Using artificial intelligence in insurance: ZhongAn Company as a case study
Youzhi WANG, Yuliya A. SOLOV'EVA · Finance and Credit · 28 Oct 2026
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- Will AI actually boost productivity and growth? · its finding: it depends (why studies differ)
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Abstract
Subject. Application of artificial intelligence technologies in the operations of the Chinese internet insurance company ZhongAn – the first professional online insurer in China. Objectives. To conduct a comprehensive assessment of the impact of artificial intelligence technologies on the operational efficiency of the insurance company and to identify factors limiting the full realization of the potential of digital transformation. Methods. The study employed comparative analysis of operational indicators for 2019–2024, trend analysis of the dynamics of investments in research and development, financial analysis of performance indicators, SWOT analysis, and content analysis. Results. It has been established that the automation of the insurance company’s key business processes through artificial intelligence has reached extremely high levels: the underwriting automation rate is 99%, the reduction in claims settlement time is 87.5%, and employee productivity has increased 30‑fold. A paradox of efficiency has been identified: the growth in operational performance is accompanied by a persistently high level of consumer complaints, the opacity (non‑interpretability) of algorithms, risks of homogenization, and a shortage of personnel. A similar phenomenon has also been observed in the Russian insurance market. The hypothesis has been confirmed that technological efficiency alone is not a sufficient condition for sustainable profitability and consumer trust. Conclusions. For Russian insurers, ZhongAn’s experience demonstrates the need for the simultaneous development of technological infrastructure, human capital, and a customer‑oriented culture. The key success factor is the transformation from a technological pioneer into a responsible leader by ensuring the transparency of artificial intelligence systems and striking a balance between innovation and trust.
About this publication
Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.
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- 2026 (recently)
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