XGBOOST BOOTSTRAP ENSEMBLE

Intelligent Fraud
Routing Engine.

A decision-theoretic framework that routes transactions by evaluating not just risk, but the uncertainty of its models and the novelty of the behavior.

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LOW RISK
HIGH UNCERTAINTY

284K+

Live Transactions Processed

31 DIMS

PCA Feature Space

5 NODES

Bootstrap Evaluation

5 DECISIONS

Asymmetric Cost Actions

The Three Pillars of Decision

MARI processes data through three distinct computational layers to determine the most cost-effective routing outcome.

Ensemble Risk

Calculates the calibrated fraud probability from an XGBoost bootstrap ensemble. Higher values indicate stronger fraud signals.

Predictive Uncertainty

Measures disagreement across 5 bootstrap models via standard deviation. High variance indicates low model confidence.

Novelty Isolation

An Isolation Forest trained purely on legitimate behavior flags zero-day exploits and totally unseen data profiles.

Ready to observe the pipeline in action?

Simulate transactions, inject extreme scenarios, and audit the cost simulations.

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