Recognizing 10 Years of Innovation with Equifax Academic Partnerships

Through its Academic Partnerships program, Equifax collaborates with top universities to research and develop next-generation data science solutions. To continue pushing the boundaries of what is possible, the organization partners with leading academic institutions to give students hands-on experience using Equifax differentiated data to solve real-world business problems. 

Since 2016, these course-long capstone projects are undertaken by students at the end of their academic programs and give them an opportunity to apply what they’ve learned in the classroom to create a real-life customer-focused solution.

“The Equifax academic partnership program allows us to continually work with university professors and their students to bring a fresh perspective to solving business challenges while simultaneously giving students a competitive edge in their future careers through hands-on access to exclusive data and advanced technology,” said Gail Wetzel, Vice President of Data & Analytics at Equifax. “The program has resulted in over 40 completed capstone projects, 11 foundational patents filed by Equifax from its work with universities, and invaluable experience for the data and analytic leaders of the future.”

Recent projects from the spring 2026 semester tackled a range of current complex challenges, from data quality automation to explainable AI modeling:

Georgia Tech

A team of students from the Scheller College of Business Steven A. Denning Technology & Management program focused on the development of Bilinear Self-Attention Regression (BSAR). This explainable AI architecture is tailored for analyzing consumer credit data, specifically addressing the "black box" limitations of traditional AI. The students created a novel, interpretable model that offers high predictive accuracy alongside transparent decision reasoning. The transformer-based models achieved substantial improvements on datasets related to payment grids and credit utilization.

Also at Georgia Tech, students in the Quantitative Computational Finance (QCF) program developed explainable, attention-based modeling for credit risk using BSAR Transformers.

• By analyzing raw credit data, including 24-month utilization and payment behavior sequences, the team achieved a 9.3% performance lift over traditional models.

• They laid the foundations for translating complex AI attributes into understandable concepts.

• The project delivered reusable infrastructure to explore how to make AI attributes  analyst-friendly and ready for governance-compliant deployment.

University of Georgia

Students in the Terry College of Business’  MS in Business Analytics program focused on developing an internal dashboard to enhance operational insights into the Equifax Ignite® platform. By centralizing disparate data sources through advanced analytics and visualization, the team created a unified interface for monitoring customer engagement. The dashboard enables the proactive management of account health and the effective identification of potential churn risks. The project established a robust technical framework for future AI-driven capabilities, such as predictive scoring and anomaly detection.

Emory University

In the Goizueta Business School’s MS in Business Analytics program, the capstone project included creating a streamlined workflow to automate manual data quality validation processes.

• The team developed a three-layer pipeline that executed deterministic checks, provided diagnostic remediation, and integrated human-in-the-loop approvals.

• By shifting from a manual process to an intelligent, configuration-driven automation, the team reduced the time requirements of a core component of validation from weeks to hours.

• This implementation will lower operational costs, standardize high-quality governance documentation, and accelerate model deployment.

University of Central Florida

Students in the Barry S. Miller College of Business' MS in FinTech program completed two separate advanced projects. The first project estimated the effect of government intervention programs on consumer default risk using causal machine learning. The second project focused on synthetic identity fraud detection via address intelligence, equipping businesses with new ways to identify and stop sophisticated fraud attempts.

These capstone projects demonstrate the power of collaboration between industry and academia. By partnering with universities, Equifax gains access to cutting-edge research and fresh perspectives, while students gain valuable real-world experience and the opportunity to make a real impact.

Groundbreaking research is one step in creating industry-leading data solutions. Learn how Equifax approaches the development of new innovations.