How a leading US based bank used Predictive Insights to lower delinquencies and net loss

One of the leading banks in East Coast USA – has been witnessing rapid growth in their loan portfolios, and they were facing an increase in their overall delinquency rates and potential losses due to net charge-offs. It was imperative for the bank to overhaul their debt collection strategy.

Different initiatives were attempted, such as a new core collections strategy and implementing statistical models for risk segmentation, but there were challenges in implementation which was complicated by the manual effort required and rising operational costs. There was an urgent need for a solution to that could be used across products consistently, and be easily modified based on business needs.

With Edgeverve’s FinXEdge Collect (formerly CollectEdge) – a data-driven intelligent application powered by advanced Machine Learning and AI, the bank was able to

  • Segment accounts based on the likelihood of recovery
  • Identify patterns in customer behavior for improved engagement
  • Co-relate macro-economic factors such as weather, economy etc.
  • Initiate risk evaluation early on in the loan lifecycle
  • Predict future delinquencies with intelligent insights

Read this case study to learn how FinXEdge Collect helped the bank achieve 105 bps reduction in roll rates, and over 70% improvement in savings.

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