The escalating significance of data in the digital economy cannot be overstated. Data serves as a fundamental input in driving advancements in Artificial Intelligence (AI), Machine Learning (ML), and Financial Information (FinTech) technologies, offering the potential to foster substantial innovation, enhance efficiency, lower inequality, inform policies and strategies, enlarge current markets, or penetrate novel markets. At the same time, the rise of the data economy is changing sources of revenue and sources of risk. Our research is designed to investigate the strategic utilization of data for growth and innovation, for transforming financial inclusion and democratizing financial markets, and for changing the competition landscape, and to undertake a comprehensive evaluation of policy regulations pertaining to data use and privacy.
Team
Core academic members
Affiliated academic members
Georgii Zvonka
Former PhD Student and Lab Web Manager
HEC Lausanne
Private sector project partners
Projects
Data and the Aggregate Economy
What do we know about attitudes towards privacy and the willingness of individuals or businesses to provide sensitive data?
What is the value of data for firms and consumers?
How is big data changing risk and uncertainty?
Who should own the data? How much should individuals be compensated for their data?
What is the relationship between Big Tech and big data?
Is the primary mechanism for addressing societal risks and potential harms by AI a solution that targets technical progress, regulations, consumer trust or something else?
Welfare and Inequality in the Digital Era
How do differences in access to digital services affect the way households save?
What are the implications of the rise of big data in finance?
How is inequality impacted by advances in financial information technologies?
What is the value of data for investors?
What are the implications of open-banking initiatives?
How can organizations quantify risks to individuals when risks and technologies are constantly changing?
Regulating the Data Economy
When developing best practices to audit their AI models, how should organizations effectively govern algorithmic models, data sets and algorithmic parameters?
How does digital regulation affect data collection and use?
What is the impact of digital regulation on firms and consumers?
What are the consequences of regulating BigTech?
What do we know about the value of research done using sensitive or confidential data, and of the costs associated with reducing the precision of the outputs of that research?
How will regulation of payment for order flow impact market data pricing?
Reviewer or Program Committee for AI & Finance-Related Conferences
