The COST Action Fintech and Artificial Intelligence in Finance

The COST (Cooperation in Science and Technology) Action 19130
49 countries, 200+ researchers from 100+ universities
Funded by the Horizon Europe Framework Programme of the EU
The network
Management CommitteeWorking group members

The Research Topics
Fintech, Artificial Intelligence in Finance, Transparency in Finance, Machine Learning, Blockchain, Cryptocurrencies
How to join our COST Action
Sign up for working group membership here.


Forum for interdisciplinary discussions and exchange of ideas on the adoption of innovative technologies in finance, bringing together academic and industry experts. The topics we would aim to cover include (but are not limited to):

  • Opportunities for AI adoption by the financial sector;
  • Challenges emerging from the fast adoption of novel technologies in the provision of financial services;
  • State of the art solutions.

In terms of the organization, we envision three sessions:

  • one featuring academic talks on AI’s applications in finance;
  • one offering the industry perspective; and finally,
  • one roundtable session with academic and industry experts

The conference is for free. We would kindly ask you to register: Conference Registration 


Artificial Intelligence in Finance

September 30, 2022, 13:00 – 17:00 (BFH Bern Business School, and online)

12:00 – 13:00

Registration and Check-In

13:00 – 13:15

Welcome and Opening

Prof. Dr. Christian Hopp, Prof. Dr. Branka Hadji Misheva, Prof. Dr. Jörg Osterrieder

Session I: COST Fintech and AI in Finance

Chair: Prof. Dr. Branka Hadji Misheva

13:15 – 13:45

Academic Keynote

Prof. Dr. Wolfgang K. Härdle, Humboldt University Berlin, Germany

13:45 – 14:05

Attention and sentiment around scheduled macroeconomic news announcements and the volatility on the U.S. Equity market

Prof. Dr. Stefan Lyocsa, Masaryk University, Brno, Czech Republic

14:05 – 14:25

Human-centered AI-based Bespoke Indexing Methodologies

Prof. Dr. Ronald Hochreiter, Vienna University of Business and Finance, Austria

14:25 – 14:45

Industry – Academia Talk on Fintech and Artificial Intelligence in Finance

Dr. Paul Bilokon, Imperial College and The Thalesians, London, UK

14:45 – 15:05

Industry Talk on Fintech and Artificial Intelligence in Finance

Bern Cantonal Bank, Switzerland

15:00 – 15:30

Coffee Break

Session II: COST Fintech and AI in Finance

Chair: Prof. Dr. Joerg Osterrieder

15:30 – 16:00

Industry Keynote

Bern Cantonal Bank, Switzerland

16:00 – 16:20

Why AI in Finance: A critical reflection and outlook in the year 2022

Sandro Schmid, LPA, Switzerland

16:20 – 16:30

Artificial Intelligence in Finance – The European COST Network

Prof. Dr. Joerg Osterrieder

16:30 – 17:00

Academic and Industry Roundtable, Closing and Outlook

17:00 – 18:00


18:00 – 20:30

Unesco World Heritage Walk and Conference Dinner

Info and Location

The conference is hosted at the BFH Bern University of Applied Sciences.

The Institute for Applied Data Science & Finance aims to establish itself as a leading Swiss research institute for data-driven, finance-based and strategic insights, analysis and value creation. To this end, an interdisciplinary team of around 25 researchers conducts research and teaching on topics relating to data science, data ethics, data and technology management, data-based business models, corporate financing, digital financing, taxation, accounting and financial reporting.

Bern University of Applied Sciences

Brückenstrasse 73


3005 Bern


Programme Committee

Prof. Dr. Nguyen Cuong, Lincoln University, New Zealand
Prof. Dr. Christian Hopp, BFH Bern University of Applied Sciences, Switzerland
Prof. Dr. Branka Hadji Misheva, Zurich University of Applied Sciences, Switzerland
Prof. Dr. Audrius Kabasinskas, Kaunas University of Technology, Lithuania 
Prof. Dr. Jörg Osterrieder, Zurich University of Applied Sciences, Switzerland
Prof. Dr. Valerio Poti, University College Dublin, Ireland
Prof. Dr. Catarina Silva, University of Coimbra, Portugal
Prof. Dr. Alessandra Tanda, University of Pavia, Italy
Prof. Dr. Simon Trimborn, City University Hong Kong, Hong Kong
Prof. Dr. Ania Zalewska, University of Bath, United Kingdom

Bios and Abstracts

Prof. Dr. Wolfgang Karl Härdle, Humboldt University Berlin, Germany

Wolfgang Karl Härdle completed his Dr. rer. nat. in Mathematics at Heidelberg University and received his habilitation in Economics at Bonn University. He was the founder and Director of Collaborative Research Center CRC 373 “Quantification and Simulation of Economic Processes” (1994 – 2003), Director of CRC 649 “Economic Risk” (2005 – 2016) and also of C.A.S.E. (Center for Applied Statistics and Economics) (2001 – 2014). He is currently heading the Sino-German Graduate School (洪堡大学 + 大学) IRTG1792 on “High dimensional non stationary time series analysis”. He is the Ladislaus von Bortkiewicz Professor at Humboldt-Universität zu Berlin and director of the BRC the joint Blockchain Research Centre with Zurich U.

His current research focuses on modern machine learning techniques, smart data analytics and the cryptocurrency eco system. He has published more than 40 books and more than 350 papers in top statistical, econometrics and finance journals. He is highly cited, and among the top scientist registered at REPEC and has similar top notch rankings in other scales, such as the Handelsblatt ranking. 

He has professional experience in financial engineering, structured product design and credit risk analysis. His recent research extends nonparametric paradigms into machine learning, decision analytics and data science for the digital economy. He is the Editor in Chief of the Springer Journal „Digital Finance“. He supervised more than 60 PhD students and has long-term research relations to research partners in the USA, Singapore, Prague, Warsaw, Paris, Cambridge, Beijing, Xiamen, Taipei among others.

Prof. Dr. Štefan Lyócsa, Masaryk University, Czech Republic 

Štefan Lyócsa is a professor at the Department of Finance of the Masaryk University, Brno, Czech Republic, where he supervises PhD students and leads Financial Management and Artificial Intelligence in Finance courses. He is also a researcher at the Slovak Academy of Sciences, where he is supervising research on ‘Systemic risk on financial markets: interconnectedness of financial institutions (APVV-18-0335)’. His main research interest is centered around market and credit risks. Over the past 5 years he published 30+ peer-reviewed papers among others in ‘International Journal of Forecasting’, ‘Journal of Economic Dynamics and Control’, ‘Journal of the Operational Research Society’, ‘The European Journal of Finance’, ‘Energy Economics’ or ‘Expert Systems with Applications’.

Attention and sentiment around scheduled macroeconomic news announcements and the volatility on the U.S. Equity market

Most of the literature recognizes the existence of a relationship between attention and sentiment of the general public with market price fluctuations. Yet, for forecasting purposes, it is unclear what information should we look for. Scheduled macroeconomic news announcements are regular and potentially price moving events; thus representing a potential target for information retrieval. We analyze how information related to scheduled macroeconomic news announcements retrieved from multiple data sources improves volatility forecasts of over 400 major U.S. stocks. Specifically, we extract attention and/or sentiment from social media, news articles, information consumption and search engine. Working within the penalized regression framework, complete sub-set regression framework and random forest, we identify which data sources and measures of public interest are driving future price fluctuations.

Prof. Dr. Jörg Osterrieder

Joerg Osterrieder is Professor of Finance at ZHAW. He has been working in the area of financial statistics, quantitative finance, algorithmic trading, and digitisation of the finance industry for more than 15 years.

Joerg is the Action Chair of the European COST Action 19130 Fintech and Artificial Intelligence in Finance, an interdisciplinary research network combining 200+ researchers and 38 European countries as well as five international partner countries. He is the director of studies for an executive education course on “Big Data Analytics, Blockchain and Distributed Ledger”, co-director of studies for “Machine Learning and Deep Learning in Finance” and has been the main organizer of an annual research conference series on Artificial Intelligence in Industry and Finance since 2016. He is a founding associate editor of Digital Finance, an editor of Frontiers Artificial Intelligence in Finance and frequent reviewer for academic journals.

In addition, he serves as an expert reviewer for the European Commission on the “Executive Agency for Small & Medium-sized Enterprises” and the “European Innovation Council Accelerator Pilot” programmes

Previously he worked as an executive director at Goldman Sachs and Merrill Lynch, as quantitative analyst at AHL as well as a member of the senior management at Credit Suisse Group. Joerg is now also active at the intersection of academia and industry, focusing on the transfer of research results to the financial services sector in order to implement practical solutions.

Artificial Intelligence in Finance – The European COST research network

Joerg will give an overview of the European COST Action Fintech and Artificial Intelligence in Finance. COST stands for Cooperation in Science and Technology and the is the longest running research funding agency in Europe. He is the Action Chair of this COST Action, a network of more than 200 researchers from 38 European countries and 5 international partner countries. The research is broadly focusing on Artificial Intelligence in Finance, with a specific emphasis on transparent financial markets, methods and products.

Prof. Dr. Ronald Hochreiter, WU Vienna
Ronald Hochreiter is Docent at WU Vienna University of
Economics and Business. He is President of the Academy of Data Science in Finance since 2017 and Vice-president of the Austrian Society of Operations Research since 2013. His research is based on Decision Science (Operations Research and Optimization under Uncertainty) as well as Data Science (Artificial Intelligence and Machine Learning) and applied to Algorithmic & Quantitative Finance, Social Science, Public Management, and Health Management. He serves as Principal Investor and partner for various national and international (EU) research projects. He is Program Director of the module Data Science within the Professional MBA on Digitalization and Data Science at the WU Executive Education.

Human-centered AI-based Bespoke Indexing Methodologies


Sandro Schmid, LPA
Sandro has over 20 years of experience in the financial services industry where he held different senior functions in front, risk, operations, and IT such as CEO, CRO, and COO. He was also a partner for two Big4s where he built up the advisory and risk consulting. Further, he founded “AAAccell”, a global Top100 FinTech and the “Swiss Risk Association”, which he chaired as president for almost 10 years. Sandro studied Economy and holds an MBA and a MAS as well as FRM and AI diplomas. He is/was also lecturing at different Universities such as University of Zurich, SFI and others.


Artificial intelligence (AI) is rapidly advancing in most industries around the world. To what extent did/will it transform financial services and if so, why or why not?



The conference is for free. We would kindly ask you to register: Conference Registration