Correspondent banking gains a clear picture of financial crime with adaptive machine learning

Clarity across borders with holistic risk management

Gain context where there is none. Featurespace’s Adaptive Behavioral Analytics spots suspicious activity without needing the full picture, evaluating all available party information within transactions, and providing insight to help investigators identify suspicious actors.

Map out risk as adaptive machine learning reveals networks of financial crime across multiple entities and across borders.

Efficiently manage risk using the most dynamic and innovative profiling techniques, while minimizing false positive levels and prioritizing alerts.


Detect Risk More Efficiently

Truly adaptive machine learning models spot new and known suspicious behavior in real time

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Multi-Entity Analysis

Analyze transactions and networks across all jurisdictions

Asset 124Machine learning analytics

Explainable Models

Self-learning, explainable machine learning models with clear reason code extraction

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Reduce and Prioritize Alerts

Maximum efficiency with automatically prioritized alerts and decreased case volumes

Asset 119Ops Efficiency

Fast Deployment

Get set up quickly with standalone or complementary augmented analytics


100% POCs Won

Proof of concepts across use cases have consistently found Featurespace selected

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Find out more about ARIC Risk Hub for Correspondent Banking AML