With appropriate privacy safeguards, enhanced financial data sharing could improve market discipline, augment consumer protection, and unlock new opportunities for research. To that end, could regulatory agencies set up “clean rooms” to share anonymi...
What is the future of financial data modeling and analytics? This panel explores cutting-edge techniques including agent-based modeling, machine learning, textual extraction and computational representation, and predictive analytics, and explores pot...
What are the most significant barriers data scientists face in integrating and reconciling various types and sources of data, including issues of standards, unique identity, ownership, and semantic translation? How should users efficiently and effect...
Conference welcome by Michael Barr, Faculty Director, University of Michigan Center on Finance, Law and Policy; Roy F. and Jean Humphrey Proffitt Professor of Law, University of Michigan Law School; Professor of Public Policy, University of Michigan ...
As the number and scope of available data sets proliferate, can we help ensure that proprietary data remains private and secure on one hand, and usable and shareable within and among organizations on the other hand? This panel will explore challenges...
Private-sector firms, regulators, and academic researchers alike face challenges regarding the reliability and availability of market-wide financial data. Even when reliable data is available, moreover, “stovepipes” within firms and within and among ...
Big Data raises a number of significant ethical, legal, and sociopolitical questions. Is Big Data used in discriminatory ways and, if so, how can discrimination be prevented? Is Big Data invading our privacy? Who owns Big Data, and what does it mean ...
