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Core Insights on Ping An Good Doctor's 'Commercial Insurance Direct Settlement' Service

#commercial_insurance_direct_settlement #online_medical #medical_insurance_ecosystem #revenue_optimization #risk_analysis
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HK Stock
December 29, 2025

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Core Insights on Ping An Good Doctor's 'Commercial Insurance Direct Settlement' Service

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Core Insights
  1. User Growth:
    Ping An Good Doctor’s ‘Commercial Insurance Direct Settlement’ service significantly shortens the closed-loop time from medical treatment to claim settlement for patients, providing the platform with an ultra-simple experience of ‘settlement upon discharge, zero advance payment’. This directly eliminates consumers’ concerns about tedious claim procedures, and is expected to attract high-frequency claim customers both inside and outside the Ping An ecosystem—especially high-net-worth comprehensive financial customers and employees covered by corporate health plans. These users have high repurchase rates and lifetime value, and strong demand for continuous services. [0][2]

  2. Revenue Model Optimization:
    This service strengthens the synergy between medical services and insurance payments, providing a fulcrum for Ping An Good Doctor to extend its service revenue toward higher value-added directions. On one hand, it can improve the bargaining power and fulfillment efficiency of scenario-based medical services, thereby increasing the gross margin of medical services; on the other hand, by leveraging the group’s insurance traffic (health insurance, property insurance, pension insurance, etc.) and superimposing the ‘commercial insurance + medical insurance’ clearing and settlement model, it further promotes the ‘managed care’ model, increases the proportion of non-pharmaceutical service revenue, and improves the quality of overall operating income. [0][3]

  3. Medical Ecosystem Competitiveness:
    ‘Commercial Insurance Direct Settlement’ is the concrete implementation of the ‘medical + insurance’ ecosystem synergy, strengthening the platform’s ability to deeply connect with high-quality tertiary hospitals (such as Wuhan Third Hospital). Once a standardized replication path is formed, it can become the platform’s differentiated moat. By deeply integrating with the insurance payment end, Ping An Good Doctor can more quickly integrate resources such as hospitals, doctors, pharmaceuticals/medical devices, and health management, forming a management closed loop similar to HMO, resisting internet medical platforms that rely solely on traffic or drug sales, and enhancing policy adaptability and service barriers. [0][4]

  4. Risks and Observations:
    Currently, the platform still has weak profitability (ROE 2.39%, net profit margin 3.05%) and high valuation risks (P/E ratio of about 145 times for 2025). Short-term observation is needed on the cost and institutional feasibility of replicating the ‘Commercial Insurance Direct Settlement’ service in other regions, as well as the pace of synchronous advancement of medical insurance and commercial insurance policies. [0]

  5. Recommendations:
    If further quantification is needed regarding the service’s penetration into B-end corporate customers, cost savings brought by medical-insurance data feedback, and the gap with competitors (such as Alibaba Health, JD Health) in the commercial insurance segment, consider enabling the
    in-depth research mode
    to obtain richer industry reports, professional databases, and chart analyses.

References

[0] Jinling API Data
[1] VBData - “Settlement Upon Discharge, Zero Advance Payment: Ping An’s ‘Commercial Insurance Direct Settlement’ Service Lands in Wuhan” (https://www.vbdata.cn/1519055981)
[2] Ping An Good Doctor - “New Benchmark for Integration of Medical Insurance and Commercial Insurance, Opening a New Era of Seamless Fast Settlement” (https://www.pagd.net/allPage/sustainableDevelopment/article/101118)
[3] Sina Finance - “Behind Rising Expectations: Ping An Good Doctor Creates a New Model of Chinese HMO | Industry Observation” (https://finance.sina.com.cn/xwzmt/2025-12-22/doc-inhcsrpa9069140.shtml?froms=ggmp)

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Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.