Scientific Grant Holder: COST Action CA19130 - Fintech and AI in Finance
Hadji Misheva Branka is the scientific grant holder for COST Action CA19130. The primary responsibilities of a Grant Holder Manager include: coordination and implementation, financial and administrative duties, support and advisory role.
Factsheet
- Schools involved Business School
- Institute(s) Institute for Applied Data Science & Finance
- Research unit(s) Finance, Accounting and Tax
- Funding organisation Europäische Union
- Duration (planned) 01.06.2022 - 30.09.2024
- Head of project Prof. Dr. Jörg Robert Osterrieder
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Project staff
Prof. Dr. Jörg Robert Osterrieder
Prof. Dr. Branka Hadji Misheva
Yiting Liu
Lennart John Baals - Keywords Fintech, Artificial Intelligence, Finance
Situation
For the Scientific Grant Holder, the focus is placed on scholarly and research-oriented tasks. In the specific case of the COST Action on "FinTech and Artificial Intelligence in Finance," the Scientific Grant Holder is responsible for teaching data analytics, digital finance, AI, and ML for finance, alongside holding a pivotal administrative role in the COST Action.
Course of action
The COST FinAI network strategically navigates through research in AI and FinTech by promoting interdisciplinary collaboration across Europe, uniting academies, industry, and government organizations. The approach is comprehensive and develops innovative methodologies and conceptual tools to review financial services and their providers in the field of FinTech, utilizing advanced machine learning methods for early warnings and the detection of fraudulent behavior. It aims to enhance transparency within AI-supported processes and bridge the understanding gap between extensive AI applications in the financial world and public insight. Research objectives are structured to produce diverse outcomes such as stakeholder engagement strategies, policy development, comprehensive databases, and methodological advancements. Each activity is carefully aimed at contributing essential inputs to policy, industry practices, and academic research, with the promise to redefine the standards of transparency, integrity, and innovation in the financial world.
Result
The key objectives are: 1. to improve transparency of AI supported processes in the Fintech space 2. 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 3. to develop methods to scrutinize the quality of products, especially rule-based “smart beta” ones, across the asset management, banking and insurance industries.
