Fraud Score API
Event signals in. Fraud probability, the reasons, and a decision out.
Transactional and account fraud risk scoring powered by Brainiall Fraud engine. Send whatever signals you have for a payment, signup or login â amount vs. the account's norm, velocity, device/IP novelty, geo mismatches, AVS/CVV, chargeback history â and get back a 0-1 fraud probability, a risk level, the exact risk factors that drove the score, and a recommended allow / review / deny decision. $0.0075/event. Report real outcomes via /feedback and the model re-calibrates to your own data.
How we compare
The incumbents either make you train and host a model yourself (AWS Fraud Detector), gate the product behind an enterprise sales motion and a percentage-of-GMV contract (Sift, Kount, Signifyd, Riskified), or only score the payments that flow through one processor (Stripe Radar). Brainiall is a flat per-event REST call: send signals, get a scored decision with the reasons attached, improve it with your own labels â self-serve from the first call, no platform to adopt.
| Provider | Shape | Pricing model | Approx. price | Onboarding |
|---|---|---|---|---|
| Brainiall Fraud Score | REST: /score + /feedback â explainable, model-agnostic signals | Per scored event | $0.0075 / event (/feedback free) | Self-serve, instant API key |
| AWS Fraud Detector | Train & host your own model on AWS, then call it | Per prediction (+ training/storage) | ~$0.005â$0.03 / prediction | AWS account + model training |
| Stripe Radar (for Fraud Teams) | Rules + ML, bundled into Stripe payments | Per transaction | ~$0.05 / transaction (Radar for Fraud Teams) | Stripe-processed payments only |
| Sift / Kount / Signifyd / Riskified | Enterprise fraud platform (often chargeback-guarantee) | % of GMV / per-order contract | Enterprise pricing | Sales-led, long onboarding |
Prices are list-price approximations for orientation, not quotes â most fraud vendors price by negotiation. Always check each vendor's current terms.
Pricing
One per-event price for scoring; submitting outcomes via /feedback is unmetered. The free tier is enough to wire scoring into a checkout flow and start collecting feedback.
Free
$0/mo
100 scored events/month · /feedback unmetered · forever free
Starter
$39/mo
~10,000 events/month · custom decision bands · feedback dashboard
Pro
$149/mo
~50,000 events/month · priority queue · 99.5% SLA
Business
$499/mo
~200,000 events/month · re-calibration on your labels · dedicated capacity · email + Slack
PAYG: $0.0075 / scored event (Brainiall Fraud engine). /feedback calls are free. No minimum spend, no contract, no percentage of your GMV.
Two calls: score, feedback
# 1. Score an event â send whatever signals you have; all fields are optional
POST https://api.brainiall.com/v1/fraud/score
{"event_id": "ord_8821", "event_type": "payment",
"amount": 4200, "currency": "USD", "avg_txn_amount_30d": 85,
"txn_count_1h": 7, "distinct_cards_24h": 4, "distinct_countries_24h": 3,
"is_new_device": true, "is_new_ip": true, "is_tor": true,
"card_country": "US", "ip_country": "RU", "account_age_days": 0,
"avs_match": false, "cvv_provided": false, "prior_chargebacks": 1}
-> {"event_id": "ord_8821", "fraud_probability": 0.99, "risk_level": "critical",
"decision": "deny", "risk_score_points": 28.0,
"risk_factors": [
{"factor": "amount_far_above_typical", "weight": 5.0, "direction": "increases_risk",
"detail": "amount is 49.4x the 30-day average (4200.00 vs 85.00)"},
{"factor": "tor_exit_node", "weight": 3.5, "direction": "increases_risk",
"detail": "request originated from a Tor exit node"},
... ],
"decision_bands": {"allow_below": 0.40, "review_below": 0.75},
"model": "Brainiall Fraud engine"}
# override the bands per request: "decision_bands": {"review": 0.30, "deny": 0.80}
# 2. Report the confirmed outcome so the model re-calibrates to your data
POST https://api.brainiall.com/v1/fraud/feedback
{"event_id": "ord_8821", "label": "chargeback", "notes": "issuer dispute, fraud confirmed"}
-> {"event_id": "ord_8821", "label": "chargeback", "accepted": true, "feedback_id": 42}
# label â fraud | legitimate | chargeback | dispute
GET https://api.brainiall.com/v1/fraud/feedback/stats
-> {"total": 1240, "by_label": {"legitimate": 1180, "fraud": 41, "chargeback": 19}}Every field is optional â start with the three or four signals you already have and add more over time; the score and the risk-factor list adjust accordingly. The response is fully explainable: risk_factors lists exactly which signals moved the score and by how much (positive = increases risk, negative = a mitigant), so you can show a human reviewer why an event was flagged.
What it's for
- Checkout / payment risk: score each transaction at authorization time and auto-approve the clearly-good, send the borderline to manual review, and block the clearly-bad â with the reasons attached for the review queue.
- Signup & account-creation abuse: catch fake-account farming and promo abuse from the velocity, device/IP novelty, disposable-email and VoIP-phone signals before the account does anything.
- Account-takeover signals: flag logins and account changes that come from a new device/IP, an anonymizing network, or a country that doesn't match the account's history.
- Card-testing detection: spot bursts of small transactions across many cards on one account â the classic stolen-card validation pattern.
- Tune it to your business: override the allow/review/deny probability bands per request, and feed confirmed outcomes (chargebacks, disputes, confirmed-good) back via
/feedbackso the model re-calibrates to your own fraud rate. - One bill, one key: same Brainiall API key and usage-based billing as the rest of the catalog â no separate fraud vendor to procure, no percentage of GMV.
Press kit & resources
What reviewers, integrators and procurement teams typically ask for.
One-page datasheet
Pricing, the signal list, and copy-pasteable curl snippets on one page â built for buyer review.
Download PDFAPI reference
OpenAPI spec, the full signal schema, the risk-factor catalog, error codes and rate limits.
Read docs âCompare the catalog
How Brainiall's specialty APIs line up against AWS, Stripe and the fraud specialists, use case by use case.
See the comparison âMore specialty APIs
Same single API key, same usage-based pricing, different problem solved.



