Guest editorial by J.D. Crouch, Director of Business Development, Lokyata
By their nature, credit unions have always been committed to serving the entirety of their communities, yet there has remained an underserved group of consumers (so-called “no file,” “thin file,” or “credit invisibles”) who lack access to credit and even basic financial services. The reasons for this are well documented, as traditional data sources and methods of decisioning loan applicants have often prevented credit unions from serving this market.
The Consumer Financial Protection Bureau estimates that about a tenth of American adults have no credit history at all. That is equivalent to about 26 million people. An additional 18 million Americans lack enough credit data to generate a usable score. While traditional credit scoring has proven itself effective for many Americans, some of its shortcomings have been revealed in response to significant world events such as the Covid pandemic and the resulting impact on the economy. For example, since the pandemic, credit scores have gone up on the whole, but some of this increase is likely driven by relief programs instituted in response to the pandemic. But how can credit unions know for sure when evaluating potential borrowers?
Credit unions are also feeling some regulatory pressure to expand lending in support of financial equity and inclusion. And just as times have changed in the post-pandemic economy, how credit unions gather consumer data to make lending decisions must also change. In the age of digital transformation and data analytics, the path forward is built around the use of alternative data paired with actionable data insights – enabling credit unions to expand lending while responsibly managing risk.
These initiatives actually pre-date the pandemic, as in December 2019, five federal financial regulatory agencies, including the NCUA, provided a statement that allowed underwriting by credit unions to use alternative data. These agencies recognized data changes for financial inclusion were necessary, and that information not included in traditional data, such as rent rolls, utility bills, and mobile phone payment data is equally helpful when considering the credit history of loan applicants.
Alternative data helps to close the gaps for many loan applicants currently considered “thin files.” Borrower-permissioned access to this data creates opportunities for credit unions to develop better, more inclusive loan programs and in turn, responsibly grow membership. When paired with intelligent automation, underwriting staff can better utilize their time by directing it toward helping more non-prime consumers on the pathway to near-prime and even, prime.
To leverage these tools and successfully meet financial inclusion goals, credit unions should focus on:
Improving the speed and accuracy of the loan process;
Approving opportunities to those previously denied;
Allowing members to have better control over pricing;
Re-evaluating creditworthiness as opportunities arise with newly available data; and
Creating a new system for underwriters to set up borrowers for future success.
As inflation and interest rates rise, and thoughts of a recession loom, the time is now to focus on the improvement process of growing loans. If credit unions can focus on this underserved market in meaningful ways, it could have a profound positive effect on the communities that they serve.
About Author: J.D. Crouch is Director of Business Development for Lokyata, a company focused on delivering products that digitize, automate, and scale lenders’ credit decisions. https://www.lokyata.com/