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Sesame Enterprise Credit Business Profile Reconstruction for Micro-Merchant Credit

1) Charging financial institutions credit assessment API call fees and data service fees; 2) Charging merchants value-ad

MODEL

Key Fields

FIELD STAMPS
IndustryFintech
RegionChina
ScaleGiant
ChannelOnline

📌 Background

By the end of 2024, China had over 60 million SMEs and approximately 125 million individual industrial and commercial households with opaque information, making it difficult for systems to systematically identify their true operating status. In 2026, Ant Group's Sesame Enterprise Credit launched a business profile reconstruction solution for small and medium-sized merchants, covering 50 million SMEs nationwide for the first time. It replaces single credit scores with hourly updated data on business registration, judicial records, and store sales, alongside 'person-enterprise-store' relationship chains. After integrating this solution, a leading B2B platform saw its potential customer reach rate increase to 50% and its paid member conversion rate double.

👤 Target Customers

Financial institutions (banks, consumer finance companies) pay for credit assessment and marketing services; micro-merchants gain loan matching opportunities.

💰 Revenue Streams

1) Charging financial institutions credit assessment API call fees and data service fees; 2) Charging merchants value-added credit certification service fees; 3) Revenue sharing with loan-facilitation platforms based on loan matching volume.

🧮 Cost Structure

Data collection and compliance governance costs AI model training and computing power costs Business channel expansion and personnel costs

🛡️ Moat

Massive payment and business behavior data accumulated within the Ant ecosystem Over a decade of credit technology model iteration experience Network effects covering 50 million merchants

🔑 Keys to Success

  • Multi-dimensional data fusion under a data compliance framework
  • Continuous iteration of business profile model prediction accuracy
  • Financial institution channel expansion and scenario embedding

⚠️ Risks

  • Data sources restricted due to tightening data privacy regulations
  • Financial institutions replacing third-party services with self-built risk controls

🏢 Cases

  • Sesame Enterprise Credit Person-Enterprise-Store Business Profile Reconstruction Solution
  • Ant Sesame Credit SME Credit Assessment Service

📊 SWOT Analysis

Strengths

  • Deep data barriers within the Ant ecosystem
  • Leading scale with business profiles covering 50 million SMEs
  • Proven doubling of conversion rates

Weaknesses

  • Increasing regulatory pressure on data compliance and personal information protection
  • Over-reliance on data sources within the Alipay ecosystem

Opportunities

  • Continued release of policy dividends for the 'last mile' of micro-finance
  • New entrants like ByteDance's Zixin validating market value and expanding the market

Threats

  • Entry of competitors such as ByteDance's Zixin dividing the market
  • Traditional banks enhancing their self-built risk control capabilities, reducing outsourcing demand