Innovation
Our products are backed by research, data science, and population-level survey responses. We’re advised by technology and finance industry experts to create best-practice tools that truly benefit schools and students.
Academic Backing
Our ideas stem from academic theories dating back to Milton Friedman’s 1955 essay on how the government can help diversify education risk to a population level. Since then, we’ve taken the core, and learned from previous implementations, like the Department of Education’s SAVE and REPAYE programs, to evolve our idea to correctly address problems of today.
Model Projections
Using large data bases of higher education data concerning grants, earning outcomes, costs, and other metrics, we’ve built a robust machine learning model to accurately project earning distributions for decades after graduating, for any student, any major, at any school. Our databases allow us to mitigate risk in income-contingent repayment programs.
Survey Results
We conducted large scale surveys to determine whether or not our innovations will have positive reception. Using the survey results, we’ve been able to fine-tune our products and understand education financing trends among students that did not attend college due to financial barriers.