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AI and Risk Modeling

Past Event
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About Event

AI LA's virtual Special Interest Group (SIG) will include guest speakers on the topic of AI in finance. After our speakers present, we will begin our fireside chat and Q&A.


Jorge Tarraso - Libretto, Research, and Professional Development

In 2017, Jorge received a PhD in Economics from the University of Southern California, where he researched biases in financial decision-making. From 2017 to 2018 he worked as an Assistant Professor of Economics at Minerva University, a university that is pioneering in implementing the science of learning in higher education. He continues to leverage the science of learning in his work. In 2017 Jorge joined Libretto, a comprehensive wealth management software platform that enables advisers to produce robust financial solutions at scale, and currently leads research and professional development there.

Jorge’s talk with cover:

What is the difference between risk and uncertainty? Why are tools to solve problems under uncertainty different than tools to solve problems under risk? Under which risk-related decision-making circumstances does modeling fall short and instead we need solutions that do not require us to predict?

Jay Budzik - CTO, Zest.AI

Jay Budzik is the chief technology officer at Zest AI, a software company that helps banks and lenders build, run, and monitor fully explainable machine learning underwriting models. As CTO, Jay oversees Zest’s product and engineering teams. His passion for inventing new technologies—particularly in data mining and AI—has played a central role throughout his career. Before joining Zest, he held varied positions, including founding an AI enterprise search company, helping major media organizations apply AI and machine learning to expand their audiences and revenue, and developed systems that process tens of trillions of data points. Jay has a Ph.D. in computer science from Northwestern University.

Jay’s talk will cover:

AI increases the accuracy of lending decisions -- leading to more approvals and decreased risk compared to traditional credit scores.  But if left unchecked, AI might also amplify historical biases, leading to the increased race and gender discrimination.  I'll talk about how Zest is using advanced methods to take bias out of models and make financial services fairer.

The fireside chat will be moderated by Macielle Osterling.

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