vocabulary:
  id: amazon-fraud-detector-vocabulary
  name: Amazon Fraud Detector Vocabulary
  description: Controlled vocabulary for Amazon Fraud Detector real-time ML fraud detection.
  version: 1.0.0
  provider: Amazon Web Services
  resources:
  - name: Detector
    description: Orchestrates ML models and rules to generate fraud predictions for events.
    operations:
    - putDetector
    - getDetectors
    - deleteDetector
  - name: Model
    description: ML model trained on labeled event data to score fraud probability.
    operations:
    - putModel
    - getModels
    - deleteModel
    - createModelVersion
    - trainModelVersion
  - name: Rule
    description: A conditional expression using model scores and event variables to trigger outcomes.
    operations:
    - createRule
    - getRules
    - updateRule
    - deleteRule
  - name: EventType
    description: Schema defining the variables, labels, and entity types for a class of events.
    operations:
    - putEventType
    - getEventTypes
    - deleteEventType
  - name: Label
    description: A classification label (e.g., fraud, legit) used to annotate historical events.
    operations:
    - putLabel
    - getLabels
    - deleteLabel
  - name: Tag
    description: Key-value metadata label applied to Fraud Detector resources.
    operations:
    - listTagsForResource
    - tagResource
    - untagResource
  actions:
  - name: put
    description: Create or update a resource.
  - name: get
    description: Retrieve one or more resources.
  - name: create
    description: Create a new resource.
  - name: delete
    description: Remove a resource.
  - name: train
    description: Initiate ML model training.
  - name: tag
    description: Attach metadata to a resource.
  concepts:
  - term: Fraud Score
    definition: A numeric output (0-1000) from an ML model indicating the probability that an event is fraudulent.
  - term: DETECTORPL
    definition: The Amazon Fraud Detector rule language for writing conditional expressions.
  - term: Outcome
    definition: An action label returned when a rule fires (e.g., block, review, allow).
  - term: Online Fraud Insights (OFI)
    definition: An ML model type optimized for detecting real-time online account and payment fraud.
  - term: Transaction Fraud Insights (TFI)
    definition: An ML model type for detecting fraud in financial transaction flows.
  - term: Account Takeover Insights (ATI)
    definition: An ML model type for detecting unauthorized account access and takeover fraud.
  - term: Entity Type
    definition: The subject of an event (e.g., customer, account) used for fraud scoring context.
  - term: Event Variable
    definition: A named attribute of an event (e.g., ip_address, transaction_amount) used as model input.
  tags:
  - Fraud Detection
  - Machine Learning
  - Security
  - Financial Services
  - Real-Time
  - AWS