[Product Features]
- Extensive information learning to mitigate false positives and enhance the detection rate of anomalous transactions
- Real-time monitoring allows for immediate response to detected abnormal transactions
- Compatible with existing monitoring systems to facilitate hybrid detection rule systematization
- Automates the process of directly tuning, registering, renewing, and deleting black/white lists and statistical rules using machine learning, etc.

[Key Features]
- Supports detection models based on profiling individual financial transaction information
- Enables real-time detection, response, and monitoring of abnormal financial transactions using in-memory technology
- Generates foundational data for analyzing and processing learning data based on basic data
- Extracts features by applying the processed learning data and calculated functional expressions
- Validates the model (prediction function) through simulation before applying the learned model to the operational system