Artificial Intelligence solutions are being rapidly adopted in the financial services industry covering a wide range of applications, as well as having an impact on risk management functions.
Data-driven approaches to risk management use technologies such as Machine Learning and Text Analytics to distill and correlate informative signals from large and unstructured data sources.
In this webinar the Prometeia Data Science team outlines the common thread of AI risk-related applications and techniques, as well as present some specific use cases.
Enzo is Head of Data Science Business Development at Prometeia. He has been working for 15+ years in the consulting industry where he managed several “Finance & Risk projects”, mainly for T1 banks and insurance companies.He combines management consulting and advanced analytics skills, supporting clients in the evolution of Risk Management framework leveraging on Artificial Intelligence and other Data Science techniques.He has a Master Degree in Risk Management and a Bachelor Degree in Mechanical Engineering from University of Palermo (Italy).
Michele Filannino, Ph.D.
Michele is a Research Data Scientist in Prometeia and a Research Scholar in the Computer Science and Artificial Intelligence Lab at the Massachusetts Institute of Technology. In Prometeia, his research focuses on applications of artificial intelligence and text analytics to economics. He taught Natural Language Processing and Artificial Intelligence at George Mason University (VA) and SUNY Albany (NY) as Adjunct Professor. He has a doctorate in computer science from The University of Manchester (UK) and a master's degree from the University of Bari (Italy).