Overview
A fraud detection system analyzes transactions and account activity in real time to flag payments that look suspicious, using a combination of rules, machine learning models, and signals like device, location, and behavior. Each transaction gets a risk score that decides whether it is approved, challenged, or blocked.
Why It Matters
Blocking too little means chargebacks and direct losses, while blocking too much turns away genuine customers — and both errors are expensive. Static rules alone fall behind quickly, since fraudsters adjust to whatever they learn the rules are.
How Dotcode Applies It
We combine a configurable rules engine with machine learning scoring and feed chargeback and manual-review outcomes back into the model, building on the practices in our AI Integration glossary entry.
