Understanding the Underserved
“These potential borrowers are not from any particular ethnic or socio-economic background—it’s more situational,” says Brian Biglin, chief credit officer of Elevate, an alternative credit provider that lends to customers underserved by mainstream lenders. The firm has originated $5.9 billion in credit to more than 2 million non-prime customers in the U.S. and U.K. through its installment loan and line-of-credit products.
Through its research arm, the Center for the New Middle Class, Elevate is able to take an aerial view of the underserved market. “We encounter attorneys, doctors, teachers, and many gig economy workers. Many of them have volatile or irregular income,” Biglin says. Elevate’s data-driven approach to understanding their customers reflects its approach to lending, but like other non-prime lenders, they cannot aggregate and analyze vast amounts of customer data on their own. They need the right technology platforms in place to make that possible.
Elevate Credit are industry leaders when it comes to approving loans for high-risk consumers, and their approach is helping make lending both fairer and more inclusive. The Elevate team are known for their forward-thinking approach to risk decisioning, so we asked Ken Schultz, VP of Data Science at Elevate, to discuss how data and technology make it possible to quickly decision non-prime loan applications. Listen to him talk about using smarter risk decisioning to expand your market in the webinar recording.
Technology helps balance risk and opportunity
Non-prime lenders must balance their desire to maximize revenue, lend responsibly, and manage risk. To do this, they must use non-traditional data to find and underwrite customers who others cannot, with speed and efficiency. It’s a tall order for some: non-prime lending is a category mired in paper-based processing of leads and applications in a market where the speed of approval is everything to an anxious applicant.
“Our credit-approval system is driven by data and analytics,” Biglin says, referring to his firm’s extensive use and scrutinization of alternative data—financial information that typically isn’t available through a traditional credit report. “For example, expats and millennials have cell phones, cable bills, utility bills, subscriptions. Yet, a good majority of what they pay on daily terms isn’t even present on their credit report—if they even have one.”
Risk assessment: Call in the tech wizards
Alternative data is part of a larger qualification and approval microcosm that can include several technologies, processes, and business partners. Elevate works with its internal data scientists to take streams of unstructured, alternative data—often thousands of alternative data points—and run them through its risk models. These models employ algorithms, fostered by advanced machine learning techniques, to score creditworthiness and regulatory compliance, including a prospect’s potential for default
Pulling this all together for Elevate is the Provenir risk analytics and decisioning platform. This hub stores Elevate’s alternative data streams in the cloud, where risk-assessment modeling on prospects and customers takes place. The Elevate team then shares modeling results with its data scientists, who adjust and refine the model and put it back into production. By continually refining and repeating this data filtration and analysis, Elevate can increase the number of credit approvals they make, and thus provide access to credit for thousands of additional households.
Technology also allows Elevate to tailor the user application experience based on specific risk factors, so higher risk applicants, with inconsistencies in their applications, will trigger additional verification steps, “The Provenir risk decisioning platform allows us to create customized risk-based experiences. We can use thousands of data elements in real time to ease the user experience and make decisions,” said Biglin.
Expanding Your Market: Using Data to Reduce Lending Risk and Increase Approval Rates
In this on-demand webinar award-winning lender Elevate Credit’s VP of Data Science discusses lending in the non-prime market, using technology to improve decisioning accuracy, and how data can expand your market.