For Agents
Score a transaction for fraud risk and submit post-transaction feedback through FraudLabs Pro's v1 fraud-detection endpoints. Authentication is the API key on each request.
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the FraudLabs Pro Fraud Detection, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
What an agent can do with FraudLabs Pro Fraud Detection API.
Score a transaction for fraud risk via /v1/order/screen with order, billing, IP, and payment fields
Receive a fraud score and recommended action (approve, review, reject) for each scored order
Submit post-transaction feedback (approved, rejected, chargeback) via /v1/order/feedback
Detect proxy, VPN, and high-risk IP signals as part of the screening response
GET STARTED
Use for: I need to score a transaction for fraud risk, Send a chargeback signal for an order I screened earlier, Check whether the customer's IP looks like a proxy, Mark an order as approved so the model learns the outcome
Not supported: Does not handle payment processing, refunds, or SMS verification — use for transaction fraud scoring and post-transaction feedback only.
Jentic publishes the only available OpenAPI document for FraudLabs Pro Fraud Detection, keeping it validated and agent-ready.
FraudLabs Pro Fraud Detection is the version 1 fraud-screening API for online merchants who need to detect chargeback risk on credit-card, PayPal, and cash-on-delivery transactions. The spec exposes two endpoints: /v1/order/screen scores a transaction in real time and returns a fraud verdict with the underlying signals, while /v1/order/feedback records the eventual outcome (approved, rejected, chargeback) so the per-merchant model improves with usage.
Improve the per-merchant fraud model over time by sending consistent feedback
Patterns agents use FraudLabs Pro Fraud Detection API for, with concrete tasks.
★ Real-Time Order Screening
An online merchant calls /v1/order/screen during checkout with the cart, billing and shipping addresses, customer IP, and payment method. FraudLabs Pro returns a numeric fraud score plus recommended action so the merchant can auto-fulfil low-risk orders, route medium-risk to manual review, and reject high-risk ones before settlement.
POST /v1/order/screen with the API key plus the order, billing, shipping, IP, and payment payload, then act on the recommended action in the response
Post-Transaction Feedback Loop
Once the bank settles or charges back, the merchant calls /v1/order/feedback with the original order id and the realised outcome. FraudLabs Pro uses the feedback to tune the per-merchant model so future screens reflect what is actually fraud for that merchant's customer base.
POST /v1/order/feedback with the order id and the status (APPROVED, REJECTED, or CHARGEBACK) once the transaction settles
Cash-On-Delivery Risk Filter
Cash-on-delivery merchants in Southeast Asia screen orders against FraudLabs Pro before dispatching the courier. The screen catches obvious fraud signals (mismatched IP and shipping country, proxy IPs, blacklisted phone numbers) so the merchant avoids the most expensive failure mode for COD: a delivered order the customer refuses.
POST /v1/order/screen with the COD order's phone, address, and IP and decline dispatch if the recommended action is REJECT
AI Agent Fraud Triage
An agent triages a checkout queue, calling FraudLabs Pro through Jentic to score each order and submitting feedback once outcomes are known. The agent never sees the API key directly and surfaces a plain-language summary explaining the verdict for each order.
Search Jentic for 'score an order for fraud risk', load the /v1/order/screen schema, execute against each pending order, then post a summarised verdict to operations
2 endpoints — fraudlabs pro fraud detection is the version 1 fraud-screening api for online merchants who need to detect chargeback risk on credit-card, paypal, and cash-on-delivery transactions.
METHOD
PATH
DESCRIPTION
/v1/order/screen
Score an order for fraud risk
/v1/order/feedback
Submit post-transaction feedback (APPROVED, REJECTED, CHARGEBACK)
/v1/order/screen
Score an order for fraud risk
/v1/order/feedback
Submit post-transaction feedback (APPROVED, REJECTED, CHARGEBACK)
Three things that make agents converge on Jentic-routed access.
Credential isolation
The FraudLabs Pro license key is stored encrypted in the Jentic vault and replaced with a scoped execution token before each call. Even a fully compromised agent prompt cannot leak the key.
Intent-based discovery
Agents call Jentic search with intents like 'score an order for fraud risk' and Jentic returns the matching FraudLabs operation with its input schema, so the agent only deals with two endpoints rather than parsing the spec.
Time to first call
Direct integration of the v1 endpoints: about a day to wire screen and feedback into the order lifecycle. Through Jentic: under 30 minutes — search, load, execute.
Alternatives and complements available in the Jentic catalogue.
FraudLabs Pro v2 API
v2 of the same FraudLabs Pro product with refreshed paths and SMS verification endpoints
Choose v2 for new integrations; use v1 only when migrating an existing customer who already calls /v1 paths.
Sift
Sift is a higher-end fraud and trust platform with richer event types and configurable ML
Choose Sift for high-volume merchants with dedicated risk engineering; choose FraudLabs Pro when cost-effective per-transaction scoring is the priority.
MaxMind minFraud
MaxMind minFraud focuses on IP intelligence and device-based fraud signals
Choose MaxMind when IP and geolocation signals dominate the use case; choose FraudLabs Pro for full order-level scoring with feedback.
Specific to using FraudLabs Pro Fraud Detection API through Jentic.
What authentication does the FraudLabs Pro Fraud Detection API use?
The v1 fraud-detection API takes the FraudLabs Pro license key on each request as a parameter. Through Jentic, the key is stored encrypted in the vault and substituted at execution time so it never enters the agent's context.
Can I score a credit-card transaction for fraud risk with this API?
Yes. POST to /v1/order/screen with the billing address, shipping address, customer IP, item list, and payment method. The response carries a numeric fraud score, a recommended action, and the underlying signals such as IP proxy detection and address mismatch.
What are the rate limits for the FraudLabs Pro Fraud Detection API?
FraudLabs Pro applies monthly transaction quotas per plan rather than per-second rate limits. The free Micro plan covers a few hundred screens per month and paid plans scale into the millions; only /v1/order/screen calls count toward quota, not feedback.
How do I send chargeback feedback through Jentic?
Search Jentic for 'send fraud feedback', load the /v1/order/feedback schema, and execute it with the order id from the original screen plus status set to CHARGEBACK. The feedback retrains the per-merchant model so future screens of similar customers are more accurate.
Is the FraudLabs Pro v1 API free?
FraudLabs Pro offers a free Micro plan with a small monthly screen allowance, and paid plans scale by volume. The v1 fraud-detection endpoints share the same plan and quota as the rest of the FraudLabs Pro product.
Should I use v1 or v2 of the FraudLabs Pro API?
New integrations should use v2 (under /v2/order/screen) for the latest signals and the SMS verification endpoints. The v1 endpoints under /v1 remain supported for legacy integrations and follow the same scoring contract.