Increased customer lifetime value, reduced competitive threats with optimized credit lines increase


The client is a top national bank in Asia with over 100MM credit card customers. The client was facing high competition with some banks offering Credit Line Increase (CLI) as a solid lever to increase customer stickiness, loyalty and revenue generated. The client lacked a systematic and quantitative framework to do CLI to balance risk and revenue.


ElectrifAi implemented a machine learning-based risk assessment for CLI on both permanent and temporary credit line increases. Leveraging quantitative method with a sensitivity model, a CMV (Card Member Value) based optimization solution was implemented to determine the optimal credit line for each customer. A detailed strategy and execution framework was designed to facilitate CLI implementation for customer's business.


increase in profit from servicing current customers
Faster credit line increase decision times with Machine Learning
Improve customer loyalty without higher risk of default