Real-Time Protection

Stop Fraud Before It Happens

Our deep learning models analyse hundreds of signals simultaneously — detecting fraudulent patterns in under 3 milliseconds while preserving a seamless customer experience.

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How It Works

Multi-Layered Fraud Intelligence

Combining graph analytics, behavioural biometrics, and ensemble machine learning, our fraud engine adapts to new attack vectors faster than any rule-based system.

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Behavioural BiometricsAnalyse typing cadence, device orientation, and navigation patterns to verify genuine user identity without friction.
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Graph-Based Network AnalysisMap relationships between accounts, devices, and entities to expose coordinated fraud rings invisible to traditional monitoring.
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Adaptive ThresholdsSelf-calibrating models adjust decision boundaries in real time based on current fraud velocity and customer behaviour drift.
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Explainable DecisionsEvery fraud score comes with a plain-language explanation — enabling analysts to act with confidence and satisfy regulators.

Coverage

Every Fraud Vector, Covered

Our models are trained on the industry's largest annotated fraud dataset — covering every major attack type across all channels.

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Card-Not-Present Fraud

Real-time CNP scoring using 200+ features including device fingerprinting, velocity checks, and 3DS authentication signals.

Payments

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Account Takeover

Detect credential stuffing, SIM swapping, and social engineering attacks through continuous session behavioural analysis.

Identity

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APP & Push Fraud

Identify authorised push payment scams through payee profiling, transaction context analysis, and mule account detection.

Transfers

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First-Party Fraud

Distinguish genuine customers from those deliberately misrepresenting their financial position at origination and over the customer lifecycle.

Lending

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Synthetic Identity Fraud

Uncover fabricated identities created from real and fictitious data points using document verification AI and bureau correlation.

Identity

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Market Manipulation

Detect spoofing, layering, wash trading, and insider trading patterns across equities, FX, and derivatives markets.

Markets

Technology

The Science Behind Our Detection Engine

Deep Neural Networks

Transformer-based models trained on 14 billion labelled fraud events, continuously fine-tuned on your institution's specific patterns and attack landscape.

Graph Neural Networks

Model complex relationships between accounts, merchants, devices, and beneficiaries to surface fraud rings that linear models miss entirely.

Federated Learning

Train on consortium data from 320+ institutions without sharing raw customer data — benefiting from network intelligence while preserving privacy.

Streaming Architecture

Apache Kafka-based event streaming delivers sub-3ms scoring for every transaction — scalable to 50,000 transactions per second per cluster node.