'Trusted AI' for central banks

Eva Morin is currently working as an AI expert within the SupTech function at the European Central Bank (ECB), where I contribute to the development and deployment of data-driven and machine learning solutions to enhance supervisory processes. Previously, she worked as a supervisor in vertical supervision, which gives me both an operational and strategic perspective on the use of AI in supervision.

All financial organizations currently face an exceptionally challenging external environment: increasing regulatory pressures, heavy reliance on external third-parties, dominance of cloud based services and Artificial Intelligence (AI), all amid makes issues related to Third Party Risk Management prominent for both regulators and organizations alike.

With a track record of successfully establishing a robust third party risk management (TPRM) function at the International Monetary Fund (IMF), Section Chief, Suyog Peshkar brings a unique perspective on the intersection of operational risks and outsourcing.

In his twenty plus years’ experience, Suyog has advised global firms as well as provided hands-on expertise in delivering outsourcing solutions to generate higher cost savings, mitigate risks and derive efficiencies. Suyog completed a LLM in Commercial and Corporate Law from the University of London and a Masters in Analysis, Design and Management of Information Systems from the London School of Economics (LSE), which enables him to provide ‘techno-legal’ advisory on complex issues related to sourcing governance, risk management and third party compliance.

Recognized as an operational and third party risk expert, Suyog is regularly invited to speak at industry conferences, risk panels and UN seminars. 

Juri Marcucci is Advisor at the DG for Economics, Statistics and Research at the Bank of Italy. He has served as adjunct professor at the Universities of Bologna, Rome Tor Vergata, and Rome Sapienza, and has been a visiting scholar at the Federal Reserve Bank of Boston, Universitat Pompeu Fabra, and UC San Diego. He holds a Ph.D. in Economics from UC San Diego and a doctoral degree from the Sant’Anna School of Advanced Studies in Pisa. His research lies at the intersection of macroeconomic forecasting and data science, with a particular focus on artificial intelligence, machine learning, natural language processing, and big data. He is the organizer of the Italian Summer School of Econometrics and co-organizer of the international webinar series Applied Machine Learning, Economics, and Data Science (AMLEDS). His work has appeared in leading peer-reviewed journals, and he has served as guest editor for the Journal of Econometrics, the International Journal of Forecasting, and Econometrics.