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The impact of big data technology application on the technical efficiency of insurance firms: empirical evidence from Chinese insurers

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  • Guo, Jiafeng
  • Yang, Luwei
  • Zhou, Xinhong
  • Jiang, Guoliang

Abstract

Big data technologies have increasingly permeated the entire value chain of the insurance industry, encompassing all stages of firm operations. However, whether the application of big data can enhance the technical efficiency of insurance firms and address challenges stemming from historically extensive management practices remains insufficiently examined. This study constructs a dictionary-based measure of big data technology application across three dimensions: foundational big data infrastructure, data analytics capabilities, and application scenarios within the firm. Using micro-level panel data from 88 Chinese insurance companies spanning 2012 to 2023, we estimate firms’ technical efficiency and its decomposition by applying the Slack-Based Measure Data Envelopment Analysis (SBM-DEA) model with undesirable outputs. To assess the causal impact of big data adoption on technical efficiency, we employ a variety of empirical strategies, including fixed effects panel models, instrumental variable (IV) estimation, difference-in-differences (DID), and double machine learning methods. The results consistently show that big data technology application significantly improves the technical efficiency of insurance firms. We identify three primary mechanisms underlying this effect: the development of insurtech, improved risk-bearing capacity, and enhanced claims settlement performance. These findings underscore the importance of promoting the adoption of big data technologies in the insurance sector, with particular emphasis on optimizing factor allocation, fostering knowledge-sharing, and advancing insurtech innovation.

Suggested Citation

  • Guo, Jiafeng & Yang, Luwei & Zhou, Xinhong & Jiang, Guoliang, 2025. "The impact of big data technology application on the technical efficiency of insurance firms: empirical evidence from Chinese insurers," Finance Research Letters, Elsevier, vol. 86(PF).
    • Handle: RePEc:eee:finlet:v:86:y:2025:i:pf:s1544612325020823
    DOI: 10.1016/j.frl.2025.108828
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