Fraud Prevention & FRAML
Stopping account takeover, synthetic identities, push-payment scams, and first-party fraud, increasingly run on the same models as AML detection.
Model risk governance for AI-driven finance
Onboarding and monitoring run from one case file, so investigators stop stitching evidence together across tools and file better-supported SARs faster.
Headquartered in United States·Founded 2012·51-200 employees·Pre-Seed
Demo available. Contact vendor
GRC-style controls testing tuned for the operational rhythm of mid-market financial institutions.
Stopping account takeover, synthetic identities, push-payment scams, and first-party fraud, increasingly run on the same models as AML detection.
Aggregating financial, operational, conduct, and strategic risk into a single view for the board and the second line, with risk appetite tracking and scenario modelling.
Vendor due diligence, ongoing monitoring, concentration risk analysis, and fourth-party visibility, including DORA's critical-provider regime.
Model inventory, validation, bias and fairness testing, and ongoing performance monitoring for the AI systems regulators now treat as high-risk, including under the EU AI Act and model risk management regimes.
Orchestrates document, biometric, and database checks across multiple KYC vendors from one API.
Financial Crime · Fraud Prevention & FRAML
Scores payments in real time with hybrid rules and ML, routing only meaningful alerts to analysts.
Financial Crime · Fraud Prevention & FRAML
Authors, versions, and attests policies with exception tracking auditors can self-serve.
Compliance Management · Regulatory Change Management
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