Collaborations within the Network
Anomaly and fraud detection in blockchain networks
This project will study the problem of anomaly and fraud detection from the perspective of blockchain-based networks. Anomaly and fraud detection in blockchain-based networks is more complex due to their unique properties such as decentralisation, global reach, anonymity, etc., which make them different from traditional networks.
International Advanced Fellowship on Digital Finance
The ongoing programme for strengthening and supporting research excellence at the BabeÈ™-Bolyai University (UBB) is further developed through the “STAR-UBB Academic Research Network of Excellence (STAR-UBB-N)” project, based on the Science, Technology, Engineering and Mathematics (STEM+) model implemented at an institutional level and coordinated by the Institute for Advanced Studies in Science and Technology – STAR-UBB – (STAR – Scientific and Technological Advanced Research)
COST Action 19130 - Fintech and AI in Finance
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.
SNSF - Narrative Digital Finance
The detection of financial bubbles is a topic of significant importance, not only for the financial industry but for society overall. For central banks it is crucial to identify systemic risks from imbalanced markets as early as possible in order to counteract timely and avoid financial crises.
The SNSF Narrative Digital Finance project aims to explore financial markets analysis around asset price bubbles and structural breaks with a novel approach, integrating narrative economics and natural language processing (NLP), with the ultimate goal of formulating a more holistic approach by including more available data.
SNSF - Network-based Credit Risk Modeling in Peer-to-Peer Lending Markets
The SNSF project "Network-Based Credit Risk Models in P2P Lending Markets" focuses on developing advanced and interpretable credit risk models tailored for peer-to-peer (P2P) lending platforms. Unlike traditional bank lending, P2P lending connects borrowers directly with investors via online platforms, bypassing banks. While P2P platforms offer lower operational costs and attract diverse investors, they also face higher credit risks due to looser regulation and greater information asymmetry. The project aims to address these risks by creating robust credit risk models to build trust and mitigate issues like adverse selection and moral hazard, especially in the face of economic crises.
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