Uncover the schemes no rule was written for

Theta Monitor is ThetaRay's transaction monitoring engine. It uses ensemble machine learning that finds unknown risk typologies, to uncover the schemes no rule was written for.

Yes. Theta Monitor resolves customers, counterparties and accounts that belong to the same real-world entity, then maps the connections between them. Analysts see the whole network, such as a mule ring or layered shell companies, instead of isolated transactions.

Theta Monitor raises an alert only when its ensemble of 20 proprietary algorithms agrees. Like a committee, each algorithm reviews the same activity from a different point of view, so one model's blind spot is covered by the others. The result is fewer false positives and detection of typologies that no single model or rule would catch.

It detects without thresholds. Unsupervised models learn each customer's and corridor's normal behavior and flag anomalous structure that no predefined typology describes, without needing labeled examples of crime. Semi-supervised models then learn from the small set of confirmed cases and analyst decisions to sharpen what gets flagged. New typologies are surfaced monthly.

Theta Monitor scores against 30+ weighted risk features, with risk weighted per corridor, product and customer segment. The result is 50%+ alert-volume reduction and 10x fewer false positives.

Yes. Every detection maps to the features that drove it, in regulator-ready language, and returns an explainable decision with a documented trail. A model validation pack is included.