What is Fraud Detection?

Fraud detection is the real‑time and batch process of separating normal behavior from abuse across signups, payments, and account changes. Rules catch clear tells—mismatched AVS/CVV, repeat declines, sudden velocity. Machine learning handles the gray—device graphs, graph centrality, corridor risk, behavior rhythm. The strategy decides: approve, challenge, hold, or decline. Fast, explainable, and measured.

Ingredients: clean capture, feature pipelines, champion/challenger models, reason codes, and analyst feedback loops. Measure what matters—approval rate, fraud per approved dollar, false positives, time‑to‑decision. Log everything so disputes and audits aren’t archaeology projects three months later.

Where value climbs (payouts, recovery), bind users with robust identity verification. At the edge, harden checkout and post‑purchase flows using our payment fraud prevention guidance, so friction lands where it hurts attackers, not customers.

Detection isn’t justice. It’s triage—fast, biased toward safety, and always learning.