Daniela Scidá is Manager and Financial Economist on our Quantitative Supervision and Research team in the Supervision, Regulation and Credit Department at the Richmond Fed. Scidá’s research interests include applied econometrics, network analysis, banking, and Artificial Intelligence (AI). Her recent work leverages AI methods to analyze financial networks, studying interconnectedness and its potential implications for financial stability.

At the Richmond Fed, Scidá co-leads a Risk and Surveillance team. She also leads projects that bring innovation into supervision through natural language processing. Scidá has extensive experience in stress testing, model development, and supervisory examination. Since joining the Richmond Fed in 2016, she also has contributed to supervisory research, coordinated seminar series, and managed research assistant teams.

Scidá holds a Ph.D. in economics and a master’s degree in economics from Brown University, a master’s in economics and finance from CEMFI in Spain, and a bachelor’s degree in economics from Universidad Nacional de Tucumán, Argentina.