Overview

The financial system is in a phase of significant change; there are two major trends:

  1. Financial Data. Financial markets, the financial institutions operating in these markets, and the organizations and individuals using financial services generate massive amounts of data. Examples include market data, order book and transactions data, credit data, payment data, and behavioral data. While these data provide significant opportunities for financial firms, regulators, and policy makers, their processing and analysis is challenging, making it hard to harness the data for better decision making, more accurate analysis of risk, and higher efficiency.
  2. Financial Technology. The financial services industry is one of the biggest consumers of information technology (hard- and software). The technologies developed over the past several decades have dramatically changed the business of financial institutions. Recent innovations such as online payment technologies, equity crowdfunding, and marketplace lending have a significant impact on financial markets, institutions, corporations, and individuals.

The Center for Financial and Risk Analytics pioneers quantitative models, statistical methods, numerical algorithms, and software to address the challenging and important problems arising in this context. The Center’s faculty and doctoral students combine expertise in core areas such as stochastics, optimization, data science, and networks and algorithms with a deep understanding of financial markets and institutions to make fundamental advances of broad relevance. The Center promotes cross-disciplinary, multi-faceted approaches that draw from finance, economics, operations research, statistics, law, computational mathematics, computer science, and other fields.

The Center’s researchers are particularly interested in the analytics issues associated with big financial data. This includes the design, analysis and testing of efficient computational and statistical methods for processing and analyzing massive financial data sets. It also includes the development of comprehensive tools for making data-driven pricing, risk management, regulatory, and business decisions. The Center’s researchers have also a strong interest in the development of innovative financial technologies that have the potential to disrupt the financial services industry.

network

Core-periphery banking network. An illustration of the remarkable interconnectedness in the U.S. banking industry. Blue dots represent the biggest banks. Smaller banks are arranged according to their financial exposure, and therefore risk, to default by the larger institutions. Note, for instance, how strongly connected Freddie Mac is.