Trade Entity Risk Model
Description
The need to continuously assess and identify trade entity risk to help better assess cargo threats.
Detailed example
The calculated risk measures produced by the Trade Entity Risk model can be integrated into broader AI and machine learning systems to improve the evaluation of cargo-related threats. This output supports the standardization of trade entity risk, facilitating better data development for future predictive models.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
The Trade Entity Risk model enhances existing predictive threat models by compiling a risk profile that includes historical transaction data, relationships with trading partners, and relevant compliance information. This aggregated data helps create measurable risk indicators for trade entities.
Audit / financial statement impact
The Trade Entity Risk model/tool enhances cargo predictive threat models by providing a comprehensive risk profile that aggregates historical trade entity transactions, trading partner relationships, reviews, examinations, and violations (within CBP data holdings) to create quantifiable risk measures for all trade entities. The AI model serves as an input to larger AI/ML cargo risk targeting models to better assess cargo threats and inform focus areas for trade targeting. Its outputs are not directly shared with users or operators and the output does not serve as a principal basis for decision or actions.
Controls / human review
ATO: Yes; PIA: https://www.dhs.gov/sites/default/files/publications/privacy_pia_cbp_tsacop_09162014.pdf
Data needed
This model leverages data provided by carriers within the Automated Commercial Environment (ACE), as well as transformations of that data within the Automated Targeting System (ATS).