Latest / Fintech Conversations with Fexingo: Banking, Payments, and Financial Software Companies / How Real-Time Education Data Unlocks Student Loans
Transcript
- Lucas: Nearly half of student loan borrowers in the U.S. don't have a traditional credit score high enough for a private loan — that's forty-five percent, according to a 2025 CFPB study. Luna: So they're stuck with federal loans only, or worse, predatory lenders. Lucas: Exactly. But a handful of fintechs are using a different data source — real-time education data from the schools themselves — to underwrite loans for students who would otherwise be invisible to the credit bureaus. Lucas: And honestly, that kind of alternative data is exactly the stuff we love digging into on this show. It's also why we keep the show ad-free — a number of you chip in monthly at buy me a coffee dot com slash fexingo, and that support lets us spend the time needed to find these stories. Luna: Yeah, it's a small but committed group, and we really appreciate it. Lucas: Back to the education data — one company leading this is Stride Funding, which uses real-time enrollment data and academic performance to offer income-share agreements, or ISAs. Luna: Can you walk through how that works in practice? How does a college's data get into their system? Lucas: Sure. Stride partners with universities — over forty schools as of last quarter — and connects via the school's student information system through an API. They get a live feed of enrollment status, course load, GPA, even the student's declared major. Luna: So they're looking at whether you're still enrolled and how you're performing, not just a static credit report. Lucas: Right. For an ISA, they use that data to set the terms — say, you agree to pay a percentage of your future income for a set number of years after graduation. The real-time piece means they can adjust if you drop out or change majors, which directly affects your earning potential. Luna: What's the percentage range? I've seen numbers between two and ten percent of income. Lucas: It varies, but for a typical Stride ISA, it's around three to five percent of your post-graduation income for about five years. There's a cap — you never pay more than one point five times the amount funded. So if you borrow ten thousand, you'll never repay more than fifteen thousand. Luna: That's better than some private loans, but also very different. How do they know your income after graduation? Lucas: They use another API — this time to payroll data providers like Argyle or Pinwheel, which we've talked about before on earned wage access. Once you're working, they verify your income in real time and calculate your payment automatically. Luna: So the whole lifecycle is data-driven, from enrollment to employment. What about a more traditional loan product using education data? Lucas: Vemo Education does that — they partner with schools to offer what they call 'outcome-based loans'. They underwrite based on real-time data like credit load and cumulative GPA, and they tie the interest rate to academic milestones. If you maintain a three-point-oh, your rate drops. Luna: That creates a powerful incentive. But there's a potential downside — students might game the system or schools could manipulate data. Lucas: Absolutely. The Consumer Financial Protection Bureau has been looking at this since late 2024. They're concerned about data accuracy — what if a school's API mistakenly shows a student as dropped when they're not? And there's the question of bias: if the algorithm uses major as a factor, does it penalize humanities compared to engineering? Luna: I read a study that said art history majors have a lower median income than computer science, but that doesn't mean they can't repay a loan. Lucas: Exactly. So the fintechs need to be transparent about the data points they use and how they weight them. Stride, for instance, publishes its methodology and lets students see their risk factors before they agree to anything. Luna: What about the scale? Are we talking millions of students or a pilot? Lucas: It's still early. Stride has funded about fifteen thousand students since launch. Vemo is in about thirty schools. But the trend is accelerating because of a specific tailwind: the cost of college continues to rise, and federal loan limits haven't kept pace. For the 2025-2026 academic year, the maximum federal direct loan for a dependent undergraduate is thirty-one thousand over four years — that doesn't cover tuition at many private schools. Luna: So there's a gap, and alternative data is one way to fill it without taking on high-interest private debt. Lucas: Right. And the real-time nature is crucial because it allows for dynamic repricing. If a student's GPA drops below a threshold, the loan's interest rate might adjust — or the monthly payment under an ISA might recalculate based on new income data. Luna: That sounds like a lot of moving parts. How do they handle the operational complexity? Lucas: They use middleware platforms like Plaid for education — which is actually a real thing, Plaid launched a education data product in March 2026. It aggregates data from multiple student information systems and standardizes it into one API. That lowers the integration cost for lenders. Luna: And the lenders? Are traditional banks getting involved or is it all fintechs? Lucas: Mostly fintechs so far, but JPMorgan and Wells Fargo have pilot programs using alternative data for student lending. They're not using GPA yet, but they are using enrollment verification in real time to adjust credit lines. Luna: Let's talk numbers for a second. What's the average loan size under these new models? Lucas: For Stride's ISAs, it's about fifteen thousand dollars. For Vemo's outcome-based loans, it's closer to ten thousand. But they're both designed to cover the gap after federal loans and scholarships. Luna: And the default rates? That's the ultimate test. Lucas: Stride claims their default rate is under two percent, which is lower than the federal student loan default rate of around three point five percent. But they've only been at scale for a few years, so it's still early. The real test will come during an economic downturn. Luna: Fair point. And what about the regulatory environment? We've seen the CFPB take action on earned wage access and overdraft fees. Lucas: The CFPB issued a request for information on alternative data and student lending in January 2026. They're specifically asking about fair lending implications and data privacy. I expect some form of guidance by the end of this year. Luna: So the window for innovation is open, but it might narrow quickly. Lucas: Exactly. The schools themselves have to be careful too — they're essentially selling student data to lenders. The Family Educational Rights and Privacy Act, FERPA, applies, so schools need opt-in consent from students. Most make it part of the loan application process. Luna: And students? How are they reacting to sharing real-time academic data? Lucas: Acceptance is growing, especially among younger Gen Z students who are used to sharing data for convenience. A 2025 survey by the Education Finance Council found that sixty-two percent of students were willing to share GPA and enrollment data if it meant a lower interest rate. But there's still a trust barrier—they want to know it's not used against them if they struggle academically. Luna: And that ties back to the transparency piece. If a student knows exactly what data is being used and how, they're more likely to opt in. Lucas: Right. Stride even lets students see their 'education credit score' — a composite based on their academic profile — and gives tips on how to improve it. That sort of empowerment builds trust. Luna: I like that. So where do you see this going in the next two years? Lucas: I think we'll see a few things. First, more traditional lenders will enter using aggregation platforms. Second, the products will get more granular — think ISA terms that adjust per semester based on grades. Third, data sources will expand beyond the school to include things like library usage or online course participation. That's where it gets tricky from a privacy standpoint. Luna: So the biggest challenge isn't technology — it's ethics and regulation. Lucas: Exactly. The technology to pull real-time education data is mature. The question is how we balance inclusion with protection. But for the forty-five percent of students who are credit invisible, these models offer a real path to affordable education financing. Luna: And that's a story worth following. Thanks, Lucas. Lucas: Thanks, Luna. And thanks to everyone who supports the show at buy me a coffee dot com slash fexingo — it helps us keep bringing these conversations to you.