Automated mortgage underwriting systems use debt, income, down payment and credit scores to determine a loan applicant’s eligibility and ability to pay. This underwriting methodology can be problematic, because it overlooks millions of consumers who pay their rent, utility and phone bills on time but lack lengthy credit histories or credit scores. A disproportionate number of these consumers are people of color — demographics that are growing fast.
Research from the CFPB has shown that cash-flow and residual income data can help lenders identify borrowers with a low likelihood of serious delinquency who might not receive financing based on their credit scores alone.
If these methods prove successful, lenders will have widespread access to tools beyond traditional credit scores and credit histories to qualify otherwise creditworthy buyers.