Component Supplier Lowers Bad Debt $15M With Machine Learning Credit Risk Assessment


A national distributor of electrical components had a significant problem on its hands. Because of the pandemic impact on retailers, their method of tracking and predicting credit risk was becoming strained. With over 10,000 clients – many of them small retailers, they needed a new approach. Download our case study and learn:

  • How they used dotData to identify 400+ predictive signals
  • The significant impact it had on the business, including recovering over $15M per year in AR.
  • Read how they did it all without hiring a single data scientist.

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