A new study by ID Analytics (www.idanalytics.com), which specializes in consumer risk management, finds that using alternative credit scores for safe lending can dramatically increase the number of individuals that are considered eligible for credit.
Through the use of alternative scores, lenders are able to see a more complete picture of an applicant’s credit worthiness. This enables more marginal, subprime or unscoreable individuals to take advantage of mainstream financial services.
While a significant number of U.S. consumers rely on credit for financial stability, many have difficulty gaining access to credit due to no or poor traditional credit scores. Millennials, immigrants and individuals with lower incomes are groups that are most likely to be seen by lenders and bureaus as “unscoreable.”
Traditional credit scores take into account data from credit card, mortgage, student and auto loan records, but they don’t consider modern responsibilities that offer additional predictive insights into other credit behavior such as payment data from wireless, cable and utility accounts; online marketplace, payday and subprime lending; alternative billing methods; checking accounts; and other credit-relevant alternative data sources.
In the two-part study, ID Analytics examined credit applicants at key lenders across the auto, telecommunications, credit card and marketplace lending industries from 2012-2016 using the latest version of its credit score, Credit Optics Full Spectrum. Key findings of the study include:
° ID Analytics was able to predictively score 75% of the unscoreable population using alternative data. Depending on the lender, 10-40 percent of these previously unscoreable applicants would have been seen as credit eligible without an increase in risk.
° Analysis of a top-10 U.S. credit card issuer’s credit applications found that an additional six percent of applicants, considered to be unscoreable, could have been activated with no additional risk to the lender in one year.
° Depending on the lender, research found that as many as 50% of the applicants were considered to be subprime, and Credit Optics Full Spectrum was able to classify 14% of these subprime applicants as credit eligible.
“The use of alternative data in credit scoring leads to improved credit decisioning and enables organizations to be more inclusive in their lending decisions without increasing their risk,” said Ajay Nigam, senior vice president, product and technology, ID Analytics. “This is a win-win for lenders and consumers especially young adults and other populations that have historically been marginalized by traditional scoring models.”
