An Unscoreable Consumer Could Become Your Next Great Member

Posted by Miriam De Dios Woodward on March 6, 2018

Somewhere between 50 and 80 million U.S. consumers have little or no credit history. That’s somewhere in the range of 15 to 25 percent of the U.S. population. What this means is that a massive number of people in America are “unscoreable” by most traditional models.

At the same time, acquiring new members is becoming increasingly difficult for credit unions. Competition and financial consumer expectations have never been more complex and fast-moving.

What if there was a way for credit unions to avoid turning away “unscoreable” consumers for loans and other services? What if there was a way to welcome them without increasing a cooperative’s risk profile?

No Credit Does Not Mean Bad Credit

Just because a consumer is unscoreable by most traditional credit scoring models doesn’t mean he or she won’t be able to pay back a loan. Several alternative models available today can help a lender evaluate a consumer’s ability to repay. Below are some examples, along with the types of data they incorporate into their models:

eCredable – Bills, such as rent, utilities, mobile phone, cable/satellite TV and insurance

Cignifi – Mobile phone behavior data

First Access – Prepaid mobile-phone payment histories

TrustingSocial – Social, web and mobile data

Kabbage – e-commerce histories from sites like Amazon

Experian’s Emerging Credit Score – Internet and direct-marketing purchases, property and asset records and telecommunications and utility data

TransUnion CreditVision Link – Property tax records and checking/debit account records

LexisNexis RiskView – Residential stability, asset ownership, derogatory status, life-stage analysis

One thing all these companies have in common: They’re using big data to create better outcomes for consumers and meaningful value for lenders. And credit unions have the opportunity to do so, as well.

Alternative sources of consumer data, such as utility records, cell phone payments, medical payments, insurance payments, remittance receipts, direct deposit histories and more, can be used to build better risk models. Armed with this information – and with the proper programs in place to ensure compliance with regulatory requirements and privacy laws – credit unions can continue making responsible lending decisions while better serving the underserved.

How One Organization Successfully Uses Alternative Credit Scoring

Kinecta Federal Credit Union uses an alternative data score from LexisNexis known as Riskview to assess creditworthiness for traditionally unscoreable borrowers. The model factors in data from sources like utility bills, public records, address and employment stability, among many others alternative data elements. The result is a Fair Credit Reporting Act (FCRA) regulated score.

By using nontraditional credit verification methods, Kinecta is able to approve more than 60 percent of the applications it receives. Since 2014, Kinecta has made about 20,000 loans for more than $30 million.”

How Alternative Credit Scoring Fits the Credit Union Philosophy

Credit unions exist to help people, not make a profit. Their goal is to serve all members well, including those of modest means – the very people most likely to be unscoreable by traditional credit scoring models. Many of these consumers fall into one or more of the following segments:

• Unbanked/underbanked
• First-generation immigrants
• Millennials
• Rural consumers

Alternative credit scoring provides credit access to consumers who may otherwise be turned down for a loan or forced to turn to a predatory lender. Using payment history and other data sources to evaluate a consumer’s creditworthiness is an excellent example of “people helping people” – one that benefits both consumers and credit unions alike.

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