Article section
Real-Time Business Intelligence: A Review of Applications in Finance, Healthcare, and Retail
Abstract
Real-Time Business Intelligence (RTBI) bridges data collection and actionable insight, transforming organizational decision-making. Unlike batch-oriented Business Intelligence, RTBI leverages streaming analytics, in-memory computing, and AI to deliver rapid, context-aware insights. This review examines RTBI adoption in finance, healthcare, and retail, revealing both shared enablers and sector-specific adaptations. Comparative analysis highlights distinct sectoral priorities: finance emphasizes speed and risk management, healthcare prioritizes accuracy and regulatory compliance, while retail focuses on customer-centric innovation and operational efficiency. Key applications include fraud detection, algorithmic trading, and risk monitoring in finance; patient monitoring, disease prediction, and hospital resource optimization in healthcare; and dynamic pricing, personalization, and supply chain efficiency in retail. Despite these benefits, RTBI adoption is hindered by challenges such as data quality, system integration, high infrastructure costs, and privacy concerns. Emerging technologies—including cloud computing, IoT, machine learning, 5G, and blockchain—are expanding RTBI capabilities, enabling predictive automation and continuous organizational agility. The review concludes with practical recommendations, identifies gaps in comparative research, and suggests avenues for future study, positioning RTBI as a strategic driver of competitiveness in a data-driven world.
Keywords:
Artificial Intelligence Data-Driven Systems Decision-Making Finance Healthcare Retail Real-Time Business Intelligence Streaming Analytics
Article information
Journal
Journal of Economics, Business, and Commerce
Volume (Issue)
2(2), (2025)
Pages
119-128
Published
Copyright
Copyright (c) 2025 Loveth Itohan Obozokhai, Jacob Miracle Godswill, Isaac Oluwaseyi Balogun, Olukunle O. Akanbi (Author)
Open access

This work is licensed under a Creative Commons Attribution 4.0 International License.
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References
Abayomi, A. A., Uzoka, A. C., Ogeawuchi, J. C., Agboola, O. A., Gbenle, T. P., & Akpe, O. E. (2025). Revolutionizing Business Intelligence Reporting: Advances in Cloud-Native Data Visualization Tools for Real-Time Insights. International Journal of Advanced Multidisciplinary Research and Studies, 3(6), 1582–1588.
Abikoye, B. E., Akinwunmi, T., Adelaja, A. O., Umeorah, S. C., Ogunsuji, Y. M., Abikoye, B. E., Akinwunmi, T., Adelaja, A. O., Umeorah, S. C., & Ogunsuji, Y. M. (2024). Real-time financial monitoring systems: Enhancing risk management through continuous oversight. GSC Advanced Research and Reviews, 20(1), 465–476. https://doi.org/10.30574/gscarr.2024.20.1.0287
Abikoye, B. E., Umeorah, S. C., Adelaja, A. O., Ayodele, O., & Ogunsuji, Y. M. (2024). Regulatory compliance and efficiency in financial technologies: Challenges and innovations. World Journal of Advanced Research and Reviews, 23(1), 1830–1844. https://doi.org/10.30574/wjarr.2024.23.1.2174
Aghazadeh Ardebili, A., Hasidi, O., Bendaouia, A., Khalil, A., Khalil, S., Luceri, D., Longo, A., Abdelwahed, E. H., Qassimi, S., & Ficarella, A. (2024). Enhancing resilience in complex energy systems through real-time anomaly detection: A systematic literature review. Energy Informatics, 7(1), 96. https://doi.org/10.1186/s42162-024-00401-8
Alex-Omiogbemi, A. A., Sule, A. K., Omowole, B. M., & Owoade, S. J. (2024). Conceptual framework for advancing regulatory compliance and risk management in emerging markets through digital innovation. World Journal of Advanced Research and Reviews, 24(3), 1155–1162. https://doi.org/10.30574/wjarr.2024.24.3.3752
Bourechak, A., Zedadra, O., Kouahla, M. N., Guerrieri, A., Seridi, H., & Fortino, G. (2023). At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives. Sensors, 23(3), 1639. https://doi.org/10.3390/s23031639
Burlea-Schiopoiu, A., & Ferhati, K. (2020). The Managerial Implications of the Key Performance Indicators in Healthcare Sector: A Cluster Analysis. Healthcare, 9(1), 19. https://doi.org/10.3390/healthcare9010019
Conduah, A. K., Ofoe, S., & Siaw-Marfo, D. (2025). Data privacy in healthcare: Global challenges and solutions. Digital Health, 11, 20552076251343959. https://doi.org/10.1177/20552076251343959
Crossette-Thambiah, G., Berleant, D., & AbuHalimeh, A. (2024). An Information Quality Framework for Managed Health Care. Journal of Healthcare Leadership, 16, 343–364. https://doi.org/10.2147/JHL.S473833
Eboigbe, E. O., Farayola, O. A., Olatoye, F. O., Nnabugwu, O. C., & Daraojimba, C. (2023). Business intelligence transformation through AI and data analytics. Engineering Science & Technology Journal, 4(5), 285–307. https://doi.org/10.51594/estj.v4i5.616
Fagbenle, E. (2025). Leveraging predictive analytics to optimize healthcare delivery, resource allocation, and patient outcome forecasting systems. International Journal of Research Publication and Reviews, 6(4), 6224–6239. https://doi.org/10.55248/gengpi.6.0425.14143
Fanta, S., Amir, M., & Riau, D. P. (2024). The Role of Protocols in Facilitating the Activities of Regional Heads Secretariat at the Central Buton District. International Journal of Scientific Research in Science, Engineering and Technology, 11(2), 04–09. https://doi.org/10.32628/IJSRSET2411135
Fournier, F., & Skarbovsky, I. (2021). Real-Time Data Processing. In C. Södergård, T. Mildorf, E. Habyarimana, A. J. Berre, J. A. Fernandes, & C. Zinke-Wehlmann (Eds.), Big Data in Bioeconomy: Results from the European DataBio Project (pp. 147–156). Springer International Publishing. https://doi.org/10.1007/978-3-030-71069-9_11
Hassan, M., Kushniruk, A., & Borycki, E. (2024). Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review. JMIR Human Factors, 11, e48633. https://doi.org/10.2196/48633
Kgakatsi, M., Galeboe, O. P., Molelekwa, K. K., & Thango, B. A. (2024). The Impact of Big Data on SME Performance: A Systematic Review. Businesses, 4(4), 632–695. https://doi.org/10.3390/businesses4040038
Kumar, Y., Marchena, J., Awlla, A. H., Li, J. J., & Abdalla, H. B. (2024). The AI-Powered Evolution of Big Data. Applied Sciences, 14(22), 10176. https://doi.org/10.3390/app142210176
Lawal, O. P., Igwe, E. P., Olosunde, A., Chisom, E. P., Okeh, D. U., Olowookere, A. K., Adedayo, O. A., Agu, C. P., Mustapha, F. A., Odubo, F., & Orobator, E. T. (2025). Integrating Real-Time Data and Machine Learning in Predicting Infectious Disease Outbreaks: Enhancing Response Strategies in Sub-Saharan Africa. Asian Journal of Microbiology and Biotechnology, 10(1), 147–163. https://doi.org/10.56557/ajmab/2025/v10i19371
Lawal, O. P., Taiye, A. F., Okafor, C. E., Elechi, K. W., Orobator, E. T., Kolapo, T. J., Olaniyi, A. O., Mandal, M., & Olaniyi, H. I. (2025). The Automated Insulin Delivery System in Nigeria: Advances, Challenges, And Future Prospects in Closed-Loop Insulin Delivery Systems. Journal of Medical Science, Biology, and Chemistry, 2(1), Article 1. https://doi.org/10.69739/jmsbc.v2i1.501
Martin, K. D., Kim, J. J., Palmatier, R. W., Steinhoff, L., Stewart, D. W., Walker, B. A., Wang, Y., & Weaven, S. K. (2020). Data Privacy in Retail. Journal of Retailing, 96(4), 474–489. https://doi.org/10.1016/j.jretai.2020.08.003
Matshaka, L., Fumani, N. M., Khoza, J. K., Thango, B. A., & Matshaka, L. (2024). Evaluating the Impact of Database and Data Warehouse Technologies on Organizational Performance: A Systematic Review (No. 2024100059). Preprints. https://doi.org/10.20944/preprints202410.0059.v1
Mositsa, R. J., Van der Poll, J. A., & Dongmo, C. (2023). Towards a Conceptual Framework for Data Management in Business Intelligence. Information, 14(10), 547. https://doi.org/10.3390/info14100547
Oladejo, M. T., Botes, V., Low, M., & Reeves, S. (2024). Blockchain technology disruptions: Exploring accounting and auditing academics and practitioners' perception. Accounting & Finance. https://doi.org/10.1111/acfi.13383
Olaitan, O. F., Akatakpo, O. N., Victor, C. O., Emejulu, C. J., Ayoola, T. M., Olayiwola, D. E., & Ajibola, A. A. (2025). Secure and Resilient Industrial IoT Architectures for Smart Manufacturing: A Comprehensive Review. Journal of Engineering Research and Reports, 27(6), 331–344. https://doi.org/10.9734/jerr/2025/v27i61548
Olaitan, O. F., Ayeni, S. O., Olosunde, A., Okeke, F. C., Okonkwo, U. U., Ochieze, C. G., ...., & Akatakpo, O. N. (2025). Quantum Computing in Artificial Intelligence: A Review of Quantum Machine Learning Algorithms. Path of Science, 11(5), Article 5. https://doi.org/10.22178/pos.117-25
Ragazou, K., Passas, I., Garefalakis, A., & Zopounidis, C. (2023). Business intelligence model empowering SMEs to make better decisions and enhance their competitive advantage. Discover Analytics, 1(1), 2. https://doi.org/10.1007/s44257-022-00002-3
Rane, N. L., Mallick, S. K., Kaya, O., & Rane, J. (2024). Applications of machine learning in healthcare, finance, agriculture, retail, manufacturing, energy, and transportation: A review. Applied Machine Learning and Deep Learning: Architectures and Techniques (112-131). Deep Science Publishing. https://doi. org/10.70593/978-81-981271-4-3_6.
Sedlakova, J., Daniore, P., Horn Wintsch, A., Wolf, M., Stanikic, M., Haag, C., Sieber, C., Schneider, G., Staub, K., Alois Ettlin, D., Grübner, O., Rinaldi, F., & von Wyl, V. (2023). Challenges and best practices for digital unstructured data enrichment in health research: A systematic narrative review. PLOS Digital Health, 2(10), e0000347. https://doi.org/10.1371/journal.pdig.0000347
Seh, A. H., Zarour, M., Alenezi, M., Sarkar, A. K., Agrawal, A., Kumar, R., & Ahmad Khan, R. (2020). Healthcare Data Breaches: Insights and Implications. Healthcare, 8(2), 133. https://doi.org/10.3390/healthcare8020133
Shamsuddoha, M., Khan, E. A., Chowdhury, M. M. H., & Nasir, T. (2025). Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow. Information, 16(1), 26. https://doi.org/10.3390/info16010026
Sidek, R. S., Samsudin, A. Z., Rozali, E. A., Sham, F. M., Hanafiah, M. H. M., Safiai, M. H., & Murtza, M. H. A. (2025). Feasibility Studies Across Disciplines: A Systematic Review of Methodologies, Applications, and Strategic Insights. International Journal of Research and Innovation in Social Science, 9(3), 209-212.
Tong, L.-K., Tam, H.-L., & Mao, A.-M. (2025). A Bibliometric Review of Person-Centered Care Research 2010–2024. Healthcare, 13(11), 1267. https://doi.org/10.3390/healthcare13111267
Vudathaneni, V. K. P., Lanke, R. B., Mudaliyar, M. C., Movva, K. V., Mounika Kalluri, L., & Boyapati, R. (n.d.). The Impact of Telemedicine and Remote Patient Monitoring on Healthcare Delivery: A Comprehensive Evaluation. Cureus, 16(3), e55534. https://doi.org/10.7759/cureus.55534
Yin, J., Qiu, X., & Wang, Y. (2025). The Impact of AI-Personalized Recommendations on Clicking Intentions: Evidence from Chinese E-Commerce. Journal of Theoretical and Applied Electronic Commerce Research, 20(1), 21. https://doi.org/10.3390/jtaer20010021
Zreikat, A. I., AlArnaout, Z., Abadleh, A., Elbasi, E., & Mostafa, N. (2025). The Integration of the Internet of Things (IoT) Applications into 5G Networks: A Review and Analysis. Computers, 14(7), 250. https://doi.org/10.3390/computers14070250