How Data Can Serve the Credit Invisible

One in four Americans have a limited or nonexistent credit history. That’s 80 million people where credit scores can’t help lenders make a credit decision. However, these thin-file or no-file consumers could still be more than capable of paying back a loan.

The lending industry is undergoing significant transformation as digitization – cloud, mobility, big data & analytics – is impacting various credit decisioning processes. As these capabilities come online, lenders will increasingly turn to additional data sources, such as a borrower’s financial transaction history, to complement traditional credit scores. This is good news for consumers who may not have a credit score – or in certain cases where a credit score is not reflective of their financial health – but likely have a checking and savings account. With a borrower’s permission, data aggregators can retrieve online financial accounts and analyze up to two years of a borrower’s transaction history, while also looking at income and assets.

This look into transaction history, as well as a borrower's current financial situation, will enable lenders to have a real-time view of a borrower’s cash flow along with their history of consistently making major payments like rent, phone bills, and utilities. This insight can provide a very strong indicator of a borrower’s ability to consistently meet the payment obligations of a new loan.

Leveraging a digital credit decisioning process also permits rapid analysis of assets and income providing verifications that are quicker and more accurate than traditional methods. For example, it typically takes 60-70 days for a borrower to be approved for a mortgage, but digitizing the process can shorten it significantly. And as more steps are digitized, utilizing online data sources, the approval process could move from weeks to days.

One group that would greatly benefit from digitally-driven lending solutions are millennials. In 2015, the Consumer Financial Protection Bureau (CFPB) released a study showing that 26 million Americans are credit invisible, with an estimated 12 million being millennials. This lack of credit data means they are often unable to get approved for a loan, or they end up with sky-high interest rates. As more lenders lean on the rich insights from transaction data, underserved demographics like millennials will have the opportunity to prove their financial stability and loan eligibility.

Transaction data analysis could also eventually be applied to help underserved consumers around the world, especially in emerging markets. Many citizens living in developing countries are unable to build credit due to either their lack of knowledge or their country’s credit infrastructure, which in some cases is very weak. For example, 85% of Indian residents don’t know their credit score. In fact, 53% of the Indian population doesn’t even know that credit scores exist, according to a survey conducted by Credit Sudhaar.

However, consumers in emerging markets are becoming more tech savvy. India, for example, has the highest yearly growth rate of internet users. As these people move online, new methods of credit decisioning can gather alternate data to determine their creditworthiness. Access to financial account transaction data and alternative financial data could allow consumers in emerging markets to better secure loans.

This ‘digital model’ has the potential to transform the global state of lending, and improve the lives of millions of people. Allowing consumers around the world to get access to loans they would not previously have been approved to receive. Additionally, underserved demographics, such as millennials and emerging markets, will no longer be considered credit invisible. Through user-permissioned data aggregation, we’re creating a future in which anyone who is capable of repaying a loan will be better positioned to secure one.