The University of California, Berkeley (UC Berkeley) and State Street Global Exchange today announced a collaboration to establish the Consortium for Data Analytics in Risk (CDAR), a new research center focused on applying advanced data-science techniques to manage and mitigate economic and financial risk. The announcement comes as State Street opens GX Lab, its new presence in Silicon Valley focused on partnering with local talent, industry leaders, and academic institutions to create solutions for its clients in the fields of data science and risk management.
CDAR will bring together researchers from across UC Berkeley and build upon the programs of the Center for Risk Management Research (CRMR), an existing unit dedicated to understanding the dynamics of risk in financial markets. The work of the consortium will be tied to the mission of CRMR to address the most important and pressing issues in risk and portfolio management – a goal closely aligned with State Street’s commitment to helping solve its clients’ pressing challenges.
An additional founding member of the consortium is Stanford University’s Center for Financial and Risk Analytics, which pioneers models, algorithms and numerical tools to address questions related to financial markets. A fourth founding member from within the technology industry will be named later this year.
“We are excited to be working with leading data scientists to tackle the immensely complex data challenges that face our clients and the institutional financial services industry today,” said Jessica Donohue, executive vice president and chief innovation officer, State Street Global Exchange. “CDAR has significant potential to forge new pathways in the fields of data science and risk management and improve insights that can be actionable for our clients.”
As part of the collaboration, CDAR will organize and sponsor conferences, workshops and research related to data and analytics with industry and academic experts in fields such as statistics, economics, finance, mathematics, electrical engineering, computer science and industrial engineering and operations.
“We are honored that State Street has chosen UC Berkeley to oversee this vitally important research initiative,” says Carla Hesse, executive dean for the College of Letters & Science. “This consortium will provide our researchers with a unique opportunity to work with and learn from State Street, and to apply leading-edge analysis tools to both public and proprietary data to better understand the complex interactions that drive the global economy. CDAR has the potential to become a formidable brain trust for merging data science with risk measurement and management.”
State Street will draw upon the expertise of data scientists from across disciplines through its new membership in the Berkeley Institute for Data Science (BIDS), which was established in 2013 to explore how data science can address important questions about highly complex topics, such as the nature of the universe, climate and biodiversity, seismology, neuroscience, human behavior and other areas. BIDS is led by Saul Perlmutter, a Nobel Prize-winning physicist, and brings together domain experts from the life, social, and physical sciences and methodological experts from computer science, statistics, and applied mathematics to address major challenges related to data-centric research.
“The financial crisis highlighted the urgent need for better financial risk management tools,” says Robert M. Anderson, director of the CRMR. “We are delighted to partner with State Street Global Exchange to develop data-driven tools to manage financial risk.” Lisa R. Goldberg, CRMR’s research director, commented that “There is tremendous power in a partnership between industry and academia. Together, they can achieve much more than either can do alone.”
According to a recent survey commissioned by State Street of more than 400 senior executives at investment organizations, integrating data scientists and their insight into existing operations is the number one priority, with fifty percent of respondents intending to prioritize investment in the quality and availability of data talent over the next three years.