Case Study: Large Retail Credit Card Issuer achieves 5–10% predictive lift and faster model governance with Experian's custom machine-learning acquisition model

Advanced custom acquisitions model based on machine learning

A large issuer of co-branded bank and retail credit cards needed to redevelop its custom acquisition models after discovering its third‑party attribute set was outdated, limited in granularity, and underinvested. The client required a faster, more predictive solution that would replace legacy attributes quickly, comply with strict model governance, and ultimately expand their lendable population; they engaged Experian and a competitor to build parallel custom models.

Experian delivered a machine‑learning acquisition model using proprietary Premier AttributesSM and Trended 3DTM, a sophisticated segmentation approach, and reject‑inferencing parceling, backed by thorough documentation and knowledge transfer. The model was deployed on time and on budget, passed the client’s governance process more smoothly than the competitor’s, and validated to produce a 5–10% lift across all segments; the client has since engaged Experian to develop additional acquisition models.