Social media algorithms help financial institutions make credit-related decisions 

Social Media Analytics Algorithms

Last month we talked about the use of social media to help lenders get a better idea of what an applicant is like, and if he or she is a qualified borrower. With so much banking done remotely, financial institutions are having a harder time getting a feel of what an applicant is like, and social media can help fill in the gap. But some banks are even going so far as looking into social media-related algorithms to make decisions about their applicants.

An article in The Economist explained that the founder of Douglas Merrill, the creator of online lender ZestFinance found that “Applicants who type only in lower-case letters, or entirely in upper case, are less likely to repay loans, other factors being equal,” when looking at applicants’ emails and social media updates. Navin Bathija, the founder of Neo, a company that determines car loan applicant’s’ credit worthiness, is looking into the effect of an applicant’s racist comments on Facebook and lack of credibility – and is sure that within a year, there will be evidence of a correlation.

In a less data-heavy form, Bathija is also looking at the LinkedIn profiles of applicants to verify information as well as look into the connections a user has, claiming that if professional contacts can determine the “character and capacity” of the applicant.

The use of alternative data for credit risk monitoring has likely come about since so many millennials and members of Gen Y have grown up giving out their information over the internet. Some banks are taking advantage of this not just by using sites to make decisions, but cutting interest rates of users that help promote their bank on their social media profile. And as millennials become a larger percentage of applicants, cruising social media sites may become the norm.

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