Bogotá District Inspectorate Wins CAF Call to Public Institutions

With the proposal “Artificial Intelligence for Forecasting Irregularities and Inefficiencies in Bogotá Government Procurement,” the Bogotá District Inspectorate won the call organized by CAF—development bank of Latin America—to municipal public institutions to implement a project for the strategic use of data and artificial intelligence in cities in CAF partner countries. 

The objective of the winning project is to develop a system of early warnings, using artificial intelligence tools, to identify contracts concluded by the city of Bogotá that pose a greater risk of corruption, irregularities and inefficiencies, and that serves as input for the District Inspectorate as an oversight entity.

For the evaluation committee, the proposal stood out among the others due to its great potential to leverage the fight against corruption, for its contribution to increased efficiency in the delivery of goods and services by the government, based on the proposal for collaborative work with other government agencies for exchange of information, results and lessons learned, and for its replicability in Latin American countries.

CAF Vice President of Knowledge Pablo Sanguinetti stressed that “the project presented by the District Inspectorate aligns with the proposal promoted by CAF on integrity and transparency, to take action and use new technologies and data that facilitate forecasting and preventing irregularities that impact public administration.”

CAF received a total of 89 proposals from almost 70 cities and municipalities from 11 Latin American countries in response to the call to receive proposals for projects that improve public policy design, provision of services to the public and municipal internal administration, making strategic use of data and artificial intelligence.

Therefore, CAF also wishes to make an honorable mention to the project presented by the municipality of San Martín of the Province of Buenos Aires, Argentina, titled “Intelligent Early Warning (ATI),” which calls for an intelligent analysis system with (in-streaming) live machine learning designed to detect early infection hotspots or potential epidemic outbreaks. This innovative proposal will not only allow authorities to make decisions regarding the return to productive activities in the municipality and epidemiological surveillance to prevent a second wave of COVID-19 outbreaks, but also for an early detection of other health, environmental or road safety risks that may arise in the future.

CAF appreciates the proposals from all participants and encourages institutions in the region to continue to generate public value with the use of data and artificial intelligence for the identification, detection, forecast and optimization of processes, systems and services that provide alternatives to tackle the large number of public problems faced by people in Latin America.