University of Maryland
In a graduate finance class, students are using Google’s AI suite, including Gemini, NotebookLM and AI Studio, to reimagine credit risk analysis. Using AI to process large amounts of public data from 40 banks and 17 fintechs over two years, they built a tool that is able to rate credit risk management effectiveness across financial institutions. “This project underscores AI’s capacity to distill profound insights from quantitative and complex qualitative data, revolutionizing financial analysis,” says Dr. Clifford V. Rossi, Academic Director, Smith Enterprise Risk Consortium, University of Maryland.
John Jay College
John Jay College collaborated with Google.org and DataKind on a predictive AI model to identify students most at risk of dropping out. Using 75 indicators, including attendance patterns and grade variations, the AI model creates a risk score for every student. Based on the score, the school can offer one-on-one coaching and support before the student faces trouble. After implementing the tool, senior graduation rates at John Jay rose from 54% to 86% in three years, an increase nearly unheard of in higher education.
Arizona State University
Working with Google Cloud AI, the Knowledge Enterprise team at Arizona State University can scale quickly and support many types of research needs, including big data analytics, complex simulations and machine learning models. ASU used Google Cloud AI to achieve a four times more accurate prediction of enrollment, boosting online registrations by 52%, and has been able to accelerate information sharing and collaboration between ASU researchers and partner organizations.
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