Citation:

Thulasiram Prasad, Pasam. "Transforming Insurance Operations with Real-Time Data: Boosting Efficiency and Customer Engagement" International Research Journal of Economics and Management Studies, Vol. 4, No. 3, pp. 202-209, 2025.

Abstract:

The research demonstrates the way data in real-time influences business operations and client interaction in business, using the case of the insurance sector. Insurance businesses optimize their workflows, reduce waste, and enhance their client interactions through data analytics in real time. The influence of data incorporation on business decisions and where business improvement is possible is prioritized by the study. The report mentions using data in real time to ensure business competition in an ever-changing industry. It offers insights into successful applications in business, using the case of the insurance sector.

References:

[1] Mbau, R., Musiega, A., Nyawira, L., Tsofa, B., Mulwa, A., Molyneux, S., Maina, I., Jemutai, J., Normand, C., Hanson, K. and Barasa, E., 2023. Analysing the efficiency of health systems: a systematic review of the literature. Applied health economics and health policy, 21(2), pp.205-224.
[2] Abikoye, B.E., Akinwunmi, T., Adelaja, A.O., Umeorah, S.C. and Ogunsuji, Y.M., 2024. Real-time financial monitoring systems: Enhancing risk management through continuous oversight. GSC Advanced Research and Reviews, 20(1), pp.465-76.
[3] Javed, A.R., Shahzad, F., ur Rehman, S., Zikria, Y.B., Razzak, I., Jalil, Z. and Xu, G., 2022. Future smart cities: Requirements, emerging technologies, applications, challenges, and future aspects. Cities, 129, p.103794.
[4] Ngcobo, K., Bhengu, S., Mudau, A., Thango, B. and Lerato, M., 2024. Enterprise data management: Types, sources, and real-time applications to enhance business performance-a systematic review. Systematic Review| September.
[5] Zarifis, A., Holland, C.P. and Milne, A., 2023. Evaluating the impact of AI on insurance: The four emerging AI-and data-driven business models. Emerald Open Research, 1(1).
[6] Kargar, K. and Joksimovic, D., 2024. Analysis of sewer blockage causes using open data. Water Practice & Technology, 19(9), pp.3855-3866.
[7] Kargar, K. and Joksimovic, D., 2024. Analysis of sewer blockage causes using open data. Water Practice & Technology, 19(9), pp.3855-3866.
[8] Ajiga, D., Okeleke, P.A., Folorunsho, S.O. and Ezeigweneme, C., 2024. Methodologies for developing scalable software frameworks that support growing business needs. Int. J. Manag. Entrep. Res, 6, pp.2661-2683.
[9] Xu, Y., Zhang, X., Li, H., Zheng, H., Zhang, J., Olsen, M.S., Varshney, R.K., Prasanna, B.M. and Qian, Q., 2022. Smart breeding is driven by big data, artificial intelligence, and integrated genomic-environs prediction. Molecular Plant, 15(11), pp.1664-1695.
[10] Lechner, H.J., 2023. The knowledge-sharing culture in an operational excellence plants as competitive advantage for forward-thinking organizations. International Journal of Social Sciences, 9(1), pp.23-39.
[11] Botha, M., 2025. Critical realism, community psychology, and the curious case of autism: A philosophy and practice of science with social justice in mind. Journal of Community Psychology, 53(1), p.e22764.
[12] Babu, M.M., Rahman, M., Alam, A. and Dey, B.L., 2024. Exploring big data-driven innovation in the manufacturing sector: evidence from UK firms. Annals of Operations Research, 333(2), pp.689-716.
[13] Waldock, C., Stuart‐Smith, R.D., Albouy, C., Cheung, W.W., Edgar, G.J., Mouillot, D., Tjiputra, J. and Pellissier, L., 2022. A quantitative review of abundance‐based species distribution models. Ecography, 2022(1).
[14] Cahyaningrum, Y., 2024. Optimization of Information Technology Through Intelligent System Integration: Comprehensive Exploration. Journal of Intelligent Systems and Information Technology, 1(1), pp.1-5.
[15] Sembiring, I., Rahardja, U., Manongga, D., Aini, Q. and Wahab, A., 2024. Enhancing aiku adoption: Insights from the role of habit in behavior intention. Aptisi Transactions on Technopreneurship (ATT), 6(1), pp.84-108.
[16] Sedrak, M.S., Freedman, R.A., Cohen, H.J., Muss, H.B., Jatoi, A., Klepin, H.D., Wildes, T.M., Le‐Rademacher, J.G., Kimmick, G.G., Tew, W.P. and George, K., 2021. Older adult participation in cancer clinical trials: a systematic review of barriers and interventions. CA: a cancer journal for clinicians, 71(1), pp.78-92.

Keywords:

Insurance, Customer, Insurance Businesses, Industry.