HercRisk AI – Qlik Sense–Powered AML Effectiveness Demo

This prototype simulates how HercRisk AI uses Qlik Sense as the analytics engine to perform full-population testing over an institution’s customer base, transactional data, and regulatory reporting data (e.g., STRs, LCTRs, EFTIs, sanctions cases) to flag:
• Potential inaccurate risk ratings (e.g., Low-rated customers with high-risk behaviour),
• Potential missed or inconsistent STR candidates,
• 3V anomalies (Volume, Velocity, Variety) only where they co-occur with alerts and/or STR gaps, and
• Exposure to FATF grey/black list jurisdictions and sanctions-evasion indicators.

In a real deployment, these analytics are executed in Qlik Sense using parameterised scripts and rules that are explicitly mapped to FINTRAC requirements and the organization’s AML policy and risk appetite. This web page shows a simplified, front-end view of the type of results Internal Audit would see.

* Prototype logic and data structure are simplified for demo purposes. In a live engagement, HercRisk AI connects to the client’s environment and runs all analytics in Qlik Sense, using scripts and controls mapped to FINTRAC obligations and the client’s AML policy framework. This web demo is a thin presentation layer to illustrate the type of outputs Internal Audit and AML stakeholders would receive.