ZestFinance takes an entirely different approach to underwriting using machine learning and large-scale big data analysis. With a team of some of the world’s best data scientists from Google and lending experts from Capital One, ZestFinance analyzes thousands of potential credit variables – everything from financial information to technology usage – to better assess factors like the potential for fraud, the risk of default, and the viability of a long-term customer relationship.
Their big data underwriting model provides a 40% improvement over the current best-in-class industry score. That translates into more accurate credit decisions, which leads to increased credit availability for borrowers and higher repayment rates for lenders.
This new approach to underwriting will enable lenders to expand their customer base, take business from their competitors, and better serve existing borrowers – without affecting their default rate. Alternatively, lenders can use their model to lower default rates while maintaining a particular approval rate, limiting losses and significantly improving returns.
ZestFinance helps lenders in all credit segments better assess the credit risk of potential borrowers. Their technology can supplement or replace an organization’s current underwriting algorithms. With a proven, transparent method to help lenders measure the impact of their underwriting platform against current models, they can also help assess results in advance.