Payment fraud poses a significant challenge in the digital economy, with e-commerce businesses losing an estimated $48 billion annually to fraudulent transactions and banks facing potential annual fraud losses exceeding $40 billion by 2027. As fraudsters exploit digital payment vulnerabilities, companies are pressed to balance fraud prevention with maintaining seamless customer experiences, making the selection of effective fraud detection tools crucial. The difficulty in detecting fraud arises from the sophisticated tactics used by fraudsters, which often mimic legitimate customer behavior, complicating efforts to distinguish between genuine and fraudulent transactions. To address this, advanced payment fraud detection tools leverage machine learning, device intelligence, and behavioral analytics to identify and prevent fraudulent activities without disrupting legitimate transactions. Businesses must consider industry-specific needs, integration capabilities, and pricing models when selecting these tools, which should continuously evolve to counteract emerging fraud tactics while minimizing false positives and maintaining customer trust.