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Estimating Policy Functions in Payments Systems Using Reinforcement Learning
Pablo Samuel Castro

Sat Jul 23 10:30 AM -- 11:00 AM (PDT) @
in AI for Agent-Based Modelling (AI4ABM) »

High-value payments systems (HVPSs) are used to settle transactions between large financial institutions and are considered the core national financial infrastructure. In collaboration with the Bank of Canada, we have been exploring the use of reinforcement learning techniques to understand the behaviour of banks participating in the Canadian HVPS. This understanding could help regulators design policies to ensure the safety and efficiency of these systems.

Author Information

Pablo Samuel Castro (Google Brain)

Pablo was born and raised in Quito, Ecuador, and moved to Montreal after high school to study at McGill. He stayed in Montreal for the next 10 years, finished his bachelors, worked at a flight simulator company, and then eventually obtained his masters and PhD at McGill, focusing on Reinforcement Learning. After his PhD Pablo did a 10-month postdoc in Paris before moving to Pittsburgh to join Google. He has worked at Google for almost 6 years, and is currently a research Software Engineer in Google Brain in Montreal, focusing on fundamental Reinforcement Learning research, as well as Machine Learning and Music. Aside from his interest in coding/AI/math, Pablo is an active musician (https://www.psctrio.com), loves running (5 marathons so far, including Boston!), and discussing politics and activism.

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