Fraud score
Every triggered rule, summed into one number — the primary signal for approve, review or decline.
Atna's Scoring Engine evaluates every signal in a transaction, turning your rules and machine-learning models into one verdict — approve, review, or decline — with absolute, auditable precision.
Sophisticated fraud requires layered precision. The engine reads every vector a single check would miss, then weighs each one into the decision.
Every triggered rule, summed into one number — the primary signal for approve, review or decline.
An independent 0–100 probability from the model, catching complex patterns rules alone miss.
Risk from signals tied to the email or phone, enriched with global consortium fraud history.
VPN, TOR, datacenter and proxy detection that pinpoints true origin and neutralises cross-border rings.
Fingerprint, OS and browser anomalies that flag emulators, spoofed setups and repeat offenders.
Send your own fields and aggregates, then score against them with fully tailored rules.
Each transaction crosses four stages — from raw signal to final verdict — every step logged and returned for forensic certainty.
Incoming data is supplemented with extra data points derived from the API request.
Each data point is checked across footprint, device, IP, email and phone.
Rules with a score action sum their values into the fraud score.
The score resolves to approve, review or decline — with the full rule trail.
Atna rolls every score and module check into a single, shareable report — an overall Atna score, AI-written intel, and a per-module breakdown that separates established histories from synthetic, thin-file risk.
One pipeline orchestrates enrichment, rules, lists and machine learning — passively, in real time, before a decision is ever returned.
Atna silently reads device fingerprint, IP reputation and behaviour to build a risk baseline with zero friction.
Default and custom rules fire, each adding, subtracting or forcing a state.
Signals resolve into a fraud score and an explainable AI Insights score.
Labelled outcomes feed back, sharpening every future decision.
Engineered to provide a multi-dimensional view of risk by combining advanced machine learning with real-time data orchestration. Rules give you immediate, explainable control; the models detect synthetic patterns legacy systems miss — together, one structured verdict.
Learn MoreRules, machine learning, lists and categories combine into one structured verdict — far stronger and more accurate than any single check.
Every transaction is scored instantly and assigned a verdict, with the exact signals that raised and lowered the score on show.
Blacklists and whitelists set absolute outcomes; custom lists feed your rules without adding friction for trusted users.
Every decision ships with its rule trail in the API response and on the event timeline. Nothing is a black box.