safe Financial Big Data Cluster (safeFBDC) – Use Case: Sustainable Finance


German Federal Ministry for Economic Affairs and Climate Action  (Bundesministerium für Wirtschaft und Klimaschutz BMWK)

Project Leader

Dr. Christian Haas – Postdoctoral Researcher

Mathilde Bossut – Junior Researcher


Description of Project

The safeFBDC project aims at developing a secure solution for the cross-organizational exchange of data and at driving AI-related innovation in the financial sector. In particular, the use case sustainable finance led by the Frankfurt School is looking at improving methods in considering sustainability factors in credit and investment decisions.

A decentralized approach to financial data availability

In recent years the will to thrive towards a competitive and prosperous digital environment rose to the top of the European agenda. Early-2020, French and German ministries launched the project Gaia-X with the aim to develop a federated and secure European Data infrastructure. This initiative also resonated in the financial markets. On the grounds of a project founded by the Federal Ministry for Economic Affairs and Climate Action (BMWK), major European economic players joined forces to form a Financial Big Data Cluster (FBDC); making it the use case of Gaia-X in the financial domain. The Financial Big Data Cluster (“FBDC”) aims at building a decentralized data and infrastructure ecosystem for finance and hence, enable a secure cross-organizational exchange of data and increase transparency in financial markets while safeguarding individual data sovereignty.

 safeFBDC, a R&D Project to drive AI-related innovation in finance

 In connection to the FBDC, the BMWK is funding a Research & Development project called “Investigation of the Suitability of a Financial Big Data Cluster (FBDC) for Securing Data Sovereignty in the Financial Sector” (project acronym “safeFBDC”), as part of the BMWK innovation competition “Artificial Intelligence as a Driver for Economically Relevant Ecosystems”.  During this three year-project, the consortia partners will research, develop, and prototypically validate AI-based methods in five use cases – i.e., sustainable finance, supply-chain finance, anti-money laundering finance, market integrity and monetary policy. The safeFBDC use cases and the respective results shall be implemented and perpetuated in the FBDC, as far as possible. The Frankfurt School and its researchers are leading two of the use cases.

The Frankfurt School-UNEP Centre leads on Sustainable Finance

The Frankfurt School-UNEP Centre leads the Sustainable Finance uses case, supported by the Helaba bank, Deloitte and further strategic partners. The aim of the use case is to improve the currently often insufficient availability and quality of ESG data. The central approach is to test and further develop innovative AI and ML methods to improve the consideration of ESG risks in financial institutions’ credit and investment decisions.  The work of the Frankfurt School researchers is organised in three workstreams:

  • Identification of creditworthiness-driving sustainability factors for capital market-oriented and private companies.
  • Analysis of patterns in successful recovery of companies exposed to floods and identification of resilience-determining factors for private companies.
  • Contribution to the provision of climate stress-testing methodologies and ML-based forecasts at the company-level.

Towards a platform solution for sustainable finance

Finally, the use case sustainable finance is working in close collaboration with the European Data Trustee (EuroDaT ) to develop a platform for sustainable finance. Based on a close exchange with financial institutions and real economy actors, including SMEs, we aim at identifying, and, when possible, untangling the legal and technological challenges.  The FBDC aims at providing a solution for the exchange of data between real and financial entities.

Learn more about the FBDC project on the official project website.