With Amazon Fraud Detector, you pay only for what you use, and there are no minimum fees or no upfront commitments. You are charged based on the compute hours used to train and host your models and per the quantity of fraud predictions you make.
Get started with Amazon Fraud Detector for free today. For the first two months after sign-up, you are offered:
Up to 50 compute hours for model training per month.
Up to 500 compute hours for model hosting per month.
Up to 5,000 real-time Online Fraud Insight predictions and 5,000 real-time rules-based fraud predictions per month.
Pricing at a glance
You are charged for the compute hours consumed to train a custom model with your data. A compute hour represents one hour of compute capacity using 8v CPUs and 32 GiB memory. Amazon Fraud Detector automatically chooses the most efficient instance types to train your data, which may be an instance that exceeds the baseline specifications in order to complete your job more quickly. Therefore, the number of compute hours billed may be greater than the number of elapsed training hours.
You are charged for compute capacity by the hour for on-demand hosting of your deployed models so they are available for real-time predictions.
You are charged per real-time fraud prediction by Amazon Fraud Detector. The price you are charged varies based on whether you are using machine learning or evaluate fraud using only rules. Your fraud predictions are aggregated for each month's usage and billed according to the pricing tiers.
Example 1: Real-time online fraud detection for an ecommerce merchant
An ecommerce merchant protects against high risk guest checkout orders and chargebacks through real-time detection of fraud based on order attributes. They train a single Online Fraud Insights model twice per month with each training consuming 10 compute hours to complete. Further, the customer deploys one of the models for the entire month and uses it to generate 1,000 real-time fraud predictions per day.
The bill for the month for using Amazon Fraud Detector will be:
Training charge = 10 compute hours x 2 trainings x $0.39 per compute hour = $7.80
Hosting charge = 30 days x 24 hours x 1 model x $0.06 per compute hour = $43.20
Fraud prediction charge (real-time) = 1,000 predictions / day x 30 days x $0.03 per Online Fraud Insights prediction = $900
Total cost = $7.80 + $43.20 + $900 = $951