Document Type : Original Research Paper

Author

• Leili Niakan

Associate Professor, General Insurance Group, Insurance Research Center, Tehran, Iran.

Abstract

BACKGROUND AND OBJECTIVES: The insurance industry, as a critical pillar of national economic infrastructure, is increasingly data-driven, facing the challenge of managing and utilizing vast volumes of both structured and unstructured data. With the exponential growth of digital operations, the ability to effectively harness big data has become essential for enhancing organizational performance, improving customer experiences, and gaining competitive advantage. This study focuses on evaluating the maturity of big data implementation in the Iranian insurance sector over an extended period, identifying key progress areas, existing challenges, and practical pathways to advancement.
METHODS: To this end, a longitudinal, descriptive-survey research design was employed. The research was conducted at two distinct time points—2016 and 2024—across a sample of 25 Iranian insurance companies. The study adopted the TDWI Big Data Maturity Model, selected due to its comprehensive framework, industry validation, and clarity in categorizing organizational maturity into five levels: nascent, pre-adoption, early adoption, corporate adoption, and mature/visionary. Data collection was carried out using a standardized TDWI questionnaire, administered to a statistical sample comprising IT managers, domain experts, and senior personnel with in-depth knowledge of their companies’ data practices. Participants completed the questionnaire through a self-assessment process. The TDWI model used in this study incorporates multiple dimensions of big data maturity, including technical capabilities, organizational readiness, and customer-related aspects—most notably, customer online trust. Each dimension was evaluated through a range of indicators aimed at measuring implementation, integration, and strategic alignment with big data goals.
FINDINGS: The findings demonstrate a clear and significant increase in big data maturity across the sector over the eight-year study period. The average maturity score among the participating companies rose from 12 in 2016—corresponding to the "nascent" stage—to 29 in 2024, placing them within the "early adoption" category. More specifically, the number of companies operating at the nascent level dropped drastically from 18 to only 2, while the number of organizations attaining higher maturity levels saw a proportional rise. This trend signals growing awareness, investment, and institutional commitment to data-driven strategies within the industry. The study also reveals the progress made in individual maturity dimensions. Indicators related to "customer online trust" experienced marked improvement in the majority of companies, implying that insurers have made efforts to align digital platforms and service delivery with customer expectations regarding privacy, transparency, and system reliability. However, despite overall progress, the "data management" dimension continued to lag behind others, with an average score of 25, indicating a “pre-adoption” status. This reflects a persistent challenge in establishing strong data governance frameworks, centralized data architectures, and integrated data lifecycle management practices. In terms of statistical analysis, correlation tests were conducted to explore potential relationships between big data maturity and organizational characteristics. Results disclosed no significant correlation between maturity levels and company size—measured by the number of employees, number of branches, or financial turnover. In contrast, significant positive correlations were found between maturity levels and two key factors: the size of the IT budget allocated and the perceived level of online trust in the company’s information systems; especially when benchmarked against peer organizations. These results suggest that investment in digital infrastructure and customer trust-building measures are more predictive of maturity advancement than traditional organizational metrics. Based on these insights, the study offers several practical recommendations. Firstly, it underscores the need for insurance companies to develop and implement a comprehensive big data strategy aligned with business objectives and customer needs. Secondly, investing in the education, training, and development of specialized human resources in big data analytics is essential to sustaining long-term progress. Thirdly, fostering cross-organizational collaboration, including knowledge-sharing and benchmarking activities among insurance firms, can accelerate collective maturity growth across the industry.
CONCLUSION: This study highlights significant progress in big data maturity across the Iranian insurance industry between 2016 and 2024. While notable improvements have been achieved—particularly in customer-oriented dimensions such as online trust—core areas like data management remain underdeveloped, indicating the need for more balanced digital growth. The lack of correlation between maturity level and company size suggests that strategic vision and IT investment play a greater role than scale alone. To advance further, insurance firms should prioritize developing long-term data strategies, invest in specialized human capital, and foster industry-wide knowledge sharing. Policymakers can support this evolution through standardized frameworks and benchmarking initiatives. Overall, digital transformation through big data is well underway in the sector, but unlocking its full value requires strengthening internal capabilities, aligning organizational structures with data objectives, and cultivating a culture of innovation and trust.

Keywords

• Big data
• Data analysis
• Maturity assessment model
• Insurance industry longitudinal study

Main Subjects

• New Insurance Technologies