ArielIQ is an ACH payment intelligence platform designed for credit unions, combining machine learning, simulation, and rule-based decisioning to identify, quantify, and act on transaction-level risk.

The platform integrates a multi-layer architecture, including NACHA-calibrated Monte Carlo simulation, out-of-time validated ensemble models, and a multi-dimensional risk scoring system that evaluates transactions across unauthorized, administrative, funding, aggregate, and uncertainty dimensions.

Rather than providing a single risk score, ArielIQ generates structured, actionable decisions—mapping each transaction to a five-tier risk framework with NACHA-aligned recommendations, escalation pathways, and resubmission guidance.

In testing, the system has demonstrated strong predictive performance (ROC AUC ~0.91) while effectively concentrating a majority of total risk within a small subset of transactions, enabling targeted intervention with minimal operational burden.

ArielIQ is currently deployed in a limited number of structured pilot programs using historical, anonymized transaction data to evaluate real-world performance and operational integration

ArielIQ

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ArielIQ

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