Inventory
info icon
Single family homes on the market. Updated weekly.Powered by Altos Research
721,576-14142
30-yr Fixed Rate30-yr Fixed
info icon
30-Yr. Fixed Conforming. Updated hourly during market hours.
6.97%0.00
MortgagePolitics & Money

Fannie Mae changes underwriting to help ‘credit invisible’ borrowers

The goal is to expand mortgage loan eligibility and simplify the loan process for underserved borrowers without credit scores

Fannie Mae announced on Tuesday that it will make changes to its automated underwriting system in order to expand mortgage loan eligibility and simplify the loan process for underserved borrowers without credit scores.

The enhancements are slated to roll out in mid-December and will include an update to borrower eligibility criteria to align with Fannie Mae’s standard selling guide requirements for loans in which the borrower has no credit score, according to a press release from the government sponsored enterprise.

In addition, the selling guide policy requirement will be automated to document nontraditional sources of credit and enable the evaluation of monthly cash flow via borrowers’ bank statement data.

The goal is to provide a “more comprehensive view into a borrower’s financial health that can help enhance the credit assessment as part of the lender’s underwriting decision,” according to the GSE.

“Traditional lending practices make it hard for borrowers with no credit score to access credit, so we’ve taken steps that may help them responsibly qualify for a home loan using data that provides a more holistic view of how they manage their money,” Malloy Evans, Executive Vice President and Head of Single-Family Business at Fannie Mae, said in a statement. 

According to Fannie Mae, millions of Americans are credit invisible, meaning that their documented credit history is so limited that they are lacking credit credit scores or that their scores are not based on a complete debt repayment history.


The role of consumer transaction data in increasing homeownership access

Effective natural language processing technologies extract deeper meaning from unstructured data to make a difference in the lives of countless would-be homebuyers who are credit invisible or have not had the ability to obtain access to affordable housing finance.

Presented by: FormFree


Rates of credit invisible Black and Latino/Hispanic borrowers are disproportionately higher than other demographics. Nearly 15% of Black and Latino/Hispanic Americans are considered credit invisible, according to the Consumer Financial Protection Bureau (CFPB), while just 9% of their white and Asian counterparts fall into this category.

These types of imbalances reinforce the racial disparities related to credit and quality affordable housing access, according to Fannie Mae. Without credit scores or full credit histories, borrowers face more hurdles in mortgage lending, as credit information is a vital part of the mortgage underwriting process.

“We believe consumers should benefit from their responsible money management habits and a steady stream of income when buying a home, even if they don’t have an established credit history,” Evans said.

According to the Fannie Mae, its preliminary research has shown that using bank statement data to assess a borrower’s cash flow activity can make more predictive risk assessments — especially for those with no credit score or limited credit history.

Leave a Reply

Your email address will not be published. Required fields are marked *

Most Popular Articles

Latest Articles

Lower mortgage rates attracting more homebuyers 

An often misguided premise I see on social media is that lower mortgage rates are doing nothing for housing demand. That’s ok — very few people are looking at the data without an agenda. However, the point of this tracker is to show you evidence that lower rates have already changed housing data. So, let’s […]

3d rendering of a row of luxury townhouses along a street

Log In

Forgot Password?

Don't have an account? Please