Cornell students integrate AI and large language models to advance financial forecasting tools
Two Cornell students are developing a financial forecasting app using AI and large language models like ChatGPT. Their research improves sales forecasting methods for retail companies.

Cornell Students Apply AI to Enhance Financial Forecasting Tools
Two Cornell College students are developing a more efficient financial forecasting tool by integrating artificial intelligence, specifically large language models (LLMs) like ChatGPT. This work is part of the Cornell Summer Research Institute (CSRI) and involves collaboration with Associate Professor of Finance Huan Cai.
Jillian Witt, a rising junior, and Liam Borer Seabloom, a rising senior studying finance and data science, focus on improving sales forecasting methods used by retail companies. Their goal is to build a user-friendly app that combines AI capabilities with established financial forecasting techniques.
“AI can solve complex problems and improve productivity,” Witt said. “Our research helps reveal both the benefits and limitations of AI in finance.”
Borer Seabloom has been programming in Python and using OpenAI’s API to interact with ChatGPT 4.1. He explained, “We prompt the model with financial statements to extract clear, well-formatted insights that support forecasting.”
Witt handles competitive research and outreach, connecting with software developers to analyze existing products and ensure their app offers unique value. She noted, “Working with Professor Cai is rewarding—she supports my growth beyond this project.”
Professor Cai emphasizes the importance of sales forecasting as the foundation of equity valuation. “Our research explores how LLMs can improve this critical first step,” she said.
The CSRI program concludes on July 11. Cornell College is a private liberal arts school located in Mount Vernon, with an undergraduate enrollment of just over 1,000 students for the 2025-26 academic year.
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