With the mandate by FHFA that mortgage applications for loans financed by either Fannie Mae and Freddie Mac to include VantageScore 4.0, the use of “trended credit data” has become as mainstream as credit scores themselves. VantageScore 4.0 was the first tri-bureau generic scoring model to use trended credit data by evaluating a consumer’s credit behavior over a longer time period, ultimately, providing a more comprehensive look at a consumer’s overall credit health.
What is trended credit data?
Trended credit data is a type of credit reporting that includes historical information about a borrower’s credit behavior over time. This provides lenders with a more complete picture of a borrower’s creditworthiness, allowing them to make more informed lending decisions. By analyzing data on payment history, credit utilization, and balances over months or years, lenders can identify borrowers who consistently pay off their credit card balances each month or gradually pay down their debt over time. This allows lenders to assess risk and determine whether borrowers are likely to repay a loan or credit line in a timely manner. Overall, trended credit data offers lenders a more nuanced view of a borrower’s credit history, enabling them to offer more competitive rates and terms to qualified borrowers.
PREDICTIVE POWER:
Trended credit data can provide up to a 20 percent improvement in predictive performance within Prime and SuperPrime consumers, where risk is scarce and often harder to delineate…and where lenders often see unexpected defaults.
CREDIT CARD USERS REWARDED:
An estimated 53% of Americans carry revolving credit card debt from month to month, which may be an indication of either healthy or risky credit balance trajectories. Some consumers might be earning cash back and rewards but paying those balances off while other consumers might be under financial stress and not be able to pay off those balances.
By leveraging trended credit data, VantageScore 4.0 is better able to distinguish between these two types of credit behaviors, which results in a more accurate reflection of their creditworthiness.
