Contact to us

News

Know about market updates

VantageScore uses trended data and machine learning to provide more accurate credit scores

if(typeof(jQuery)==”function”){(function($){$.fn.fitVids=function(){}})(jQuery)};
jwplayer(‘jwplayer_ZZgB8MSn_5xQXXB63_div’).setup(
{“playlist”:”https://content.jwplatform.com/feeds/ZZgB8MSn.json”,”ph”:2}
);

VantageScore President and CEO Barrett Burns discusses the FHFA’s new credit score competition rule issued in August and what it means for the mortgage industry and consumers. Burns says the decision will open up competition for all credit score developers to apply for usage by the GSEs and will in a safe and sound manner help provide more access to credit for consumers and a larger pool of customers for lenders.

Credit score competition in other loan categories has spurred innovation in the industry and enabled more predictive models that expand the scoreable population. VantageScore’s latest model, VantageScore 4.0, allows lenders to accurately score about 40 million more people than other models, and about 10 million of those people have a score of 620 or above.

This is because VantageScore 4.0 uses modern trended consumer credit data and machine learning analytics, which account for shifting consumer behaviors and patterns of usage, enabling it to score creditworthy individuals who may have thin, dormant or no-trade credit files. Conversely, other models use a point-in-time gradation of the data, only looking at a singular moment in time to measure a person’s creditworthiness.

VantageScore models are routinely tested for performance by VantageScore Solutions and the more than 2,200 regulated financial institutions that use them.

Learn more about VantageScore and its Trended Data credit model by visiting https://www.vantagescore.com/trended-data.

The post VantageScore uses trended data and machine learning to provide more accurate credit scores appeared first on HousingWire.

Source: 1