Quantifind provides AML and fraud prevention intelligence by integrating internal bank records with external sources  Quantifind is able to link entities in bank cases to news feeds, social chatter and the deep web with high confidence, relevancy, and disambiguation, by leveraging a predictive modeling AI platform  Our platform provides efficiency savings by algorithmically identifying which incidents and alerts are likely candidates for Suspicious Activity Reports, and helps the investigator rapidly and with low false positive rates discover the necessary background to make a filing decision Furthermore, Quantifind has a proven ability to discover the sharp needle that was missed when transaction and internal data alone were relied on Let us demonstrate

Make better and faster SAR filing decisions

reduce the false positive rates of negative news feeds and reduce the false negative rates of google searches

Quantifind for Financial Institutions


External Data

Social Media
Global News
Financial Forums
Dark Web
Employer Review Sites

Internal Data

Fraud Alerts
Case Data
Employee Ethics Hotline
Applications and Contracts

Predictive Data Modeling

SaaS Suite
Multi-User, Always-On, Secure Applications, Intuitive Data Visualizations, Downloads
Customer Success and Data Analyst Partners, Custom Reporting

Business Use Cases

Surface emergent trends in internal/external fraud and AML

Triage alerts and case files in the AML investigative pipeline

Provide alerting and assign risk factors without hard-coded rules or data models

Provide real-time visibility of trends and topics across the enterprise

Our Unique Value Proposition

Enrich internal bank data with external news sources, social chatter, and deep web

Augment rules-based engines with predictive signals from external social graphs and text features to discover unknown bad actors

Discover related cases across silos to bundle SARs and provide richer context