By the end of 2017, the education debt in the U.S. rose to nearly $1.38 trillion, with 11 percent of borrowers 90 days or more delinquent. Many borrowers are having a hard time finding effective resources that will help them deal with the financial burden of their student loans.
Anik Khan, formerly of Accenture and Capital One, and David Gao, former software consultant at VMWare, co-founded financial tech startup MaxRewards to provide customized guidance to those borrowers and help them tackle their loans once and for all.
“We studied student loan repayment options by extensively reviewing the federal student loan repayment website and official repayment forms,” says CEO Khan. “We tested our repayment estimates by comparing our results with the federal repayment estimator and made a standard optimization algorithm to minimize total cost while keeping monthly payment below budgeted monthly payment.”
While other sites may direct you to look at comparison charts, the team doesn’t think this is the best approach since many Americans are not fully financially literate.
MaxRewards uses algorithm-based online apps — from a loan payment action plan to personalized content and AI-powered auto-pay that calculates the best additional payment schedule — to put all of your resources into one platform. The startup also aims to help those looking to maximize their credit card rewards.
“Our differentiation are our algorithms designed to maximize rewards and savings and look at problems holistically,” says Khan. “We don’t just answer if you could benefit from refinancing, but should you be considering every possible alternative — which for many users will be over 100+ scenarios.”
Here, Khan shares more about their initial inspiration, their newly-released platform and how they stand out in a very crowded student loan market.
What prompted the idea for MaxRewards?
We started off with credit cards. I was using credit cards in a way that most people normally don’t, which is building out an Excel spreadsheet to figure out what kind of cards I should get. Ultimately it led to this bigger idea of when people look for credit cards, they’re typically recommended a general list. To expect other people, who don’t have that background to do it, it’s going to take them a long time.
I shared this idea with my co-founder, whose background is in engineering and computer science, and he was really amazed by the difference between the benefits of a great financial decision versus the default option. It really resonated with him and when we were thinking about our bigger vision, where we could we apply this to have the most impact, student loans came to the top.
How did you approach the problem once you had your vision?
This is the bigger problem: how do you make personal finance something that people can do a lot more easily? If you think about it, most people spend a little bit of time to get just enough financial information, to get a sense of what to do and make a decision. This often it leads to very suboptimal decisions. Instead, we approach the decision-making process of guiding by automating processes.
The approach that we’re taking is narrow by answering specific questions. Ultimately you indicate what your situation is, if you’re looking for estimates for different repayment plans or you want to defer your loans. You read the articles that are going to be relevant for you; instead of having an entire website to go through, you have two or three different articles to learn about that concept.
The next thing is you need to do the math and figure out what do these options look like — so we have the student loan repayment calculator, which prints every single repayment option available to you in one place. If you have different types of loans and different service providers, we also break these apart and identify that this set of loans is eligible for this type of payment plan and you can see exactly what the estimates would be for all of the eligible payment plans.
We even do things like color-coding so you know what’s above your budget. Once you have an idea of the plan moving forward, the next step is to actually implement it. This can be a little bit challenging so we provide the “how to’s” on exactly what you need to do, say for signing up for a Public Service Loan Forgiveness or getting on an income-driven repayment plan, refinancing your loans and follow-up forms and alerts for year over year. Lastly, we provide smart auto-pay, where our platform figures out every month how much extra you can pay toward your student loans and then if you have multiple service providers or multiple banks, it applies it to the one that’s going to help you pay it off the fastest or let you pay the least amount of interest.
Who is your target audience?
We’re targeting people who are almost about to graduate or recently graduated. I think with this whole solution we have it helps pretty much everyone, including people who might be a couple of years into their repayment because they can still use the smart auto-pay and pay off things faster.
It’s important to clarify that they’re not moving loans to our platform. What we really do is advise people on what to do on the loans that already exist. For refinancing, we recommend people to our partners. Everything is really happening on their existing platforms, we just automated it and made it simpler.
What’s your revenue model?
We think a certain portion of users will refinance, will benefit from refinancing and we have partnerships with different refinance companies, but none of our algorithms or technology looks into recommending that beyond what is going to be good for you. On a longer term, we think if we can provide value in the future when you’re looking for a credit card or look into buying a house we’ll have other types of solutions where we can provide you additional value and there will be additional revenue opportunities there as well.
Who are your competitors and how do you stand out?
We see two main groups of competitors: content-focus and promotion-focused. Content-focused companies are NerdWallet, Student Loan Hero, CreditCard.com, and others like them that have lots of educational materials. The way they recommend products is by creating lists like “Top Travel Cards.” For users to get the maximum value from these sites, they need to spend a lot of time reading articles and understanding what is relevant to their situation.
Promotion-focused companies like Credit Karma, Credit Sesame, and Mint use algorithms to recommend the next best product. This is typically better than picking a card from a list, but these algorithms are not completely objective. They also don’t consider how to use multiple products effectively.
