Daniela Scidá is a manager and financial economist in the Quantitative Supervision and Research group of the Richmond Fed’s Banking Supervision function. Scidá is currently based in Charlotte, North Carolina. Her research interests lie in the areas of applied econometrics, time series methods, network analysis, banking, financial stability and Natural Language Processing (NLP). Her recent research focuses on financial networks estimation through NLP methods.

Scidá currently leads a supervisory innovation project that leverages NLP methods. Previously, she served as deputy lead of the Pre-Prevision Net Revenue modeling team of the Federal Reserve System Stress Testing program. Scida’s supervisory experience includes model development and forecasting under stress conditions, as well as examination from participation in the CCAR program and climate scenario analysis from participation in the Fed’s Climate Scenario Analysis (CSA) Pilot. She served as coordinator of the QSR Seminars and Brown Bags series for many years. She currently manages and mentors our Research Assistants team.

Before joining the Richmond Fed in 2016, Scidá completed her doctorate in economics at Brown University. She received a bachelor’s degree in economics from Universidad Nacional de Tucumán, Argentina, a master’s degree in economics and finance from Centro de Estudios Monetarios y Financieros (CEMFI), Spain, and a master’s degree in economics from Brown University. Scidá is originally from Tucumán, a small province in the north of Argentina.