Ein Blog der ZHAW Zürcher Hochschule für Angewandte Wissenschaften
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 […]
In recent years, data science methods have been developed considerably and have consequently found their way into many business processes in banking and finance. One example is the review and approval process of credit applications, where they are employed with the aim to reduce rare but costly credit defaults in portfolios of loans. But there […]
“The major winners will be financial services companies that embrace technology.” Alexander Peh, PayPal and Braintree Over the last few years, Reinforcement Learning (RL) has gained significant attention as a framework for learning optimal decisions even in complex environments. Moreover, RL is currently considered one of the most promising research areas in machine learning and […]
For Switzerland, the reputation of stable long-standing financial institutions has always represented a crucial advantage for the acquisition and retention of customers. However, as the financial service industry becomes more global, clients expect personalized offerings and inclusiveness of service which in turn requires lenders to rely extensively on alternative data and advanced modelling techniques. Swiss […]
Identifying optimal strategies for sustainable investing remains hampered by a plethora of technical and methodological challenges. We propose to leverage patent data and AI to take green finance to a new level of efficiency in mitigating global threats such as climate change and pollution.
