This workshop will focus on opportunities for big data and predictive analytics in finance and economics, including new approaches to modeling, measuring, and understanding risk.
Technological advancements have transformed financial markets into increasingly complex and dynamic systems. Organizations including banks, asset management firms, information technology firms, and regulatory agencies are all: increasingly interconnected; managing transactions at sub-millisecond time scales; and generating, storing, and managing masses of data. This creates challenges and opportunities when it comes to understanding and managing risk in financial systems — for example: How can we leverage big data to develop better analytical methods for predicting bubbles and collapses in financial systems? Can we use data to map and model interconnections across financials systems toward better understanding systemic risk and how disruptions propagate? What are the opportunities for creating new financial forecasting tools and risk metrics? This workshop will bring together stakeholders from across industry, government and academia to discuss these opportunities and priorities for research and innovation in this area.
This workshop will explore:
- priorities for financial firms and regulators in assessing and managing risk;
- opportunities for big data and machine learning in better understanding behavior and modeling the interconnections and complex dynamics in financial systems;
- using statistical models and algorithms to improve decision-making and design policies;
- novel applications for emerging technologies, including blockchain and encryption techniques;
- applying new techniques to enable data sharing while managing privacy;
- opportunities to collaborate on developing resources, open source tools and platforms, and new predictive analytic metrics that enable a deeper understanding of risk and new approaches to monitoring risk and improving stability in financial markets.
Invited participants will bring perspectives from across disciplines including finance, economics, statistics and data science, and social sciences. We will use this workshop to explore innovate ideas at the intersection of these fields and generate an output document that summarizes challenges and priorities for research.
Founded July 2015, the mission of MIT’s new Institute for Data, Systems, and Society (IDSS) is to advance education and research in state-of-the-art, analytical methods in information and decision systems; statistics and data science; and the social sciences, and to apply these methods to address complex challenges in areas such as finance, energy, urbanization, and health.