Bolster alumni engagement as a motivated donor base to offset declining student enrolment leading US university
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.