Part 2/9:
Historically, the landscape of payment fraud detection has relied heavily on classical machine learning techniques. These typically involve engineering specific features from transactional data—like payment method, zip code, and other identifiers—to discern and minimize fraudulent activity. Each model has focused on specific tasks like authorization, fraud detection, and dispute management, often limiting their effectiveness in spotting developing fraud trends.