Almost exactly two years ago, Chris Abkarians and Nikhil Agarwal met online. They had plenty in common: Both lived on the West Coast, both had been accepted to Harvard Business School and, crucially, both were part of a WhatsApp group for incoming HBS students.
It was that WhatsApp group that would connect the two not just as classmates, but as entrepreneurs. Conversation in the group that summer turned quickly from icebreakers to financial challenges, particularly student loan rates.
"People were talking about the different options for paying for school," Abkarians said. "One of the first things we did was was start a thread where people were posting quotes they were getting from different lenders. I built some models to compare those. Then, my co-founder proposed the idea of seeing if we could get a group discount by going to banks as a group."
Abkarians and Agarwal collected quotes from about 70 of their classmates. The idea was to take all of those quotes and, through collective bargaining, get banks to lower their rates.
It didn't go so well at first. As Abkarians recounted, bank after bank saw the size of the group and turned them away. But once the team got more students on board, they had more power with the lenders.
"As the group got larger, more people said yes, and that's the theme that's kind of continued," Abkarians said.
Today, Abkarians and Agarwal have a pool of 16,000 students for whom they negotiate student loan rates. They also have a startup that's powering this initiative: LeverEdge, which the two incubated at Harvard i-lab during their time at HBS. (They graduated this spring.)
"We drive the market toward the lender that has the lowest overall rates. That's been our business model."
The proposition to users is simple. Each student provides LeverEdge with basic information including where and when they're going to school, how much they want to borrow, their self-reported credit score and whether they have a co-signer. LeverEdge then takes that data and aggregates and anonymizes it to present to lenders: "Hey, we have X amount of dollars of demand—what's the best you can do for our group?"
The startup makes money by charging lenders a pre-set referral fee, which varies based on the loans that are grouped together, for each tranche of loans negotiated between students and lenders. All lenders participating in the auction agree to pay that fee if they have the winning bid.
LeverEdge has expanded quickly. Abkarians and Agarwal hired a team in January, bringing the startup's headcount to 10 full-time employees. The company also has a handful of MBA interns for the summer.
In May, LeverEdge raised a $2.5 million seed round led by NFX along with Global Founders Capital and founders from fintech companies Earnest and SoFi. But LeverEdge has brought in funding even without institutional investment.
"We've been profitable from the time we started," Abkarians said. "Traditionally, there's a lot of different student loan companies that charge relatively high amounts to lenders. Lenders traditionally pay high amounts to acquire loans. We drive the market toward the lender that has the lowest overall rates. That's been our business model."
Over the next six to 12 months, LeverEdge is working to expand to more students on more campuses. The startup began offering its services to undergraduates in June, but marketing will need to be a major focus; Abkarians estimates that 90 percent of users have signed up for LeverEdge through word of mouth.
Longer-term, Abkarians said, the team is dreaming up ways to apply the LeverEdge model to other financial products, like auto loans, mortgages and insurance. The team will run experiments over the next 18 months to identify the next step.
"The core itself is profitable. It's stable and growing quite nicely," Abkarians said. "But the bigger picture is: There is not a lot of transparency in financial services. There never really has been. I really do believe that there are way too many steps between somebody who actually takes out a loan and whatever entity holds it or owns it. We should be able to intermediate a lot of steps in between and make it a more efficient market."
