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Home / Business and Economy / Stripe Mafia' Funds Business ID Startup Duna to $33M

Stripe Mafia' Funds Business ID Startup Duna to $33M

5 Feb

•

Summary

  • Business identity startup Duna secured €30 million in Series A funding.
  • The company aims to build a global trust infrastructure for businesses.
  • Duna's vision includes a digital passport for businesses to reuse verified identity information across platforms.
Stripe Mafia' Funds Business ID Startup Duna to $33M

Business identity verification startup Duna has secured €30 million in Series A funding, solidifying its position as a well-funded European venture. Co-founded by former Stripe employees Duco Van Lanschot and David Schreiber, Duna focuses on improving business customer onboarding for fintech companies.

The startup's core offering helps reduce churn associated with corporate ID checks and fraud prevention. Duna's ambition extends to creating a global trust infrastructure, enabling businesses to use a 'digital passport' for verified identity information across various platforms.

This vision attracted investment from Alphabet's CapitalG, which led the round. Duna's approach of generating its own data, rather than aggregating existing sources, sets it apart from competitors in the Know Your Business (KYB) sector.

With backing from notable figures in the fintech space, including current and former Stripe executives, Duna is poised to scale its operations. The company is strategically targeting "patches of networks" to accelerate the adoption of its identity verification reuse system.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
Duna aims to build a global trust infrastructure, offering a digital passport for businesses to reuse verified identity information across multiple platforms.
Duna was co-founded by former Stripe employees Duco Van Lanschot and David Schreiber.
Duna distinguishes itself by generating its own data for business verification, rather than aggregating existing, often incomplete, data sources.

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