A Comprehensive Guide to Alternative Data Sources

Amy Hou  |  December 28, 2018   |  Credit & Lending  


There’s no question that the U.S. is in need of more expansive credit scoring models. The Consumer Financial Protection Bureau (CFPB) estimates that 45 million Americans struggle to get a loan because of insufficient credit history. To date, a number of promising solutions have already come out of the woodwork to address the gap. But, out of the growing multitude of alternative data sources, how can lenders sift through the noise and find the right types of alternative credit data to use?


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While each has its pros and cons, a few stand out as clear winners in the categories of predictive accuracy, reliability, and access. So without further ado, we present: The definitive guide to alternative data sources for credit risk decisioning.

Retailer & Purchase Data

Retailers collect a substantial amount of behavioral data that can provide meaningful insights for credit risk. Purchases of diapers or school supplies on a loyalty card, for example, would reasonably indicate a certain family income and structure. However, access to this type of data is hard to come by. Retailers typically will not sell point-of-service data to lenders or credit bureaus.

For that reason, purchase data is likely better suited for marketing purposes than for credit scoring. Platforms like Cardlytics aggregate anonymized purchase data for retailers, identifying potential customers through browser cookies and device ID. With this data, marketers can easily create targeted digital ads, all without collecting personally identifiable information (PII). Access to anonymous purchase data for marketing is promising; access to individual data for credit scoring is less so.

Social Media Profiles

While certainly non-traditional, social media profiles do contain a wealth of publicly available information on consumer behavior. On the one hand, a lender could view an individual’s LinkedIn profile to assess employment history and professional connections. Facebook and Instagram profiles can reveal lifestyle choices and spending habits. On the other hand, social media history can still be fabricated, and is not easily verified.

Moreover, younger demographics like Generation Z are shifting away from heavy social media use. Aware of potential consequences of public posts, they prefer ephemeral platforms like Snapchat that don’t leave a lasting history. That’s why using social media profiles as a means of establishing credit risk will be less and less reliable over time.

Rent Payments

According to the Center for Financial Services Innovation, rental payments are among the most reliable alternative data sources. Monthly rent payments reveal a steady history of consistent behavior and fiscal responsibility (or lack thereof). Thus, it’s not surprising that when landlords reported rental payments to TransUnion in an experimental study, nearly 20 percent of subjects saw their credit scores increase by 10 points or more after just one month.

Fortunately, rental payment data is also increasingly accessible. After lenders verify rental history with the landlord, tenants can utilize services like Rapid Rent Reporting to add rent as a tradeline to their credit reports. The service will only make sense for consumers if they gain more in lower interest payments than they pay for the service, but the data shows that most underbanked consumers stand to benefit.

Banking Data

Bank account data is one of the most accurate and real-time types of alternative credit data. When lenders and credit bureaus have access to a consumer or business’ bank statements, they can see every credit and debit activity. And, unlike traditional credit reports that are pulled once every 30 days, bank statement data is up-to-date, to the minute that it’s retrieved.

Platforms like Yodlee, Plaid, and Finicity have mastered the secure transfer of bank data to lenders and credit reporting agencies. Many offer consumer-permissioned access channels, ensuring FCRA compliance and allowing consumers to be fully in control of their data. Users simply link their bank accounts via their login credentials, and they can opt-in to share transaction data for credit decisions.

Some consumers may be wary of providing lenders with access to their banking data, as bank accounts do contain sensitive information and would be one of the most damaging accounts to suffer from a cyberattack. Bank statements can also leave out important context. You may be able to tell, for example, that someone pays their rent on the same day every month, which is a good sign. But you can’t tell if they’re paying the full amount that they owe, or even if they’re paying on time (they could just be consistently late).

Utility & Telecom Data

Telecom companies hold copious amounts of relevant data, but some of its use cases are still experimental. Some have proposed using real-time mobile phone data to capture an individual’s location and verify their work and home addresses, thereby determining stability.

Even more accurate of a source is the phone bill itself. A mobile phone bill contains the following data points:

  • Full name
  • Billing address
  • Due date
  • Actual payment date
  • Amount due
  • Actual amount paid

Taken together, these data points reveal a customer’s overall payment history, and not only whether they pay on time every month, but whether they’re paying the full amount they owe.

Utility bills — including electric, water, natural gas, waste, and cable — offer the same data points. These types of alternative credit data, though excluded from traditional credit scoring models, nevertheless show a sound monthly history of payment patterns. The Center for Financial Services Innovation report put utility bill payments on par with rent payments, when it comes to predictive accuracy.

New Ways to Access Alternative Data Sources

More and more lenders are keying in to the notion that utility and telecom histories are valuable alternative data sources. Experian and Finicity just launched a new platform, Experian Boost, that enables consumers to instantly add utility and phone payments to their credit reports. Experian Boost also follows a user-permissioned model; users give Experian permission to access their bank accounts to identify utility and phone payments, and then confirm that the data is accurate.

In terms of access, there’s another, more direct way to retrieve utility and phone payment data, and that’s from the utilities themselves. Urjanet’s Utility Data Platform leverages existing integrations with over 1,000 utility and telecom providers to streamline and deliver accurate phone and utility payment data.

Direct access to utility and telecom payment data can enable lenders to uncover new revenue within their decline traffic, and safely expand credit access to millions of consumers.

With Urjanet’s user-permissioned model, lenders and credit reporting agencies can tap into new alternative data sources with confidence that the data they’re relying on is accurate and compliant. Direct access to utility and telecom payment data can enable lenders to uncover new revenue within their decline traffic, and safely expand credit access to millions of consumers.

The Race for the Right Types of Alternative Credit Data

The credit industry is fully aware of the lending gap it needs to close. Rightfully, lenders and agencies have taken their time investigating various types of alternative credit data, but the clock is ticking. While the near-prime consumer population is growing, only a finite portion are high-quality applicants. Lenders that tap into the right alternative data sources first will gain a vital advantage in reaching and successfully serving this market.

Interested in learning more about accessing utility and telecom payment data from Urjanet? Request a demo today.

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About Amy Hou

Amy Hou is a Marketing Associate at Urjanet, writing about emerging topics in sustainability, energy management, and data innovation.

Tags   Alternative Data   |   Credit   |   Financial Services   |   FinTech   |   Lending   |   Risk Assessment   |   Urjanet   |   Utility Data   |