FICO and CoreLogic Announce Availability of More Predictive Mortgage Credit Score Designed to Enable Growth in Mortgage Lending Market Innovative predictive score can help lenders safely grow mortgage origination volumes
SANTA ANA, CA—July 10, 2012—CoreLogic (NYSE: CLGX), a leading provider of information, analytics and business services, and FICO (NYSE: FICO), the leading provider of predictive analytics and decision management technology, today jointly introduced a high-performance consumer credit risk score that is expected to improve lending decision quality and increase the number of mortgage loans lenders make. The new FICO® Mortgage Score Powered by CoreLogic® evaluates the traditional credit data from the national credit data repositories and the unique supplemental consumer credit data contained in the CoreLogic CoreScore™ credit report, introduced in October 2011, to deliver a more comprehensive and accurate view of a consumer’s credit risk profile for loan prequalification and origination. The new scoring model was designed specifically to predict mortgage loan performance and has shown a substantial improvement in risk prediction over other generally available risk scores in use today. As a result, this new scoring model developed by FICO to leverage data only available on the CoreLogic CoreScore credit report, will help mortgage lenders more safely and profitably expand their origination volumes, ultimately strengthening and growing the overall mortgage lending market. According to a recent FICO quarterly survey of bank risk professionals, conducted by the Professional Risk Managers’ International Association (PRMIA), bankers continue to lack confidence in the housing finance marketplace. Of bankers surveyed, approximately 75 percent of respondents expect the level of mortgage delinquencies to increase or stay the same over the six-month period following the survey, and more than 85 percent hold the same view for home equity line delinquencies. “In this complicated operating environment, lenders are increasingly turning to new data sources to help better interpret a consumer’s credit risk, so that more loans can be approved while mitigating potential losses,” said Tim Grace, senior vice president of product management at CoreLogic. “Today, we are announcing an industry first—a new composite, multi-bureau credit score generated from both traditional credit data and CoreLogic supplemental data, expanding the applicant credit spectrum by including property transaction data, landlord/tenant data, borrower-specific public data, and other alternative credit data. For a top-20 lender processing 300,000 applications a year, adopting this new score could translate into 3,900 more loans approved every year along with a net financial benefit of $14.5 million. As such, it not only provides a more complete and predictive evaluation of a consumer’s credit risk profile, but it can empower lenders to better mitigate risk and approve more loans for more consumers.” “The new FICO Mortgage Score is designed especially for prequalification and origination and delivers increased insight when it matters most,” said Joanne Gaskin, senior director of Scores product management and mortgage practice leader at FICO. “For many lenders, the increased predictive lift will translate into thousands of new mortgages, and the avoidance of millions of dollars in bad loans and associated costs. This innovation is a win-win for lenders and consumers alike.” The new FICO® Mortgage Score Powered by CoreLogic® maintains a consistent score range, set of reason codes and odds-to-score relationship with prior FICO® Score versions, making it easy for lenders to integrate and for consumers to understand. Additionally, the CoreScore Solution maintains backward compatibility making it readily available within existing CoreLogic Credco Instant Merge® integrations – the most widely used credit report in the mortgage industry. For more information about the new FICO® Mortgage Score Powered by CoreLogic® and the CoreScore credit report, visit www.CoreScore.com.