Case Study: Private Label Credit Card Provider achieves 20% operational efficiency gain and 25% bad-debt reduction with Dun & Bradstreet custom risk analytics

Private Label Credit Card Provider Increases Efficiency 20%

A leading private‑label credit card issuer faced a sudden surge in volume after winning a major retailer contract—applications jumped from about 3,000 to 7,000 per month. Their existing off‑the‑shelf scoring models and manual reviews couldn’t deliver the instant, accurate decisions required at scale, and hiring large teams was not a viable option. The company needed more precise, API‑integrated risk models to automate decisions while maintaining low credit losses.

Dun & Bradstreet’s Advanced Analytics team built and hosted custom predictive models using the Data Cloud plus small‑business repositories (SBRI and SBFE), integrated via API for real‑time scoring and lifecycle management. The solution automated over 80% of credit decisions, cut bad debt by 25%, and improved collections and operational efficiency by about 20%, enabling faster turnaround and full automation without adding staff, supported by ongoing monitoring and partnership.