AI-powered Integrated Risk Management Framework Concept Demonstration – Sample Shipment
Targeting dangerous non-compliance is key
Resources are limited and will never be enough to inspect everything
-
We help you identify which regulated products or businesses would be more dangerous when non-compliant.
-
We help you identify which regulated products or businesses are most likely to be non-compliant.
-
We help you distribute available resources in the most effective way.
Design a data-driven, risk-based enforcement framework
Define roles, risk tolerance, targeting logic, and review cycles
We have developed a set of custom GPTs that guide regulators through the key processes involved in designing and implementing a risk-based enforcement framework.
As examples, try out the tools for:
Learn more about the structure of the framework and its core risk engine
Prioritize non-compliance risk
Identify where non-compliance is most likely and most harmful
A risk engine evaluates which products, shipments, businesses, or transactions are most likely to be non-compliant — and where non-compliance would have the most serious consequences.
By combining probability and impact, a risk engine enables regulators to:
-
focus on the most dangerous non-compliance
-
prioritize inspections intelligently
-
allocate limited resources where they matter most
There is no universal risk engine. Every sector, authority, and regulatory objective requires a context-specific approach.
ResidualRisk.ai helps regulators design and run tailored risk engines — from defining risk factors to prioritizing actions — so they can clearly see high-risk areas and know the residual risk.