Poste Italiane S.p.A.

Total investments

10

Average round size

41M

Portfolio companies

7

Lead investments

2

Follow on index

0.30

Areas of investment
InternetSoftwareFinancial ServicesFinTechInformation TechnologyFinanceBankingBitcoinAdviceWealth Management

Summary

The typical startup value when the investment from Poste Italiane S.p.A. is 100-500 millions dollars. The top activity for fund was in 2019. The usual things for fund are deals in the range of 50 - 100 millions dollars. The fund is generally included in 2-6 deals every year.

The typical case for the fund is to invest in rounds with 3-4 participants. Despite the Poste Italiane S.p.A., startups are often financed by Upscale, United Ventures, Fondazione di Sardegna. The meaningful sponsors for the fund in investment in the same round are Opera Tech Ventures, Insight Partners, Heartcore Capital.

Among the most popular portfolio startups of the fund, we may highlight Moneyfarm. Moreover, a startup needs to be at the age of 6-10 years to get the investment from the fund. Among the most successful fund investment fields, there are Financial Services, Wealth Management.

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Investments analytics

Analytics

Total investments
10
Lead investments
2
Follow on index
0.30
Investments by industry
  • Financial Services (6)
  • FinTech (5)
  • Software (5)
  • Banking (2)
  • Wealth Management (2)
  • Show 8 more
Investments by region
  • Sweden (2)
  • United Kingdom (2)
  • Italy (3)
  • United States (3)
Peak activity year
2020

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Quantitative data

Avg. startup age at the time of investment
8
Avg. valuation at time of investment
218M
Group Appearance index
0.70

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Latest deals

Company name Deal date Industry Deal stage Deal size Location
Scalapay 03 May 2022 E-Commerce, Internet, Retail, Information Technology, Mobile Payments Early Stage Venture 27M Lombardy, Milan, Italy
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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.