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Up to 97% of sanctions alerts are false positives creating unnecessary workload, slowing investigations, and stretching compliance resources. The guide explains why rules-based systems generate such high alert volumes and why thresholds are often set artificially low.
Through a practical worked example, the guide shows how traditional systems fail to distinguish context (such as a London entertainment company versus a sanctioned Russian vessel with the same name), leading to unnecessary alerts.
Discover how SensaAI uses GenAI entity extraction and predictive AI to structure unstructured data and determine match probability more intelligently.
Rather than replacing your sanctions system, SensaAI overlays it. It analyzes “match candidates” using a two-step AI process:
You’ll see how AI scores, feature breakdowns, and natural-language explanations are returned directly into your existing case management workflow.
Recent proofs of concept have demonstrated:
When nearly all alerts are false positives, teams are forced into repetitive, low-value triage. This guide explains how AI-driven prioritization and auto-hibernation of low-risk alerts can significantly reduce workload and accelerate case handling.
Sanctions breaches carry severe financial and reputational consequences, with billions in fines issued globally. Intelligent scoring and explainable outputs demonstrate a proactive, technology-forward compliance strategy.
SensaAI enables institutions to reduce false positives while retaining 100% of true positives in testing, meaning that efficiency gains do not come at the expense of compliance integrity.
Upgrades can be expensive. Thankfully, SensaAI augments your existing sanctions and case management systems via API or deployment options, allowing immediate impact without a full technology overhaul.
From offline simulations using historical datasets to phased rollouts and governance modeling, SensaAI for Sanctions can be implemented via a structured, low-risk adoption framework. Download the guide today.