Case Study

Large Lender Improves Targeting and Segmentation without Adding Friction

Case Study

Large Lender Improves Targeting and Segmentation without Adding Friction

Financial firms struggle to get accurate customer income estimations, which they need for the entire consumer lifecycle - from prospecting to account management. Traditional income models have been helpful, but oftentimes they result in friction, coverage gaps, and inaccuracy. However, there is a better way.

In this case study, we show how one large lender achieved its goals by leveraging a next generation income model that:

  • provided a more accurate and reliable income estimation
  • more accurately scored a wider consumer audience, including those who lack traditional credit
  • worked automatically behind the scenes, thus improving the customer experience

The results were stunning. The lender saw a double-digit lift in income estimation accuracy and scored nearly 100% of consumer names. With these results, the lender was able to:

  • Quickly verify income to clear loan stipulations and accelerate funding
  • Gain a better understanding of risk throughout the consumer lifecycle
  • Improve non-adverse action risk management
  • Help provide a frictionless process for customers

Find out more about this next generation income model and what it could do for your company.