ZestFinance Helps Millennials Get Financing
ZestFinance announced the release of its Zest Automated Machine Learning (ZAML) Platform for credit underwriting. ZAML, which was created to help Millennials and those with a limited credit history get financing, helps potential lenders analyze non-traditional credit data.
ZAML, which complies with all regulatory requirements, will help banks, credit card issuers and auto financiers increase their revenues while managing risk. On the consumer side, it will help new borrowers, particularly Millennials, finance their first major purchase.
“The difficulty financial institutions face underwriting millennials is their limited credit histories — they’re a classic example of thin-file or no-file borrowers,” said Douglas Merrill, Founder and CEO of ZestFinance. “Traditional underwriting works well when evaluating borrowers with long credit histories, but when there is limited data, it can’t differentiate between creditworthy and high-risk applicants. Machine learning fills those gaps by analyzing a vastly broader set of data.”
Traditional underwriting systems , which rely on data provided from credit bureaus, often overlook Millennials or those who have a limited credit history, such as recent immigrants or new small business owners. Some of these applicants would actually make good borrowers, but traditional lending models do not give financial institutions any insights into the risk involved with these applicants. Not only does this block these borrowers from gaining a line of credit, the banks also miss out on potential profits and growth.
ZAML analyzes payment histories, purchase transactions and customer support data, and can even combine traditional credit information with nontraditional credit variables, including how a customer navigates a lender’s site, fills out a form and more. This will help banks better assess the risk involved with applicants who have a limited credit history.
Zest Finances has also partnered with China’s largest online direct sales company, JD.com, to expand consumer credit in China. Since there are more than half a billion people in China without a credit history, it is extremely difficult for banks to expand to this market, as traditional underwriting makes it difficult to assess risk.