Open Lending Corporation released the addition of new alternative data attributes for auto loan applicants to more accurately inform the risk score generated by its Lenders Protection? solution. Access to expanded criteria from TransUnion and LexisNexis allows Lenders Protection to analyze more robust car buyer data for loan decisioning.

These enhancements help financial institutions provide more competitive pricing to a larger borrower pool, increase loan volume, minimize risk and grow return on assets with the true capability that comes from extensive data fueling cutting-edge AI. Traditional metrics often fail to provide a comprehensive view of potential borrowers' creditworthiness, according to Harvard Business School ("Invisible Primes: Fintech Lending with Alternative Data?, 2021). Open Lending?s Lenders Protection?

utilizes alternative data within its industry-leading AI and machine learning decisioning engine to identify near- and non-prime borrowers with low credit scores and short credit histories who are less likely to default. Without considering these alternative data attributes, otherwise qualified candidates face rejection or higher interest rates. To provide greater access to vehicle ownership at a fair interest rate, Lenders Protection now offers: Decisioning that includes new data sources and new alternative data attributes, like the number of payments made over the past year, time elapsed since the initiation of the first auto loan, total good ACH amount, and the number of auto and non-auto inquiries over the last three years.

Extended loan protection with a more inclusive credit score range that aligns with the decline of consumer credit scores. These new criteria promote greater inclusivity by increasing overall approval rates and yielding higher approval rates for car buyers with limited credit history. These scorecard enhancements are now in place for all Open Lending customers.