Dr. Fatena El-Masri is a Senior Financial Analyst at the Federal Deposit Insurance Corporation. She is a data scientist with years of experience in financial engineering, applied statistics, quantitative risk modeling, and market, credit and operational risk management. For her Computational Science and Data Science Ph.D. dissertation at George Mason University, she used Python and agent-based models to study the stability of the banking network. Dr. El-Masri has also managed a Proof of Concept Artificial Intelligence project using IBM Watson, Natural Language Processing, and Robotic Process Automation (RPA) for object detection & Video Analytics.
You can find her talk from QuantCon 2018, titled Network-based Modeling of Complex Systems, with Applications to Cascading and Contagion Events in Networks, below. In this talk, she looks at how network-based modeling can be used to analyze cascading and contagious events in financial networks. Dr. El-Masri’s research started with the simulation of 63 million records to determine the network and dynamic connectivity between different banks. This connectivity is determined by transforming the adjacency matrix for the data using Python. The agent-based model is then applied using dynamic modeling and validated using real data. The results are then implemented using network-based modeling for complex financial institutions to discover the cascading and contagious event behavior in the networks.
In addition to her talk, Dr. El-Masri also sat down for an interview to give us insight into her personal and professional life. In this video, she walks us through her professional journey from studying Engineering in Lebanon to working in Finance in the United States. She talks about her current research on network-based modeling and how the idea of “Too Small to Fail” can be applied to failing banks. She also opens up about her hope to create a program that would inspire young girls to explore STEM fields in the future. See the full interview below:
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