IMPLICATIONS FOR BIG DATA AND ANALYTICS ON UNDERWRITING PRACTICES IN INSURANCE SECTOR
DOI:
https://doi.org/10.47672/ajdikm.1135Keywords:
Big Data, Analytics, Underwriting Practices, Insurance SectorAbstract
Purpose: Many businesses' approaches to data management have been revolutionized as a result of the advent of big data analytics. These days, companies are harnessing the power of the insights offered by big data in order to instantly establish more information about their customers and the ways in which they conduct business. The goal of this research is to analyze the implications for Big Data and analytics on underwriting practices in insurance sector.
Methodology: This was accomplished through the use of a desktop literature review. The use of Google Scholar was utilized in order to locate seminal references and journal articles that were pertinent to the study. Papers that were published no more than ten years prior were required to meet the inclusion criteria.
Findings: According to the findings of the study, top insurers' underwriting was significantly impacted by the digitization of their claims processes, which made use of big data and analytics. In this paper, the beneficial role of adopting technologies and tools of big data has been justified. These technologies and tools make it possible to develop powerful new business models, which, in turn, make it possible for the role of insurance to transition from "understand and protect" to "predict and prevent."
Unique contribution to theory, practice and policy: According to the findings of the study, various aspects of building up digital insurance control mechanisms that assist in maintaining the data integrity of underwriting processes should be implemented. When such advanced security frameworks are implemented, data integrity can be assured, and instances of fraud losses can be significantly reduced. In addition to this, there is a requirement for need-based training to be provided to underwriters regarding the implementation of digital management systems. Moreover, insurance companies should take advantage of the opportunities presented by technology in order to provide underwriters with an early warning of any potentially fraudulent activities
Downloads
References
Akkor, D. G., & Ozyukse, S. (2020). The effects of new technologies on the insurance sector: a proposition for underwriting qualifications for the future. Eurasian Journal of Business and Management, 8(1), 36-50.
Bhalla, A. (2012). Enhancement in predictive model for insurance underwriting. Int J Comput Sci Eng Technol, 3, 160-165.
Boyd, D. and Crawford, K., "Critical Questions for Big Data: Provocations for a Cultural, Technological and Scholarly Phenomenon" (2012) 15 Information Communication and Society 662, 663.
Burke, J., Bradley, L., & McLaughlin, C. (2021, August). Technological Advances in Life Insurance Underwriting Processes. In Irish Academy of Management Annual Conference 2021.
Dahiya, M., Sharma, S., & Grima, S. (2022). Big Data Analytics Application in the Indian Insurance Sector. In Big Data Analytics in the Insurance Market (pp. 145-164). Emerald Publishing Limited.
Desalegn, A. (2014). Assessment of Motor Insurance Business on Financial Performance of Insurance Company, The Case of Awash Insurance Company (Doctoral dissertation, St. Mary's University).
Dimas, A. (2017). Brazil: the new insurance giant. Reconteur, 7(3); 105-120
Eckert, C., & Osterrieder, K. (2020). How digitalization affects insurance companies: overview and use cases of digital technologies. Zeitschrift für die gesamte Versicherungswissenschaft, 109(5), 333-360.
Moturi, C. A., Okemwa, V. O., & Orwa, D. O. (2022). Big data analytics capability for digital transformation in the insurance sector. International Journal of Big Data Management, 2(1), 42-59.
Ndambo, D. (2016). Big data analytics and competitive advantage of commercial banks and insurance companies In Nairobi, Kenya (Doctoral dissertation, University of Nairobi).
Neale, F. R., Drake, P. P., & Konstantopoulos, T. (2020). InsurTech and the Disruption of the Insurance Industry. Journal of Insurance Issues, 43(2), 64-96.
Ngiri, S. M. (2021). Effect of Technology Adoption on Underwriting Processes among Top Five Insurance Companies in Nairobi County (Doctoral dissertation, United States International University-Africa).
Onyango, Otieno Winstan. (2021). Information and Communications Technology Capabilities and Performance of Insurance Companies in Kenya (Master Thesis dissertation, Kenyatta University).
Schmid, E. (2019). Underwriting Advisor to the Group EC, TechInsurer, 4(4); 28-36
The Geneva Association (2018). Big data and insurance: Implications for innovation, competition and privacy. [online] Available at: [Accessed on 12 March 2019].
Ularu, E. G., Puican, F. C., Apostu, A., & Velicanu, M. (2012). Perspectives on big data and big data analytics. Database Systems Journal, 3(4), 3-14.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Dr. Ben Kajwang PhD
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution (CC-BY) 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
