Get the most out of AI & machine learning
Overview
AI and machine learning algorithms identify the patterns and typical behaviors behind fraudulent transactions and help you catch them earlier with improved accuracy.
By processing hundreds (sometimes even thousands) of approved and declined transactions, our models can discover connections you didn't even know were there.
Our AI and machine learning models will create new human-readable AI rule suggestions or assign an AI insights score to each transaction.
Both are available to you in SEON, and you can choose how you want to use them.
SEON's AI and machine learning tools
SEON’s AI and machine learning features help fraud and risk teams move from investigation to action quickly. Our AI tools highlight important details such as fraud scores, summaries, network patterns and rule suggestions to aid analysts in decision-making.
AI rules suggestions
Our AI Rule suggestions algorithms analyze your transaction history to discover fraud patterns and create rules suggestions. You can then implement its fully explainable rules to block certain user actions, such as suspicious logins, identity theft, or fraudulent transactions.
AI Insights score
Similar to the AI Rule suggestions, an AI Insights model trains itself on historical data to help you find fraud patterns that stay hidden from the human eye. The difference lies the scope— while you can get Ai suggesting rules you are missing from your fraud detection toolbox, the AI Insights model reduces your complete fraud detection apparatus with 900 signals to a single fraud likelihood score. The model can make surprising connections and discover behaviors that would be hard to translate to a human reader and it can be blended into rules.
Feedback loops
At its heart, machine learning algorithms learn from good and bad examples. By default, our AI and machine learning solutions learn from transaction states, but you can finetune their performance with our Label API. Create positive and negative transaction labels to give more accurate feedback and rule out false positives.