色花堂

AI and Financial Risk Modeling

date
May 31, 2022
To
time
7:00-8:00pm
听辫蝉迟
location
ZOOM
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AI and Financial Risk Modeling

date
May 31, 2022
To
time
7:00-8:00pm
听辫蝉迟
location
ZOOM
join us!
THANK YOU!

We will send you an confirmation to your email as soon as possible.

Oops! Something went wrong while submitting the form.
Watch

description

Our virtual 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.

鈥婼辫别补办别谤蝉

鈥 - , 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鈥檚 talk with cover:

鈥媁hat 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?

鈥 - CTO,

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鈥檚 product and engineering teams. His passion for inventing new technologies鈥攑articularly in data mining and AI鈥攈as 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鈥檚 talk will cover:

鈥婣I increases the accuracy of lending decisions -- leading to more approvals and decreased risk compared to traditional credit scores. 聽But if left unchecked, AI might also amplify historical biases, leading to the increased race and gender discrimination. 聽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 .

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