Big Data and Credit{1}

This article, “Big Data for the Poor” presents that lenders are now able to better determine borrowers credit score. ZestCash aimed to move past the 40 year old system of how lenders determined a borrowers credit score by looking at many other variables such as, the area the borrower lived in to giving up a prepaid cell phone. Many borrowers are poor in data because they have not established long enough credit history or work records.

I felt that this article was related to our weekly topic because we discussed a lot of data redundancy, entities and their relationships. A lot of credit bureaus are poor in data because the data they have in their system may not be enough to see if a borrower is a good return or a risk. The credit bureaus base their decisions on the borrowers history and it may not be a good determinant as it doesn’t show the borrower’s current situation. Because the lenders do not have enough data about their borrowers, lenders might reject many potential good, reliable customers and accept poor, risky borrowers instead.

I thought it was a good article because it has opened my eyes about credit. I know credit history is a good indicator of how well a person can pay off their debt but I don’t think it should be an only indicator. I know of many reliable people that are willing to pay off their loans as soon as they can but they won’t be able to receive a good loan because of their non-existent credit history. I really liked the creative ways ZestCash is looking for other variables in determining a person’s credit score such as the area they live in, how fast they fill the application or even by their phone plan.

Hardy, Q. (2012, July 05). Big Data for the Poor. Retrieved from