This paper presents key findings from interviews with fraud executives in three different verticals: fashion, sporting goods, and airline travel. Each business used Cybersource fraud solutions built on a unique combination of flexible rules, predictive fraud models, and machine learning. These powerful fraud tools estimate the outcome of each transaction acceptance, rejection, or manual review while reducing fraud losses.
The use cases offer insights into building comprehensive, adaptive fraud management programs to control losses and enhance acceptance rates—even while expanding into new channels across borders and into new product lines.