Amazon Fraud Detector
Amazon Fraud Detector is a fully managed service that uses machine learning to identify potentially fraudulent activities and accurately distinguish between legitimate and high-risk transactions. It uses your data and the same technology that Amazon uses to protect its own business from fraud.
Amazon Fraud Detector publishes 7 APIs on the APIs.io network, including Detectors API, Event Types API, Labels API, and 4 more. Tagged areas include Financial-Services, Fraud Detection, Machine-Learning, and Security.
The Amazon Fraud Detector catalog on APIs.io includes 1 JSON-LD context and 2 Spectral governance rulesets.
Amazon Fraud Detector’s developer surface includes authentication, developer portal, documentation, support, engineering blog, developer console, signup flow, and 24 more developer resources.
Kin Score
Kin Score
How this is scored →scored 2026-09-08 · rubric v0.20.0
APIs 7
Individual APIs this provider publishes, each with its own machine-readable definition.
Amazon Fraud Detector Detectors API
Fraud detector configurations
Amazon Fraud Detector Event Types API
Event schema definitions
Amazon Fraud Detector Labels API
Fraud and legitimate transaction labels
Amazon Fraud Detector Models API
ML model training and versioning
Amazon Fraud Detector Predictions API
Real-time fraud prediction
Amazon Fraud Detector Rules API
Business logic rules for fraud decisions
Amazon Fraud Detector Tags API
Resource metadata labels
Scroll for all 7
Postman Collections 1
Ready-to-run Postman collections for exercising this provider's APIs.
Amazon Fraud Detector API
POSTMANOpen Collections 9
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
API Collection
OPEN COLLECTIONAmazon Fraud Detector Detectors API
OPEN COLLECTIONAmazon Fraud Detector Detectors Event Types API
OPEN COLLECTIONAmazon Fraud Detector Detectors Labels API
OPEN COLLECTIONAmazon Fraud Detector Detectors Models API
OPEN COLLECTIONAmazon Fraud Detector Detectors Predictions API
OPEN COLLECTIONAmazon Fraud Detector Detectors Rules API
OPEN COLLECTIONAmazon Fraud Detector Detectors Tags API
OPEN COLLECTIONAmazon Fraud Detector API
OPEN COLLECTIONScroll for all 9
Arazzo Workflows 8
Multi-step API workflows described with the Arazzo specification.
Amazon Fraud Detector Author Rule
Create a DETECTORPL rule for a detector and read the detector's rules back to confirm it.
ARAZZOAmazon Fraud Detector Bootstrap Event Type
Create fraud and legit labels, define an event type that uses them, then confirm the event type exists.
ARAZZOAmazon Fraud Detector Decommission Detector
Inspect a detector's rules and then delete the detector, branching when rules still block deletion.
ARAZZOAmazon Fraud Detector Detector Pipeline
Define an event type, create a detector and a rule, then score a sample event against the detector.
ARAZZOAmazon Fraud Detector Inventory Models and Detectors
List models for an event type, then list detectors and tag a chosen detector with its model count.
ARAZZOAmazon Fraud Detector Provision Model and Detector
Define an event type, create an ML model and a detector on top of it, then confirm the detector exists.
ARAZZOAmazon Fraud Detector Score Event and Tag
Score an event against a detector and branch on the returned model score to tag the detector accordingly.
ARAZZOAmazon Fraud Detector Tag and Audit Resource
Assign tags to a Fraud Detector resource and read its tags back to confirm they were applied.
ARAZZOScroll for all 8
Pricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Amazon Fraud Detector Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Features 7
Notable capabilities this provider offers.
No ML Expertise Required
Automatically trains and deploys ML models using your historical transaction data without requiring ML expertise.
Real-Time Fraud Scoring
Returns fraud scores within milliseconds for integration into transaction approval flows.
Pre-Built Models
Online Fraud Insights (OFI), Transaction Fraud Insights (TFI), and Account Takeover Insights (ATI) pre-trained model types.
Rule Engine
DETECTORPL rule language allows writing conditional logic using model scores and event variables.
Model Explainability
Variable importance scores explain which factors most influenced a fraud prediction.
Cold Start Protection
Uses Amazon fraud experience to provide immediate predictions even with limited historical data.
Event Ingestion
Ingest historical labeled events to continuously improve model accuracy over time.
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Semantic Vocabularies 1
JSON-LD contexts and semantic vocabularies used across these APIs.
Spectral Rules 2
Spectral governance rulesets for linting and validating these APIs.
Amazon Fraud Detector API Rules
SPECTRALAmazon Fraud Detector API Rules
SPECTRALJSON Schema 5
Standalone JSON Schema definitions for this provider's data models.
JSON Structure 5
JSON Structure definitions describing this provider's data shapes.
Amazon Fraud Detector Detector Structure
JSON STRUCTUREAmazon Fraud Detector Event Type Structure
JSON STRUCTUREAmazon Fraud Detector Model Structure
JSON STRUCTUREAmazon Fraud Detector Rule Structure
JSON STRUCTUREAmazon Fraud Detector Tag Structure
JSON STRUCTUREExamples 5
Example request and response payloads for these APIs.
Security Posture 4
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
Recommended x-agentic-access execution contracts for AI agents.
Use Cases 6
What developers build with this provider.
Payment Fraud Detection
Score credit card and payment transactions in real-time to block fraudulent purchases.
Account Takeover Prevention
Detect unauthorized login attempts and account compromise using behavioral signals.
New Account Fraud
Identify fraudulent new account registrations at signup to prevent synthetic identity fraud.
Promotion Abuse Detection
Flag users abusing discount codes, referral bonuses, and promotional offers.
Chargeback Prevention
Reduce chargeback rates by blocking high-risk transactions before they complete.
Insurance Claims Fraud
Score insurance claims for fraudulent patterns in real-time during claim submission.
Resources
Get Started 3
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 11
Pagination, idempotency, versioning, errors, and events
Scroll for all 11
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
Other 1
Properties that don't map to a standard resource type
Source (apis.yml)
Work with this as data
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