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Insforce AI No-Code Insurance Core Platform

1) Platform Subscription: Annual SaaS subscription fees charged to small and medium-sized insurers and reinsurers; 2) Tr

MODEL

Key Fields

FIELD STAMPS

IndustryFintech

RegionChina

ScaleMid-size

ChannelOnline

📌 Background

In 2026, the insurance industry faces pressure for digital transformation, with regulators encouraging the use of technology to improve underwriting efficiency and claims experience. AI and low-code platforms enable small and medium-sized insurance companies to rapidly launch new products, implement dynamic pricing, and achieve intelligent underwriting. According to the 2025 annual report of ZhongAn Online, its total annual premiums reached 35.735 billion yuan, a year-on-year increase of 6.9%, with an underwriting profit of 1.412 billion yuan, up 42.5%, marking its fifth consecutive year of underwriting profitability. Over 45% of health insurance cases are processed through automated review, with the fastest settlement taking only 15 seconds.

👤 Target Customers

Insurance companies, particularly small and medium-sized insurers and reinsurance institutions, paying platform usage fees and value-added service fees.

💰 Revenue Streams

1) Platform Subscription: Annual SaaS subscription fees charged to small and medium-sized insurers and reinsurers; 2) Transaction-based Fees: Platform usage fees charged based on the volume of policies underwritten; 3) Advanced Model Commission: Transaction commissions charged for the use of advanced models; 4) Custom Implementation: One-time implementation fees charged for customized projects.

🧮 Cost Structure

R&D and model training costs, cloud computing resources, data acquisition and compliance audits, sales and channel expenses.

🛡️ Moat

Proprietary industry-specific underwriting model library, no-code rapid deployment framework, and deep integration with regulatory data interfaces.

🔑 Keys to Success

Continuous iteration of AI models
No-code platform ecosystem partners
Standardization of regulatory data interfaces

⚠️ Risks

Rapid technological evolution requires frequent platform upgrades
Changes in regulatory policies leading to increased compliance costs
Potential payout risks if core models exhibit bias or errors

🏢 Cases

Insforce platform completed its first round of financing in 2025 and has served over 30 insurance companies
ZhongAn Online achieved a 10% premium growth in 2025 by utilizing the AI underwriting system

📊 SWOT Analysis

Strengths

Industry-specific AI models with high accuracy
No-code platform shortens time-to-market
Initial pilot programs secured with multiple insurance companies

Weaknesses

High dependency on high-quality labeled data
High costs for model compliance audits

Opportunities

Regulatory push for InsurTech upgrades
Continuous growth in demand for online insurance

Threats

Homogeneous competition from large InsurTech giants like Ping An Technology
Stricter data privacy regulations may limit model training

Sources