Case Study: a leading NBFC in Sri Lanka speeds up gold loan approvals with NeenOpal's AI credit scoring model

Leading NBFC Company - Customer Case Study

The client, a leading NBFC company in Sri Lanka, struggled with inefficient and outdated manual processes for its gold loan risk assessments. This led to inconsistent loan-to-value (LTV) decisions, delayed approvals, and a lack of personalized offers for customers. To address these challenges, the NBFC partnered with vendor NeenOpal to develop a machine learning-based credit scoring solution.

NeenOpal built an automated customer scoring model using predictive analytics to assess individual risk profiles. The solution segmented customers into risk tiers, which allowed the client to confidently offer higher LTVs to trustworthy borrowers. This data-driven approach implemented by NeenOpal resulted in a 40% reduction in average loan approval times and a significant increase in both customer retention and portfolio quality.