Founder Posts | Taking a Different Perspective Through Data

I’ll never forget the moment I thought I would have to drop out of college because I couldn’t afford my next tuition check.

I had busted my ass for years to get there. I took classes at night. I took classes on the weekend. I took classes while deployed to Iraq. I had completed my FAFSA, maxed out my GI BIll (this is before the 9/11 GI BIll had passed), applied for every scholarship I could. I had done everything I was told I was supposed to do and yet there I was facing a $16,000 bill that I clearly couldn’t afford. 

I was told by my college that maybe I could apply for a loan, and so I did that too. I typed in the income from my three part-time jobs, and was told that there wasn’t really anything that could be done. “Maybe I could find a co-signer?” they said... No. My mom was bankrupt and did not qualify. 

I talked to my grandma, and she was very hesitant to sign for a massive loan for something I was doing. Frustrated, I remember thinking that this was ridiculous. Of course I took my education seriously. Of course, I was doing well enough to graduate. Of course, I would find a job when I graduated (I had three at the time!). It didn’t matter.  Luckily I managed to convince my grandmother to co-sign. To this day, I shudder to think about I would have had to do if she hadn’t agreed to do so. 

This is, of course, why I started A.M. Money. A credit score or my income back then clearly wasn’t a reflection of who I was or what I was doing. 

So what should be used to determine a student’s ability? A story is great, but you can’t run an analytical business on a story. You need numbers to not only tell the story, but to build the backbone of how you will make decisions and take on risk. 

To do so, I spent 6 months in a rabbit hole learning everything I could about student debt, and educational and career attainment. There are robust sets of data that can help you paint a picture but you need to paint it for an audience (investors etc) that isn’t used to looking at this type of data and in the way that we use it. 

Along the way I talked to hundreds of people about how to think about this data (and others like it), and I imagine I’ll talk to hundreds more as we continue to grow and expand our model. As we do this, I’ve always found that it’s helpful to not just view the data dispassionately, but to talk to people who not just have an understanding of the data, but have also lived it themselves. This allows for you to get inferences and insights that even the best statistical technique may struggle to see, let alone understand.

As such, I’m happy to announce that we will be launching our first ever Data Hackathon in conjunction with Capital One and The Polsky Center for Entrepreneurship & Innovation. We’ll be introducing some of the basic educational datasets we use in our underwriting model, explore some of the insights and techniques we have used to make sense of them, and then hopefully use that as an opportunity to learn how others might think about and use this data. 

If any of this sounds interesting, I hope you’ll join us:

The A.M. Money Data Hackathon

Part of the Career Boot Camp

Presented by A.M. Money, The Academy Group, and College Greenlight

- - -

January 8, 2020 | 10am-6pm | 1452 E 53rd Street