Renzo advises financial institutions on using analytics tools to solve complex business and economic problems, and address regulatory issues. He is a thought leader in credit risk modeling, Comprehensive Capital Analysis and Review (CCAR), and model risk management using econometrics, statistics, probability theory, and machine learning.
With 15 years of experience advising financial institutions, Renzo develops bespoke risk management solutions using econometric modeling techniques, grounded in a deep understanding of the business and economic nature of each problem. He has developed and validated a large variety of models used by banks to manage financial risks, including credit risk models for underwriting and meeting the Current Expected Credit Losses standard (CECL), CCAR models, and equity valuation models. He has pioneered the use of machine learning in banks with a focus on explainability and transparency. He has led complex programs to remediate regulatory actions, applying analytics and economics.
Renzo has a master of arts degree, a master of philosophy, and a PhD in economics from Yale University, a master of science degree in economics from the London School of Economics, and a bachelor of arts degree, also in economics from Bocconi University in Milan. He has served as peer reviewer for the National Science Foundation.