Ein Blog der ZHAW Zürcher Hochschule für Angewandte Wissenschaften
On 2 October 2025, more than 2,000 participants gathered in Oerlikon to explore one of today’s most transformative topics: the impact of artificial intelligence on business, science, and society. The large-scale event, organised in collaboration with the ETH AI Center, ZHAW, and the University of Zurich, brought together experts and innovators from across disciplines to […]
Artificial intelligence is transforming the financial industry, from consulting and analysis to asset management. The MSc Banking & Finance at ZHAW not only imparts in-depth financial knowledge, but also expands on this with practical skills in the field of artificial intelligence. From 2026, the new major Generative AI & AI Agents, led by Dr. Bledar […]
On November 14, 2024, Marc Weibel had the opportunity to moderate a roundtable at the Swiss AI Summit in Zurich. The topic, „AI in Finance and Sustainable Investing“, brought together experts from academia and industry. The stage featured Nicolas Jamet, Portfolio Manager at RAM AI, and Kai Gramke, CEO of Econsight AG, who shed light […]
The AI in Risk & Compliance – Know-How & Networking Event focuses on cross-bank exchange and the transfer of relevant knowledge regarding how AI impacts the risk and compliance functions within financial institutions. Technological progress is reshaping the risk and compliance functions of Swiss and Liechtenstein financial institutions. It is crucial to position oneself, leverage […]
Using sentiment information in the analysis of financial markets has attracted much attention. Natural language processing methods can be used to extract market sentiment information from texts such as news articles. The objective of this paper is to extract financial market sentiment information from news articles and use the estimated sentiment scores to predict the […]
Our innovative idea is to provide a Proof of Concept concerning a superior and adaptive rating system applicable to both SME and personal lending, able to cope with low-quality, sparse data that is commonplace in the context of P2P lenders. If successful, we will have both a new methodology (how to deal with low-quality, sparse […]
