Machine Learning

Combine machine intelligence with human insights. Let the machine-learning module generate precise risk scores, and stay in control to improve catch rates and reduce false positives over time. 

 

You can learn more about how to augment your manual fraud prevention efforts with the efficient use of machine learning here. The machine learning engine learns through feedback you provide, which is explained in the Feedback section.

 

Tailored Industry Rules

Deploy hundreds of risk rules tailored to your specific industry risk vectors, out of the box. Import and test custom rules on a confusion matrix, and improve detection accuracy in no time.

 

Whitebox ML

Improve decision accuracy with SEON’s machine learning module. The algorithm learns from your fraud patterns and retrains itself numerous times a day. Get results via human-readable rule suggestions with specific accuracy percentages, where rules are branches and parameters are the nodes of a decision tree. Our dedicated data scientists can also help you with resources and reporting. 

 

Blackbox ML

SEON provides precise, predictive scoring based on logic involving neural networks, string similarity, AdaBoost, XGBoost, CatBoost and other technologies which help catch even the most sophisticated attacks.

 

Feedback Loops

Label transactions via API or through the SEON Admin Panel. It improves the algorithm to reduce fraud while lowering the rate of false positives or negatives based on your specific use cases.

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