Case Study: a leading gold loan provider reduces churn with NeenOpal's customer churn prediction model

Leading Gold Loan Provider - Customer Case Study

The case study details a project for a leading gold loan provider, a Non-Banking Financial Company (NBFC) in Sri Lanka, which was struggling with rising customer churn. They lacked a predictive framework to identify at-risk customers and understand the drivers of churn. NeenOpal was engaged to address these challenges with a machine learning solution.

NeenOpal developed a machine learning-driven churn prediction model that analyzed customer behavior to forecast risk. The solution achieved 90% accuracy in predicting churn, which enabled the client to run targeted retention campaigns. This led to a 20-30% reduction in customer churn and provided a 3x return on investment from focusing on high-risk segments.