comprehensive analysis of three case studies in the banking and investment sectors. By examining HPC implementations in complex financial modeling, real-time risk analysis, and large-scale data processing, we demonstrate significant improvements in model accuracy, risk mitigation strategies, and decision-making processes. Our findings reveal that HPC-driven solutions achieved a 40% increase in modeling speed, a 30% enhancement in risk prediction accuracy,

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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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S, ABHILASH. "The Power of Big Data: Enhancing Business Strategy with Real-Time Analytics." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–9. https://doi.org/10.55041/isjem02855.

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In today’s fast-paced business environment, organizations face the challenge of making timely and informed decisions to maintain a competitive edge. The Power of Big Data: Enhancing Business Strategy with Real-Time Analytics explores how big data analytics (BDA) transforms raw data into actionable insights, enabling real-time decision- making and strategic planning. This paper delves into the technologies, methodologies, and tools that facilitate the collection, processing, and analysis of large datasets from diverse sources such as social media, IoT devices, and transactional systems. It high

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Aria, Seyed Sina, Seyed Hossein Iranmanesh, and Hossein Hassani. "Optimizing Multivariate Time Series Forecasting with Data Augmentation." Journal of Risk and Financial Management 17, no. 11 (2024): 485. http://dx.doi.org/10.3390/jrfm17110485.

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The convergence of data mining and deep learning has become an invaluable tool for gaining insights into evolving events and trends. However, a persistent challenge in utilizing these techniques for forecasting lies in the limited access to comprehensive, error-free data. This challenge is particularly pronounced in financial time series datasets, which are known for their volatility. To address this issue, a novel approach to data augmentation has been introduced, specifically tailored for financial time series forecasting. This approach leverages the power of Generative Adversarial Networks

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Samuel Jesupelumi Owoade, Abel Uzoka, Joshua Idowu Akerele, and Pascal Ugochukwu Ojukwu. "Enhancing financial portfolio management with predictive analytics and scalable data modeling techniques." International Journal of Scholarly Research and Reviews 5, no. 2 (2024): 089–102. http://dx.doi.org/10.56781/ijsrr.2024.5.2.0050.

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The financial industry faces an increasingly complex landscape for portfolio management, where data-driven insights are crucial for optimizing asset allocation and managing risk. This paper explores the integration of predictive analytics and scalable data modeling techniques in enhancing financial portfolio management. By leveraging machine learning algorithms, big data architectures, and real-time data processing, predictive analytics can forecast asset trends, detect market anomalies, and assess portfolio risk with high precision. We evaluate several predictive models, including time-series

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Kalapati, Sravanthi. "Transforming Value-Based Care with Scalable Data Pipelines: Enabling Real-Time Insights for Improved Healthcare Outcomes." Journal of Technology and Systems 7, no. 2 (2025): 1–6. https://doi.org/10.47941/jts.2548.

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Purpose: This paper aims to explore the transformative role of scalable data pipelines in enabling real-time insights essential for the success of Value-Based Care (VBC). It examines how these pipelines support efficient data integration, real-time analytics, and actionable insights, driving improved healthcare outcomes. Methodology: A qualitative research design was adopted, leveraging case studies and data analytics models to investigate the impact of scalable data pipelines on healthcare efficiency and patient care optimization. Data was collected from electronic health records (EHRs), clai

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