Last updated on August 7, 2025
Amazon Fraud Detector Cheat Sheet
Amazon Fraud Detector is a fully managed service that uses machine learning and Amazon’s expertise to help businesses identify and prevent online fraud. It enables quick and effective creation, deployment, and management of fraud detection models, even for those with limited ML experience.
Features
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Automated Model Creation: Automatically builds and trains custom fraud detection models from historical data.
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Real-Time Predictions: Installing fraud risk assessments for individual events or batch processing occurs.
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Customizable Rules Engine: Offers flexible rule-based decisions that integrate with fraud detection models and external inputs.
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Continuous Model Improvement: Models evolve as more data becomes available, improving fraud detection.
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Integration with AWS Services: Integrates easily with AWS Lambda, Amazon SageMaker, and Amazon EventBridge to create scalable, event-driven workflows.
Use Cases
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New Account Fraud: Detect fraudulent account registrations during the signup process.
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Payment Fraud: Identify and block suspicious payment transactions before processing.
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Account Takeover: Flag compromised accounts during login attempts.
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Trial and Loyalty Program Abuse: Prevent abuse of free trials and loyalty offers.
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Marketplace Seller Fraud: Detect fraudulent activity from sellers in online marketplaces.
Security
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Data Encryption: All data is encrypted in transit and at rest, ensuring complete confidentiality.
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Access Control: Leverage AWS IAM for fine-grained permissions and access management.
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Private Connectivity: Use AWS PrivateLink for secure, private connectivity within your VPC.
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Compliance: Meets various industry standards and regulations, supporting compliance needs.
Pricing
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Pay-As-You-Go: Charges based on fraud predictions, compute hours, and storage usage.
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Free Tier: Up to 30,000 fraud predictions are free each month.
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No Minimum Fees: Flexible and scalable Pricing with no upfront commitment required.
References:
https://docs.aws.amazon.com/frauddetector/