ZhongAn Online P & C Insurance Co (ZZHGF) Fair Value & Analysis
Financial Services · US · Market cap $2.5B
Fair value as of: Jun 26, 2026
Analysis
ZhongAn Online P & C Insurance Co (ZZHGF) currently trades at $1.50, while our model-based Fair Value estimate is $1.26 — implying the stock looks roughly 16.0% overvalued today. We read business quality at 95/100 (high quality), in the Financial Services sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
ZhongAn Online P & C Insurance Co., Ltd., an Internet-based Insurtech company, provides internet insurance and insurance information technology services in the People's Republic of China. It operates through Insurance, Technology, Banking, and Others segments. The company offers critical illness, health, and outpatient and emergency insurance; e-commerce insurance; travel accident, and flight or hotel cancellation insurance; motor insurance; cargo and shipping return insurance; credit and bond insurance; pet, pet food safety, pet transport protection, pet anesthesia accident, pet critical illness insurance, pet third-party liability, pet death compensation, and employee accident insurance for the pet industry; liability insurance; and drone and household property insurance solutions. It also offers IT related business, international IT consulting; banking services; and online life insurance services, insurance brokerage, and medical services. In addition, the company offers technolo…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.