How Data Science in Consumer Lending Drives Market Efficiency

About 16 percent of Americans have really bad credit and another 17 percent have poor credit, according to 2020 Experian reports. Unable to get approved for conventional loans, many seek out alternative products. Thanks to big data analytics in consumer lending, fintech consultants and alternative lenders are steadily expanding loan options for the people who don’t have perfect credit scores.

The Need for Expanded Loan Products

A Bankrate survey in 2020 reported that nearly four in 10 Americans wouldn’t be able to handle a $1,000 emergency from their own savings. This suggests that nearly half the population has potential financial gaps.

In times of need, some of those people don’t have the option of using a credit card or borrowing from a family member or friend. But if someone who desperately needs a loan has a credit score under 620, their chances of getting approved from a traditional financial institution are slim.

Historically, a person’s credit score has been the measuring stick for whether or not they are likely to repay a loan. That’s why nonprime or subprime borrowers don’t qualify for conventional loans. Their credit scores say to traditional lenders that they are too high of a risk.