Description of the service
Identification of possible technical and open smuggling behavior in LATAM.
Problem that it solves
Smuggling is a problem that affects and threatens mainly consumers because it exposes them to counterfeit, altered, and unapproved products (pharmaceuticals and food). It also affects lawful companies with unfair practices generating losses and impacting formal employment, and the government tax collection.Type of AI app used
Events detection (anomaly detection and early warning), Reasoning with knowledge structures
Main results to June 30, 2021
Identifying companies with possible technical smuggling behavior, quantified in units of products entering the country and their respective amounts. Identifying amounts of money and product quantities not registered in the country that left the origin country.
Three main bottlenecks faced during implementation
- Data access and data quality
- High data cost and high processing cost
- Changes in data access legislation
Lessons learned in the design or use of AI for social impact
- Stakeholder involvement
- Scalability
- Access to funding
Country of origin
Geographic scope of operations
Bogotá
Type of executing entity
StartupSector/industry
Sustainable Development Goal(s) to which your AI solution contributes
1 (no poverty), 8 (decent work and economic growth), 9 (industry, innovation, and infrastructure), 10 (reduced inequalities), 12 (responsible consumption and production)IA app developed internally or by a third party
Internally
Name of implementing entity
CVN
Stakeholders involved
Customs administrations, tax administrations, foreign trade regulators, associations, consumer associations, police, and others
Percentage of the development team that are women
25%
Year they started using AI-based models
2008It may interest you
The Regional Landscape and 12 Country Snapshots
This self-assessment tool is designed to allow the mitigation of ethical risks associated with the use/application of new technologies. It is available so that the ethical performance of each system can be evaluated from the beginning.
El presente documento presenta un estudio de caso de un proyecto piloto en el estado de Jalisco que utilizó inteligencia artificial (IA) para el tamizaje de la Retinopatía Diabética.