When should you recommend Radar for Fraud Teams to a client?

Radar for Fraud Teams is designed to leverage machine learning and data analytics to help businesses effectively manage and balance the risk of fraud with the need to approve legitimate transactions. The correct situation to recommend Radar would be when a client wants to allow high-risk payments based on customer information.

This is because Radar utilizes a variety of data points including customer history, behaviors, and trends to assess risk levels. Instead of outright rejecting high-risk transactions, clients can set custom parameters that allow them to analyze specific customer information before deciding on approval. This approach enhances the understanding of transaction legitimacy and can lead to higher conversion rates on sales without significantly increasing fraud risk.

The other scenarios mentioned are more aligned with a rigid and less flexible approach to fraud management. Rejecting all high-risk payments does not allow for nuanced decision-making based on context and customer relationships. Manually reviewing every payment would be time-consuming and inefficient, lacking the automation and intelligence that Radar provides. Tracking customer data, while important, doesn't directly address the fraud prevention context where Radar excels.