Being the best at what you do is both a blessing and a curse: business grows rapidly, but fraudsters also take notice. For Toronto-based dbrand – the foremost leader the custom electronics skin industry – malicious users on their e-commerce site lead to costly chargebacks and threatened the user experience for legitimate shoppers. Fraudsters wielding stolen credit card information would come to dbrand’s site, and the Customer Service team was tasked with managing the resulting manual review required. When their chargeback rate hit an average monthly high of 2.18%, dbrand was ready for a more sustainable solution.
With Sift Science, dbrand demolished fraud on their site. The chargeback rate dropped to 0.12%, saving the company thousands of dollars every month. How did dbrand manage this turnaround in mere weeks? With large-scale and real-time machine learning. Learn more about the special tools and features that dbrand uses in our new case study.
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