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| + | - Bi-weekly coffe chats - next on Thu Nov 5th 09am https://www.meetup.com/Fintech_AI_in_Finance/ | ||
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* [[Technical Coordination]] | * [[Technical Coordination]] | ||
* [[News]] | * [[News]] | ||
Revision as of 10:12, 4 November 2020
CA19130 - Fintech and Artificial Intelligence in Finance - Towards a transparent financial industry
- Working group 1 - Transparency in FinTech
- Working group 2 - Transparent versus Black Box Decision-Support Models in the Financial Industry
- Working group 3 - Transparency into Investment Product Performance for Clients
Action Content at this Wiki
- Next MC meeting 12th November 9-11am
- Bi-weekly coffe chats - next on Thu Nov 5th 09am https://www.meetup.com/Fintech_AI_in_Finance/
COST Action Summary
The financial sector is the largest user of digital technologies and a major driver in the digital transformation of the economy. Financial technology (FinTech) aims to both compete with and support the established financial industry in the delivery of financial services. Globally, more than $100 billion of investments have been made into FinTech companies and Artificial Intelligence (AI) since 2010, and continue growing substantially. In early 2018, the European Commission unveiled (a) their action plan for a more competitive and innovative financial market, and (b) an initiative on AI with the aim to harness the opportunities presented by technology-enabled innovations. Europe should become a global hub for FinTech, with the economy being able to benefit from the European Single Market.
The Action will investigate AI and Fintech from three different angles: Transparency in FinTech, Transparent versus Black Box Decision-Support Models in the Financial Industry and Transparency into Investment Product Performance for Clients. The Action will bridge the gap between academia, industry, the public and governmental organisations by working in an interdisciplinary way across Europe and focusing on innovation.
The key objectives are:
- to improve transparency of AI supported processes in the Fintech space
- to address the disparity between the proliferation in AI models within the financial industry for risk assessment and decision-making, and the limited insight the public has in its consequences by developing policy papers and methods to increase transparency
- to develop methods to scrutinize the quality of products, especially rule-based “smart beta” ones, across the asset management, banking and insurance industries.