Fighting Fraud with Dynamic Predictive Segmentation
The rapidly changing landscape of fraud requires a tool that can swiftly adapt to emergent threats. simMachines’ Dynamic Predictive Segmentation provides a highly accurate way to identify threats new and old by coupling cutting edge accuracy with unparalleled transparency and continuous learning. The union of these powerful features results in a tool that not only provides top-tier fraud detection but also enables customers to proactively combat fraud by identifying the underlying factors that are evidence of fraud for each transaction. For this demonstration we’ve trained a classifier with a credit card transaction dataset labeled with transaction state: fraud / normal and built clusters around that classifier. The result is highly accurate predictive clusters that identify the different types of fraud being committed. Let’s take a dive into the clusters.