One of India's largest Non-Banking Financial Companies (NBFCs) manages a diverse loan portfolio across multiple retail lending segments. As the business expanded, the organization faced growing challenges in monitoring collection performance across internal teams and outsourced field agents while maintaining portfolio quality and operational efficiency. To address rising bounce rates, increasing Non-Performing Loans (NPLs), and escalating collection costs, the client partnered with Network Science to build an AI-powered debt collection platform that transformed collection operations through automation and advanced analytics.
The client’s collection ecosystem relied on multiple teams and channels operating across a large borrower base. Limited visibility into collection performance made it difficult to identify risks early and optimize recovery efforts.
Network Science implemented an AI and machine learning-powered debt collection platform designed to create a centralized and data-driven collections operation.
The solution integrated multiple data sources, including:
The platform automated operational workflows and leveraged advanced analytics to prioritize accounts, identify risk patterns, and recommend targeted collection actions.
The transformation delivered measurable improvements within the first six months:
