China Fintech Fund

Total investments

2

Average round size

107M

Portfolio companies

2

Lead investments

1

Exits

1

Areas of investment
AccountingInternetSoftwareFinancial ServicesFinTechB2BFinanceEnterprise SoftwareNetwork SecurityBanking

Summary

When the investment is from China Fintech Fund the average startup value is 100-500 millions dollars. The usual things for fund are deals in the range of more than 100 millions dollars. The important activity for fund was in 2015. The fund is generally included in less than 2 deals every year.

We can highlight the next thriving fund investment areas, such as Financial Services, FinTech. Besides, a startup needs to be aged 2-3 years to get the investment from the fund. Among the most popular portfolio startups of the fund, we may highlight Dianrong, freee.

The usual cause for the fund is to invest in rounds with 5 partakers. Despite the China Fintech Fund, startups are often financed by DCM Ventures, e.ventures, Tiger Global Management. The meaningful sponsors for the fund in investment in the same round are Tiger Global Management, Standard Chartered Bank, SBI Asset Management. In the next rounds fund is usually obtained by Simone Investment Managers, SBI Investment, ORIX Asia Capital Ltd.

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Investments analytics

Analytics

Total investments
2
Lead investments
1
Exits
1
Investments by industry
  • Finance (2)
  • Financial Services (2)
  • Software (1)
  • B2B (1)
  • Enterprise Software (1)
  • Show 6 more
Investments by region
  • China (1)
  • Japan (1)
Peak activity year
2015
Number of Unicorns
1
Number of Decacorns
1

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Quantitative data

Avg. startup age at the time of investment
8
Avg. valuation at time of investment
710M
Group Appearance index
1.00
Strategy success index
0.40

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Dianrong 20 Aug 2015 Internet, Financial Services, FinTech, Finance, Marketplace Late Stage Venture 207M China, Shanghai
How we get our data

At Unicorn Nest, we combine cutting-edge technology with human expertise to build one of the most reliable venture capital databases in the market. Our process begins with automated AI-enhanced data collection, leveraging the full potential of Large Language Models (LLMs).

Later, our team of analysts takes it further with manual verification, using proprietary tools for data cleaning and validation to ensure accuracy and reliability. We cross-check and enhance our findings through press and media monitoring, integrating information from trusted news outlets and venture capital aggregators. Finally, we stay ahead of the curve by monitoring social networks like LinkedIn and X.com.