Finance
Real-time ML systems that detect fraudulent transactions by analysing behavioural patterns, graph relationships, and anomaly signals across every payment event.
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Industry overview
Machine learning systems that score every transaction in milliseconds — analysing behavioural signals, device fingerprints, and account graph relationships to block fraud before funds move.
At a glance
Financial fraud cost the global economy over $5 trillion in 2023. Rule-based systems catch known patterns but miss novel attack vectors. ArrayMatic builds fraud detection models that learn from live transaction data, flag anomalies at sub-50ms latency, and retrain continuously as tactics evolve.
We engineer feature pipelines from transaction history, device fingerprinting, behavioural signals, and graph relationships between accounts. Models run at inference fast enough to approve or flag a card swipe before the terminal responds — and every decision carries an explainable audit trail for compliance teams.
Key capabilities
Engagements are scoped to your business context — these are the core capabilities we bring to finance clients.
Real-time transaction scoring at sub-50ms latency
Behavioural biometric and device fingerprint profiling
Graph network analysis for fraud ring detection
Explainable AI audit trails for compliance teams
Model drift monitoring and automated retraining
Multi-channel fraud correlation across card, ACH, and wire
Built with
Financial institutions typically need fraud detection systems, regulatory compliance platforms, trading systems, payment processing solutions, and customer-facing banking applications built with enterprise-grade security.
AI helps finance through automated fraud detection, algorithmic trading, credit risk assessment, customer service chatbots, and predictive analytics for investment decisions.
Work with us
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