Case Study: a regional retailer eliminates $5M in fraud with dotData

How A Regional Chain of Stores Eliminated $5M in Fraud with Predicitve Analytics

A regional retailer with over 200 locations was struggling to manually monitor and prevent widespread fraud, including employee-assisted theft and customer return fraud. This manual process was consuming valuable manager time and was ineffective at providing actionable insights across all of its stores, leading to significant revenue loss. The retailer engaged dotData to leverage its automated feature engineering (AutoFE) and machine learning (AutoML) technology to address this challenge.

dotData's AI-powered solution analyzed billions of data points to identify subtle, hidden fraud patterns. This allowed the retailer to quickly generate and deploy highly targeted fraud prevention measures. The results were significant, with dotData's solution enabling an estimated cost recovery of over $5 million. Furthermore, the entire process required zero lines of code and allowed the retailer to update its fraud prevention policies in less than one day based on the model's output.