FAME is a joint effort of world-class experts in data management, data technologies, the data economy, and digital finance, aiming to develop and launch to the global market a unique, trustworthy, energy-efficient, and secure federated data marketplace for Embedded Finance (EmFi).
6 Reasons to Explore
Single federated data marketplace platform.
Discover, Exchange and Trade Data Assets across heterogeneous data platforms and Marketplaces.
Managing Data in-line with European Values.
Learning Center (LC) for tech and non-tech users.
Transparency and Flexibility in Market-Driven Value-based Monetization.
Interconnected marketplace with more than twelve (12+) existing data marketplaces
Discover FAME’s Innovative Solutions
Marketplace
The FAME Federated Data Marketplace for Embedded Finance is a Data Space, according to the definition of the EU, customized for buying and selling federated data assets in the financial sector.
Accessible through a unified entry point, the Marketplace allows for secure data access, sharing, trading and analysis through FAME’s analytical tools for both finance and non-finance organizations, tech and non-tech users, and other end-users.
Learning Centre
The FAME Learning Centre (LC) integrates and offers training resources for both tech and non-tech users through a variety of formats, such as training courses, whitepapers, webinars, technical documentation, as well as step-by-step tutorials about FAME developments and the FAME Marketplace.
The LC’s training resources will be integrated as data assets in the Marketplace, and a selection of them are already available on the project website and/or YouTube channel.
Pilots
FAME’s seven pilot projects address unique challenges in the finance sector, each aiming to test and validate the FAME Marketplace and the analytical tools. From citizens wallets to using advanced technology to simplify financial operations and ESG investments to climate predictions for property insurance, FAME’s pilots cover a variety of use cases.
DISCLAIMER
The FAME project has received funding from the European Union’s Horizon 2023 Research and Innovation Programe under grant agreement nª 101092639.
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Horizon Europe. Neither the European Union nor the granting authority can be held responsible for them.
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