New CFPB study highlights need for more inclusive credit data

Updated: July 14, 2026 by Guest Contributor 4 min read June 13, 2017

Blog-inclusive-credit-data-930x420

On June 7, the Consumer Financial Protection Bureau (CFPB) released a new study that found that the ways “credit invisible” consumers establish credit history can differ greatly based on their economic background. The CFPB estimated in its May 2015 study “Data Point: Credit Invisibles” that more than 45 million American consumers are credit invisible, meaning they either have a thin credit file that cannot be scored or no credit history at all.

The new study reviewed de-identified credit records on more than one million consumers who became credit visible. It found that consumers in lower-income areas are 240 percent more likely to become credit visible due to negative information, such as a debt in collection. The CFPB noted consumers in higher-income areas become credit visible in a more positive way, with 30 percent more likely to become credit visible by using a credit card and 100 percent more likely to become credit visible by being added as a co-borrower or authorized user on someone else’s account. The study also found that the percentage of consumers transitioning to credit visibility due to student loans more than doubled in the last 10 years.

CFPB’s research highlights the need for alternative credit data

The new study demonstrates the importance of moving forward with inclusion of new sources of high-quality financial data — like on-time payment data from rent, utility and telecommunications providers — into a consumer’s credit file.

Experian recently outlined our beliefs on the issue in comments responding to the CFPB’s Request for Information on Alternative Data.

As a brand, we have a long history of using alternative credit data to help lenders make better lending decisions. Extensive research has shown that there is an immense opportunity to facilitate greater access to fair and affordable credit for underserved consumers through the inclusion of on-time telecommunications, utility and rental data in credit files. While these consumers may not have a traditional credit history, many make on-time payments for telephone, rent, cable, power or mobile services. However, this data is not typically being used to enhance traditional credit files held by the nationwide consumer reporting agencies, nor is it being used in most third-party or custom credit scoring models.

Further, new advances in financial technology and data analytics through account aggregation platforms are also integral to the credit granting process and can be applied in a manner to broaden access to credit. Experian is currently using account aggregation software to obtain consumer financial account information for authentication and income verification to speed credit decisions, but we are looking to expand this technology to increase the collection and utilization of alternative data for improving credit decisions by lenders.

Policymakers should act to help credit invisible consumers

While Experian continues to work with telecommunications and utility companies to facilitate the furnishing of on-time credit data to the nationwide consumer reporting agencies, regulatory barriers continue to exist that deter utility and telecommunications companies from furnishing on-time payment data to credit bureaus. To help address this issue, Congress is currently considering bipartisan legislation (H.R. 435, The Credit Access and Inclusion Act of 2017) that would amend the FCRA to clarify that utility and telecommunication companies can report positive credit data, such as on-time payments, to the nation’ s credit reporting bureaus. The legislation has bipartisan support in Congress and Experian encourages lawmakers to move forward with this important initiative that could benefit tens of millions of American consumers.

In addition, Experian believes policymakers should more clearly define the term alternative data. In public policy debates, the term “alternative data” is a broad term, often lumping data sources that can or have been proven to meet regulatory standards for accuracy and fairness required by both the Fair Credit Reporting Act and the Equal Credit Opportunity Act with data sources that cannot or have not been proven to meet these standards. In our comment letter, Experian encourages policymakers to clearly differentiate between different types of alternative data and focus the consumer and commercial credit industry on public policy recommendations that will increase the use of those sources of data that have or can be shown to meet legal and societal standards for accuracy, validity, predictability and fairness.

More info on Alternative Credit Data

More Info on Alternative Financial Services

Related Posts

Rethinking Charged-Off Portfolio Prioritization

Experian’s new Recovery Scores model turns portfolio intelligence into more focused recovery strategies, helping organizations improve returns, direct effort and accelerate speed to cash. The challenge isn’t simply working more accounts. Whether a debt buyer is evaluating an acquisition, an agency is deciding where to assign collector time or a lender is managing its own post-charge-off accounts, the question is similar: How can limited capacity be directed toward accounts with the greatest potential for recovery? Prioritizing accounts mainly by age, balance or when they were last worked may not show which ones are most likely to generate a recovery. With the new Recovery Scores model, organizations can rank charged-off accounts by expected collectability, providing a consistent signal to inform placement strategy and treatment decisions across the recovery lifecycle. Make collector capacity a strategic resource Working every account with the same level of attention isn’t always practical. The more useful question is: Where should teams focus first to protect speed to cash? Our model performance analysis found: 80% of recovered dollars come from the top 40% of accounts worked. The value isn’t simply a better ranking. It’s how organizations can use it for collections optimization. Score bands can inform different strategies for placement, outsourcing, auction and legal channel treatment rather than applying the same approach across an entire portfolio. For debt buyers: The scores can inform acquisition pricing and how a newly purchased portfolio is divided across internal collections, legal channels and resale. Expected collectability can shape debt portfolio analysis, including how a portfolio is valued and segmented before collection work begins. For agencies: Score bands can help teams focus collector resources on accounts with stronger recovery potential. For first-party lenders: Managing recovery internally, the scores provide another signal to help structure decisions about which accounts to work and in what order. Look beyond collectability alone Prioritization rarely comes down to a single variable. Consider two accounts that both rank highly for expected collectability, but one has a substantially larger balance. Their recovery likelihood may be similar, but the potential dollars recovered are not. The Recovery Scores model uses debt collections analytics by combining Experian’s bureau-based score with current balance information. This helps organizations consider both the likelihood of recovery and the potential dollars at stake, while sensitive balance information remains within the organization’s working environment. Monitor accounts as they change The first decision about an account is rarely the last. Teams continually make choices about treatment, placement and resource allocation as accounts move through the recovery process. Recovery Scores is also available as a trigger. When underlying information changes, teams can receive an update and reconsider an account’s placement without waiting for the next portfolio-wide re-score. An account that shows lower recovery potential today may have a different recovery outlook later. Turn recovery potential into a portfolio strategy When portfolios contain more accounts than teams can work at once, the question isn’t simply, “How many accounts can we work?” It is, “Where can our resources have the greatest impact?” The latest Recovery Scores model helps organizations sharpen placement and treatment decisions. It gives debt buyers a way to price and segment portfolios with greater confidence and gives lenders another tool to direct limited collector time across their own post-charge-off portfolios. Learn more about Experian Recovery Scores

November 10, 2026 by Zohreen Ismail
What Is a Third-Party Breach? How to Prepare for and Respond to Vendor Incidents

Learn what a third-party breach is and steps to prepare, contain risk, and support affected customers. Read more!

November 9, 2026 by Laura Burrows
Mortgage Underwriting Moves from Modernization Talk to Action 

Mortgage underwriting is entering a new phase. In a recent conversation with HousingWire’s Allison LaForgia, Michele Bodda, Group President of Experian Housing, Verification Solutions, and Employer Services, discussed how modern credit scores, alternative data and verification tools are changing how lenders evaluate borrowers.  Lenders can now judge modernization by its results, Bodda said. “Now we’re actually letting more modern scores get into underwriting to help price loans and go all the way through to securitization,” she told HousingWire. “We’re letting the scores and the data actually speak for itself instead of just talking about it.”  The Right Data at the Right Time  Modernizing underwriting means providing useful information at the right stage, rather than giving lenders everything at once. “You don’t need everything all at once. You don’t need everything on initial pull,” Bodda said.  Alternative data, such as rental payments and buy now, pay later activity, can help show how consumers manage obligations, especially those with thinner credit files. A thin credit file does not necessarily mean someone has a thin financial life.  “It’s our responsibility as one of the primary data providers to make sure we can make all of that available, so that we’re best representing the consumer,” Bodda said. A fuller view of data may help lenders identify creditworthy applicants who might otherwise be difficult to assess.  Simplifying Verification and Reducing Friction  Bodda also shared how Experian is making credit information more easily accessible and reducing unnecessary costs during the originations process, explaining that new enhancements to Experian’s Power Profile Plus allow lenders to pull credit data at the start of underwriting and request another score later without repurchasing the data.  “You can pull it later and not pay for the credit data again,” Bodda said.   Experian is also investing in income and employment verification, including through a new partnership with Workday. Bodda explained that Experian will continue to focus on process improvement, competition and innovation across the mortgage ecosystem.  A Broader Path to Homeownership  As consumer expectations and underwriting capabilities evolve, borrowers want a process that reflects their financial lives, while lenders seek greater efficiency. Modern scores, relevant data, and streamlined verification can help lenders assess applications with more context—and may help more people pursue homeownership.  “If we as an industry can open this up and bring more people into the process, then we’re going to thrive,” Bodda said in the interview.   Watch the interview and hear all of Michele’s insights, and more here.  

November 6, 2026 by Caroline Basile

Subscribe to our Newsletter

Enter your name and email for the latest updates.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Subscribe to our Newsletter

Don't miss out on the latest industry trends and insights!
Subscribe