Trended Credit Data Improves DU Risk Assessment and Supports Access to Mortgage Credit

Credit scoring models assess the ability and willingness of borrowers to pay their debts using data collected by the three consumer credit reporting companies: Equifax, TransUnion, and Experian. Regardless of their income or wealth, borrowers obligate themselves for debt repayment in various ways – many successfully, but some, through poor matching of income and consumption, disorganization, or for other reasons, less successfully. The assessment of debt repayment behavior expressed as a credit score is highly predictive of the probability of repaying current and future debts.

Credit scoring models have been part of Fannie Mae’s automated underwriting since we introduced Desktop Underwriter® (DU®) in 1995. DU created a huge advancement in the precision of mortgage underwriting, which previously had relied largely on the loan-to-value ratio of the proposed loan, with no analytic consideration of credit history. Initially, DU relied heavily on the prospective borrower’s FICO® (Fair Isaac Corporation) credit score as the primary indicator of creditworthiness. In 2000, we replaced the credit score with a proprietary credit risk assessment that is more predictive of performance because it is modeled directly on Fannie Mae loans.

DU’s comprehensive risk assessment considers a number of factors (see Fannie Mae Selling Guide section B3-2-02: Risk Factors Evaluated by DU) such as loan purpose and loan-to-value ratio as well as borrower credit report data. To assess borrower creditworthiness, DU considers many credit report factors (described in the Fannie Mae Selling Guide, section B3-5.3-09: DU Credit Report Analysis).

Trended Credit Data Improves Modeling of Loan Performance

In recent years, expanded information on borrower credit histories has become available. What is called “trended credit data” is historical data at a tradeline (credit line) level on several monthly factors, including: amount owed (balance), minimum payment due, and payment amount made. In 2015, Fannie Mae used 3.7 million credit reports with trended data (dated June 2009 through August 2012) to conduct modeling and analytics to support a comprehensive review and redevelopment of DU’s credit risk assessment.

Including trended data materially improved modeling of loan performance. Based on that finding, Fannie Mae has worked with the credit reporting agencies to have trended data included in the consumer credit reports used for underwriting loans through DU, effective with DU Version 10.0(scheduled for release the weekend of June 25, 2016). Trended data is not considered in currently available credit scores, so consideration in the DU credit risk assessment will be its first widespread use in the mortgage lending industry.

Trended Data Empowers Creditworthy Borrowers

Including the trended data in DU’s credit risk assessment: 1) improves the accuracy of DU’s overall risk assessment, and 2) will benefit borrowers who regularly pay off revolving debt, increasing the likelihood that they will receive an Approve recommendation from DU. This means that use of trended data in DU’s credit risk assessment can provide more creditworthy borrowers access to mortgage credit. The overall percentage of loans that receive an Approve/Eligible recommendation is expected to remain relatively stable.

Giving weight to how borrowers pay off credit debt puts more power in their hands to control their credit evaluation. Payment delinquencies are a significant factor in credit scores, and borrowers can do nothing but wait for the delinquencies to grow ever farther back in time. But when trended data is considered, by paying credit card balances in full or in large part for a few months, borrowers can demonstrate that a late payment was not deeply reflective of their general debt repayment ability and behavior.

Based on Fannie Mae’s analysis, borrowers can potentially improve their evaluation by the DU credit risk assessment each month by paying off credit card bills in full.

DU Supports Access to Credit with Prudent Risk Management

DU has been the industry leading automated mortgage underwriting system for more than 20 years. DU’s evaluation is fair and objective, applying the same criteria to every mortgage loan application it considers. Fannie Mae is committed to continuous improvement of the DU risk assessment model. We continue to make ongoing investments in our risk management tools, to enable the origination of better performing loans, resulting in reduced costs to service those loans. The addition of trended data to the credit risk assessment is an update that will help to support creditworthy borrowers’ access to mortgage credit while reducing risk.

Acknowledgments

The author thanks Stacey Shifman and Kristi Heutink for their contributions to this analysis.

What does this mean for you?

Confident credit risk underwriting is contingent upon successfully predicting consumer behavior in the future. The ability to see how a consumer’s credit activity is evolving over time, or trended credit data, provides you insight into behaviors and patterns,  which can be used to help make stronger, more confident lending decisions.

What is trended credit data?

Trended credit data provides a sequence of 24 months of the borrower’s payment patterns, and offers a historical perspective of specific consumer payment behavior – including scheduled payments, actual payments and past balances.  This expanded, two-year, granular viewpoint of the consumer creates the opportunity to extract meaningful statistics to help predict future behavior.

Gain deeper customer insight

Using trended credit data will help mortgage lenders examine how consumers are managing their credit accounts over time.  Today, you can see consumers’ existing balances and determine whether they have paid their bills on time; however, you cannot tell if consumers are consistently carrying debt loads on revolving accounts, such as credit cards, or whether they pay their balances in full every month.

For example, a consumer with a large credit card balance who pays in full every month (a “transactor”) likely has a higher level of creditworthiness than a consumer with a large credit card balance who only makes the minimum required payment (a “revolver”).  Existing credit reports can’t always differentiate between these two types of consumers.

A bill introduced Thursday in the House of Representatives would allow Fannie Mae and Freddie Mac to consider alternative credit-scoring models beyond the FICO credit score the government-sponsored enterprises currently use when determining what loans to purchase.

The bill, which is entitled the “Credit Score Competition Act of 2015,” was introduced Thursday by Rep. Ed Royce, R-CA., and Rep. Terri Sewell, D-AL.

According to a joint release from Royce and Sewell, the bill would enable Fannie and Freddie to consider other credit-scoring models, which would level the playing field for borrowers whose credit doesn’t meet FICO’s standards and make it easier for them to buy a home.

“Fannie Mae and Freddie Mac are the largest mortgage purchasers in the nation, but they rely on credit score models that don’t necessarily take into account something as simple as whether borrowers have paid their rent on time,” Sewell said in a statement.

“Home ownership is an integral part of the American Dream that shouldn’t be out of the reach for low-income, rural, and minority borrowers who lack access to traditional forms of credit,” Sewell continued. “This legislation takes an important step towards addressing this issue and helps make homeownership a reality for more Americans across the country.”

According to Royce and Sewell, allowing Fannie and Freddie to make mortgage purchasing decisions with access to “multiple empirically derived, statistically sound credit scoring models” alleviates some of the risk in their portfolios and lowers the chance of systemic risk to the housing market.

“Fannie and Freddie’s 90% share of the secondary mortgage market and reliance on one credit scoring model has created a near monopoly in this field,” Royce and Sewell’s statement reads. “Opening the GSEs up to other credit scoring models will foster competition and innovation in the credit scoring industry.”

According to Royce and Sewell, potential homebuyers without a FICO score or with a FICO score below 620 are ineligible for a mortgage that can be sold to Fannie or Freddie and are often “frozen out of the housing market” by the current system.

“The GSEs' use of a single credit score is an unfair practice that stifles competition and innovation in credit scoring,” Royce said. “Breaking up the credit score monopoly at Fannie and Freddie will also assist them in managing their credit risk and decreases the potential for another taxpayer bailout.”

In Royce and Sewell’s view, lower-to-middle income Americans who are qualified to buy a home but are unable to do so because of their FICO score or lack thereof will “specifically benefit from the GSEs using other credit scoring models.”

Royce and Sewell’s bill becomes the latest in a growing movement to push beyond FICO.

Last year, Freddie Mac’s CEO Donald Layton told HousingWire that Freddie was already considering “one or two alternatives to FICO.”

Proponents for FICO alternatives note that GSEs currently use the FICO 4 model, which has been in use by Fannie and Freddie since before the housing crisis.

FICO itself released FICO 9 last year, which is supposedly more accurate and beneficial for first-time homebuyers, but the GSEs have not adopted it yet.

The Department of Housing and Urban Development and the Federal Housing Administration have already stated that alternatives to FICO need to be considered.

In a speech earlier this year, HUD Secretary Julian Castro said that HUD is open to alternatives.

“I know that new credit scoring models are being developed so that non-traditional factors can be considered when determining creditworthiness,” Castro said in April, adding that the FHA is exploring the use of new credit scoring models.

“We’ll look at every option that brings housing opportunities within reach of more Americans,” Castro said.

One of the alternatives to FICO is VantageScore, which enthusiastically welcomed Royce and Sewell’s bill, which would in VantageScore’s opinion “end the GSE lockout and FICO monopoly” on credit scoring.

“Outdated credit scoring models required by Fannie Mae and Freddie Mac limit opportunities for millions of creditworthy borrowers who, through no fault of their own, are unfairly locked out of the automated underwriting programs used by most mortgage lenders,” VantageScore Solutions President and CEO Barrett Burns said in a statement.

“Locking out competitive models and creating what is essentially a government sanctioned monopoly also undermines innovation among model developers, which must be preserved and encouraged in order for the market to operate efficiently for borrowers and lenders,” Burns continued.

“We strongly support a bill that promotes access to sustainable mortgage credit, and healthy choice and competition among credit scoring models,” Burns said. “We encourage industry leaders to voice their support of this bipartisan measure.”