Amazon Fraud Detector is no longer open to new customers as of November 7, 2025. For capabilities similar to Amazon Fraud Detector, explore Amazon SageMaker, AutoGluon, and AWS WAF. # Model scores Amazon Fraud Detector generates model scores differently for different model types. For **Account Takeover Insights (ATI)** models, Amazon Fraud Detector uses only aggregated value (a value calculated by combining a set of raw variables) to generate the model score. A score of -1 is generated for the first event of a new entity, indicating an *unknown risk*. This is because for a new entity, the values used for calculating the aggregate will be zero or null. Account Takeeover Insights (ATI) model generates model scores between 0 and 1000 for all subsequent events for the same entity and for existing entities, where 0 indicates *low fraud risk* and 1000 indicates *high fraud risk*. For ATI models, the model scores are directly related to the challenge rate (CR). For example, a score of 500 corresponds to an estimated 5% challenge rate whereas a score of 900 corresponds to an estimated 0.1% challenge rate. For **Online Fraud Insights (OFI)** and **Transaction Fraud Insights (TFI)** models, Amazon Fraud Detector uses both aggregated value (a value calculated by combining a set of raw variables) and raw value (the value provided for the variable) to generate the model scores. The model scores can be between 0 and 1000, where 0 indicates *low fraud risk * and 1000 indicates *high fraud risk*. For the OFI and TFI models, the model scores are directly related to the false positive rate (FPR). For example, a score of 600 corresponds to an estimated 10% false positive rate whereas a score of 900 corresponds to an estimated 2% false positive rate. The following table provides details of how certain model scores correlate to estimated false positive rates. | Model score | Estimated FPR | | --- | --- | | 975 | 0.50% | | 950 | 1% | | 900 | 2% | | 860 | 3% | | 775 | 5% | | 700 | 7% | | 600 | 10% |