In yet another significant change, Fannie Mae is incorporating Trended Credit Data into its Automated Underwriting System, AKA Desktop Underwriter (DU).
This change to the mortgage credit reporting process that will affect underwriting decisions for U.S. consumers will be implemented June 25, 2016.
WHAT IS TRENDED CREDIT DATA?
Trended credit data is a two-year historical perspective on a consumers utilization of credit accounts, giving lenders a means to better analyze a borrower’s behavior and extract more meaningful statistics.
Lenders will be able to determine more in-depth behaviors on a borrower’s credit behavior such as:
- If the borrower tends to pay off revolving credit lines each month
- If the borrower makes minimum or other monthly payment amounts
- If the borrower is reducing total amount borrowed over time
- If the borrower makes inconsistent or seasonal changes in monthly payments
The trended data will be included on virtually all active trade lines, not just revolving accounts, and will include credit cards, home equity lines of credit (HELOC), student loans, car loans and mortgages.
Lenders will be able to choose from almost 100 attributes.
The credit scores used in most lending decisions currently do not distinguish between folks who carry balances on credit cards and those who pay them off each month.
Trended data will help lenders see if a borrower is continually making just the minimum payments each month or if they are paying more each month. It will tell the lender if the borrower is doing it occasionally or consistently, and whether or not they’re paying down balances which ultimately improves their utilization.
Trended data provides a fuller picture of a consumer’s credit trends, supplementing the traditional moment-in-time credit snapshot with a more dynamic picture that includes managing revolving accounts.
HOW CONSUMERS WILL BENEFIT FROM TRENDED DATA
Giving credit to how revolving debt is paid empowers borrowers by giving them more control of their credit worthiness.
According to TransUnion, using trended credit data would increase the percentage of consumers in its Super Prime tier from 12 percent to 21 percent of the U.S. adult population.
This more wide-ranging look will help lenders differentiate between “transactors” and “revolvers”. Transactors tend to pay their balances in full every month whereas revolvers typically make minimum payments (or a payment less than the full balance).
Existing credit reports cannot differentiate between the two. As such, transactors aren’t able to reap the benefits of being less risky to lenders.
Payment delinquencies are a substantial factor in credit scores, and borrowers can’t really do much but wait for the delinquencies to season over time. But when trended credit data is considered, by paying credit card balances in full or in large part for a few months, borrowers can essentially counter that late payment and show that it wasn’t a true reflection of their general debt repayment ability and behavior.
Trended credit information has proven to be more predictive of a consumer’s future credit performance than traditional credit scoring.
Predictive risk scores that leverages trended data is an enhanced way to evaluate consumer credit. This can potentially open doors for millions of U.S. consumers to access credit and obtain better terms on their mortgage loans.
Trended data can unveil the true directional path of a consumer’s credit usage, thus generating insights into past payment behavior in order to predict future behavior.
With trended data, lenders can improve their decision making process and engage the most qualified borrowers.
Trended credit data is destined to be the standard for future credit decisions made by lenders, allowing for a more comprehensive representation of a borrower’s ability to manage their credit.